diff --git a/notebooks/lectures/Introduction_to_Market_Microstructure/notebook.ipynb b/notebooks/lectures/Introduction_to_Market_Microstructure/notebook.ipynb new file mode 100644 index 00000000..4e6e8e29 --- /dev/null +++ b/notebooks/lectures/Introduction_to_Market_Microstructure/notebook.ipynb @@ -0,0 +1,2348 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Market Microstructure\n", + "\n", + "By Beha Abasi, Jonathan Larkin, Maxwell Margenot, and Delaney Granizo-Mackenzie\n", + "\n", + "Part of the Quantopian Lecture Series:\n", + "\n", + "* [www.quantopian.com/lectures](https://www.quantopian.com/lectures)\n", + "* [github.com/quantopian/research_public](https://github.com/quantopian/research_public)\n", + "\n", + "Notebook released under the Creative Commons Attribution 4.0 License." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Market microstructure is the broad study of the functions and operations of financial markets. This field includes research on how exchanges and trading venues are created and how they facilitate the transfer of financial assets between buyers and sellers. It also looks at the tension between the conflicting interests of opposing parties and how this affects price discovery. Furthermore, quotes, spreads, and transaction costs are important pillars of this field. Due to the proliferation of algorithmic trading, market microstructure has turned into one of the fastest growing domains of microeconomic research$^{[1]}$." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Although much of economic theory suggests that markets are frictionless, that is never the case and it is this same friction that often leads to costly implementation of investment strategies and alpha deterioration. A common reason why investment ideas conceived in research sometimes fail to pan out in the actual execution is because crucial market considerations were not accounted for, leading to the improper trading of alpha generating strategies." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "As briefly discussed in the [Volume, Slippage, and Liquidity](https://www.quantopian.com/lectures/introduction-to-volume-slippage-and-liquidity) lecture, a good starting point in microstructure would be to look at intraday profiles. These plots give us a concise overview of how market participants are behaving with regards to different market conditions, particularly looking at how behaviours change at varying times of day. Although measures of volatility and volume that are calculated on a per day basis can be quite helpful in giving us a big picture understanding of stocks and sectors, it is the intraday profiles that reveal what actual trading would be like, and potentially what pitfalls lay ahead. We will consider the intraday movements of volume and volatility, compare across different classes of assets and discuss why these considerations may be the determinants of whether a strategy is profitable or not. Intraday profiles can be used to make comparisons and provide insights across almost anything that is tradeable. As a taste, we will look at how trading of large cap and small cap stocks differ. \n", + "\n", + "Let's start by making some imports." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import numpy as np\n", + "from quantopian.pipeline import Pipeline\n", + "from quantopian.pipeline.data import morningstar\n", + "from quantopian.pipeline.factors import Returns, Latest\n", + "from quantopian.pipeline.filters.morningstar import Q1500US, Q500US\n", + "from quantopian.research import run_pipeline\n", + "import matplotlib.pyplot as plt\n", + "from quantopian.pipeline.data.builtin import USEquityPricing\n", + "import time\n", + "import scipy.stats as stats" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We'll gather some of the data we will use in this section and later parts of the lecture, and define our asset groups." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "collapsed": false, + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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Q1500Q500large_capmarket_capreturnsshares_outstandingsmall_capvolume
2016-12-01 00:00:00+00:00Equity(21 [AAME])FalseFalseFalse7.655710e+070.0666672.047530e+07True469.0
Equity(24 [AAPL])TrueTrueTrue5.943400e+11-0.0084345.332310e+09False25115705.0
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Equity(39 [DDC])FalseFalseFalse8.307590e+080.0100488.781810e+07False221162.0
Equity(41 [ARCB])FalseFalseFalse7.763620e+080.0066012.574970e+07False257181.0
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" + ], + "text/plain": [ + " Q1500 Q500 large_cap \\\n", + "2016-12-01 00:00:00+00:00 Equity(21 [AAME]) False False False \n", + " Equity(24 [AAPL]) True True True \n", + " Equity(31 [ABAX]) False False False \n", + " Equity(39 [DDC]) False False False \n", + " Equity(41 [ARCB]) False False False \n", + "\n", + " market_cap returns \\\n", + "2016-12-01 00:00:00+00:00 Equity(21 [AAME]) 7.655710e+07 0.066667 \n", + " Equity(24 [AAPL]) 5.943400e+11 -0.008434 \n", + " Equity(31 [ABAX]) 1.176550e+09 -0.012450 \n", + " Equity(39 [DDC]) 8.307590e+08 0.010048 \n", + " Equity(41 [ARCB]) 7.763620e+08 0.006601 \n", + "\n", + " shares_outstanding small_cap \\\n", + "2016-12-01 00:00:00+00:00 Equity(21 [AAME]) 2.047530e+07 True \n", + " Equity(24 [AAPL]) 5.332310e+09 False \n", + " Equity(31 [ABAX]) 2.253300e+07 False \n", + " Equity(39 [DDC]) 8.781810e+07 False \n", + " Equity(41 [ARCB]) 2.574970e+07 False \n", + "\n", + " volume \n", + "2016-12-01 00:00:00+00:00 Equity(21 [AAME]) 469.0 \n", + " Equity(24 [AAPL]) 25115705.0 \n", + " Equity(31 [ABAX]) 163531.0 \n", + " Equity(39 [DDC]) 221162.0 \n", + " Equity(41 [ARCB]) 257181.0 " + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "def make_pipeline():\n", + " \n", + " # define our pipeline\n", + " pipe = Pipeline()\n", + " \n", + " # get daily volume data\n", + " volume = Latest([USEquityPricing.volume])\n", + " pipe.add(volume, 'volume')\n", + " \n", + " # get daily returns\n", + " returns = Returns(window_length=2)\n", + " pipe.add(returns, 'returns')\n", + " \n", + " # get shares outstanding (this will be used later in the lecture for market impact)\n", + " shares_outstanding = Latest([morningstar.valuation.shares_outstanding])\n", + " pipe.add(shares_outstanding, 'shares_outstanding')\n", + " \n", + " # get market cap\n", + " market_cap = Latest([morningstar.valuation.market_cap])\n", + " pipe.add(market_cap, 'market_cap')\n", + " \n", + " market_cap_rank = market_cap.rank()\n", + " biggest = market_cap_rank.top(1000)\n", + " pipe.add(biggest, 'large_cap')\n", + " smallest = market_cap_rank.bottom(1000)\n", + " pipe.add(smallest, 'small_cap')\n", + " \n", + " # in Q1500US\n", + " q1500_universe = Q1500US()\n", + " pipe.add(q1500_universe, 'Q1500')\n", + " \n", + " # in Q500US\n", + " q500_universe = Q500US()\n", + " pipe.add(q500_universe, 'Q500')\n", + " \n", + " return pipe\n", + "\n", + "# Initializing the pipe\n", + "pipe = make_pipeline()\n", + "\n", + "# Dependency Graph\n", + "pipe.show_graph('png')\n", + "\n", + "# Now let's start the pipeline\n", + "start_date, end_date = '2016-12-01', '2016-12-31' \n", + "\n", + "pipeline_results = run_pipeline(pipe, start_date, end_date)\n", + "pipeline_results.dropna(inplace=True)\n", + "pipeline_results.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "large_cap_assets = pipeline_results[pipeline_results.large_cap].xs('2016-12-1').index.values\n", + "small_cap_assets = pipeline_results[pipeline_results.small_cap].xs('2016-12-1').index.values\n", + "Q500_assets = pipeline_results[pipeline_results.Q500].xs('2016-12-1').index.values\n", + "Q1500_assets = pipeline_results[pipeline_results.Q1500].xs('2016-12-1').index.values\n", + "other_assets = pipeline_results[~(pipeline_results.Q1500) & ~(pipeline_results.Q500)].xs('2016-12-1').index.values" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Intraday Profiles of Volume/Volatility" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Our intraday profiles will show the day's activity as broken up into 10 minute bars. Within these 10 minute bars, we'll show how the distribution of volume and volatility looks across different days. We'll also show how much volume/volatility exists in each interval, as a percentage of the entire day's worth. Since we want to look at intraday movements, we'll need to use the get_pricing method instead of pipeline for minutely data. Volume is a standard field on the Quantopian platform, so we can call it directly without the need for any other calculations." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "collapsed": false, + "scrolled": false + }, + "outputs": [], + "source": [ + "all_large_cap_data = get_pricing(large_cap_assets, frequency='minute',start_date='2016-12-1', end_date='2016-12-31')\n", + "large_cap_volume = all_large_cap_data['volume'] # the only field we care about right now\n", + "large_cap_volume = large_cap_volume.tz_convert('US/Eastern') # Q data comes in as UTC\n", + "\n", + "all_small_cap_data = get_pricing(small_cap_assets, frequency='minute', start_date='2016-12-1', end_date='2016-12-31') \n", + "small_cap_volume = all_small_cap_data['volume']\n", + "small_cap_volume = small_cap_volume.tz_convert('US/Eastern')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We'll define some general functions for the use of modelling our data and generating the intraday profiles." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "def intraday_volume_profile_data(intraday_data):\n", + " # this method will define clearly all the data we need in plotting out volume profiles\n", + " \n", + " intraday_data = pd.DataFrame(intraday_data.mean(axis=1))\n", + " \n", + " # how much volume is there in an interval (minute, for now)\n", + " intraday_data.columns = ['interval_value']\n", + "\n", + " # how much volume is there in each day\n", + " dailySum = intraday_data.resample('d').sum()\n", + " dailySum.columns = ['daily_value']\n", + " dailySum['day'] = dailySum.index.date\n", + "\n", + " intraday_data['minute_of_day'] = (intraday_data.index.hour - 9) * 60 +\\\n", + " (intraday_data.index.minute - 30)\n", + " intraday_data['time'] = intraday_data.index.time\n", + "\n", + " # redefine our intervals as 10 minute bars, using the conversion below\n", + " conversion = {'interval_value' : 'sum', 'minute_of_day': 'last', 'time': 'last'}\n", + " intraday_data = intraday_data.resample('10t', closed='right').apply(conversion)\n", + " intraday_data['day'] = intraday_data.index.date\n", + "\n", + " # calculate the percentage of volume in each interval\n", + " intraday_data = intraday_data.merge(dailySum, how='left', on='day')\n", + " intraday_data['interval_pct'] = intraday_data['interval_value'] / intraday_data['daily_value']\n", + "\n", + " intraday_data.head()\n", + " \n", + " return intraday_data\n", + "\n", + "def intraday_profile(intraday_data, plot_title, y_axis_one, y_axis_two):\n", + " # this method will actually plot the intraday profile\n", + " \n", + " # we want to look across days, comparing what happens are the same time of day\n", + " intraday_grouped = intraday_data.groupby('time')\n", + "\n", + " intraday_grouped_median = intraday_grouped.median()\n", + "\n", + " # each interval (10 minutes) is a bucket\n", + " buckets = intraday_grouped_median.index\n", + " bucket_data = intraday_grouped_median['interval_pct']\n", + "\n", + " figure, ax = plt.subplots()\n", + " plt.title(plot_title)\n", + " \n", + " ax.bar(buckets, 100 * bucket_data, -60 * 10, alpha = 0.75, color='navy')\n", + " ax.set_ylabel(y_axis_one)\n", + " ax_twin = ax.twinx()\n", + "\n", + " ax_twin.plot(buckets, (100 * bucket_data).cumsum(), color='r')\n", + " ax_twin.grid(None)\n", + " ax_twin.set_ylim(0, 100)\n", + " ax_twin.set_ylabel(y_axis_two)\n", + "\n", + "def intraday_groups(group_one, group_two, y_axis_one, y_axis_two, title='Small vs. Big', \n", + " group_one_name='Large Cap', group_two_name='Small Cap'):\n", + " # this method will be used to plot two intraday profiles against each other\n", + " # used for making pattern comparisons\n", + " # this is the same code as above, except now for two data sets \n", + " \n", + " group_one_grouped = group_one.groupby('time')\n", + " group_two_grouped = group_two.groupby('time')\n", + " \n", + " group_one_median = group_one_grouped.median()\n", + " group_two_median = group_two_grouped.median()\n", + " \n", + " buckets = group_one_median.index\n", + " group_one_bucket_data = group_one_median['interval_pct']\n", + " group_two_bucket_data = group_two_median['interval_pct']\n", + " \n", + " figure, ax = plt.subplots()\n", + " plt.title(title)\n", + " \n", + " ax.bar(buckets, 100 * group_one_bucket_data, -60 * 10, alpha=0.75, color='r')\n", + " ax.bar(buckets, 100 * group_two_bucket_data, -60 * 10, alpha=0.75, color='navy')\n", + " ax.legend([group_one_name, group_two_name], loc=1)\n", + " ax.set_ylabel(y_axis_one)\n", + " ax_twin = ax.twinx()\n", + " \n", + " ax_twin.plot(buckets, (100 * group_one_bucket_data).cumsum())\n", + " ax_twin.plot(buckets, (100 * group_two_bucket_data).cumsum())\n", + " ax_twin.grid(None)\n", + " \n", + " ax_twin.legend([group_one_name, group_two_name], loc=2)\n", + " ax_twin.set_ylim(0, 100)\n", + " ax_twin.set_ylabel(y_axis_two)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Volume - Large Cap" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We'll begin our study by looking at the trading profiles of large cap stocks. We will average out the volume profiles across all the large cap stocks that we found to find general patterns that should be applicable not just to individual stocks. Although, if you have a smaller, more specific universe, these profiles could be used on a per stock basis." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "collapsed": false, + "scrolled": false + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " Equity(24 [AAPL]) Equity(62 [ABT]) \\\n", + "2016-12-01 09:31:00-05:00 570839.0 101061.0 \n", + "2016-12-01 09:32:00-05:00 176608.0 10629.0 \n", + "2016-12-01 09:33:00-05:00 148342.0 5102.0 \n", + "2016-12-01 09:34:00-05:00 212701.0 6622.0 \n", + "2016-12-01 09:35:00-05:00 192160.0 18223.0 \n", + "\n", + " Equity(64 [ABX]) Equity(67 [ADSK]) \\\n", + "2016-12-01 09:31:00-05:00 272246.0 28791.0 \n", + "2016-12-01 09:32:00-05:00 46518.0 12299.0 \n", + "2016-12-01 09:33:00-05:00 87521.0 1100.0 \n", + "2016-12-01 09:34:00-05:00 99279.0 16252.0 \n", + "2016-12-01 09:35:00-05:00 55978.0 17515.0 \n", + "\n", + " Equity(76 [TAP]) Equity(100 [IEP]) \\\n", + "2016-12-01 09:31:00-05:00 23976.0 1076.0 \n", + "2016-12-01 09:32:00-05:00 2800.0 0.0 \n", + "2016-12-01 09:33:00-05:00 8736.0 0.0 \n", + "2016-12-01 09:34:00-05:00 8200.0 0.0 \n", + "2016-12-01 09:35:00-05:00 4000.0 0.0 \n", + "\n", + " Equity(114 [ADBE]) Equity(122 [ADI]) \\\n", + "2016-12-01 09:31:00-05:00 41591.0 58364.0 \n", + "2016-12-01 09:32:00-05:00 4743.0 12892.0 \n", + "2016-12-01 09:33:00-05:00 10295.0 7132.0 \n", + "2016-12-01 09:34:00-05:00 8465.0 4323.0 \n", + "2016-12-01 09:35:00-05:00 2750.0 13162.0 \n", + "\n", + " Equity(128 [ADM]) Equity(154 [AEM]) \\\n", + "2016-12-01 09:31:00-05:00 56137.0 16279.0 \n", + "2016-12-01 09:32:00-05:00 800.0 7100.0 \n", + "2016-12-01 09:33:00-05:00 5050.0 5790.0 \n", + "2016-12-01 09:34:00-05:00 5946.0 3700.0 \n", + "2016-12-01 09:35:00-05:00 2162.0 2100.0 \n", + "\n", + " ... Equity(50049 [FTV]) \\\n", + "2016-12-01 09:31:00-05:00 ... 0.0 \n", + "2016-12-01 09:32:00-05:00 ... 400.0 \n", + "2016-12-01 09:33:00-05:00 ... 28611.0 \n", + "2016-12-01 09:34:00-05:00 ... 3248.0 \n", + "2016-12-01 09:35:00-05:00 ... 13022.0 \n", + "\n", + " Equity(50117 [LN]) Equity(50242 [DVMT]) \\\n", + "2016-12-01 09:31:00-05:00 4758.0 10412.0 \n", + "2016-12-01 09:32:00-05:00 100.0 1100.0 \n", + "2016-12-01 09:33:00-05:00 300.0 800.0 \n", + "2016-12-01 09:34:00-05:00 400.0 4000.0 \n", + "2016-12-01 09:35:00-05:00 1005.0 1455.0 \n", + "\n", + " Equity(50307 [ASB_PRD]) Equity(50382 [FTS]) \\\n", + "2016-12-01 09:31:00-05:00 2000.0 46290.0 \n", + "2016-12-01 09:32:00-05:00 200.0 30568.0 \n", + "2016-12-01 09:33:00-05:00 2100.0 1648.0 \n", + "2016-12-01 09:34:00-05:00 0.0 1473.0 \n", + "2016-12-01 09:35:00-05:00 500.0 2452.0 \n", + "\n", + " Equity(50390 [ADNT]) Equity(50392 [YUMC]) \\\n", + "2016-12-01 09:31:00-05:00 17437.0 0.0 \n", + "2016-12-01 09:32:00-05:00 200.0 60652.0 \n", + "2016-12-01 09:33:00-05:00 2623.0 5300.0 \n", + "2016-12-01 09:34:00-05:00 5761.0 5700.0 \n", + "2016-12-01 09:35:00-05:00 341.0 8384.0 \n", + "\n", + " Equity(50421 [ZTO]) Equity(50428 [AA]) \\\n", + "2016-12-01 09:31:00-05:00 8142.0 85914.0 \n", + "2016-12-01 09:32:00-05:00 1340.0 28991.0 \n", + "2016-12-01 09:33:00-05:00 4500.0 27066.0 \n", + "2016-12-01 09:34:00-05:00 200.0 23027.0 \n", + "2016-12-01 09:35:00-05:00 14690.0 19745.0 \n", + "\n", + " Equity(50471 [MTFB]) \n", + "2016-12-01 09:31:00-05:00 200.0 \n", + "2016-12-01 09:32:00-05:00 0.0 \n", + "2016-12-01 09:33:00-05:00 0.0 \n", + "2016-12-01 09:34:00-05:00 0.0 \n", + "2016-12-01 09:35:00-05:00 0.0 \n", + "\n", + "[5 rows x 991 columns]" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "large_cap_volume.head()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "As a sample, we'll look at the intraday volume for a single day, 2016-01-01. Notice that we see large spikes in volume at the beginning of the day and towards the close." + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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HJ9rsegphIiIiIiLSom3YcJBVq3602fUUwkREREREpEWrqKi26fUUwkREREREpEVTCBMR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\nGTt25FpDWVVA++ab3Xzzze5qb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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "large_cap_avg_volume = large_cap_volume['2016-12-1'].mean(axis=1)\n", + "\n", + "plt.subplot(211)\n", + "plt.plot(large_cap_avg_volume.index, large_cap_avg_volume, color='navy')\n", + "plt.title(\"Intraday Volume - Large Cap\")\n", + "plt.ylabel('Volume')\n", + "\n", + "resampled_large_cap_avg_volume = large_cap_avg_volume.resample('10t', closed='right').sum()\n", + "\n", + "plt.subplot(212)\n", + "plt.plot(resampled_large_cap_avg_volume.index, resampled_large_cap_avg_volume/large_cap_avg_volume.sum(), color='navy')\n", + "plt.title(\"Intraday Volume as % of Total Day - Large Cap\")\n", + "plt.ylabel('Volume as % of Total Day')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now, we'll average across all days in the month of December 2016 to see how the volume patterns distribute. It seems that there is a much larger proportion of volume towards the end of the day, on one day there is more than 12% of total daily volume in just the last 10 minutes of trading.\n", + "\n", + "One reason why this may occur is because it may be risky to hold positions overnight and traders make a concious effort to close out positions at the end of the day. Doing it the next morning can be tricky as morning trading is often marred with lots of volatility. There may also be information released after the close that could cause adverse price movements, but since the markets are closed there would be little that could be done to handle the situation.\n", + "\n", + "Another contributing factor may be due to the proliferation of index funds$^{[2]}$. The value of index funds are determined by the day's closing price, and so to minimize tracking error, portfolio managers of index funds will aim to trade as close to the closing price as possible." + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": 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dKBGKAAAAAIRMQUGJ1zocCEUAAAAAQiYqyuW1DgdCEQAAAICQiYur57UOB0IR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\nhbf430CDTP6ecm8B4Dymv4w75eKKndd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N/yuTJEnKaRITYdIk6NEDfvkFChUK9grr0sVNm6UMZBmTJEnKSRYuDDZtXroU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\n1yuvvCJJ6t69u5YtW+b9YczHx0fVq1eXJK1bt07dunUjiAG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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "large_volume = intraday_volume_profile_data(large_cap_volume)\n", + "\n", + "plt.scatter(large_volume.minute_of_day, large_volume.interval_pct*100, color='navy')\n", + "plt.title('% of Volume in 10 Minute Intervals - Large Cap')\n", + "plt.xlim(0, 400)\n", + "plt.ylabel('% of Volume')\n", + "\n", + "intraday_profile(large_volume, 'Intraday Volume Profile - Large Cap', '% of Day\\'s Volume in Bucket', 'Cumulative % of Day\\'s Volume')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Volume - Small Cap" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now, let's do a similar volume study but on small cap stocks. Again, we will average out the trading patterns for all the small cap stocks we found to demonstrate general volume profiles." + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "collapsed": false, + "scrolled": false + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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Equity(21 [AAME])Equity(106 [ACU])Equity(112 [ACY])Equity(117 [AEY])Equity(225 [AHPI])Equity(392 [AMS])Equity(535 [ARTW])Equity(680 [AXR])Equity(925 [BKSC])Equity(1031 [BONT])...Equity(50188 [GEMP])Equity(50237 [SNDE])Equity(50285 [AZRX])Equity(50327 [TYHT])Equity(50349 [AMMA])Equity(50360 [MRAM])Equity(50369 [BCTF])Equity(50374 [OTTW])Equity(50456 [DFFN])Equity(50476 [GNUS])
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5 rows × 933 columns

