GOAL: The goal of this program is to allow for quick multivariate analysis for a wide range of stock trading hypotheses.

fundamental.py

• Used for all handling of fundamental data and calculations related to it. This is where all the Roaring Kitty analysis happens
• Very much a WIP
• getStatements() takes a stock ticker and gets cashflow_statement, balance_sheet, and income_statement. returns them as individual dataframes
• calc() will be renamed, this will be the function that 'builds' the dataframe(spreadsheet) using all the other functions
• class Calculations contains all the calculations I had in my attempt to recreate roaring kitty's spreadsheet. If you're aware of his work and notice a calculation missing please add it.

indicators.py

• VWAP() calculates vwap
• AVWAP() takes var window_days calculates vwap with a rolling window average
• rest of functions are various functions used to generate a trendline indicator. Probably very messy and almost certainly needs refactor

main.py

• testPerf = False // True runs performance calculations on the code
• lookback // should be refactored as its a var for an indicator
• view // should be refactored as its a var for a strategy
• strat // int representing the strategy you're picking. Need to think of better solution
• d1 // string of date that you start at year-month-day
• d2 // end date string year-month-day
• stocks = [] // list of stock tickers you want to analyze
• if(testPerf) ignore this if you set it to false, but if True you need to change the function call to processDataMultiple in this aswell

MAIN FUNCTION CALL

• results.processDataMultiple(stocks, d1, d2, lookback, view, strat = strat, plotMe = True) this is the MEAT of the program. Analyzes all the stocks you have in your list
• and calls all other functions. Plots and or outputs results for strategy and stocks you selected. Below that is formatting for sql and for convenience of messing with random tests.

performance.py

Used for calculating various performance metrics

• calc() calculates various metrics..
• output() writes certain metrics to console
• basePerf() returns profit factor, sharpe and sortino ratios for stock.

raw_data.db

Database for storing RAW ohlc and volume data from yfinance

results.py

Main code for handling the processing of the data and the performance results

• processData() used for calculating various performance metrics for the stock
• average() should probably be in sql.py idk messy code for getting the average of the buy and hold & strategy performance results. Used when manually messing with things not sure if this is called anywhere
• processDataMultiple() This is lazily done for now as it takes some input args related to strategies, when they should be seperate. That being said this func takes a list of stocks, date from, date to, an indicator variable "lookback" and a strategy variable "view" (these are the things that need to be refactored) along with an int representing the strategy being selected, and plotMe which is a bool that decides whether or not to plot performance plots for the list of stocks.
• There's also initial_balance and position_size_percent again this was hastily done but this is for generating the equity curve, should probably be a var that you can change in main

signals.py

• Used to generate buy or sell signals based on strategy selected. Most of the functions need to be moved to indicators.py
• signal() this is a really messy function right now but it's currently setup to handle the strategy logic for each strategy. I want to make this more clear as I want to be able to mix and match indicators as well as strategy logic.
• a dumb example is lets say RSI strat that uses signal generated from RSI is returning a 1, and you want to combine that with a VWAP strategy to only have the final signal return 1 when they both return 1
• This should be possible and modular just like combining indicators to generate a strategy will be

sql.py

• Contains all sql functionality
  • deleteTable() deletes table in db
  • getTables() lists all the tables in the db
  • writeRaw() writes the raw data to the raw_data db
  • exists() checks to see if data for a specific stock & time period exists in the DB to avoid downloading from yfinance again
  • getData() used to get the data from sql

stock_data.db

Database for storing log data and ideally any calculations made on the raw data that may be reused later (again from yfinance)

temp.csv

• temp file used for thoughts & notes that have no real place in code / too bulky