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" + ], + "text/plain": [ + " Equity(21 [AAME]) Equity(106 [ACU]) \\\n", + "2016-12-01 09:31:00-05:00 1004.0 400.0 \n", + "2016-12-01 09:32:00-05:00 0.0 0.0 \n", + "2016-12-01 09:33:00-05:00 0.0 0.0 \n", + "2016-12-01 09:34:00-05:00 0.0 0.0 \n", + "2016-12-01 09:35:00-05:00 0.0 0.0 \n", + "\n", + " Equity(112 [ACY]) Equity(117 [AEY]) \\\n", + "2016-12-01 09:31:00-05:00 0.0 0.0 \n", + "2016-12-01 09:32:00-05:00 0.0 0.0 \n", + "2016-12-01 09:33:00-05:00 0.0 155.0 \n", + "2016-12-01 09:34:00-05:00 0.0 0.0 \n", + "2016-12-01 09:35:00-05:00 0.0 0.0 \n", + "\n", + " Equity(225 [AHPI]) Equity(392 [AMS]) \\\n", + "2016-12-01 09:31:00-05:00 1250.5 0.0 \n", + "2016-12-01 09:32:00-05:00 0.0 611.0 \n", + "2016-12-01 09:33:00-05:00 0.0 0.0 \n", + "2016-12-01 09:34:00-05:00 0.0 106.0 \n", + "2016-12-01 09:35:00-05:00 50.0 0.0 \n", + "\n", + " Equity(535 [ARTW]) Equity(680 [AXR]) \\\n", + "2016-12-01 09:31:00-05:00 0.0 0.0 \n", + "2016-12-01 09:32:00-05:00 0.0 0.0 \n", + "2016-12-01 09:33:00-05:00 0.0 0.0 \n", + "2016-12-01 09:34:00-05:00 0.0 0.0 \n", + "2016-12-01 09:35:00-05:00 0.0 0.0 \n", + "\n", + " Equity(925 [BKSC]) Equity(1031 [BONT]) \\\n", + "2016-12-01 09:31:00-05:00 300.0 1208.0 \n", + "2016-12-01 09:32:00-05:00 0.0 0.0 \n", + "2016-12-01 09:33:00-05:00 0.0 0.0 \n", + "2016-12-01 09:34:00-05:00 135.0 0.0 \n", + "2016-12-01 09:35:00-05:00 0.0 0.0 \n", + "\n", + " ... Equity(50188 [GEMP]) \\\n", + "2016-12-01 09:31:00-05:00 ... 0.0 \n", + "2016-12-01 09:32:00-05:00 ... 0.0 \n", + "2016-12-01 09:33:00-05:00 ... 0.0 \n", + "2016-12-01 09:34:00-05:00 ... 0.0 \n", + "2016-12-01 09:35:00-05:00 ... 0.0 \n", + "\n", + " Equity(50237 [SNDE]) Equity(50285 [AZRX]) \\\n", + "2016-12-01 09:31:00-05:00 0.0 250.0 \n", + "2016-12-01 09:32:00-05:00 0.0 0.0 \n", + "2016-12-01 09:33:00-05:00 0.0 1000.0 \n", + "2016-12-01 09:34:00-05:00 0.0 0.0 \n", + "2016-12-01 09:35:00-05:00 0.0 0.0 \n", + "\n", + " Equity(50327 [TYHT]) Equity(50349 [AMMA]) \\\n", + "2016-12-01 09:31:00-05:00 0.0 0.0 \n", + "2016-12-01 09:32:00-05:00 0.0 0.0 \n", + "2016-12-01 09:33:00-05:00 0.0 0.0 \n", + "2016-12-01 09:34:00-05:00 0.0 0.0 \n", + "2016-12-01 09:35:00-05:00 0.0 0.0 \n", + "\n", + " Equity(50360 [MRAM]) Equity(50369 [BCTF]) \\\n", + "2016-12-01 09:31:00-05:00 540.0 0.0 \n", + "2016-12-01 09:32:00-05:00 0.0 0.0 \n", + "2016-12-01 09:33:00-05:00 0.0 0.0 \n", + "2016-12-01 09:34:00-05:00 0.0 0.0 \n", + "2016-12-01 09:35:00-05:00 0.0 0.0 \n", + "\n", + " Equity(50374 [OTTW]) Equity(50456 [DFFN]) \\\n", + "2016-12-01 09:31:00-05:00 138.0 0.0 \n", + "2016-12-01 09:32:00-05:00 0.0 0.0 \n", + "2016-12-01 09:33:00-05:00 0.0 0.0 \n", + "2016-12-01 09:34:00-05:00 0.0 0.0 \n", + "2016-12-01 09:35:00-05:00 0.0 0.0 \n", + "\n", + " Equity(50476 [GNUS]) \n", + "2016-12-01 09:31:00-05:00 0.0 \n", + "2016-12-01 09:32:00-05:00 0.0 \n", + "2016-12-01 09:33:00-05:00 0.0 \n", + "2016-12-01 09:34:00-05:00 0.0 \n", + "2016-12-01 09:35:00-05:00 900.0 \n", + "\n", + "[5 rows x 933 columns]" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "small_cap_volume.head()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Similar to large cap stocks, we see an uptick in volume at the open and close. However, this occurs on drastically different scales. Not only do small cap stocks trade a lower frequencies and volumes, they also follow a different pattern." + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "collapsed": false, + "scrolled": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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/+Afz58/Hx8eH3r174+DgwIgRIxg4cCBGo5GhQ4fi5uZGaGgoUVFRhIeH4+Liwvjx4+3Z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\niFuVlFSZhaizZ4saloVNBqqgIB/CwnrQr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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "small_cap_avg_volume = small_cap_volume['2016-12-1'].mean(axis=1)\n", + "\n", + "plt.subplot(211)\n", + "plt.plot(small_cap_avg_volume.index, small_cap_avg_volume, color='navy')\n", + "plt.title(\"Intraday Volume Profile - Small Cap\")\n", + "plt.ylabel(\"Volume\")\n", + "\n", + "resampled_small_cap_avg_volume = small_cap_avg_volume.resample('10t', closed='right').sum()\n", + "\n", + "plt.subplot(212)\n", + "plt.plot(resampled_small_cap_avg_volume.index, resampled_small_cap_avg_volume/small_cap_avg_volume.sum(), color='navy')\n", + "plt.title(\"Intraday Volume Profile as % of Total Day - Small Cap\")\n", + "plt.ylabel('Volume as % of Total Day')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "As the graphs below show, small cap stocks trade a very large portion of their daily volume at the beginnig of their day. Often going above 10% in just the first 10 minutes. This is the exact opposite pattern we saw with our large cap stocks. A reason why small cap stocks may not follow the same pattern is because they are rarely included in index fund portfolios. This causes them to be of no interest to one of the largest sources of volume." + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": { + "collapsed": false, + "scrolled": false + }, + "outputs": [ + { + "data": { + "image/png": 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jPfnkk9qxY4cee+wxZWRk+Dw+OzvbkvM+/HC2/vnPA944JaWjnn46yZK2AQAA\nAIRfUpK5+/uQjxR98sknuvLKKyVJF110kQ4ePKiKigq5XC6fjzH75M60aFF3TZq00rDQQlxcVNDt\nOkV2drYl1wHB4TqEH9fAHrgO9sB1CD+ugT1wHewhmMGUkCdF5557rj777DOlpKRo//79io6O9psQ\nWSUuLoo5RAAAAADOUus+RTt27ND111+vwYMHS5Jefvllff7556ZPmJ6erv3792vcuHF64IEHNH36\ndNNtBaKgwKP09Az16vWa0tMz5HYXh+S8AAAAAOyt1pGiJ598UjNnztSMGTMkSUOHDtXUqVO1cOFC\nUyeMjo7Wn/70J1OPDQarzwEAAACoSa0jRU2aNNFFF13kjRMTE9WkScir7oLG6nMAAAAAalKnpGjf\nvn3eeT+bN29ukBuhJia29hsDAAAAcKZah3weeughTZ48Wbm5uUpKSlKnTp00a9asUPTNUnPmDJMk\nw+pzAAAAAFBrUnThhRdqxYoVcrvdatasmWJiYkLRL8ux+hwAAACAmtSaFH3zzTd65513VFRUZCib\ne/rpp+u1YwAAAAAQCrUmRXfffbeGDRum888/PxT9AQAAAICQqjUp6tSpk+68885Q9KVB2bXriAYO\n/Lvc7mLFxUUpM3OCunWLC3e3AAAAAASo1qRoxIgRmj17tnr27GlYivvyyy+v147Z3cCBf1deXpEk\nyeMp0oABb2jfvvvC3CsAAAAAgao1KVqxYoVyc3P1/vvve//mcrn01ltv1WvHrFZQ4NHkyasMq8/F\nxUWZbs/tLvYbAwAAAGgYak2K3G63Nm7cGIq+1KvJk1dp8eIcSVJWVr4kBbUaXVxclDyeIkMMAAAA\noOGpdfPWyy+/XHv37g1FX+pVbm6h3zhQmZkT1LlzrKKjm6hz51hlZk4Iqj0AAAAA4VHrSNEHH3yg\nBQsWqE2bNmrSpIkqKirkcrmUmZkZgu5ZJzGxtXeEqCoORrduccwhAgAAABqBWpOiuXPnhqIf9W7O\nnGGSZJhTBAAAAAC1JkUffvhhjX+/8cYbLe9MfYqLiwpqDhEAAACAxqnWpCg7O9v73yUlJfriiy90\n2WWXNbikyOrV5wAAAAA0DrUmRU8//bQhLi4u1tSpU+utQ/XF6tXnAAAAADQOta4+V11UVFSDXI3O\n6tXnAAAAADQOtY4U3XzzzXK5XN740KFDuvDCC+u1U/XB6tXnAAAAADQOtSZF99xzj/e/XS6XYmJi\ndNFFF9VDs12XAAAgAElEQVRrp+oDq88BAAAAqInPpMjXqnOFhYXatm2b+vTpU2+dqg+sPgcAAACg\nJj6TotmzZ/t8kMvlanBJEQAAAADUxGdSNH/+/FD2AwAAAADCotbV53bv3q3x48frsssuU1JSkm69\n9dYGufocAAAAANSk1qRo+vTpmjhxot5//3299957GjNmjJ544olQ9A0AAAAA6l2tSVFFRYUGDBig\n6OhotWzZUikpKSorKwtF3wAAAACg3tWaFJ0+fVpfffWVN/7iiy9IigAAAAA0GrXuU/TQQw9pypQp\ncrvdkqRzzjlHs2bNqveOAQAAAEAo+EyKDh06pPbt26tHjx5au3atioqKvJu3AgAAAEBj4bN8bvjw\n4brjjju0fv16lZaWKjY2loQIAAAAQKPjMynasmWLRowYocWLF2vAgAGaNWuWdu/eHcq+AQAAAEC9\n81k+17x5cw0bNkzDhg3TDz/8oBUrVujee+9VdHS0brzxRt14442h7CcAAAAA1ItaV5+TpHbt2unW\nW2/VH//4R3Xq1ElPPvlkffcLAAAAAEKi1tXnjh07ppUrV2rJkiUqKSnRjTfeqEcffTQUfQMAAACA\neuczKdq0aZOWLFmi7OxspaSk6PHHH9cll1wSyr4BAAAAQL3zmRTNmzdPN954o5599lm1aNEilH0C\nAAAAgJDxmRQtWLAglP0AAAAAgLCo00ILAAAAANBY+UyKysrKJEmlpaUh60xDUlDgUXp6hnr1ek3p\n6Rlyu4vD3SUAAADA9ux4H+0zKRo7dqwkaeLEiSHrTEMyefIqLV6co6ysfC1enKNJk1aGu0sAAACA\n7dnxPtrnnCKXy6UrrrhCx44d04ABA7x/r6iokMvlUmZmZgi6Z1+5uYV+YwAAAABns+N9tM+k6K23\n3tKhQ4c0bdo0PfXUU6HsU4PQsWOMIU5IiPFxJAAAAIAqiYmtlZWVb4jDzWdSFBERoY4dO+pvf/ub\n8vLylJOTI5fLpV/84hdKSEgIZR9tqbS03BCfPl3u40gAAAAAVebMGSapcoQoMbG1Nw4nn0lRlYUL\nF+rVV1/VxRdfLEn6n//5H915550aNWpUvXfOzj78MM9vDAAAAOBscXFRWrRodLi7YVBrUrR06VKt\nWbNGzZs3lyR5PB7dcsstjk+KAAAAADQOte5T1KRJE29CJEnR0dFq2rRpvXaqPli99F9ycle/MQAA\nAICGodaRog4dOmj69Onq27evJOn9999Xx44d671jVqta+k+Sd2JXMMN28+aN1KRJK21VCwkAAAAg\ncLUmRdOnT9f8+fP1zjvvyOVyqUePHho3blwo+mYpq5f+s2MtJAAAAIDA1ZoURUVF6Y477ghFX+qV\nHZf+AwAAABB+tSZFjYUdl/4DAAAAEH6OSYrsXO5WUODR5MmrDAlbXFxUuLsFAAAAOEKdk6KvvvpK\ne/fuVXx8vH71q1/J5XLVZ79sz8pExupFIAAAAADUXZ2Soj//+c86ffq0unbtqp07d+qNN97Qyy+/\nXN99s7WJE5dp+fKdkioTmVOnSrV06U2m2rJ6EQgAAAAAdedzn6JXXnlFZWVlkqQDBw7ovvvu0+jR\no3X33XfryJEjIeugXW3ZstcQv/feXh9H1q76og8sAgEAAACEjs+Rog4dOmjChAm6++67NXz4cE2c\nOFGSVFJSouuvvz5kHXQCFoEAAAAAwsdnUjRy5Ej1799fzz//vFwul/70pz+pVatWlpx0+fLlev31\n19WkSRP9v//3/9S/f39L2g2l3r07a82ab71xnz6dTbdl50UgAAAAgMbOZ/mcJLVp00ZPPfWUrrvu\nOt11111avnx50CcsLCzUyy+/rIULF2ru3LnauHFj0G2GQ7NmxpeuaVO/LyUAAAAAm/J5J//ll19q\n6tSpuuOOO7RmzRr94Q9/0IEDB/S73/1Oe/bsMX3CrVu3ql+/foqKilJ8fLyefPJJ022FU37+cb9x\nIAoKPEpPz1CvXq8pPT1DbndxsN0DAAAAUEc+y+emT5+uF154Qe3bt9fu3bs1Y8YM/fWvf9W+ffs0\na9Ys/eUvfzF1wv3796u4uFiTJk1SUVGRfv/736tPnz6mn0C4dOwYY4gTEmJ8HFk7luQGAACAU9hx\nj06fSZHL5VJ+fr7Ky8t14MABNW3aVJLUpUsX0wmRJFVUVKiwsFCzZ89WXl6exo8fr3fffdfvY7Kz\ns02fr74cOeI2xIcPu03388sv958V2/E527FPTsR1CD+ugT1wHeyB6xB+XAN74DrU3dSp2dqw4YCk\nygGBo0eP6umnk8LaJ59J0bPPPqu3335bbrdbnTt31syZMy05YXx8vHr27CmXy6UuXbqoZcuWcrvd\niouL8/mYpKTwvkg1+frrf1aLj5vu58UXf6ecnGNnxJ1s95yzs7Nt1ycn4jqEH9fAHrgO9sB1CD+u\ngT1wHQJTWPhJtdhlyesXTGLqMynq0qWL7rnnHtMN+9KvXz9NmzZNt99+uwoLC+XxePwmRE7AktwA\nAABwisTE1t4pI1VxuPlMiupL+/btlZqaqrS0NLlcLj3++OOh7oIlkpPP1bJl33jj/v3PNd0WS3ID\nAADAKew4IBDypEiS0tLSlJaWFo5TW2bevOs0adJKW11MAAAAwO7sOCAQlqSoMbDjxQQAAAAQOHYc\nBQAAAOBoJEUmseEqAAAA0DhQPmcSG64CAAAAjQMjRSbl5hb6jQEAAAA0DCRFJlVfT90O66sDAAAA\ndmfHaSiUz5k0Y8ZAbd26T253seLiojRz5tWm2yoo8Gjy5FWG5b3j4qIs7C0AAABgD7fdtlxLl1bu\n95mVla+SkjItWTImrH0iKTLpkUc2KS+vSJLk8RRp2rSNpucUMT8JAAAATrF58x6/cThQPmfSzp0F\nfuNAMD8JAAAACB+SIpOOHPH4jQPRsWOMIU5IiPFxJAAAANCwJSd39RuHA0mRSeec09JvHIjS0nJD\nfPp0uY8jAQAAgIbtuecGqXPnWEVHN1HnzrF6/vnUcHeJpMisn/0szm8ciK1b9/mNAQAAgMaiam6+\nx1OqvLzKufnhxkILJs2ZM0ySDCvGmXXixGm/MQAAANBY2HE+PUmRSXFxUZatEBcV1USnT5cYYgAA\nAKAxSkxs7V1xuSoON8rnbOCqqxIN8cCBiT6OBAAAABq2GTMGGuYUBbPfp1VIimzg979PUsS/r0RE\nhHTXXb3C2yEAAACgnkyZst4wp2jKlHXh7hJJkVkFBR6lp2eoV6/XlJ6eIbe72HRb1123SOX/XnCu\nvFwaNux/bdM3AAAAwEpbtuw1xO+9t9fHkaHD5BWTJk5cpuXLd0qSsrLydepUqZYuvclUWydPlvmN\nAzV58iotXpzj7Zsky+Y/AQAAAI0NI0UmWZnhtmgR6TcOlB1X9AAAAAAk6bLLOhjipKQOPo4MHZIi\nG9iyZaKioiLlcklRUZHasmViUO1VX8HDDit6AAAAAJL09ddHDHFOzhEfR4YO5XMm9e7dSWvW7PbG\nffp0Mt1WUlKCPJ5HreiWJGv3UAIAAACsVFh40m8cDowUmdS8uTGfbNbMPvllRUVFuLsAAAAA1Cgu\nLspvHA72uZNvYPbvL/IbhxMLLQAAAMCulixJV3Ly33TyZJlatIjU0qVjwt0lRorMsvO8HRZaAAAA\ngF09++xWFReXqaJCKi4u0zPPfBDuLjFSZJad5+0kJrb2jhBVxQAAAIAd7NzpNsS7drl9HBk6JEUm\nxcVF2bYkzcqEraDAo8mTV+nLL/fr4ou/05w5w2xR9wkAAICG6dAh47STgwfDPw2FpKgRsjJhO3N+\nUk7OMUnMTwIAAIB5J06c9huHA3OK4BfzkwAAAGAlj6fUbxwOJEXwy84LSgAAAKAhqr59TPi3k6F8\nzgaq5u2cOQfILvN2quYjVc4p6mSrBSUAAADQ8FTfU9MOe2ySFNnAuHHvaM2a3ZIq9xU6frxEq1aN\nDXOvKlXNT8rOzlZSUlK4uwMAAIAGzuWKkFReLQ6v8PcA2rAh1xCvX/9dmHpytoICj9LTMzR+/Bal\np2fI7S4Od5cAAADQgMXENPUbhwMjRTZQWlruNw6UleV4rD4HAAAAKyUlddDGjXu88a9+1SGMvalE\nUmQDLpd0ZimlyxVce2cmMlWbuJpNZFh9DgAAAFb6+usCQ5yTU+DjyNChfM4GmjZ1+Y0DZWUiw+pz\nAAAAsFJh4Um/cTgwUmQDkZGRkkqrxeYlJrb2jhBVxWax+hwAAACsFBcXJY+nyBCHGyNFNlBWVuY3\nDtSMGQPVuXOsoqObqHPnWM2cebXptqpWn/v736/UokWjbfGmBQCEF4vwAAjG3/42QhH/zkIiIqQ3\n3xwZ3g6JpMgWqudAQeZEeuSRTcrLK5LHU6q8vCJNm7YxuAYBADhD1dzVnJxjWrw4R5MmrQx3lwA0\nILfcslzl/15XrLxc+u1vl4a3QyIpMq3qV7JevV6z3a9kLI4AAKhPfM8ACEb1+2Y73Eczp8gkK1d4\na9++pfLzjxviYCQkxBriTp1ifRwZelYuFw4ACA8r564CcB47zikiKTJp5063Id61y+3jyNq9994t\nGjDgDbndxYqLi1Jm5oQge1dhjCoqfBwXerfdtlxLl34jqTKZLCkp05IlY8LcKwBAIFiEB0AwMjMn\nWHzvGzySIpOOHDlhiA8fPuHjyNp16xanffvuC7ZLXmeOOtUUh9PmzXv8xgAA+6tahCc7O1tJSUnh\n7g6ABqZ16xbq27eLt3KoTRtGihqs+Pho5eUVGWK7oKwBAAAAdmXlNBSrkBSZdMEFbfXZZ4cMsV1U\nlTGcOW/HLpKTu2rZsp2GGAAAAM5hx8VaSIpMsnPiYac5RNXNmzdSkyattOXrBgAAgPpnx6omkiKT\nquqp7ciOQ5JV7Py6AQAAoP7ZcXCBpKgRsuOQJAAAACDZ80dyNm81yc6bt1YfggxmSLLqeY4fv8V2\nzxMAAACwAiNFJk2cuEzLl1cuGJCVla9Tp0q1dOlNYe5VJSuHJM8sxcvJOSbJPqV4AAAAgBVIikza\nsmWvIX7vvb0+jgw9K4ckKcUDAABAY0f5HPyyshTP7uxcEgkAAID6Q1JkUnLyuYa4f/9zfRwZert2\nHVGXLi+oZcsZ6tLlBe3e7Tbd1owZA9W5c6xatIhQ586xmjnzagt7ai9VpYJZWflavDhHkyatDHeX\nAAAAEAIkRSbNm3ed0tK66/LLE5SW1l2vv35duLvkNXDg35WXVySPp1R5eUUaMOAN02098MAG5eUV\n6eTJcuXlFen++9db11GboVQQAADAmZhTZJIdlxKsUlBQ7DcOxObNe/zGjYkdNxIDAABA/SMpapQq\naolREztuJAYAAID6F7byuVOnTiklJUVLly4NVxcarW7d2viNA5Gc3NVv3JhUjf5t3367Fi0arbi4\nqHB3CQAAACEQtqRo9uzZat2a8qT60L17O79xIObNG6m0tO7q3r2V0tK6a968kcF2zzKsFgcAAAAr\nhKV87rvvvlNubq769+8fjtM3evff30crVnyjkyfL1KJFpB58sJ/ptqpGT7Kzs5WUlGRhL4N35say\nVXOB7DrPCwAAAPYVlpGiZ555Rg8//HA4Tu0I11+/WMXFZaqokIqLyzRy5MJwd6lesFocAAAArBDy\nkaKlS5fq8ssvV0JCgiSpoqL2RQCys7Pru1uNypEjJ86KrXgNrWijsLBEs2b9S/v3e5SQEK2pU3+p\nVq2amWorOrrsrNgJ7xUnPEe74xrYA9fBHrgO4cc1sAeuQ8MW8qRo8+bNysvL0/r163Xw4EE1b95c\nHTp0UJ8+fXw+xm5lW3YXH79ZeXlFZ8QtTb+Gu3Yd0cCBf9eRIycUH99SmZkT1K1bnOm+XXfdP7Rh\nwwFJUk7OMbVsGaulS28y1Vbr1jslHTojbtXo3ytWlDEWFHg0efIqwyp7LCpRd3YsJXUiroM9cB3C\nj2tgD1wHewgmMQ15UvTHP/7R+99/+ctf1LlzZ78JEQK3ZEm6kpP/5p1TtHTpGNNtDRjwpvLzj0uS\n8vKKlJz8N+3fP8V0e1u27DXE772318eRtavql68YNWMuFgAAgFHYVp9D/Xn22a2GOUXPPPOB6bYO\nHjzhNw6n6purstlq3TAXCwAAwCism7feeeed4Ty9bVhdzmTlTW/1OV91mQPmT3LyuVq27Btv3L//\nuabbYrNVcxITW3tHiKpiAAAAfxp7+X1Yk6KGzMo3htXlTFbe9MbGNtWPP542xMF45JErtH79t97S\nvkcfTTbdVtVy4QgMySQAAAhUYy+/Jykyyco3htXlTDNmDNTWrfvkdhcrLi5KM2debbqtX/2qozZt\n+s+8n8sv7xhU36qWC5f+s1z4vn33BdUmAkMyCQAAAtXYy++ZU2SSlW8Mq+fGPPLIJuXlFcnjKVVe\nXpGmTdtouq0dO44a4q+/PurjyLopKCj2GwfWlkfp6Rnq1es1padnyO023xYAAAB8a+xzuRkpMsnK\nEjWry5l27nQb4l273D6OrF1hYbHfOHDV5ySZn6PU2IdxG4rGXmMMAAAaf/k9SZFJVr4xrC5n+uEH\n49LUhw6ZXzEuLi5KHk+RIQ5Gt25t9OWXRwyxWTt3FviNERokpwAANH6NvfyepMgkO78xjh8vqRaf\nMt2WlXseSVL37u0MSVH37u1Mt3XkiMdvjNBo7DXGAACg8WNOUSMUGRnhNw6ElXseSZUjbGlp3XX5\n5QlKS+se1AjbOee09BsjNBp7jTEAAGj8GClqhJKTu2rZsp2G2CyrRwGsHGHr0MGYBHXsGGNJuwhM\nY68xBgAAjR9JUSP03HODlJ19wLsk9/PPp5puKyEh1hB36hTr48i6sXJS/mefHTTEn356IKi+wRw7\nl5ICAOBULIQUGJKiRqhqSW5J8ngql+Q2e9N66tRpv3GgrJyUf+zYKb8xAACAU7EQUmCYU2QDVu+3\nY+WS3B99lG+It23L93Fk3VhZjlf91w5+/QAAAKjEQkiBISmygapMPisrX4sX52jSpJVBtXfkiHEJ\n7sOHzS/JXVZW5jcOlJXleJmZE9S5c6yio5uoc+dYZWZOCKpvAAAAjQULIQWG8jkbsDqTj4+P9pbP\nVcVmlZSU+40DZWU5Xrducdq3776g+gMAANAYsRBSYEiKbCAxsbW31rMqDsYFF7TVZ58dMsRmuVwu\nv3GgrC7HA4DGiknSAILBQkiBISmyAasz+fvv76MVK77xbrj64IP9TLfVunVzFReXGuJglJWV+40B\nAJWYJA0AoUNSZANWZ/IjRy5ScXHl3J/i4jKNGPEP7d8/xVRbPXt21IED3xriYERHN9WPP5YYYgDA\n2ZgkDQChw0ILNmD16nOHDp3wGwfi8GGP3zhQJ0+W+o3DyerrAADBYJI0AIQOI0U2YHWJRESES2Vl\nFYbYLKvnO9mZnUtVquYWfPnlfl188XfMLQAcgEnSAOyksc9zJCmyAatLJK65JlFr1uz2xikpiabb\nqvoSrrwZ7xT0l3Lz5pHVYvu8Be1cqnJmwpaTc0ySfRI2APWDSdIA7MTOPx5bgfI5G7C6RGLBghuU\nltZdl1+eoLS07po//wbTbVVUVNR+UADOXLShMja/JLfV5W5W7qFkNTsnbAAA1CfK282x+nXbubPA\nb9zQ2ednegezukTCyl8XrR6hiIyM8BsH4rbblmvp0m8kVf5iUVJSpiVLxphuTzImgMEkhFYPMTup\njNFKjX2oHwCcoLGPUNQXq1+3I0c8fuOGjqTIBuxcImH1CEVyclctW7bTEJu1aVOu3zhQ+fnH/caB\nsPqDyOoyRqfgixQAGj6qJcyx+nU755yWyssrMsSNCeVz8Mvq0r5580YaSvvmzRtpui2P57TfOFBW\nls9Z/UFUlTj//e9XatGi0Yx21BFfpADQ8LESozlWv24/+1mc37ihY6QIflk9QmHtHCWXjCVv5lfZ\nq2Rd+RzlbvbAdQCAho+VGM2x+nVr7NeBpAh+Wb3QwsSJy7R8eWX5XFZWvk6dKtXSpTeZaismpqkK\nC08Z4mBYWT7X2D84GgquAwA0fHaeZmBnVr9uVt8T2g1JEfw6czGDnJxjQS9mkJn5vSF+993vazyu\nLvr06WxYerxv386m25KsHVWw+oOIfYrM4YsUAABrWL/Alb2QFMGvzZv3+I0DdfaS3KU+jqxds2bG\nPY+aNo30cWTd2HlUgX2KAABn4scyhJrV94R2Q1KEkGrZ0ljy1rKl+ZK33buP+o0DZeWogtVLQbNg\nAADgTPxYBliL1efgV+/eCX7jQPXp08UQ9+3bxceRtdu92+03DqeqL6usrHwtXpyjSZNWBtVex44x\nhjghIcbHkQ0bG/QBCJadP0es7Bs/ltlD1TUdP36L7d5vVrvssvaGOCmpvY8jGyZGiuBX8+ZN/caB\nKzdEFRXlPo6rXWlpmd84UFaO7uTk/OA3DlREhHFlPZcr2JX27Il9hVAbSoZQGzt/jljZN1bXtAcn\njdh9/XWBIc7JKfBxZMNEUtQIWXlzv39/kd84UB9+uN9vHIjSUv9xoKz8svr226N+40BZfR3sil8+\nURsn3YDAHDt/jljZNzb1tgc7v9+sdvToSb9xQ0f5XCNkZemW1Rt/nThx2m8ciOorQwa7UqSVH2wl\nJeV+40DZeeM6K8tB7Pw8YQ9OugGBOVZ+jlhdimdl3+y8qbedSxit5qzvreo3Wo1riW5GihohO/8S\nZeVCC1azshQhIkIqLzfGwbDzL4JWjrDZeQVA2AMlQ6iNlZ8jVpfiOeUzzs4ljFaz8/ez1X7609aG\nErqf/rRxff6SFDVC9bHfTnZ2tpKSkoLuW//+52rZsp2G2Kz27aN16JDHEAfj/vv7aMWKb3TyZJla\ntIjUgw/2M91WmzYtdPhwsSEOhtXXwUpWzp9iXyHUxkk3IDDHys8Rq0cmnfIZ56QRXTt/P1utqKjE\nb9zQUT7XCM2ZM0xpad11+eUJSkvrbqubhnnzRhr6Nm/eSNNtffDBrercOVbR0U3UuXOsPvjg1qD6\nNnLkYhUXl6miQiouLtOIEQtNt1VSUuY3DpSVq9vs2nVEXbq8oJYtZ6hLlxeCXrXPyqXRnVRyAXPs\nXDKExsdZpVHWsfp1s/K7we7fM3buX3x8tN+4oWOkqBGy8y9RVvatW7c47dt3nyVtSdLBg0V+40Ac\nP37abxwoKyeXDxjwd+XnVz43j6dIyclvaP/+YF7H6ivhmV8Zz0klFwDszynlblaz+nWz8rvB7t8z\ndu7fBRe01WefHTLEjQlJERqsXbuOaODAv8vtLlZcXJQyMyeoW7c40+1ZuXBDWVmF3zhQVpYiHDp0\n3G8cqLZto5SXV2SIzXJSyQUA+7Pzj4x2ZvXrZuV3g92/Z+zcv8b+IwHlc2iwBg78u/LyiuTxlCov\nr0gDBrwRVHuxsU39xuEUH29MNM45x3ziUX3Po+pxoDIzJxjKGDMzJ5huKyEh1hB36hTr48i6sXMZ\nAsxx0kaJACpZWY5n95JIO/evKtndvv32Rlm+zEgRGqzqN0PB3hz16NFBW7bs88Y9e3Yw3ZbVq899\n/vkhQ3zm8HWgrrnmp1qz5jtDHIzWrVuob98u3l+O2rQJ5kPSOKJWEeQ663YuQ4A57FMEOI+VIxR2\nH+2wsn9WV9RYuQ+mHZEUocFq3bqFPJ7jZ8TB/cM8c8U+Sfroo3wfR9buvPNa6dtvjxniYLjdHr9x\nIP7856G66qo3vR+SL710bVB9mzhxmZYvr1xRMCsrX6dOlWrp0ptMtZWff9xvHCg7lyE09i+X+mL1\nNXXKdXDK87Q7roM5VpbjWV3aV3VNK1fE/C7oa2pl/6oqaqTKOcQDBrwR1FzscePe0Zo1uyVVft8f\nP16iVavGWtJXOyApQkhZ+YXw85/HGW6af/7zNkH17dSpMr9xIE6eLPcbB866xQymTFlv+JCcMmWd\n6SRGkjIzvzfE7777fY3H1YXVe9DYeU8bRrHMsfqaOuU6OOV52h3XofG57bblWrr0G0mVo9clJWVa\nsmSM6fasvE8qKCj2Gwdqw4bvDPH69buDas9uSIoQUlZ+IXzyyQ9+40BZudDCOee0NCw+cM45Lc03\nJqlZs0idPFlmiM3asmWvIX7vvb0+jqwbK/ctsLqswcr2rP410M6jWHZm9T5FTrkO9TXCZtW/B6ew\n8/uNUSxzNm/e4zcOlJX3SdVL0IMtSS8trfAbN3QkRQgpO38hWOlnP4vTp58eNMTBiIyM8BsHoqys\nzG8cKJfLZfigdbnMj2IVFJzQ1q375HYX68CBIh09WhzUl3KwXwBnsnoui51HsezM6o0SnXId6nOE\njblddWfn9xujWOZY/Z1q5X1Skyb+Yxjx8iCkrPxCSE4+V8uWfeON+/c/N6i+RUZKZ36WRZofjLF8\nxOPii+O1ZUueN/7lL+NNt3XqVLnfOFDt20frwIEThtgsq+ufrfyStzqht/tkX6dwynWw+nk65Qcu\nq9n5/eaUa2r1iJiVpfeStauwFheX+Y0D1bSpS6dPVxjixoSkCCFl5RfCvHnXadKklZZ9ubRq1Vxu\n9ylDbJbVEzm3bz9giD/66ICPI2t3+nSZ3zhQW7ZM1IABbxhWtzHL6vpnK7/krf6F18pRLJjnlH1o\nrH6edh7xsDM7v9+cck2tHhE7M0moKQ7UqVOn/caBiIhwGfZJDHYLjt69E7Rly35D3JiQFCGk7LyC\nzI8/lviNA2H1MphW/hJVXu4/DlS3bnFBjeYYVf8yCe7LpWPHGEOckBDj48jazZgxUFu37tORIycU\nH99SM2deHVTfnFSqwlyFxsfquV0IPzuPYlnJ6hGxyEiXyssrDHEwqq98u22b+ZVwW7ZspsLCU4Y4\nGF9+WeA3buhIioB/s3ICYZ8+87yjHB5PkXr3/qsOH34wqP45wbnnttKOHW5DHIzqv4oFM9/pkUc2\neUv78vKKNG3axqCSGKeUqkjOSgDtyurE1Oq5XQg/K39otPMPIVaPiF1zTaJ3mWpJSklJDKo9K/Xp\n0wSDvvMAACAASURBVEVr1nzrjfv27RJUe1Yv3GA3JEXAv1lZK1u97OvIkeDKwKzUvLlLp05VGOJg\nWPnld/z4ab9xoL7//pgh3rPnmI8ja2d1EmNl3bjVrL6hsfK1s3rVMzvfvFmJxBShZOf3m9UjYgsW\n3KBJk1ZaNmpq5XzpZs2MizI1bRrcTvLNm0dWixtXGtG4ng0QhOTkrtq48T9Lafbv3zWMvak/q1aN\n1aBBC1ReLkVESKtX/yao9qzczC0+PtqwlHl8vPlFGyTp4MEiQ3zgQJGPI2tn9a+LJSXW1Y1bzeob\nGitfO6tXPbPzzZuVnDQyCXOs/IFg584Cv3E4+2Z16b3Vo6aPPHKF1q//VidPlqlFi0g9+miy6baq\n/xAYzA+DUk2l/KVBtWc3JEXAv8XGtjDEMTEtfBwZelaOYj333FbvPKLycum55z7QwIHnmW7vn//M\nNcTVN3cLRNeurfTZZ4e8cbDlc4cPn/AbB8LqOUUffJDnNw6nnTvdhnjXLrePI+vGyl9mrb65d0qy\n4JRJ9DDPyh8Ijhzx+I3D2Te7u+66hd5V4oqLyzR8+P8qP/9+U21ZfR2ql6AHU5JuR8GNowGNyP79\nRX7jQPTu3cFvHKhrrjEmLSkp5pOYjRu/N8T//Of3NR5XV2dOMK0pDkRpqXHVh9Ong1wFQtU/sM1/\ngD/wwAbl5RXp5Mly5eUV6f771wfVs+LiUr9xOB05Yl0yKf3nl9Tt22/XokWjgypPq34zH+zNvdXt\n2dWMGQPVuXOsoqObqHPn2KCTejQ+Vv5AUH3D8mA3MLe6BDc9PUO9er2m9PQMud3BlbdXtTd+/BZL\n2jt0yOM3DoTV1yE52VjKF+xWKHZDUgT8m5U3Rx06tPIbB2rBghuUltZd3bu3Ulpad82ff4PptqxM\nYiSpdetmfuNAfPhhnt84UO3aRfuNA7Fp03d+40C1bNnUbxxO1csWgy1jtNKcOcMM/xaCrd93SrJQ\ntVCIx1PqXSgkGFbfCCL8rPwOrL5hebAbmFvZt9tuW67Fi3OUlZWvxYtzdOuty4LqW1V7OTnHLGnP\nysUMOnQwJkHVV2QN1HPPpRg+L597blBQ7dkN5XPAv1WVR1Utox3MzZGVo06StTXL7du3VH7+8TPi\n4D4kmzZtIulUtdicsrJyv3Ggli+/ScnJf/PWZq9YcbPptoqKTvuNA5WUlKCNG/9Tenj55eb3e7B6\nsQCryxitZH39/ibDhsHBripoV1aXCVo9t8tKTlk8w2pWlrlavZiBle1t3rzHbxzu9mJimhq+X2Ji\nzP9g9sknBw1xdrb5PQ6l/1RMSJWfl/ffv15LlowJqk07ISkC/s3KmyM71++/994tlm22Kkk//njK\nbxyImJhmhv2hYmKC21Ph2We3Gmqzn3nmA9PX1OWSzvzBLthS6pycHwzxl1/+4OPI2lldb291GaOd\nb1Ktnj9lV1Z/Jtl5Lpad55/Y+d+CnfcRtPPSz1YvUx0T06xaUmT+e9DqOUVWJ4B2Q1IE/JuVX/J2\n3gSvdesW6tu3i7dvbdoE94UcG9tMHk/pGXFz0221atXCMIrVunVwi11YeU3btWupgwdPGOJgHDt2\nym8cCKtvUK0uY7TzTaqV86esvuG1sj2rP5Ps/MMPCVvjY+Xr1rt3gtas+c4QByMqqolhg9SoqOBu\nrdu2jdaBAycMsVkRES6VlVUYYvgWlqTomWee0SeffKKysjLdcccdSklJCUc3AAMrv+St/pXMSrfd\ntlxLl1bugZCVla+SkrKghr/P/pXM/KjC998fNcS5uUd9HFk3sbHGj7if/MT8R94FF8QZkqILLgiu\nRj4uLkoeT5EhNqt6nXhCQnAlkVaz802qlcvAW7k8vWTtjWBBwQlvefCBA0U6erQ4qPdcVVJl1d4s\nVmrb1vhjSny8fVYStfO/BTuPYln5urlcEX7jQHXoEGtIYjp0CG7PuYICj984EMnJXaptNRLc5q3J\nyV21bNlOQ9yYhDwp+uijj/Ttt99q4cKFKiws1KhRo0iKYAt2Ht2xcsNKq4e/f/ih2G8cCKvLEDZv\n3muIMzP3+jiydh9+uN9vHKjMzAmWlTFW//Uv2GVSrf4l1cofHKzevPWCC9oa5k9dcEFb021ZuTz9\n/2/vzqOjrNL8gX9T2VNkJQtgEH4imI4DLdL0gUZIiIyOy4yOg2AfRRnUthGl+zRoQ3D0nOlfQ4un\n6dM2B5Uh2M3gEURlcWEVWc4ROmmWtJF2YVFZDCEbSaqy550/clLmvkle8r73SVWR+n7+e7B8udSt\nt+o+7733uYDsQDAn58++gZvXW4vJk9c6LvMLyO/tkvT3v19S4uLiSz288sqkE4VgfoAxZ85WbNvW\nPuAtKrqAxsYWbNny0wC3qp3kd4j0TPjQoQk4duz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lrmKlW5J76tThlnEgmat/JSX1zypP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\n+53i4mI899xzqKysRHh4OBITE1FQUIBFixZ1ee937dqFNWvWwOVyYda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xw5gkSdLx/PADDB0a7Ac7fBjOPhv694cHHoCiRcNdnaTTgGFMkiTpz/71Lxgy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\nJcGPcWYNAMqGJx0R6Ybony7PIOfPn9f27dv1+uuvS5I6duy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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "small_volume = intraday_volume_profile_data(small_cap_volume)\n", + "\n", + "plt.scatter(small_volume.minute_of_day, small_volume.interval_pct*100, color='navy')\n", + "plt.title('% of Volume in 10 Minute Intervals - Small Cap')\n", + "plt.xlim(0, 400)\n", + "plt.ylabel('% of Volume')\n", + "\n", + "intraday_profile(small_volume, 'Intraday Volume Profile - Small Cap', '% of Day\\'s Volume in Bucket', 'Cumulative % of Day\\'s Volume')\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "How about if we looked at the small and large cap profiles on one plot? Below is the % of volume in each bar for large vs small cap stocks. It's clear that a large part of the daily volume for small cap stocks come out during the morning, whereas a lot of the trading for larger cap stocks occurs right before the close." + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": { + "collapsed": false, + "scrolled": false + }, + "outputs": [ + { + "data": { + "image/png": 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pjImIiIiIUxiGwfH0OJadXFd+T1iP4C7c02V8nQxhDofBwq9Psnx7Ik38Lfzm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\nDD179mTChAkMHDhQL5QiIufgMTysTFvDR9sXU+goplm9aO7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S0mLAwGQ6/+PKU1ycxeTJ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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "intraday_groups(large_volume, small_volume, '% of Day\\'s Volume in Bucket', 'Cumulative % of Day\\'s Volume')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The following graph is to give an idea of the true difference in magnitude of volume in small and large cap stocks. Quantitative strategies often find price discrepencies or miscalculations of fair value as sources of alpha. These are plentiful in thinly traded stocks. However if there isn't enough volume to complete the trades then the investment ideas have no value. Further, stocks that don't trade very often are culprits for very bad slippage. It's important to understand why volume constraints can eat away all of your returns and even put you in the red." + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": { + "collapsed": false, + "scrolled": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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CAAAAgBZYrbb/CE0AAAAA0Iz6ekmi0gQAAAAAzfomNFFpAgAAAIDm1NVJotIE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\nR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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.plot(large_cap_avg_volume.index, (large_cap_avg_volume), color='r')\n", + "plt.plot(small_cap_avg_volume.index, (small_cap_avg_volume), color='navy')\n", + "plt.legend(['Large Cap', 'Small Cap'])\n", + "plt.ylabel('Volume')\n", + "plt.xlim(large_cap_avg_volume.index[0] - pd.Timedelta(30, unit='m'), \\\n", + " large_cap_avg_volume.index[-1] + pd.Timedelta(30, unit='m'))\n", + "plt.title('Comparing Volume Magnitudes')\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Volume - Q500 vs. Others" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Doing a similar analysis on Q500 stocks versus stocks in neither the Q500 or Q1500, we find surprisingly similar intraday profiles. Although the magnitudes of volume are drastically different, the distribution throughout the day seem very similar. This points to an important issue when trading outside of the Q universes. A strategy that seems sound in research can fail to launch if there isn't enough volume to support it. Imagine a model that prescribes optimal portfolio weightings on a number of stocks. This model would be based on the idea that you would be able to trade when you'd like and you would be able to complete your whole order at one price. However, this is rarely the case. Trading within the Q universes though ensures that there is always plenty of volume. Another characteristic of the Q universes is that classes of hard-to-trade financial instruments like OTCs, ADRs, and LPs are removed. This ensures that only the stocks most easily electronically traded are included in your strategy. At Quantopian, we strongly prefer algorithms that trade within these universes as explained in [How to Get an Allocation](https://blog.quantopian.com/how-to-get-an-allocation/)." + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": { + "collapsed": false, + "scrolled": true + }, + "outputs": [], + "source": [ + "all_Q500_data = get_pricing(Q500_assets, frequency='minute',start_date='2016-12-1', end_date='2016-12-31')\n", + "Q500_volume = all_Q500_data['volume']\n", + "Q500_volume = Q500_volume.tz_convert('US/Eastern') # Q data comes in as UTC\n", + "\n", + "all_other_data = get_pricing(np.random.choice(other_assets, size=500), frequency='minute',start_date='2016-12-1', end_date='2016-12-31')\n", + "other_volume = all_other_data['volume']\n", + "other_volume = other_volume.tz_convert('US/Eastern') # Q data comes in as UTC" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Looking at the overlapped profiles below of Q500 stocks and stocks not in any of the Q universes, we see a similar pattern. The bars represent the percentage of the day's volume that occurs within that 10 minute interval, while the line plots are the cumulative percent of that entire day's volume. It seems that trading inside and outside of the Q500 wouldn't matter! Before we can say that, let's look at the actual magnitudes of volume." + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": 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bw7iu40rZUxgTEREREbkKp3PSee+3LzmSkUBtv5o8ddsDbN2Rw9SFMXh7uvHy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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "Q500_volume_data = intraday_volume_profile_data(Q500_volume)\n", + "other_volume_data = intraday_volume_profile_data(other_volume)\n", + "\n", + "intraday_groups(Q500_volume_data, other_volume_data, '% of Day\\'s Volume in Bucket', 'Cumulative % of Day\\'s Volume', 'Q500 vs. Other Stocks - Volume', 'Q500', 'Other')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The plot below shows the true extent to which volume amongst the two classes of stocks differ. Although the shapes may seem the same, placing even relatively small orders outside of the Q universes can cause really huge adverse price movements." + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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ls9k0a9asin8xBtmcJfuEVUxycrJrPhdVF+cBJM4DXMa5AInzoKrJycmRJNe1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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "Q500_volume_timeOfDay = Q500_volume.groupby(Q500_volume.index.time).mean()\n", + "plt.plot((Q500_volume_timeOfDay.mean(axis=1)), color='r')\n", + "\n", + "other_volume_timeOfDay = other_volume.groupby(other_volume.index.time).mean()\n", + "plt.plot((other_volume_timeOfDay.mean(axis=1)), color='navy')\n", + "\n", + "plt.legend(['Q500 Volume', 'Other Stocks Volume'])\n", + "plt.ylabel('Volume')\n", + "plt.title('Comparing Volume Magnitudes')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Volatility" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "As there is no measure of volatility available as a field from get_pricing(), we will have to calculate our own intraday metric. The standard measure for volatility is to use percentage changes in close-to-close prices. However, this won't help us in understanding intraday trading patterns and would not be using the rich OHLC data we have access to. Instead, we will use the Garman and Klass estimate of realized variance as explained in this paper by [Almgren (2009)](http://cims.nyu.edu/~almgren/timeseries/notes7.pdf). This estimate is the most powerful for stocks that exhibit Brownian motion, even though it assumes that there are no price jumps. Price jumps are when the close price of one bar is not equal to the open bar of the next. Since we are calculating volatility intraday, this may not be as big of an issue for us. The Garman-Klass Yang-Zhang extension may be the answer for individuals who are worried about this drawback. For demonstration purposes, the Garman and Klass estimate is quite powerful and much more efficient than the close-to-close metric." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "$$\\sigma^2 = RV_{GK} = \\sum^N_{i=1} \\left(\\frac{1}{2}\\left(H_i - L_i \\right)^2 - (2 \\log 2 -1) \\left( C_i - C_{i-1} \\right)^2 \\right)$$" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We will measure volatility over 10 minute bars, with $N = 10$; $H_i =$ high of the asset in the $i_{th}$ minute; $L = \\text{the low}$; and $C = \\text{the close}$." + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "def GK_sum(open_price, high, low, close_price, close_tm1):\n", + " return 0.5*((high - low)**2) - ((np.log10(4)-1)*((close_price-close_tm1)**2))\n", + " \n", + "def GK_var(df):\n", + " df['variance'] = GK_sum(df.open_price, df.high, df.low, df.close_price, df.close_price.shift(1))\n", + " \n", + " return pd.DataFrame({'variance': df['variance'].groupby(pd.TimeGrouper('10t', level=1)).sum()})\n", + "\n", + "def intraday_volatility_profile_data(ohlc_data):\n", + " \n", + " # calculate variance on a per stock basis\n", + " groups = ohlc_data.groupby(level=0).apply(GK_var)\n", + " \n", + " # take the mean of all variances\n", + " ten_minute_variance = pd.DataFrame({'variance': groups.groupby(level=1)['variance'].mean()})\n", + " ten_minute_variance['minute_of_day'] = (ten_minute_variance.index.hour - 9) * 60 + (ten_minute_variance.index.minute - 30)\n", + " ten_minute_variance['time'] = ten_minute_variance.index.time\n", + " \n", + " print ten_minute_variance.head()\n", + " \n", + " # calculate daily variance\n", + " dailySum = pd.DataFrame(ten_minute_variance['variance'].resample('d').sum())\n", + " dailySum.columns = ['daily_variance']\n", + " dailySum['day'] = dailySum.index.date\n", + "\n", + " # calculate interval variance\n", + " conversion = {'variance' : 'sum', 'minute_of_day' : 'last', 'time':'last'}\n", + " interval_data = ten_minute_variance.resample('10t', closed='right').apply(conversion)\n", + " interval_data['day'] = interval_data.index.date\n", + " interval_data['time'] = interval_data.index.time\n", + "\n", + " # put them together\n", + " intraday_data = interval_data.merge(dailySum, how='left', on='day')\n", + " intraday_data['interval_pct'] = intraday_data['variance'] / intraday_data['daily_variance']\n", + " \n", + " return intraday_data" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Volatility - Large Cap" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Let's look at some data now." + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " variance minute_of_day time\n", + "date \n", + "2016-12-01 09:30:00-05:00 93.328003 0 09:30:00\n", + "2016-12-01 09:40:00-05:00 33.156486 10 09:40:00\n", + "2016-12-01 09:50:00-05:00 96.613625 20 09:50:00\n", + "2016-12-01 10:00:00-05:00 103.243739 30 10:00:00\n", + "2016-12-01 10:10:00-05:00 105.477321 40 10:10:00\n" + ] + } + ], + "source": [ + "large_cap_data = all_large_cap_data\n", + "\n", + "large_cap_data.major_axis = large_cap_data.major_axis.tz_convert('US/Eastern')\n", + "large_cap_data = large_cap_data.transpose(0, 2, 1).to_frame()\n", + "large_cap_data.index.names = [\"assets\", \"date\"]\n", + "\n", + "large_cap_data.dropna(inplace=True)\n", + "\n", + "large_cap_volatility = intraday_volatility_profile_data(large_cap_data)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "As expected, the first 10 minutes of trading has an incredibly high rate of volatility. Not only is the % of volatility at the open noteworthy, but it's also interesting to see the dispersion of values in the first day minutes across different days. Some days the first bar contains less than 10% of daily volatiliy, on other days however it contains almost 60%. This demonstrates the process of price discovery. Price discovery is how the price of assets are determined in the market place and differs from valuations. The price of an asset is formed through the interactions of buyers and sellers. When we see high volatility in the beginning of the day, this is often a sign of market participants trying to determine the \"fair market price\" given the information that has come out since the market close the day before. On some days this information is especially material and can cause some huge fluctuations, often a sign of wide spreads. If you take one thing away from this lecture it is that you should not trade in the first 30 minutes of the day, spreads are unreasonably wide and are almost guaranteed to converge once the market settles." + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": 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aVampqVaVBQAAAACSLApLP//8s3JyctSvXz8ZhqFNmzZpwIABkqQBAwYoMzPT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\n", 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y5Ijeeust2/7kJD0AAAA8pWJjpcOH7UPX3r3Gml/3evZZqWlTI3QlbEWKMCsi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\n1CnuMwYA8BtXr17VoEGDlJGRYXQpAADUuUZGFwAAwDUzZsxQdna2Ro0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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# what does the plot of this look like?\n", + "plt.scatter(large_cap_volatility['minute_of_day'], large_cap_volatility['interval_pct']*100)\n", + "plt.title('% of Volatility in 10 Minute Intervals - Large Cap')\n", + "plt.ylabel('% of Volatitliy')\n", + "plt.xlim(-10, 400)\n", + "\n", + "intraday_profile(large_cap_volatility, 'Intraday Volatility Profile - Large Cap', '% of Day\\'s Volatilit in Bucket', 'Cumulative % of Day\\'s Volatility')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Volatility - Small Cap" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Looking at small cap companies, it seems that there is a much larger rate of volatility at play. One of the risks of investing in small cap stocks, apart from the risk of volume shortages, is that there is little information about them. This can mean that is it often difficult to discern the \"fair market value\" of a stock and that price discovery is especially painful. Small cap stocks also experience high rates of volatility as even small trades can become a large percentage of ADV, causing large price movements." + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " variance minute_of_day time\n", + "date \n", + "2016-12-01 09:30:00-05:00 0.116178 0 09:30:00\n", + "2016-12-01 09:40:00-05:00 0.394617 10 09:40:00\n", + "2016-12-01 09:50:00-05:00 0.396001 20 09:50:00\n", + "2016-12-01 10:00:00-05:00 1.097885 30 10:00:00\n", + "2016-12-01 10:10:00-05:00 0.399524 40 10:10:00\n" + ] + } + ], + "source": [ + "small_cap_data = all_small_cap_data\n", + "\n", + "small_cap_data.major_axis = small_cap_data.major_axis.tz_convert('US/Eastern')\n", + "small_cap_data = small_cap_data.transpose(0, 2, 1).to_frame()\n", + "small_cap_data.index.names = [\"assets\", \"date\"]\n", + "\n", + "small_cap_data.dropna(inplace=True)\n", + "\n", + "small_cap_volatility = intraday_volatility_profile_data(small_cap_data)" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "(840, 6)" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "small_cap_volatility.dropna().shape" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": 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7i1OxYWnChAm69NJLNXDgQEVGRqp69epl3mlwcLDatWsnPz8/NW7cWDVr1lSV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\nsnKa1PHjv3qUdfz4HtNlWTkl48yZw5L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QnnjCCF/t2+vHyEg1bdrUvFpxz8pYwKN169bq0qVLlnOffPKJQ33YDWMVKlTQ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\nAABJRU5ErkJggg==\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# what does the plot of this look like?\n", + "plt.scatter(small_cap_volatility['minute_of_day'], small_cap_volatility['interval_pct']*100)\n", + "plt.title('% of Volatility in 10 Minute Intervals - Small Cap')\n", + "plt.xlim(-10, 400)\n", + "plt.ylabel('% of Volatility')\n", + "\n", + "intraday_profile(small_cap_volatility, 'Intraday Volatility Profile - Small Cap', '% of Day\\'s Volatility in Bucket', 'Cumulative % of Day\\'s Volatility')\n" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": { + "collapsed": false, + "scrolled": false + }, + "outputs": [ + { + "data": { + "image/png": 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FEeQVoMlCuplnnnmG6dOn07t377Pet1MGw27ZsoV169axcuVKxo0b51xuGEar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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "intraday_groups(large_cap_volatility, small_cap_volatility, '% of Day\\'s Volatilit in Bucket', 'Cumulative % of Day\\'s Volatility')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Transaction Cost Analysis" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### What are Transaction Costs?\n", + "\n", + "Transaction costs are what you would have to pay to execute your investment ideas above and beyond the fair market costs associated the actual securities themselves. This means the difference between the price of the stock you want to buy and the final cost of actually obtaining that stock. Transaction costs are generally separated into two categories: direct and indirect.\n", + "\n", + "Direct transaction costs refer to the fees that you would pay to actual individuals and counterparties, and they are usually known beforehand. These can include commission to broker-dealers for execution services, taxes on investment income, and rebates (see [Maker-Taker Model](http://lexicon.ft.com/Term?term=make_or_take-pricing)). \n", + "\n", + "Indirect transaction costs refer to costs that are not known prior to trading and depend highly on the execution strategies used. Two of the biggest components of indirect transaction costs are market impact and opportunity costs. The latter refers to the profits forgone by not being able to enter into a position or the losses incurred by not being to exit a position in time. This can occur when there isn't enough counterparty liquidity to complete your trades or because of untimely price movements. Market impact, which we will be focusing on, is the change in the price of a stock caused by an order to buy or sell it. \n", + "\n", + "\n", + "### What is Transaction Cost Analysis?\n", + "\n", + "In the institutional setting we're in, we can ignore direct costs as they are trivial compared to the larger effects of market impact. It is immensely important that transaction costs are taken into consideration when devising investment strategies as they are one of the most common reasons why ideas borne in research can fail to pan out in actual markets. Transaction cost analysis (TCA) is helpful in understanding the pitfalls of strategies and is vital in achieving best execution. Although standard measures of best execution rely on comparisons to various benchmarks, such as the VWAP price, it is more about an investor's capability to consider market uncertainties when making trading decisions. In particular, the proliferation of algorithmic trading has advanced TCA to the point where it can be used pre-trade, intraday, and post-trade.\n", + "\n", + "Pre-trade TCA, which is the most relevant to us, deals with predicting the market impact of our trades. Specifically, TCA is being integrated into the stock selection phase of the investment cycle through quantitative overlays, market impact scores, cost curves, portfolio optimization, and backtesting. Intraday TCA involves the supervision of execution strategies to ensure they fall within the performance standards that we have set and are behaving appropriately to changing market conditions. Finally, TCA is used post-trade to measure actual performance. The cycle of transaction cost analysis is on-going and vital to the research driven investment proces. " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Market Impact" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Mathematically, market impact is defined as the \"... difference between actual price trajectory after the order is released to the market and the price trajectory that would have occured if the order were never released.\"$^{[1]}$ Market impact is broken into two components, permanent and temporary. Permanent MI occurs due to the information content you release into the market as you signal your willingness to trade. This causes market participants to alter their perception of fair value for an asset. This is the unavoidable cost of trading. Temporary MI, however, can be managed and minimized using optimal execution strategies, since it is the price change caused by your demand for liquidity. This is highly dependent on your urgency to complete an order (and of course, many other factors), but can losely be thought of as the premium you need to pay to attract counterparties to complete your trade. \n", + "\n", + "Market impact models attempt to replicate the effects that a trade would have on the greater market. Empirically, it is shown that market impact increases with the size of the trade, the volatility of the stock, and the urgency with which you would like to complete your trade." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Market Impact Model" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We will be implementing a model of market impact based on the following paper by Almgren et al. (2005): [Direct Estimation of\n", + "Equity Market Impact](http://www.cims.nyu.edu/~almgren/papers/costestim.pdf)\n", + "\n", + "The paper presents a model that breaks market impact into its two components and attempts to classify the dependence of market impact on order size and trade time. For permanent impact, it is important to have some measure of liquidity which depends on the market parameters that define each individual stock, aside from volume an volatility. Possible candidates for this are shares outstanding, bid-ask spreads, and market capitalization. The authors found shares outstanding, in particular the inverse of \"turnover\" which is the fraction of a company's total value traded each day, to be the most robust metric to use, compared to bid-ask spreads and market capitalization which was found to have no significant effect. Temporary impact was found to have no such need for stock specific modifications above volume and volatility.\n", + "\n", + "Using a modified Gauss-Newtonian optimization algorithm, parameters are found to fit the measures of permanent and temporary impact. Namely, the liquidity factor, $\\delta$, is $1/4$, and temporary impact, $\\beta$, is defined as a concave function at $3/5$. Empirically, this makes sense. As investors want to trade a larger amount, the less additional trade costs they will incur per share, as we will see. \n", + "The model is described below:" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "$$\\text{Market Impact} = \\text{Permanent Impact} + \\text{Temporary Impact}$$\n", + "\n", + "$$\\text{MI} = \\frac{1}{2} \\: \\overbrace{\\gamma \\: \\sigma \\left(\\frac{x}{v}\\right) \\left(\\frac{\\theta}{v}\\right)^{\\delta}}^{\\text{permanent}} + \\overbrace{\\eta \\: \\sigma \\: \\left| \\frac{x}{vt} \\right|^{\\beta}}^{\\text{temporary}} $$\n", + "\n", + "$$x = \\text{unsigned number of shares to trade}$$\n", + "\n", + "$$v = \\text{average daily volumme (ADV)}$$\n", + "\n", + "$$t = \\text{time width in % of trading time}$$\n", + "\n", + "$$\\sigma = \\text{daily volatility}$$\n", + "\n", + "$$\\theta = \\text{shares outstanding}$$\n", + "\n", + "$$\\delta = 1/4$$\n", + "\n", + "$$\\beta = 3/5$$\n", + "\n", + "where $\\gamma$ and $\\eta$ are the \"universal coefficients of market impact\" and estimated by the authors using a large sample of institutional trades. The interpretation of $\\frac{\\Theta}{v}$ is the inverse of daily turnover. Finally, as a simplifying measure it is assumed that the order is completed by a uniform rate of trading over the time interval.\n", + "\n", + "\n", + "### Potential Limitations\n", + "\n", + "Note that this paper was released prior to the adoption and phased implementation of [__Reg NMS__](https://www.sec.gov/rules/final/34-51808.pdf), prior to the \"quant meltdown\" of August 2007, prior to the financial crisis hitting markets in Q4 2008, and other numerous developments in market microstructure. Nevertheless, this model can provide numerous insights and act as a pivotal first step. More advanced models consider other factors such as the bid-ask spread and book depth, however the model is fit on actual execution data and the realized cost is measured against the mid price. So the act of paying the bid-ask spread over child executions of the parent order is already embedded in the data and the parameters reflect this." + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "# the break-up of the permanent and temporary impacts\n", + "# they are multiplied by 10000 since we want the cost in bps\n", + "def perm_impact(pct_adv, daily_vol_pct=0.25, inv_turnover=200):\n", + " gamma = 0.314\n", + " return 10000 * gamma * daily_vol_pct * pct_adv * (inv_turnover)**0.25\n", + "\n", + "def temp_impact(pct_adv, minutes, daily_vol_pct=0.25, minutes_in_day=60*6.5):\n", + " eta = 0.142\n", + " day_frac = minutes / minutes_in_day\n", + " return 10000 * eta * daily_vol_pct * abs(pct_adv/day_frac)**0.6\n", + "\n", + "def mi_bps(pct_adv, minutes, daily_vol_pct=0.25, inv_turnover=200, minutes_in_day=60*6.5):\n", + " perm = perm_impact(pct_adv, daily_vol_pct, inv_turnover)\n", + " temp = temp_impact(pct_adv, minutes, daily_vol_pct, minutes_in_day)\n", + " return 0.5 * perm + temp\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Replicated from the paper, we see how the permanent and temporary impacts of trading stock \"A\" changes as we allow the trade to complete slower and slower.\n", + "\n", + " Variable | Asset A\n", + " ------------- | -------------\n", + " Inverse turnover ($\\Theta/v$) | 263\n", + " Daily vol ($\\sigma$) | 1.57%\n", + " Trade % ADV (X/V) | 10%\n", + " \n", + " Item | Fast | Medium | Slow\n", + " -----|------|--------|-------\n", + " Trade duration (day fraction %) | 10% | 20% | 50%\n", + " Permanent Impact (bps) | 20 | 20 | 20\n", + " Temporary Impact (bps) | 22 | 15 | 8\n", + " Total Impact (bps) | 32 | 25 | 18\n", + " \n", + "It is important to note here that this is only replicating market impact! There are other aspects to transaction costs, namely opportunity cost, that aren't captured. As we allow ourselves to trade slower we are lowering our temporary market impact, but we are exposing ourselves more and more to adverse price movements and the risk of liquidity depletion.\n", + "\n", + "We'll now see our code estimates for the same experiment." + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": { + "collapsed": false, + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "32.2203193206\n", + "24.634874002\n", + "18.4143315025\n" + ] + } + ], + "source": [ + "print mi_bps(pct_adv=0.1, daily_vol_pct=0.0157, inv_turnover=263, minutes=0.1*60*6.5) \n", + "print mi_bps(pct_adv=0.1, daily_vol_pct=0.0157, inv_turnover=263, minutes=0.2*60*6.5) \n", + "print mi_bps(pct_adv=0.1, daily_vol_pct=0.0157, inv_turnover=263, minutes=0.5*60*6.5) " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "For all the following examples, we will fixe a rate of inverse turnover and focus more on the relationship between trade size and time time. Now, to motivate some intuition, let's look at the relationship between trade costs and trade size at two levels of volatility, given we want to complete in 30 minutes." + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": { + "collapsed": false, + "scrolled": false + }, + "outputs": [ + { + "data": { + "image/png": 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yKzMMg9PZKWxO3sXu8/GUVZZhMpkY0nkgkwPHMrjzQBzNDjechslkwtXVtZkq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IhcQiFJRERERETkEgpJIiIiIiIil1BIEhERERERuYRCkoiIiIiIyCUUkkREpIqFCxcSFRXF5MmT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\nRERERERELqGQJCIiIiIicon/BTrMTVHfUCQgAAAAAElFTkSuQmCC\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "x = np.linspace(0.0001,0.03)\n", + "plt.plot(x*100,mi_bps(x,30,0.25), label=\"$\\sigma$ = 25%\");\n", + "plt.plot(x*100,mi_bps(x,30,0.40), label=\"$\\sigma$ = 40%\");\n", + "plt.ylabel('Market Impact (bps)')\n", + "plt.xlabel('Trade as % of ADV')\n", + "plt.title('Market Impact in Basis Points of Trade Value; $\\sigma$ = 25% and 40%; time = 30 minutes');\n", + "plt.legend();" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Let's look at market impact as it pertains to different combinations of trade size and trade time. The curves below all demonstrate the tradeoff between trade time and trade size. Given a level of market impact, to achieve a higher level of volume would mean having to wait longer to be completed, and thus face the associated risks. It also seems that as you become a larger and larger portion of the average daily volume, the tradeoff becomes less material. As we saw with the graph above, the difference in market impact between two levels of volatility appears to be notable. With the same percentage of ADV and trade time, you would achieve drastically higher rates of market impact. With a trade time of 20 minutes and trade size at 1.5% of ADV, you would have a market impact of approximately 157 bps with 20% volatility, but almost 315 bps with 40% volatility. " + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": { + "collapsed": false, + "scrolled": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 29, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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krrS9QlnNSI0hIdKNIc8IDYRsEVBoM1g8oYlUvGLu5AvFaTO4vlCYAPkUMptl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12Jh8IptgJdDBLTD4MK8FJmQSLXTYt+IAKFlBCgbMprBIIBDibHJaxEtrhNibIXTS+iZIpx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\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xYmmB3a95HOZC47XGqh1F1bdHYNtHnteZuVqdUEchdOI4jjdf8wih6BhNCHWs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\nna2Bo7u1KFBLo+96o1FzgRs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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "x = np.linspace(0.001,0.03) # % of ADV\n", + "y = np.linspace(5,30) # trade time in minutes\n", + "X, Y = np.meshgrid(x,y)\n", + "Z = mi_bps(X, Y, 0.20) # 20% is daily vol pct\n", + "levels = np.linspace(0.0, 500, 20)\n", + "cmap=plt.get_cmap('jet')\n", + "\n", + "\n", + "plt.subplot(121)\n", + "CS = plt.contour(X * 100, Y, Z, levels, linewidths=3, cmap=cmap, alpha=0.55)\n", + "plt.clabel(CS)\n", + "plt.ylabel('Trading Time (minutes)')\n", + "plt.xlabel('Trade Size (% of ADV)')\n", + "plt.title('Market Impact in Basis Points of Trade Value; $\\sigma$ = 20%')\n", + "\n", + "plt.subplot(122)\n", + "Z = mi_bps(X , Y, 0.40)\n", + "CS = plt.contour(X * 100, Y, Z, levels, linewidths=3,cmap=cmap, alpha=0.55)\n", + "plt.clabel(CS)\n", + "plt.xlabel('Trade Size (% of ADV)')\n", + "plt.title('Market Impact in Basis Points of Trade Value; $\\sigma$ = 40%')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Alternatively, we might want to get some intuition as to if we wanted to limit our cost, how does the trading time vary versus percentage of ADV. On one end of the spectrum, you'll see that wanting to keep your market impact at a minimum while executing a large portion of shares means being very patient (it would take almost the entire day to complete)! As well, we can see that keeping % ADV and MI the same, we would have to accept much longer trade times on comparable stocks with greater volatility. " + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": { + "collapsed": false, + "scrolled": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 30, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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v82jlnrZ27VotX75c8+bN09GjRzV27FitXLlSl156qTwej/bs2aPvvvtOqamp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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "x = np.linspace(0.001, 0.03) # % ADV\n", + "y = np.linspace(1, 60 * 6.5) # time to trade\n", + "X, Y = np.meshgrid(x,y)\n", + "\n", + "levels = np.linspace(0.0, 400, 20)\n", + "cmap=plt.get_cmap('jet')\n", + "\n", + "plt.subplot(121)\n", + "\n", + "Z = mi_bps(X, Y, 0.20)\n", + "plt.contourf(X * 100, Z, Y, levels, cmap=cmap, alpha=0.55)\n", + "plt.title('Trading Time in Minutes; $\\sigma$ = 20%')\n", + "plt.xlabel('Trade Size (% of ADV)')\n", + "plt.ylabel('Market Impact (bps)')\n", + "plt.ylim(5, 500)\n", + "plt.colorbar()\n", + "\n", + "plt.subplot(122)\n", + "Z = mi_bps(X, Y, 0.40)\n", + "plt.contourf(X * 100, Z, Y, levels, cmap=cmap, alpha=0.55)\n", + "plt.title('Trading Time in Minutes; $\\sigma$ = 40%')\n", + "plt.xlabel('Trade Size (% of ADV)')\n", + "plt.ylim(5, 500)\n", + "plt.colorbar()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### The Breakdown: Permanent and Temporary\n", + "\n", + "For a typical stock, let's see how market impact is broken down into permanent and temporary." + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 31, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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xmj17tnJzc+Xj46P33ntPt9xyi8LCwtSyZUu1a9dOq1at0gMPPKDt27fLx8dH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\nOxQIdI2qEpWXh1RdXZvjlgLA5LFESEqlpJ07CUjZkk4bCgQC6u/v1MC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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "minutes = 30 # we want to complete our orders in 30 minutes\n", + "\n", + "x = np.linspace(0.0001,0.03) # % of ADV\n", + "\n", + "f, (ax1, ax2) = plt.subplots(ncols=2, sharex=True, sharey=False)\n", + "f.subplots_adjust(hspace=0.15)\n", + " \n", + "p = 0.5*perm_impact(x, 0.20)\n", + "t = mi_bps(x, minutes, 0.20)\n", + "\n", + "ax1.fill_between(x * 100, p, t, color='b',alpha=0.33)\n", + "ax1.fill_between(x * 100, 0, p, color='k',alpha=0.66)\n", + "\n", + "ax1.set_ylabel('Market Impact (bps)')\n", + "ax1.set_xlabel('Trade Size (% of ADV)')\n", + "ax1.set_title('Market Impact (bps) of Trade Value; $\\sigma$ = 20%; time = 30 minutes')\n", + "ax1.set_ylim(0, 400)\n", + "ax1.legend(['Temporary', 'Permanent'])\n", + "\n", + "p = 0.5*perm_impact(x, 0.40)\n", + "t = mi_bps(x, minutes, 0.40)\n", + "\n", + "ax2.fill_between(x * 100, p, t, color='b',alpha=0.33)\n", + "ax2.fill_between(x * 100, 0, p, color='k',alpha=0.66)\n", + "\n", + "ax2.set_xlabel('Trade Size (% of ADV)')\n", + "ax2.set_title('Market impact (bps) of Trade Value; $\\sigma$ = 40%; time = 30 minutes')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Ranking the Q Universes\n", + "\n", + "Now, let's look at price impact with actual stocks, comparing across those in Q universes and those not." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Taking our pipeline results from the beginning of the lecture, we'll calculate for each asset ADV, annualized volatility, and daily volatility." + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": { + "collapsed": false, + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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ADVAnnual ReturnsAnnualized VolatilityDaily VolatilityMarket CapQ1500Q500Shares Outstanding
Equity(21 [AAME])3.683864e+030.0049100.6808150.9406827.907041e+07FalseFalse2.042340e+07
Equity(24 [AAPL])2.218087e+070.0017810.2899100.4005686.075929e+11TrueTrue5.332310e+09
Equity(31 [ABAX])1.165872e+050.0005480.3881040.5362431.185146e+09FalseFalse2.253473e+07
Equity(39 [DDC])3.021574e+050.0012990.4636800.6406668.251480e+08FalseFalse8.781810e+07
Equity(41 [ARCB])2.472507e+05-0.0038120.4597220.6351977.760125e+08FalseFalse2.563985e+07
\n", + "
" + ], + "text/plain": [ + " ADV Annual Returns Annualized Volatility \\\n", + "Equity(21 [AAME]) 3.683864e+03 0.004910 0.680815 \n", + "Equity(24 [AAPL]) 2.218087e+07 0.001781 0.289910 \n", + "Equity(31 [ABAX]) 1.165872e+05 0.000548 0.388104 \n", + "Equity(39 [DDC]) 3.021574e+05 0.001299 0.463680 \n", + "Equity(41 [ARCB]) 2.472507e+05 -0.003812 0.459722 \n", + "\n", + " Daily Volatility Market Cap Q1500 Q500 \\\n", + "Equity(21 [AAME]) 0.940682 7.907041e+07 False False \n", + "Equity(24 [AAPL]) 0.400568 6.075929e+11 True True \n", + "Equity(31 [ABAX]) 0.536243 1.185146e+09 False False \n", + "Equity(39 [DDC]) 0.640666 8.251480e+08 False False \n", + "Equity(41 [ARCB]) 0.635197 7.760125e+08 False False \n", + "\n", + " Shares Outstanding \n", + "Equity(21 [AAME]) 2.042340e+07 \n", + "Equity(24 [AAPL]) 5.332310e+09 \n", + "Equity(31 [ABAX]) 2.253473e+07 \n", + "Equity(39 [DDC]) 8.781810e+07 \n", + "Equity(41 [ARCB]) 2.563985e+07 " + ] + }, + "execution_count": 32, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "T = len(pipeline_results.index.levels[0])\n", + "\n", + "metrics = pd.DataFrame({'ADV': pipeline_results.volume.mean(level=1),\n", + " 'Annualized Volatility': (pipeline_results.returns.std(level=1)*(250/(T-1)))**0.5,\n", + " 'Daily Volatility': (pipeline_results.returns.std(level=1)*(T-1))**0.5,\n", + " 'Market Cap': pipeline_results.market_cap.mean(level=1),\n", + " 'Shares Outstanding': pipeline_results.shares_outstanding.mean(level=1),\n", + " 'Annual Returns': pipeline_results.returns.mean(level=1),\n", + " 'Q1500': pipeline_results.groupby(level=1)['Q1500'].any(),\n", + " 'Q500': pipeline_results.groupby(level=1)['Q500'].any()}).dropna()\n", + "\n", + "metrics.head()\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Note: $\\sigma_{annual} = \\sqrt{\\frac{250}{T - 1}\\sum^{T}_{i = 2}(r_i - r_{avg})^2}$ and $\\sigma_{daily} = \\sqrt{\\frac{1}{T - 1}\\sum^{T}_{i = 2}(r_i - r_{avg})^2}$\n", + "\n", + "Assume we would like to trade 10% of the average daily volume and complete our orders within 30 minutes. What would our average market impact be across stocks in the Q500, Q1500, and stocks in neither of those universes?\n", + "\n", + "Looking at the box plots below, we cannot discern any difference between market impact in the Q500 and Q1500 universes, however it clear that trading outside of both universes is likely to have a material impact on returns. " + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": { + "collapsed": false, + "scrolled": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 33, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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2J9sqoh22nHvuuScTJ07MRz/60XzkIx/JRz7ykQwePPhth5k6dWqeeuqpJMnS\npUtz0EEHZciQIWlsbMy6deuyfv36LF++PLW1tRkxYkTuv//+JEl9fX2OPPLIt/28dC91df2LHQEA\ngF1Qh9MxW2tXb74u0rasWLEiX/3qV/PCCy+koqIi8+fPz9SpU3PJJZekqqoqVVVVueqqq1JZWZlp\n06Zl4sSJKS8vz5QpU9K7d++MGTMmixcvzvjx41NZWZlrrrlmh3eQ7mnOnAHpYG0QAAB4i7LW9k74\nKdi4cWP+67/+Ky+++GKSZMOGDbnllltSX1/fJQF3VKlPm9I1ysqSbb+yge7i3HObMnu2RRqgK5Xy\n7+FS/luxlL9vu5ttvQ46nEG6+OKL8/LLL+epp57KsGHD8thjj2Xq1Kk7PSQAdAYzygDsiA7PQVq1\nalXmzp2bAw44IDfeeGN+8IMf5LHHHuuKbAAAAF2qw4K0cePGbNq0KS0tLXn99dfz3ve+N88880xX\nZAMAAOhSHR5iN3z48MydOzejRo3K2LFjs99++3VFLnhHJk1qigtDAgCwozosSFOnTs3GjRtTUVGR\noUOHZu3atRkxYkRXZIO3bfLklVGQAADYUe0WpEceeWSr2/v06ZMnnngihx9+eKeFAmDXUl2dFBY7\nLUllZcVOsHV775288EKxUwDwZu0WpAkTJmTgwIEZMmRIyrbym0VBAmCzF18s3aVpS31JXwBKS7sF\n6fvf/34WLlyYZcuWZcSIEfn0pz+dwYMHd2U2AACALtVuQRo2bFiGDRuWlpaWPPjgg6mrq8tzzz2X\nE088MZ/61Kfy3ve+tytzAgAAdLoOl/nu0aNHPv7xj+fGG2/MhRdemIULF+aUU07pimzwttXV9S92\nBAAAdkEdrmL3/PPP51//9V/z05/+NB/4wAfypS99KSNHjuyKbPC2zZkzILNnFzsFAAC7mnYL0j33\n3JN/+7d/S0tLSz796U/nzjvvTJ8+fboyGwAAQJdqtyBdfvnl2X///VNTU5Of/vSnuf/++7f4+rx5\n8zo9HAAAQFdqtyD94he/6MocAAAARdduQbJKHQAA0N10uEgDtKe6+o2LQ5aqUr0A4957Jy+8UOwU\nANC5SvX3cFKaF45O3vgbgeJTkHjbXnwxaW0tdoqta2hoSG1taQ6ApfsLAwB2jlL9+yB54/dwKeej\n+Dq8DhIAAEB3oSABAAAUKEgAAAAFChIAAECBggQAQLcxaVJTsSNQ4hQkAAC6jcmTVxY7AiVOQQIA\nAChQkADYLysIAAAUxUlEQVQAAAoUJAAAgAIFCQAAoEBBAgCg26ir61/sCJQ4BQkAgG5jzpwBxY5A\nietR7AAA7PoezyFJ2RPFjrFVtcUOsA2PZ3CSxmLHAOBNFCQA3rFD05jW1mKn2LqGhobU1pZmTTq0\nLCnRbxtAt+UQOwAAgAIFCQAAoEBBAgCg25g0qanYEShxChIAAN3G5Mkrix2BEqcgAQAAFFjFjrfN\nsr5vj2V9AQBKl4LE22ZZ37fHsr4AAKXLIXYAAAAFChIAAN1GXV3/YkegxClIAAB0G3PmDCh2BEqc\nggQAAFCgIAEAABQoSAAAAAUKEgAAQIGCBABAtzFpUlOxI1DiFCQAALqNyZNXFjsCJa5HsQMAsHso\nKyt2gvbUFjtAu/beu9gJAPjfFCQA3rHW1mInaF9ZWWnnA6C0OMQOAACgQEECAAAoUJAAAOg26ur6\nFzsCJc45SLwjTsrecU7KBoDimTNnQGbPLnYKSpmCxNtWyic9Oykb2OyNa54MKHYMAHYRDrEDYLfm\nmicA7IhOL0hPPvlkTjjhhNx5551Jkj/+8Y+ZMGFCzjzzzPyf//N/8uc//zlJsnDhwowbNy6f/exn\nc++99yZJWlpactFFF2X8+PGZMGFCnn/++c6OCwAAdGOdWpBeffXVXHvttRkxYkTbthtuuCETJkzI\nHXfckfe///1ZsGBBXn311cyaNSvf/e53M2/evHz3u9/NK6+8kn//93/PXnvtle9///v5whe+kOuv\nv74z4wIAAN1cpxakysrK1NXVZd99923btnTp0owcOTJJMnLkyDz00ENZsWJFhgwZkqqqqlRWVmbY\nsGFpaGjIkiVLMmrUqCTJ8OHD8+ijj3ZmXAAAdnNvnJcI7evUglReXp5evXptse3VV19Nz549kyT7\n7LNPVq9enbVr16a6urrtNtXV1VmzZk2am5vbtpeVlaW8vDwtLS2dGZndhMEPANga5yXSkaKuYtfa\nzjJj7W3ftGnTdj1uQ0PD287E7mHy5KShwQAIvHHNk8mT/V4A/sLfimxLlxekqqqqbNiwIb169cqq\nVavSr1+/1NTUZM2aNW23WbVqVYYOHZqampo0Nzfn4IMPbps56tGj48i1taV7DRy6RkNDg9cBkCSZ\nMyeZPdsy38Ab/I1Asu2S3OXLfB999NFZtGhRkmTRokU59thjM2TIkDQ2NmbdunVZv359li9fntra\n2owYMSL3339/kqS+vj5HHnlkV8cFAAC6kU6dQVqxYkW++tWv5oUXXkhFRUXmz5+fuXPnZvr06bnr\nrrsyYMCAjB07NhUVFZk2bVomTpyY8vLyTJkyJb17986YMWOyePHijB8/PpWVlbnmmms6My4AANDN\nlbW2d8LPLsq0KYnXAfAXZWXJ7vWbDngnzj23yWG3bPNvxS4/xA66Ql1d/2JHAABK0Jw5yhHbpiCx\nWzL4AZtZ9h+AHaEgAbBbc80TAHaEggQAAFCgIAEAABQoSAAAdBvOS6QjChK7JYMfALA1zkukIwoS\nuyWDH7CZZf8B2BEKEgC7Ncv+A7AjFCQAAIACBQkAAKBAQQIAoNtwXiIdUZDYLRn8AICtcV4iHVGQ\n2C0Z/IDNLPsPwI5QkADYrVn2H4AdoSABAAAUKEgAAAAFChIAAN2G8xLpiILEbsngBwBsjfMS6YiC\nxG7J4AdsZtl/AHaEggTAbs2y/wDsCAUJAACgQEECAAAoUJAAAOg2nJdIRxQkdksGPwBga5yXSEcU\nJHZLBj9gM8v+A7AjFCQAdmuW/QdgRyhIAAAABQoSAABAgYIEAEC34bxEOqIgsVsy+AEAW+O8RDqi\nILFbMvgBm1n2H4AdoSBREg455JCUlZXttI/DDjtspz3WIYccUuxvD/AOWPYfgB3Ro9gBIEkaGxt3\n6uM1NDSktrZ2pz4mAAC7PzNIAJScnTmrnOy82WmzygC7PwUJgJLT2NiY1tbWnfKxbNmynfZYra2t\nO33GG+hazkukIwoSAADdhvMS6YiCBAAAUKAgAQAAFChIAAAABQoSAABAgYIEAEC3MWlSU7EjUOIU\nJAAAuo3Jk1cWOwIlTkECAAAoUJAAAAAKFCQAAIACBQkAAKBAQQIAoNuoq+tf7AiUOAUJAIBuY86c\nAcWOQIlTkAAAAAoUJAAAgAIFCQAAoEBBAgAAKFCQAADoNiZNaip2BEqcggQAQLcxefLKYkegxPXo\n6idcunRpvvSlL+VDH/pQWltbc/DBB+cf/uEfcvHFF6e1tTV9+/bNddddl549e2bhwoWZN29eKioq\ncuqpp2bcuHFdHRcAAOhGurwgJckRRxyRG264oe3zSy65JBMmTMjo0aMzc+bMLFiwICeffHJmzZqV\nBQsWpEePHhk3blxGjx6dPffcsxiRAQCAbqAoh9i1trZu8fnSpUszcuTIJMnIkSPz0EMPZcWKFRky\nZEiqqqpSWVmZYcOG5dFHHy1GXAAAoJsoygzSM888k/POOy8vv/xy/vEf/zGvvfZaevbsmSTZZ599\nsnr16qxduzbV1dVt96murs6aNWuKERcAAOgmurwg7b///jn//PPziU98Is8991zOOuustLS0tH39\nf88udbR9axoaGt5xTnZ9XgfAZsYDYLO6uv6ZPNmYQPu6vCD169cvn/jEJ5Ik73vf+7LvvvumsbEx\nGzZsSK9evbJq1ar069cvNTU1W8wYrVq1KkOHDt2u56itre2U7Ow6GhoavA6AJMYDYEtz5iSzZw8o\ndgyKbFtvnHX5OUg//vGPc9NNNyVJ1q5dm7Vr1+aUU07J/fffnyRZtGhRjj322AwZMiSNjY1Zt25d\n1q9fn+XLl/sFBwAAdKoun0E6/vjjM23atHzuc59La2trvv71r2fQoEH5yle+krvvvjsDBgzI2LFj\nU1FRkWnTpmXixIkpLy/PlClT0rt3766OCwAAdCNdXpCqqqpyyy23vGX7bbfd9pZto0ePzujRo7si\nFgAAQHGW+QYAAChFChIAAN3GpElNxY5AiVOQAADoNiZPXlnsCJQ4BQkAAKBAQQIAAChQkAAAAAoU\nJAAAgAIFCQCAbqOurn+xI1DiFCQAALqNOXMGFDsCJU5BAgAAKFCQAAAAChQkAACAAgUJAACgQEEC\nAKBkHXLIISkrK9tpH8nOe6xDDjmk2N8eOkGPYgcAAID2NDY27tTHa2hoSG1t7U59THYvZpAAAAAK\nFCQAAIACBQkAAKBAQQIAAChQkAAAAAoUJAAAgAIFCQAAoEBBAgAAKFCQAAAAChQkAACAAgUJAACg\nQEECAAAoUJAAAAAKFCQAAIACBQkAAKBAQQIAAChQkAAAAAoUJAAAgAIFCQAAoEBBAgAAKFCQAAAA\nChQkAACAAgUJAACgQEECAAAoUJAAAAAKFCQAAIACBQkAAKBAQQIAAChQkAAAAAoUJAAAgAIFCQAA\noEBBAgAAKFCQAAAAChQkAACAAgUJAACgQEECAAAoUJAAAAAKFCQAAIACBQkAAKBAQQIAACjoUewA\nHbn66quzYsWKlJWV5dJLL82hhx5a7EgAAMBuqqQL0iOPPJI//OEPmT9/fp555plcdtllmT9/frFj\nAQAAu6mSPsRuyZIlGTVqVJL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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "metrics['MI'] = mi_bps(0.1, 30, metrics['Daily Volatility'], metrics['Shares Outstanding']/metrics['ADV'])\n", + "\n", + "Q500_metrics = metrics[(metrics['Q500'])]\n", + "Q1500_metrics = metrics[(metrics['Q1500'])]\n", + "other = metrics[(~metrics['Q500']) & (~metrics['Q1500'])]\n", + "\n", + "plt.boxplot([Q500_metrics['MI'], Q1500_metrics['MI'], other['MI']], showfliers=False)\n", + "plt.xticks([1, 2, 3], ['Q500', 'Q1500', 'Everything Else'])\n", + "plt.ylabel('Market Impact (bps)')\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can quickly test for statistically significant differences between the groupings using the Kolmogorov-Smirnov statistic. We will test all the groups against each other, with our null hypothesis being that they are drawn from the same distribution." + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": { + "collapsed": false, + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "p-value for difference between market impact of Q500 and Q1500 stocks: 0.000627224351035\n", + "p-value for difference between market impact of Q1500 and other stocks: 9.9129022091e-172\n", + "p-value for difference between market impact of Q500 and other stocks: 3.29031211248e-99\n" + ] + } + ], + "source": [ + "d1, p_value1 = stats.ks_2samp(Q500_metrics['MI'], Q1500_metrics['MI'])\n", + "print 'p-value for difference between market impact of Q500 and Q1500 stocks:', p_value1\n", + "\n", + "d2, p_value2 = stats.ks_2samp(Q1500_metrics['MI'], other['MI']) \n", + "print 'p-value for difference between market impact of Q1500 and other stocks: ', p_value2\n", + "\n", + "d3, p_value3 = stats.ks_2samp(Q500_metrics['MI'], other['MI'])\n", + "print 'p-value for difference between market impact of Q500 and other stocks: ', p_value3" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We will also look at how they vary with respect to annual returns." + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": 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RERERUYWl8bFnPXr0gLe3N/r164datWohPDwcbdu21UdsRPSaxGxh6BCIiIiIiKiENBbk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\niIiIiNzg/wDRvGC2RX4BlAAAAABJRU5ErkJggg==\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.subplot(311)\n", + "plt.scatter(Q500_metrics['MI'], Q500_metrics['Annual Returns'], marker=\"x\", color=\"b\")\n", + "plt.axvline(Q500_metrics['MI'].mean(), color='g', linestyle='--', lw=2)\n", + "plt.title(\"MI vs. Returns - Q500\")\n", + "plt.xlabel('Market Impact (bps)')\n", + "plt.ylabel('Annual Returns')\n", + "plt.xlim(0, 6000)\n", + "plt.ylim(-0.1, 0.2)\n", + "\n", + "plt.subplot(312)\n", + "plt.scatter(Q1500_metrics['MI'], Q1500_metrics['Annual Returns'], marker=\"x\", color=\"r\")\n", + "plt.axvline(Q1500_metrics['MI'].mean(), color='g', linestyle='--', lw=2)\n", + "plt.title(\"MI vs. Returns - Q1500\")\n", + "plt.xlabel('Market Impact (bps)')\n", + "plt.ylabel('Annual Returns')\n", + "plt.xlim(0, 6000)\n", + "plt.ylim(-0.1, 0.2)\n", + "\n", + "plt.subplot(313)\n", + "plt.scatter(other['MI'], other['Annual Returns'], marker=\"x\", color=\"y\")\n", + "plt.axvline(other['MI'].mean(), color='g', linestyle='--', lw=2)\n", + "plt.title(\"MI vs. Returns - Others\")\n", + "plt.xlabel('Market Impact (bps)')\n", + "plt.ylabel('Annual Returns')\n", + "plt.xlim(0, 6000)\n", + "plt.ylim(-0.1, 0.2)\n", + "\n", + "plt.tight_layout()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### For the Optimization Objective Function\n", + "\n", + "Although beyond the scope of this lecture, the goal for pre-trade transaction cost analysis is to utilize it in our portfolio selection process. We want to ensure that the alphas we are trying to capture are not overwhelmed by their transaction costs. Usually, this would involve including a factor of trade cost into our model before the optimization step. This will be discussed in more detail in future lectures." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Sources:\n", + "\n", + "[1] Kissell, Robert. Science of Algorithmic Trading and Portfolio Management. Elsevier, Inc., 2014.\n", + "\n", + "[2] Strumpf, Dan. “Stock-Market Traders Pile In at the Close.” The Wall Street Journal, Dow Jones & Company, 27 May 2015, [www.wsj.com/articles/traders-pile-in-at-the-close-1432768080](www.wsj.com/articles/traders-pile-in-at-the-close-1432768080)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "collapsed": true + }, + "source": [ + "*This presentation is for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation for any security; nor does it constitute an offer to provide investment advisory or other services by Quantopian, Inc. (\"Quantopian\"). Nothing contained herein constitutes investment advice or offers any opinion with respect to the suitability of any security, and any views expressed herein should not be taken as advice to buy, sell, or hold any security or as an endorsement of any security or company. In preparing the information contained herein, Quantopian, Inc. has not taken into account the investment needs, objectives, and financial circumstances of any particular investor. Any views expressed and data illustrated herein were prepared based upon information, believed to be reliable, available to Quantopian, Inc. at the time of publication. Quantopian makes no guarantees as to their accuracy or completeness. All information is subject to change and may quickly become unreliable for various reasons, including changes in market conditions or economic circumstances.*" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 2", + "language": "python", + "name": "python2" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 2 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython2", + "version": "2.7.12" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} \ No newline at end of file diff --git a/notebooks/lectures/Introduction_to_Market_Microstructure/preview.html b/notebooks/lectures/Introduction_to_Market_Microstructure/preview.html new file mode 100644 index 00000000..b35c83d3 --- /dev/null +++ b/notebooks/lectures/Introduction_to_Market_Microstructure/preview.html @@ -0,0 +1,29089 @@ + + + Market Microstructure Lecture + + + + + + + + + + + + + + + + +
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Market Microstructure¶

By Beha Abasi, Jonathan Larkin, Maxwell Margenot, and Delaney Granizo-Mackenzie

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Part of the Quantopian Lecture Series:

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Notebook released under the Creative Commons Attribution 4.0 License.

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Market microstructure is the broad study of the functions and operations of financial markets. This field includes research on how exchanges and trading venues are created and how they facilitate the transfer of financial assets between buyers and sellers. It also looks at the tension between the conflicting interests of opposing parties and how this affects price discovery. Furthermore, quotes, spreads, and transaction costs are important pillars of this field. Due to the proliferation of algorithmic trading, market microstructure has turned into one of the fastest growing domains of microeconomic research$^{[1]}$.

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Although much of economic theory suggests that markets are frictionless, that is never the case and it is this same friction that often leads to costly implementation of investment strategies and alpha deterioration. A common reason why investment ideas conceived in research sometimes fail to pan out in the actual execution is because crucial market considerations were not accounted for, leading to the improper trading of alpha generating strategies.

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As briefly discussed in the Volume, Slippage, and Liquidity lecture, a good starting point in microstructure would be to look at intraday profiles. These plots give us a concise overview of how market participants are behaving with regards to different market conditions, particularly looking at how behaviours change at varying times of day. Although measures of volatility and volume that are calculated on a per day basis can be quite helpful in giving us a big picture understanding of stocks and sectors, it is the intraday profiles that reveal what actual trading would be like, and potentially what pitfalls lay ahead. We will consider the intraday movements of volume and volatility, compare across different classes of assets and discuss why these considerations may be the determinants of whether a strategy is profitable or not. Intraday profiles can be used to make comparisons and provide insights across almost anything that is tradeable. As a taste, we will look at how trading of large cap and small cap stocks differ.

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Let's start by making some imports.

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In [1]:
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import pandas as pd
+import numpy as np
+from quantopian.pipeline import Pipeline
+from quantopian.pipeline.data import morningstar
+from quantopian.pipeline.factors import Returns, Latest
+from quantopian.pipeline.filters.morningstar import Q1500US, Q500US
+from quantopian.research import run_pipeline
+import matplotlib.pyplot as plt
+from quantopian.pipeline.data.builtin import USEquityPricing
+import time
+import scipy.stats as stats
+
+ +
+
+
+ +
+
+
+
+
+

We'll gather some of the data we will use in this section and later parts of the lecture, and define our asset groups.

+ +
+
+
+
+
+
In [2]:
+
+
+
def make_pipeline():
+    
+    # define our pipeline
+    pipe = Pipeline()
+    
+    # get daily volume data
+    volume = Latest([USEquityPricing.volume])
+    pipe.add(volume, 'volume')
+    
+    # get daily returns
+    returns = Returns(window_length=2)
+    pipe.add(returns, 'returns')
+    
+    # get shares outstanding (this will be used later in the lecture for market impact)
+    shares_outstanding = Latest([morningstar.valuation.shares_outstanding])
+    pipe.add(shares_outstanding, 'shares_outstanding')
+    
+    # get market cap
+    market_cap = Latest([morningstar.valuation.market_cap])
+    pipe.add(market_cap, 'market_cap')
+    
+    market_cap_rank = market_cap.rank()
+    biggest = market_cap_rank.top(1000)
+    pipe.add(biggest, 'large_cap')
+    smallest = market_cap_rank.bottom(1000)
+    pipe.add(smallest, 'small_cap')
+    
+    # in Q1500US
+    q1500_universe = Q1500US()
+    pipe.add(q1500_universe, 'Q1500')
+    
+    # in Q500US
+    q500_universe = Q500US()
+    pipe.add(q500_universe, 'Q500')
+    
+    return pipe
+
+# Initializing the pipe
+pipe = make_pipeline()
+
+# Dependency Graph
+pipe.show_graph('png')
+
+# Now let's start the pipeline
+start_date, end_date = '2016-12-01', '2016-12-31' 
+
+pipeline_results = run_pipeline(pipe, start_date, end_date)
+pipeline_results.dropna(inplace=True)
+pipeline_results.head()
+
+ +
+
+
+ +
+
+ + +
+ +
Out[2]:
+ + + +
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
Q1500Q500large_capmarket_capreturnsshares_outstandingsmall_capvolume
2016-12-01 00:00:00+00:00Equity(21 [AAME])FalseFalseFalse7.655710e+070.0666672.047530e+07True469.0
Equity(24 [AAPL])TrueTrueTrue5.943400e+11-0.0084345.332310e+09False25115705.0
Equity(31 [ABAX])FalseFalseFalse1.176550e+09-0.0124502.253300e+07False163531.0
Equity(39 [DDC])FalseFalseFalse8.307590e+080.0100488.781810e+07False221162.0
Equity(41 [ARCB])FalseFalseFalse7.763620e+080.0066012.574970e+07False257181.0
+
+
+ +
+ +
+
+ +
+
+
+
In [3]:
+
+
+
large_cap_assets = pipeline_results[pipeline_results.large_cap].xs('2016-12-1').index.values
+small_cap_assets = pipeline_results[pipeline_results.small_cap].xs('2016-12-1').index.values
+Q500_assets = pipeline_results[pipeline_results.Q500].xs('2016-12-1').index.values
+Q1500_assets = pipeline_results[pipeline_results.Q1500].xs('2016-12-1').index.values
+other_assets = pipeline_results[~(pipeline_results.Q1500) & ~(pipeline_results.Q500)].xs('2016-12-1').index.values
+
+ +
+
+
+ +
+
+
+
+
+

Intraday Profiles of Volume/Volatility¶

+
+
+
+
+
+
+
+

Our intraday profiles will show the day's activity as broken up into 10 minute bars. Within these 10 minute bars, we'll show how the distribution of volume and volatility looks across different days. We'll also show how much volume/volatility exists in each interval, as a percentage of the entire day's worth. Since we want to look at intraday movements, we'll need to use the get_pricing method instead of pipeline for minutely data. Volume is a standard field on the Quantopian platform, so we can call it directly without the need for any other calculations.

+ +
+
+
+
+
+
In [4]:
+
+
+
all_large_cap_data = get_pricing(large_cap_assets, frequency='minute',start_date='2016-12-1', end_date='2016-12-31')
+large_cap_volume = all_large_cap_data['volume'] # the only field we care about right now
+large_cap_volume = large_cap_volume.tz_convert('US/Eastern') # Q data comes in as UTC
+
+all_small_cap_data = get_pricing(small_cap_assets, frequency='minute', start_date='2016-12-1', end_date='2016-12-31') 
+small_cap_volume = all_small_cap_data['volume']
+small_cap_volume = small_cap_volume.tz_convert('US/Eastern')
+
+ +
+
+
+ +
+
+
+
+
+

We'll define some general functions for the use of modelling our data and generating the intraday profiles.

+ +
+
+
+
+
+
In [6]:
+
+
+
def intraday_volume_profile_data(intraday_data):
+    # this method will define clearly all the data we need in plotting out volume profiles
+    
+    intraday_data = pd.DataFrame(intraday_data.mean(axis=1))
+    
+    # how much volume is there in an interval (minute, for now)
+    intraday_data.columns = ['interval_value']
+
+    # how much volume is there in each day
+    dailySum = intraday_data.resample('d').sum()
+    dailySum.columns = ['daily_value']
+    dailySum['day'] = dailySum.index.date
+
+    intraday_data['minute_of_day'] = (intraday_data.index.hour - 9) * 60 +\
+                                    (intraday_data.index.minute - 30)
+    intraday_data['time'] = intraday_data.index.time
+
+    # redefine our intervals as 10 minute bars, using the conversion below
+    conversion = {'interval_value' : 'sum', 'minute_of_day': 'last', 'time': 'last'}
+    intraday_data = intraday_data.resample('10t', closed='right').apply(conversion)
+    intraday_data['day'] = intraday_data.index.date
+
+    # calculate the percentage of volume in each interval
+    intraday_data = intraday_data.merge(dailySum, how='left', on='day')
+    intraday_data['interval_pct'] = intraday_data['interval_value'] / intraday_data['daily_value']
+
+    intraday_data.head()
+    
+    return intraday_data
+
+def intraday_profile(intraday_data, plot_title, y_axis_one, y_axis_two):
+    # this method will actually plot the intraday profile
+    
+    # we want to look across days, comparing what happens are the same time of day
+    intraday_grouped = intraday_data.groupby('time')
+
+    intraday_grouped_median = intraday_grouped.median()
+
+    # each interval (10 minutes) is a bucket
+    buckets = intraday_grouped_median.index
+    bucket_data = intraday_grouped_median['interval_pct']
+
+    figure, ax = plt.subplots()
+    plt.title(plot_title)
+    
+    ax.bar(buckets, 100 * bucket_data, -60 * 10, alpha = 0.75, color='navy')
+    ax.set_ylabel(y_axis_one)
+    ax_twin = ax.twinx()
+
+    ax_twin.plot(buckets, (100 * bucket_data).cumsum(), color='r')
+    ax_twin.grid(None)
+    ax_twin.set_ylim(0, 100)
+    ax_twin.set_ylabel(y_axis_two)
+
+def intraday_groups(group_one, group_two, y_axis_one, y_axis_two, title='Small vs. Big', 
+                    group_one_name='Large Cap', group_two_name='Small Cap'):
+    # this method will be used to plot two intraday profiles against each other
+    # used for making pattern comparisons
+    # this is the same code as above, except now for two data sets 
+    
+    group_one_grouped = group_one.groupby('time')
+    group_two_grouped = group_two.groupby('time')
+    
+    group_one_median = group_one_grouped.median()
+    group_two_median = group_two_grouped.median()
+    
+    buckets = group_one_median.index
+    group_one_bucket_data = group_one_median['interval_pct']
+    group_two_bucket_data = group_two_median['interval_pct']
+    
+    figure, ax = plt.subplots()
+    plt.title(title)
+    
+    ax.bar(buckets, 100 * group_one_bucket_data, -60 * 10, alpha=0.75, color='r')
+    ax.bar(buckets, 100 * group_two_bucket_data, -60 * 10, alpha=0.75, color='navy')
+    ax.legend([group_one_name, group_two_name], loc=1)
+    ax.set_ylabel(y_axis_one)
+    ax_twin = ax.twinx()
+    
+    ax_twin.plot(buckets, (100 * group_one_bucket_data).cumsum())
+    ax_twin.plot(buckets, (100 * group_two_bucket_data).cumsum())
+    ax_twin.grid(None)
+    
+    ax_twin.legend([group_one_name, group_two_name], loc=2)
+    ax_twin.set_ylim(0, 100)
+    ax_twin.set_ylabel(y_axis_two)
+
+ +
+
+
+ +
+
+
+
+
+

Volume - Large Cap¶

+
+
+
+
+
+
+
+

We'll begin our study by looking at the trading profiles of large cap stocks. We will average out the volume profiles across all the large cap stocks that we found to find general patterns that should be applicable not just to individual stocks. Although, if you have a smaller, more specific universe, these profiles could be used on a per stock basis.

+ +
+
+
+
+
+
In [7]:
+
+
+
large_cap_volume.head()
+
+ +
+
+
+ +
+
+ + +
+ +
Out[7]:
+ + + +
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
Equity(24 [AAPL])Equity(62 [ABT])Equity(64 [ABX])Equity(67 [ADSK])Equity(76 [TAP])Equity(100 [IEP])Equity(114 [ADBE])Equity(122 [ADI])Equity(128 [ADM])Equity(154 [AEM])...Equity(50049 [FTV])Equity(50117 [LN])Equity(50242 [DVMT])Equity(50307 [ASB_PRD])Equity(50382 [FTS])Equity(50390 [ADNT])Equity(50392 [YUMC])Equity(50421 [ZTO])Equity(50428 [AA])Equity(50471 [MTFB])
2016-12-01 09:31:00-05:00570839.0101061.0272246.028791.023976.01076.041591.058364.056137.016279.0...0.04758.010412.02000.046290.017437.00.08142.085914.0200.0
2016-12-01 09:32:00-05:00176608.010629.046518.012299.02800.00.04743.012892.0800.07100.0...400.0100.01100.0200.030568.0200.060652.01340.028991.00.0
2016-12-01 09:33:00-05:00148342.05102.087521.01100.08736.00.010295.07132.05050.05790.0...28611.0300.0800.02100.01648.02623.05300.04500.027066.00.0
2016-12-01 09:34:00-05:00212701.06622.099279.016252.08200.00.08465.04323.05946.03700.0...3248.0400.04000.00.01473.05761.05700.0200.023027.00.0
2016-12-01 09:35:00-05:00192160.018223.055978.017515.04000.00.02750.013162.02162.02100.0...13022.01005.01455.0500.02452.0341.08384.014690.019745.00.0
+

5 rows × 991 columns

+
+
+ +
+ +
+
+ +
+
+
+
+
+

As a sample, we'll look at the intraday volume for a single day, 2016-01-01. Notice that we see large spikes in volume at the beginning of the day and towards the close.

+ +
+
+
+
+
+
In [8]:
+
+
+
large_cap_avg_volume = large_cap_volume['2016-12-1'].mean(axis=1)
+
+plt.subplot(211)
+plt.plot(large_cap_avg_volume.index, large_cap_avg_volume, color='navy')
+plt.title("Intraday Volume - Large Cap")
+plt.ylabel('Volume')
+
+resampled_large_cap_avg_volume = large_cap_avg_volume.resample('10t', closed='right').sum()
+
+plt.subplot(212)
+plt.plot(resampled_large_cap_avg_volume.index, resampled_large_cap_avg_volume/large_cap_avg_volume.sum(), color='navy')
+plt.title("Intraday Volume as % of Total Day - Large Cap")
+plt.ylabel('Volume as % of Total Day')
+
+ +
+
+
+ +
+
+ + +
+ +
Out[8]:
+ + + + +
+
<matplotlib.text.Text at 0x7f75b6e1be50>
+
+ +
+ +
+ +
+ + + + +
+ +
+ +
+ +
+
+ +
+
+
+
+
+

Now, we'll average across all days in the month of December 2016 to see how the volume patterns distribute. It seems that there is a much larger proportion of volume towards the end of the day, on one day there is more than 12% of total daily volume in just the last 10 minutes of trading.

+

One reason why this may occur is because it may be risky to hold positions overnight and traders make a concious effort to close out positions at the end of the day. Doing it the next morning can be tricky as morning trading is often marred with lots of volatility. There may also be information released after the close that could cause adverse price movements, but since the markets are closed there would be little that could be done to handle the situation.

+

Another contributing factor may be due to the proliferation of index funds$^{[2]}$. The value of index funds are determined by the day's closing price, and so to minimize tracking error, portfolio managers of index funds will aim to trade as close to the closing price as possible.

+ +
+
+
+
+
+
In [9]:
+
+
+
large_volume = intraday_volume_profile_data(large_cap_volume)
+
+plt.scatter(large_volume.minute_of_day, large_volume.interval_pct*100, color='navy')
+plt.title('% of Volume in 10 Minute Intervals - Large Cap')
+plt.xlim(0, 400)
+plt.ylabel('% of Volume')
+
+intraday_profile(large_volume, 'Intraday Volume Profile - Large Cap', '% of Day\'s Volume in Bucket', 'Cumulative % of Day\'s Volume')
+
+ +
+
+
+ +
+
+ + +
+ +
+ + + + +
+ +
+ +
+ +
+ +
+ + + + +
+ +
+ +
+ +
+
+ +
+
+
+
+
+

Volume - Small Cap¶

+
+
+
+
+
+
+
+

Now, let's do a similar volume study but on small cap stocks. Again, we will average out the trading patterns for all the small cap stocks we found to demonstrate general volume profiles.

+ +
+
+
+
+
+
In [10]:
+
+
+
small_cap_volume.head()
+
+ +
+
+
+ +
+
+ + +
+ +
Out[10]:
+ + + +
+
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
Equity(21 [AAME])Equity(106 [ACU])Equity(112 [ACY])Equity(117 [AEY])Equity(225 [AHPI])Equity(392 [AMS])Equity(535 [ARTW])Equity(680 [AXR])Equity(925 [BKSC])Equity(1031 [BONT])...Equity(50188 [GEMP])Equity(50237 [SNDE])Equity(50285 [AZRX])Equity(50327 [TYHT])Equity(50349 [AMMA])Equity(50360 [MRAM])Equity(50369 [BCTF])Equity(50374 [OTTW])Equity(50456 [DFFN])Equity(50476 [GNUS])
2016-12-01 09:31:00-05:001004.0400.00.00.01250.50.00.00.0300.01208.0...0.00.0250.00.00.0540.00.0138.00.00.0
2016-12-01 09:32:00-05:000.00.00.00.00.0611.00.00.00.00.0...0.00.00.00.00.00.00.00.00.00.0
2016-12-01 09:33:00-05:000.00.00.0155.00.00.00.00.00.00.0...0.00.01000.00.00.00.00.00.00.00.0
2016-12-01 09:34:00-05:000.00.00.00.00.0106.00.00.0135.00.0...0.00.00.00.00.00.00.00.00.00.0
2016-12-01 09:35:00-05:000.00.00.00.050.00.00.00.00.00.0...0.00.00.00.00.00.00.00.00.0900.0
+

5 rows × 933 columns

+
+
+ +
+ +
+
+ +
+
+
+
+
+

Similar to large cap stocks, we see an uptick in volume at the open and close. However, this occurs on drastically different scales. Not only do small cap stocks trade a lower frequencies and volumes, they also follow a different pattern.

+ +
+
+
+
+
+
In [11]:
+
+
+
small_cap_avg_volume = small_cap_volume['2016-12-1'].mean(axis=1)
+
+plt.subplot(211)
+plt.plot(small_cap_avg_volume.index, small_cap_avg_volume, color='navy')
+plt.title("Intraday Volume Profile - Small Cap")
+plt.ylabel("Volume")
+
+resampled_small_cap_avg_volume = small_cap_avg_volume.resample('10t', closed='right').sum()
+
+plt.subplot(212)
+plt.plot(resampled_small_cap_avg_volume.index, resampled_small_cap_avg_volume/small_cap_avg_volume.sum(), color='navy')
+plt.title("Intraday Volume Profile as % of Total Day - Small Cap")
+plt.ylabel('Volume as % of Total Day')
+
+ +
+
+
+ +
+
+ + +
+ +
Out[11]:
+ + + + +
+
<matplotlib.text.Text at 0x7f75b708d250>
+
+ +
+ +
+ +
+ + + + +
+ +
+ +
+ +
+
+ +
+
+
+
+
+

As the graphs below show, small cap stocks trade a very large portion of their daily volume at the beginnig of their day. Often going above 10% in just the first 10 minutes. This is the exact opposite pattern we saw with our large cap stocks. A reason why small cap stocks may not follow the same pattern is because they are rarely included in index fund portfolios. This causes them to be of no interest to one of the largest sources of volume.

+ +
+
+
+
+
+
In [12]:
+
+
+
small_volume = intraday_volume_profile_data(small_cap_volume)
+
+plt.scatter(small_volume.minute_of_day, small_volume.interval_pct*100, color='navy')
+plt.title('% of Volume in 10 Minute Intervals - Small Cap')
+plt.xlim(0, 400)
+plt.ylabel('% of Volume')
+
+intraday_profile(small_volume, 'Intraday Volume Profile - Small Cap', '% of Day\'s Volume in Bucket', 'Cumulative % of Day\'s Volume')
+
+ +
+
+
+ +
+
+ + +
+ +
+ + + + +
+ +
+ +
+ +
+ +
+ + + + +
+ +
+ +
+ +
+
+ +
+
+
+
+
+

How about if we looked at the small and large cap profiles on one plot? Below is the % of volume in each bar for large vs small cap stocks. It's clear that a large part of the daily volume for small cap stocks come out during the morning, whereas a lot of the trading for larger cap stocks occurs right before the close.

+ +
+
+
+
+
+
In [13]:
+
+
+
intraday_groups(large_volume, small_volume, '% of Day\'s Volume in Bucket', 'Cumulative % of Day\'s Volume')
+
+ +
+
+
+ +
+
+ + +
+ +
+ + + + +
+ +
+ +
+ +
+
+ +
+
+
+
+
+

The following graph is to give an idea of the true difference in magnitude of volume in small and large cap stocks. Quantitative strategies often find price discrepencies or miscalculations of fair value as sources of alpha. These are plentiful in thinly traded stocks. However if there isn't enough volume to complete the trades then the investment ideas have no value. Further, stocks that don't trade very often are culprits for very bad slippage. It's important to understand why volume constraints can eat away all of your returns and even put you in the red.

+ +
+
+
+
+
+
In [14]:
+
+
+
plt.plot(large_cap_avg_volume.index, (large_cap_avg_volume), color='r')
+plt.plot(small_cap_avg_volume.index, (small_cap_avg_volume), color='navy')
+plt.legend(['Large Cap', 'Small Cap'])
+plt.ylabel('Volume')
+plt.xlim(large_cap_avg_volume.index[0] - pd.Timedelta(30, unit='m'), \
+         large_cap_avg_volume.index[-1] + pd.Timedelta(30, unit='m'))
+plt.title('Comparing Volume Magnitudes')
+
+ +
+
+
+ +
+
+ + +
+ +
Out[14]:
+ + + + +
+
<matplotlib.text.Text at 0x7f75b60fb450>
+
+ +
+ +
+ +
+ + + + +
+ +
+ +
+ +
+
+ +
+
+
+
+
+

Volume - Q500 vs. Others¶

+
+
+
+
+
+
+
+

Doing a similar analysis on Q500 stocks versus stocks in neither the Q500 or Q1500, we find surprisingly similar intraday profiles. Although the magnitudes of volume are drastically different, the distribution throughout the day seem very similar. This points to an important issue when trading outside of the Q universes. A strategy that seems sound in research can fail to launch if there isn't enough volume to support it. Imagine a model that prescribes optimal portfolio weightings on a number of stocks. This model would be based on the idea that you would be able to trade when you'd like and you would be able to complete your whole order at one price. However, this is rarely the case. Trading within the Q universes though ensures that there is always plenty of volume. Another characteristic of the Q universes is that classes of hard-to-trade financial instruments like OTCs, ADRs, and LPs are removed. This ensures that only the stocks most easily electronically traded are included in your strategy. At Quantopian, we strongly prefer algorithms that trade within these universes as explained in How to Get an Allocation.

+ +
+
+
+
+
+
In [15]:
+
+
+
all_Q500_data = get_pricing(Q500_assets, frequency='minute',start_date='2016-12-1', end_date='2016-12-31')
+Q500_volume = all_Q500_data['volume']
+Q500_volume = Q500_volume.tz_convert('US/Eastern') # Q data comes in as UTC
+
+all_other_data = get_pricing(np.random.choice(other_assets, size=500), frequency='minute',start_date='2016-12-1', end_date='2016-12-31')
+other_volume = all_other_data['volume']
+other_volume = other_volume.tz_convert('US/Eastern') # Q data comes in as UTC
+
+ +
+
+
+ +
+
+
+
+
+

Looking at the overlapped profiles below of Q500 stocks and stocks not in any of the Q universes, we see a similar pattern. The bars represent the percentage of the day's volume that occurs within that 10 minute interval, while the line plots are the cumulative percent of that entire day's volume. It seems that trading inside and outside of the Q500 wouldn't matter! Before we can say that, let's look at the actual magnitudes of volume.

+ +
+
+
+
+
+
In [16]:
+
+
+
Q500_volume_data = intraday_volume_profile_data(Q500_volume)
+other_volume_data = intraday_volume_profile_data(other_volume)
+
+intraday_groups(Q500_volume_data, other_volume_data, '% of Day\'s Volume in Bucket', 'Cumulative % of Day\'s Volume', 'Q500 vs. Other Stocks - Volume', 'Q500', 'Other')
+
+ +
+
+
+ +
+
+ + +
+ +
+ + + + +
+ +
+ +
+ +
+
+ +
+
+
+
+
+

The plot below shows the true extent to which volume amongst the two classes of stocks differ. Although the shapes may seem the same, placing even relatively small orders outside of the Q universes can cause really huge adverse price movements.

+ +
+
+
+
+
+
In [17]:
+
+
+
Q500_volume_timeOfDay = Q500_volume.groupby(Q500_volume.index.time).mean()
+plt.plot((Q500_volume_timeOfDay.mean(axis=1)), color='r')
+
+other_volume_timeOfDay = other_volume.groupby(other_volume.index.time).mean()
+plt.plot((other_volume_timeOfDay.mean(axis=1)), color='navy')
+
+plt.legend(['Q500 Volume', 'Other Stocks Volume'])
+plt.ylabel('Volume')
+plt.title('Comparing Volume Magnitudes')
+
+ +
+
+
+ +
+
+ + +
+ +
Out[17]:
+ + + + +
+
<matplotlib.text.Text at 0x7f75ade6c550>
+
+ +
+ +
+ +
+ + + + +
+ +
+ +
+ +
+
+ +
+
+
+
+
+

Volatility¶

+
+
+
+
+
+
+
+

As there is no measure of volatility available as a field from get_pricing(), we will have to calculate our own intraday metric. The standard measure for volatility is to use percentage changes in close-to-close prices. However, this won't help us in understanding intraday trading patterns and would not be using the rich OHLC data we have access to. Instead, we will use the Garman and Klass estimate of realized variance as explained in this paper by Almgren (2009). This estimate is the most powerful for stocks that exhibit Brownian motion, even though it assumes that there are no price jumps. Price jumps are when the close price of one bar is not equal to the open bar of the next. Since we are calculating volatility intraday, this may not be as big of an issue for us. The Garman-Klass Yang-Zhang extension may be the answer for individuals who are worried about this drawback. For demonstration purposes, the Garman and Klass estimate is quite powerful and much more efficient than the close-to-close metric.

+ +
+
+
+
+
+
+
+$$\sigma^2 = RV_{GK} = \sum^N_{i=1} \left(\frac{1}{2}\left(H_i - L_i \right)^2 - (2 \log 2 -1) \left( C_i - C_{i-1} \right)^2 \right)$$ +
+
+
+
+
+
+
+

We will measure volatility over 10 minute bars, with $N = 10$; $H_i =$ high of the asset in the $i_{th}$ minute; $L = \text{the low}$; and $C = \text{the close}$.

+ +
+
+
+
+
+
In [19]:
+
+
+
def GK_sum(open_price, high, low, close_price, close_tm1):
+    return 0.5*((high - low)**2) - ((np.log10(4)-1)*((close_price-close_tm1)**2))
+    
+def GK_var(df):
+    df['variance'] = GK_sum(df.open_price, df.high, df.low, df.close_price, df.close_price.shift(1))
+    
+    return pd.DataFrame({'variance': df['variance'].groupby(pd.TimeGrouper('10t', level=1)).sum()})
+
+def intraday_volatility_profile_data(ohlc_data):
+    
+    # calculate variance on a per stock basis
+    groups = ohlc_data.groupby(level=0).apply(GK_var)
+    
+    # take the mean of all variances
+    ten_minute_variance = pd.DataFrame({'variance': groups.groupby(level=1)['variance'].mean()})
+    ten_minute_variance['minute_of_day'] = (ten_minute_variance.index.hour - 9) * 60 + (ten_minute_variance.index.minute - 30)
+    ten_minute_variance['time'] = ten_minute_variance.index.time
+    
+    print ten_minute_variance.head()
+    
+    # calculate daily variance
+    dailySum = pd.DataFrame(ten_minute_variance['variance'].resample('d').sum())
+    dailySum.columns = ['daily_variance']
+    dailySum['day'] = dailySum.index.date
+
+    # calculate interval variance
+    conversion = {'variance' : 'sum', 'minute_of_day' : 'last', 'time':'last'}
+    interval_data = ten_minute_variance.resample('10t', closed='right').apply(conversion)
+    interval_data['day'] = interval_data.index.date
+    interval_data['time'] = interval_data.index.time
+
+    # put them together
+    intraday_data = interval_data.merge(dailySum, how='left', on='day')
+    intraday_data['interval_pct'] = intraday_data['variance'] / intraday_data['daily_variance']
+    
+    return intraday_data
+
+ +
+
+
+ +
+
+
+
+
+

Volatility - Large Cap¶

+
+
+
+
+
+
+
+

Let's look at some data now.

+ +
+
+
+
+
+
In [20]:
+
+
+
large_cap_data = all_large_cap_data
+
+large_cap_data.major_axis = large_cap_data.major_axis.tz_convert('US/Eastern')
+large_cap_data = large_cap_data.transpose(0, 2, 1).to_frame()
+large_cap_data.index.names = ["assets", "date"]
+
+large_cap_data.dropna(inplace=True)
+
+large_cap_volatility = intraday_volatility_profile_data(large_cap_data)
+
+ +
+
+
+ +
+
+ + +
+ +
+ + +
+
                             variance  minute_of_day      time
+date                                                          
+2016-12-01 09:30:00-05:00   93.328003              0  09:30:00
+2016-12-01 09:40:00-05:00   33.156486             10  09:40:00
+2016-12-01 09:50:00-05:00   96.613625             20  09:50:00
+2016-12-01 10:00:00-05:00  103.243739             30  10:00:00
+2016-12-01 10:10:00-05:00  105.477321             40  10:10:00
+
+
+
+ +
+
+ +
+
+
+
+
+

As expected, the first 10 minutes of trading has an incredibly high rate of volatility. Not only is the % of volatility at the open noteworthy, but it's also interesting to see the dispersion of values in the first day minutes across different days. Some days the first bar contains less than 10% of daily volatiliy, on other days however it contains almost 60%. This demonstrates the process of price discovery. Price discovery is how the price of assets are determined in the market place and differs from valuations. The price of an asset is formed through the interactions of buyers and sellers. When we see high volatility in the beginning of the day, this is often a sign of market participants trying to determine the "fair market price" given the information that has come out since the market close the day before. On some days this information is especially material and can cause some huge fluctuations, often a sign of wide spreads. If you take one thing away from this lecture it is that you should not trade in the first 30 minutes of the day, spreads are unreasonably wide and are almost guaranteed to converge once the market settles.

+ +
+
+
+
+
+
In [21]:
+
+
+
# what does the plot of this look like?
+plt.scatter(large_cap_volatility['minute_of_day'], large_cap_volatility['interval_pct']*100)
+plt.title('% of Volatility in 10 Minute Intervals - Large Cap')
+plt.ylabel('% of Volatitliy')
+plt.xlim(-10, 400)
+
+intraday_profile(large_cap_volatility, 'Intraday Volatility Profile - Large Cap', '% of Day\'s Volatilit in Bucket', 'Cumulative % of Day\'s Volatility')
+
+ +
+
+
+ +
+
+ + +
+ +
+ + + + +
+ +
+ +
+ +
+ +
+ + + + +
+ +
+ +
+ +
+
+ +
+
+
+
+
+

Volatility - Small Cap¶

+
+
+
+
+
+
+
+

Looking at small cap companies, it seems that there is a much larger rate of volatility at play. One of the risks of investing in small cap stocks, apart from the risk of volume shortages, is that there is little information about them. This can mean that is it often difficult to discern the "fair market value" of a stock and that price discovery is especially painful. Small cap stocks also experience high rates of volatility as even small trades can become a large percentage of ADV, causing large price movements.

+ +
+
+
+
+
+
In [22]:
+
+
+
small_cap_data = all_small_cap_data
+
+small_cap_data.major_axis = small_cap_data.major_axis.tz_convert('US/Eastern')
+small_cap_data = small_cap_data.transpose(0, 2, 1).to_frame()
+small_cap_data.index.names = ["assets", "date"]
+
+small_cap_data.dropna(inplace=True)
+
+small_cap_volatility = intraday_volatility_profile_data(small_cap_data)
+
+ +
+
+
+ +
+
+ + +
+ +
+ + +
+
                           variance  minute_of_day      time
+date                                                        
+2016-12-01 09:30:00-05:00  0.116178              0  09:30:00
+2016-12-01 09:40:00-05:00  0.394617             10  09:40:00
+2016-12-01 09:50:00-05:00  0.396001             20  09:50:00
+2016-12-01 10:00:00-05:00  1.097885             30  10:00:00
+2016-12-01 10:10:00-05:00  0.399524             40  10:10:00
+
+
+
+ +
+
+ +
+
+
+
In [23]:
+
+
+
small_cap_volatility.dropna().shape
+
+ +
+
+
+ +
+
+ + +
+ +
Out[23]:
+ + + + +
+
(840, 6)
+
+ +
+ +
+
+ +
+
+
+
In [24]:
+
+
+
# what does the plot of this look like?
+plt.scatter(small_cap_volatility['minute_of_day'], small_cap_volatility['interval_pct']*100)
+plt.title('% of Volatility in 10 Minute Intervals - Small Cap')
+plt.xlim(-10, 400)
+plt.ylabel('% of Volatility')
+
+intraday_profile(small_cap_volatility, 'Intraday Volatility Profile - Small Cap', '% of Day\'s Volatility in Bucket', 'Cumulative % of Day\'s Volatility')
+
+ +
+
+
+ +
+
+ + +
+ +
+ + + + +
+ +
+ +
+ +
+ +
+ + + + +
+ +
+ +
+ +
+
+ +
+
+
+
In [25]:
+
+
+
intraday_groups(large_cap_volatility, small_cap_volatility, '% of Day\'s Volatilit in Bucket', 'Cumulative % of Day\'s Volatility')
+
+ +
+
+
+ +
+
+ + +
+ +
+ + + + +
+ +
+ +
+ +
+
+ +
+
+
+
+
+

Transaction Cost Analysis¶

+
+
+
+
+
+
+
+

What are Transaction Costs?¶

Transaction costs are what you would have to pay to execute your investment ideas above and beyond the fair market costs associated the actual securities themselves. This means the difference between the price of the stock you want to buy and the final cost of actually obtaining that stock. Transaction costs are generally separated into two categories: direct and indirect.

+

Direct transaction costs refer to the fees that you would pay to actual individuals and counterparties, and they are usually known beforehand. These can include commission to broker-dealers for execution services, taxes on investment income, and rebates (see Maker-Taker Model).

+

Indirect transaction costs refer to costs that are not known prior to trading and depend highly on the execution strategies used. Two of the biggest components of indirect transaction costs are market impact and opportunity costs. The latter refers to the profits forgone by not being able to enter into a position or the losses incurred by not being to exit a position in time. This can occur when there isn't enough counterparty liquidity to complete your trades or because of untimely price movements. Market impact, which we will be focusing on, is the change in the price of a stock caused by an order to buy or sell it.

+

What is Transaction Cost Analysis?¶

In the institutional setting we're in, we can ignore direct costs as they are trivial compared to the larger effects of market impact. It is immensely important that transaction costs are taken into consideration when devising investment strategies as they are one of the most common reasons why ideas borne in research can fail to pan out in actual markets. Transaction cost analysis (TCA) is helpful in understanding the pitfalls of strategies and is vital in achieving best execution. Although standard measures of best execution rely on comparisons to various benchmarks, such as the VWAP price, it is more about an investor's capability to consider market uncertainties when making trading decisions. In particular, the proliferation of algorithmic trading has advanced TCA to the point where it can be used pre-trade, intraday, and post-trade.

+

Pre-trade TCA, which is the most relevant to us, deals with predicting the market impact of our trades. Specifically, TCA is being integrated into the stock selection phase of the investment cycle through quantitative overlays, market impact scores, cost curves, portfolio optimization, and backtesting. Intraday TCA involves the supervision of execution strategies to ensure they fall within the performance standards that we have set and are behaving appropriately to changing market conditions. Finally, TCA is used post-trade to measure actual performance. The cycle of transaction cost analysis is on-going and vital to the research driven investment proces.

+ +
+
+
+
+
+
+
+

Market Impact¶

+
+
+
+
+
+
+
+

Mathematically, market impact is defined as the "... difference between actual price trajectory after the order is released to the market and the price trajectory that would have occured if the order were never released."$^{[1]}$ Market impact is broken into two components, permanent and temporary. Permanent MI occurs due to the information content you release into the market as you signal your willingness to trade. This causes market participants to alter their perception of fair value for an asset. This is the unavoidable cost of trading. Temporary MI, however, can be managed and minimized using optimal execution strategies, since it is the price change caused by your demand for liquidity. This is highly dependent on your urgency to complete an order (and of course, many other factors), but can losely be thought of as the premium you need to pay to attract counterparties to complete your trade.

+

Market impact models attempt to replicate the effects that a trade would have on the greater market. Empirically, it is shown that market impact increases with the size of the trade, the volatility of the stock, and the urgency with which you would like to complete your trade.

+ +
+
+
+
+
+
+
+

Market Impact Model¶

+
+
+
+
+
+
+
+

We will be implementing a model of market impact based on the following paper by Almgren et al. (2005): Direct Estimation of +Equity Market Impact

+

The paper presents a model that breaks market impact into its two components and attempts to classify the dependence of market impact on order size and trade time. For permanent impact, it is important to have some measure of liquidity which depends on the market parameters that define each individual stock, aside from volume an volatility. Possible candidates for this are shares outstanding, bid-ask spreads, and market capitalization. The authors found shares outstanding, in particular the inverse of "turnover" which is the fraction of a company's total value traded each day, to be the most robust metric to use, compared to bid-ask spreads and market capitalization which was found to have no significant effect. Temporary impact was found to have no such need for stock specific modifications above volume and volatility.

+

Using a modified Gauss-Newtonian optimization algorithm, parameters are found to fit the measures of permanent and temporary impact. Namely, the liquidity factor, $\delta$, is $1/4$, and temporary impact, $\beta$, is defined as a concave function at $3/5$. Empirically, this makes sense. As investors want to trade a larger amount, the less additional trade costs they will incur per share, as we will see. +The model is described below:

+ +
+
+
+
+
+
+
+$$\text{Market Impact} = \text{Permanent Impact} + \text{Temporary Impact}$$$$\text{MI} = \frac{1}{2} \: \overbrace{\gamma \: \sigma \left(\frac{x}{v}\right) \left(\frac{\theta}{v}\right)^{\delta}}^{\text{permanent}} + \overbrace{\eta \: \sigma \: \left| \frac{x}{vt} \right|^{\beta}}^{\text{temporary}} $$$$x = \text{unsigned number of shares to trade}$$$$v = \text{average daily volumme (ADV)}$$$$t = \text{time width in % of trading time}$$$$\sigma = \text{daily volatility}$$$$\theta = \text{shares outstanding}$$$$\delta = 1/4$$$$\beta = 3/5$$

where $\gamma$ and $\eta$ are the "universal coefficients of market impact" and estimated by the authors using a large sample of institutional trades. The interpretation of $\frac{\Theta}{v}$ is the inverse of daily turnover. Finally, as a simplifying measure it is assumed that the order is completed by a uniform rate of trading over the time interval.

+

Potential Limitations¶

Note that this paper was released prior to the adoption and phased implementation of Reg NMS, prior to the "quant meltdown" of August 2007, prior to the financial crisis hitting markets in Q4 2008, and other numerous developments in market microstructure. Nevertheless, this model can provide numerous insights and act as a pivotal first step. More advanced models consider other factors such as the bid-ask spread and book depth, however the model is fit on actual execution data and the realized cost is measured against the mid price. So the act of paying the bid-ask spread over child executions of the parent order is already embedded in the data and the parameters reflect this.

+ +
+
+
+
+
+
In [26]:
+
+
+
# the break-up of the permanent and temporary impacts
+# they are multiplied by 10000 since we want the cost in bps
+def perm_impact(pct_adv, daily_vol_pct=0.25, inv_turnover=200):
+    gamma = 0.314
+    return 10000 * gamma * daily_vol_pct * pct_adv * (inv_turnover)**0.25
+
+def temp_impact(pct_adv, minutes, daily_vol_pct=0.25, minutes_in_day=60*6.5):
+    eta = 0.142
+    day_frac = minutes / minutes_in_day
+    return 10000 * eta * daily_vol_pct * abs(pct_adv/day_frac)**0.6
+
+def mi_bps(pct_adv, minutes, daily_vol_pct=0.25, inv_turnover=200, minutes_in_day=60*6.5):
+    perm = perm_impact(pct_adv, daily_vol_pct, inv_turnover)
+    temp = temp_impact(pct_adv, minutes, daily_vol_pct, minutes_in_day)
+    return 0.5 * perm + temp
+
+ +
+
+
+ +
+
+
+
+
+

Replicated from the paper, we see how the permanent and temporary impacts of trading stock "A" changes as we allow the trade to complete slower and slower.

+ + + + + + + + + + + + + + + + + + + + +
VariableAsset A
Inverse turnover ($\Theta/v$)263
Daily vol ($\sigma$)1.57%
Trade % ADV (X/V)10%
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
ItemFastMediumSlow
Trade duration (day fraction %)10%20%50%
Permanent Impact (bps)202020
Temporary Impact (bps)22158
Total Impact (bps)322518
+

It is important to note here that this is only replicating market impact! There are other aspects to transaction costs, namely opportunity cost, that aren't captured. As we allow ourselves to trade slower we are lowering our temporary market impact, but we are exposing ourselves more and more to adverse price movements and the risk of liquidity depletion.

+

We'll now see our code estimates for the same experiment.

+ +
+
+
+
+
+
In [27]:
+
+
+
print mi_bps(pct_adv=0.1, daily_vol_pct=0.0157, inv_turnover=263, minutes=0.1*60*6.5) 
+print mi_bps(pct_adv=0.1, daily_vol_pct=0.0157, inv_turnover=263, minutes=0.2*60*6.5) 
+print mi_bps(pct_adv=0.1, daily_vol_pct=0.0157, inv_turnover=263, minutes=0.5*60*6.5) 
+
+ +
+
+
+ +
+
+ + +
+ +
+ + +
+
32.2203193206
+24.634874002
+18.4143315025
+
+
+
+ +
+
+ +
+
+
+
+
+

For all the following examples, we will fixe a rate of inverse turnover and focus more on the relationship between trade size and time time. Now, to motivate some intuition, let's look at the relationship between trade costs and trade size at two levels of volatility, given we want to complete in 30 minutes.

+ +
+
+
+
+
+
In [28]:
+
+
+
x = np.linspace(0.0001,0.03)
+plt.plot(x*100,mi_bps(x,30,0.25), label="$\sigma$ = 25%");
+plt.plot(x*100,mi_bps(x,30,0.40), label="$\sigma$ = 40%");
+plt.ylabel('Market Impact (bps)')
+plt.xlabel('Trade as % of ADV')
+plt.title('Market Impact in Basis Points of Trade Value; $\sigma$ = 25% and 40%; time = 30 minutes');
+plt.legend();
+
+ +
+
+
+ +
+
+ + +
+ +
+ + + + +
+ +
+ +
+ +
+
+ +
+
+
+
+
+

Let's look at market impact as it pertains to different combinations of trade size and trade time. The curves below all demonstrate the tradeoff between trade time and trade size. Given a level of market impact, to achieve a higher level of volume would mean having to wait longer to be completed, and thus face the associated risks. It also seems that as you become a larger and larger portion of the average daily volume, the tradeoff becomes less material. As we saw with the graph above, the difference in market impact between two levels of volatility appears to be notable. With the same percentage of ADV and trade time, you would achieve drastically higher rates of market impact. With a trade time of 20 minutes and trade size at 1.5% of ADV, you would have a market impact of approximately 157 bps with 20% volatility, but almost 315 bps with 40% volatility.

+ +
+
+
+
+
+
In [29]:
+
+
+
x = np.linspace(0.001,0.03) # % of ADV
+y = np.linspace(5,30) # trade time in minutes
+X, Y = np.meshgrid(x,y)
+Z = mi_bps(X, Y, 0.20) # 20% is daily vol pct
+levels = np.linspace(0.0, 500, 20)
+cmap=plt.get_cmap('jet')
+
+
+plt.subplot(121)
+CS = plt.contour(X * 100, Y, Z, levels, linewidths=3, cmap=cmap, alpha=0.55)
+plt.clabel(CS)
+plt.ylabel('Trading Time (minutes)')
+plt.xlabel('Trade Size (% of ADV)')
+plt.title('Market Impact in Basis Points of Trade Value; $\sigma$ = 20%')
+
+plt.subplot(122)
+Z = mi_bps(X , Y, 0.40)
+CS = plt.contour(X * 100, Y, Z, levels, linewidths=3,cmap=cmap, alpha=0.55)
+plt.clabel(CS)
+plt.xlabel('Trade Size (% of ADV)')
+plt.title('Market Impact in Basis Points of Trade Value; $\sigma$ = 40%')
+
+ +
+
+
+ +
+
+ + +
+ +
Out[29]:
+ + + + +
+
<matplotlib.text.Text at 0x7f75b5c4ff90>
+
+ +
+ +
+ +
+ + + + +
+ +
+ +
+ +
+
+ +
+
+
+
+
+

Alternatively, we might want to get some intuition as to if we wanted to limit our cost, how does the trading time vary versus percentage of ADV. On one end of the spectrum, you'll see that wanting to keep your market impact at a minimum while executing a large portion of shares means being very patient (it would take almost the entire day to complete)! As well, we can see that keeping % ADV and MI the same, we would have to accept much longer trade times on comparable stocks with greater volatility.

+ +
+
+
+
+
+
In [30]:
+
+
+
x = np.linspace(0.001, 0.03) # % ADV
+y = np.linspace(1, 60 * 6.5)   # time to trade
+X, Y = np.meshgrid(x,y)
+
+levels = np.linspace(0.0, 400, 20)
+cmap=plt.get_cmap('jet')
+
+plt.subplot(121)
+
+Z = mi_bps(X, Y, 0.20)
+plt.contourf(X * 100, Z, Y, levels, cmap=cmap, alpha=0.55)
+plt.title('Trading Time in Minutes; $\sigma$ = 20%')
+plt.xlabel('Trade Size (% of ADV)')
+plt.ylabel('Market Impact (bps)')
+plt.ylim(5, 500)
+plt.colorbar()
+
+plt.subplot(122)
+Z = mi_bps(X, Y, 0.40)
+plt.contourf(X * 100, Z, Y, levels, cmap=cmap, alpha=0.55)
+plt.title('Trading Time in Minutes; $\sigma$ = 40%')
+plt.xlabel('Trade Size (% of ADV)')
+plt.ylim(5, 500)
+plt.colorbar()
+
+ +
+
+
+ +
+
+ + +
+ +
Out[30]:
+ + + + +
+
<matplotlib.colorbar.Colorbar at 0x7f75b5f44310>
+
+ +
+ +
+ +
+ + + + +
+ +
+ +
+ +
+
+ +
+
+
+
+
+

The Breakdown: Permanent and Temporary¶

For a typical stock, let's see how market impact is broken down into permanent and temporary.

+ +
+
+
+
+
+
In [31]:
+
+
+
minutes = 30 # we want to complete our orders in 30 minutes
+
+x = np.linspace(0.0001,0.03) # % of ADV
+
+f, (ax1, ax2) = plt.subplots(ncols=2, sharex=True, sharey=False)
+f.subplots_adjust(hspace=0.15)
+    
+p = 0.5*perm_impact(x, 0.20)
+t = mi_bps(x, minutes, 0.20)
+
+ax1.fill_between(x * 100, p, t, color='b',alpha=0.33)
+ax1.fill_between(x * 100, 0, p, color='k',alpha=0.66)
+
+ax1.set_ylabel('Market Impact (bps)')
+ax1.set_xlabel('Trade Size (% of ADV)')
+ax1.set_title('Market Impact (bps) of Trade Value; $\sigma$ = 20%; time = 30 minutes')
+ax1.set_ylim(0, 400)
+ax1.legend(['Temporary', 'Permanent'])
+
+p = 0.5*perm_impact(x, 0.40)
+t = mi_bps(x, minutes, 0.40)
+
+ax2.fill_between(x * 100, p, t, color='b',alpha=0.33)
+ax2.fill_between(x * 100, 0, p, color='k',alpha=0.66)
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+ax2.set_xlabel('Trade Size (% of ADV)')
+ax2.set_title('Market impact (bps) of Trade Value; $\sigma$ = 40%; time = 30 minutes')
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Out[31]:
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<matplotlib.text.Text at 0x7f75adf8d8d0>
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Ranking the Q Universes¶

Now, let's look at price impact with actual stocks, comparing across those in Q universes and those not.

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Taking our pipeline results from the beginning of the lecture, we'll calculate for each asset ADV, annualized volatility, and daily volatility.

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In [32]:
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T = len(pipeline_results.index.levels[0])
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+metrics = pd.DataFrame({'ADV': pipeline_results.volume.mean(level=1),
+                       'Annualized Volatility': (pipeline_results.returns.std(level=1)*(250/(T-1)))**0.5,
+                       'Daily Volatility': (pipeline_results.returns.std(level=1)*(T-1))**0.5,
+                       'Market Cap': pipeline_results.market_cap.mean(level=1),
+                       'Shares Outstanding': pipeline_results.shares_outstanding.mean(level=1),
+                       'Annual Returns': pipeline_results.returns.mean(level=1),
+                       'Q1500': pipeline_results.groupby(level=1)['Q1500'].any(),
+                       'Q500': pipeline_results.groupby(level=1)['Q500'].any()}).dropna()
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+metrics.head()
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Out[32]:
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ADVAnnual ReturnsAnnualized VolatilityDaily VolatilityMarket CapQ1500Q500Shares Outstanding
Equity(21 [AAME])3.683864e+030.0049100.6808150.9406827.907041e+07FalseFalse2.042340e+07
Equity(24 [AAPL])2.218087e+070.0017810.2899100.4005686.075929e+11TrueTrue5.332310e+09
Equity(31 [ABAX])1.165872e+050.0005480.3881040.5362431.185146e+09FalseFalse2.253473e+07
Equity(39 [DDC])3.021574e+050.0012990.4636800.6406668.251480e+08FalseFalse8.781810e+07
Equity(41 [ARCB])2.472507e+05-0.0038120.4597220.6351977.760125e+08FalseFalse2.563985e+07
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Note: $\sigma_{annual} = \sqrt{\frac{250}{T - 1}\sum^{T}_{i = 2}(r_i - r_{avg})^2}$ and $\sigma_{daily} = \sqrt{\frac{1}{T - 1}\sum^{T}_{i = 2}(r_i - r_{avg})^2}$

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Assume we would like to trade 10% of the average daily volume and complete our orders within 30 minutes. What would our average market impact be across stocks in the Q500, Q1500, and stocks in neither of those universes?

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Looking at the box plots below, we cannot discern any difference between market impact in the Q500 and Q1500 universes, however it clear that trading outside of both universes is likely to have a material impact on returns.

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In [33]:
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metrics['MI'] = mi_bps(0.1, 30, metrics['Daily Volatility'], metrics['Shares Outstanding']/metrics['ADV'])
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+Q500_metrics = metrics[(metrics['Q500'])]
+Q1500_metrics = metrics[(metrics['Q1500'])]
+other = metrics[(~metrics['Q500']) & (~metrics['Q1500'])]
+
+plt.boxplot([Q500_metrics['MI'], Q1500_metrics['MI'], other['MI']], showfliers=False)
+plt.xticks([1, 2, 3], ['Q500', 'Q1500', 'Everything Else'])
+plt.ylabel('Market Impact (bps)')
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<matplotlib.text.Text at 0x7f75b645e450>
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We can quickly test for statistically significant differences between the groupings using the Kolmogorov-Smirnov statistic. We will test all the groups against each other, with our null hypothesis being that they are drawn from the same distribution.

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In [34]:
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d1, p_value1 = stats.ks_2samp(Q500_metrics['MI'], Q1500_metrics['MI'])
+print 'p-value for difference between market impact of Q500 and Q1500 stocks:', p_value1
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+d2, p_value2 = stats.ks_2samp(Q1500_metrics['MI'], other['MI']) 
+print 'p-value for difference between market impact of Q1500 and other stocks: ', p_value2
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+d3, p_value3 = stats.ks_2samp(Q500_metrics['MI'], other['MI'])
+print 'p-value for difference between market impact of Q500 and other stocks: ', p_value3
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p-value for difference between market impact of Q500 and Q1500 stocks: 0.000627224351035
+p-value for difference between market impact of Q1500 and other stocks:  9.9129022091e-172
+p-value for difference between market impact of Q500 and other stocks:  3.29031211248e-99
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We will also look at how they vary with respect to annual returns.

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In [35]:
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plt.subplot(311)
+plt.scatter(Q500_metrics['MI'], Q500_metrics['Annual Returns'], marker="x", color="b")
+plt.axvline(Q500_metrics['MI'].mean(), color='g', linestyle='--', lw=2)
+plt.title("MI vs. Returns - Q500")
+plt.xlabel('Market Impact (bps)')
+plt.ylabel('Annual Returns')
+plt.xlim(0, 6000)
+plt.ylim(-0.1, 0.2)
+
+plt.subplot(312)
+plt.scatter(Q1500_metrics['MI'], Q1500_metrics['Annual Returns'], marker="x", color="r")
+plt.axvline(Q1500_metrics['MI'].mean(), color='g', linestyle='--', lw=2)
+plt.title("MI vs. Returns - Q1500")
+plt.xlabel('Market Impact (bps)')
+plt.ylabel('Annual Returns')
+plt.xlim(0, 6000)
+plt.ylim(-0.1, 0.2)
+
+plt.subplot(313)
+plt.scatter(other['MI'], other['Annual Returns'], marker="x", color="y")
+plt.axvline(other['MI'].mean(), color='g', linestyle='--', lw=2)
+plt.title("MI vs. Returns - Others")
+plt.xlabel('Market Impact (bps)')
+plt.ylabel('Annual Returns')
+plt.xlim(0, 6000)
+plt.ylim(-0.1, 0.2)
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+plt.tight_layout()
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For the Optimization Objective Function¶

Although beyond the scope of this lecture, the goal for pre-trade transaction cost analysis is to utilize it in our portfolio selection process. We want to ensure that the alphas we are trying to capture are not overwhelmed by their transaction costs. Usually, this would involve including a factor of trade cost into our model before the optimization step. This will be discussed in more detail in future lectures.

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Sources:

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[1] Kissell, Robert. Science of Algorithmic Trading and Portfolio Management. Elsevier, Inc., 2014.

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[2] Strumpf, Dan. “Stock-Market Traders Pile In at the Close.” The Wall Street Journal, Dow Jones & Company, 27 May 2015, www.wsj.com/articles/traders-pile-in-at-the-close-1432768080

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This presentation is for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation for any security; nor does it constitute an offer to provide investment advisory or other services by Quantopian, Inc. ("Quantopian"). Nothing contained herein constitutes investment advice or offers any opinion with respect to the suitability of any security, and any views expressed herein should not be taken as advice to buy, sell, or hold any security or as an endorsement of any security or company. In preparing the information contained herein, Quantopian, Inc. has not taken into account the investment needs, objectives, and financial circumstances of any particular investor. Any views expressed and data illustrated herein were prepared based upon information, believed to be reliable, available to Quantopian, Inc. at the time of publication. Quantopian makes no guarantees as to their accuracy or completeness. All information is subject to change and may quickly become unreliable for various reasons, including changes in market conditions or economic circumstances.

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