option order. fix vertical strategy generation.

examples/option_order_place_iron_condor.py

@@ -1,14 +1,18 @@
+#
+# IC example not functional as of the 0.3.0 release
+# pull requests welcome!
+#
+
 import configparser
 from fast_arrow import (
     Client,
     IronCondor,
     Option,
     OptionChain,
     OptionOrder,
-    Stock,
+    Stock
 )
 
-
 #
 # get the authentication configs
 #

examples/option_order_place_single.py

@@ -37,8 +37,6 @@
 ed = oc['expiration_dates'][3]
 ops = Option.in_chain(client, oc["id"], expiration_dates=[ed])
 
-import ipdb; ipdb.set_trace()
-
 #
 # select the $SPY calls
 #

examples/option_order_place_vertical.py

@@ -34,7 +34,7 @@
 stock = Stock.mergein_marketdata_list(client, [stock])[0]
 
 oc = OptionChain.fetch(client, stock["id"], symbol)
-ed = oc['expiration_dates'][3]
+ed = oc['expiration_dates'][0]
 ops = Option.in_chain(client, oc["id"], expiration_dates=[ed])
 
 #
@@ -46,20 +46,23 @@
 # genrate vertical spread table
 #
 width = 1
-df = Vertical.gen_df(ops, width, "put", "sell")
+spread_type = "put"
+spread_kind = "sell"
+df = Vertical.gen_df(ops, width, spread_type, spread_kind)
 
 #
 # select the 4th row (should be a deep OTM put, credit spread)
 #
-vertical = df.iloc[[4]]
+index = int(len(ops) / 4)
+vertical = df.iloc[[index]]
 
 #
 # create the order
 #
 direction = "credit"
 
 legs = [
-    {   "side": "sell",
+    {   "side": spread_kind,
         "option": vertical["instrument"].values[0],
         "position_effect": "open",
         "ratio_quantity": 1
@@ -85,10 +88,11 @@
 trigger = "immediate"
 order_type = "limit"
 
-print("Selling a {} {}/{} Put Spread for {} (notional value = ${})".format(
+print("Selling a {} {}/{} {} spread for {} (notation value = ${})".format(
     symbol,
     vertical["strike_price"].values[0],
     vertical["strike_price_shifted"].values[0],
+    spread_type,
     price,
     my_bid_price_rounded)
 )

fast_arrow/client.py

@@ -46,7 +46,6 @@ def get(self, url=None, params=None, retry=True):
         Execute HTTP GET
         '''
         headers = self._gen_headers(self.access_token, url)
-
         attempts = 1
         while attempts <= HTTP_ATTEMPTS_MAX:
             try:
@@ -55,7 +54,9 @@ def get(self, url=None, params=None, retry=True):
                 return res.json()
             except requests.exceptions.RequestException as e:
                 attempts += 1
-                if retry and res.status_code in [403]:
+                if res.status_code in [400]:
+                    raise e
+                elif retry and res.status_code in [403]:
                     self.relogin_oauth2()
 
 
@@ -75,7 +76,9 @@ def post(self, url=None, payload=None, retry=True):
                     return res.json()
             except requests.exceptions.RequestException as e:
                 attempts += 1
-                if retry and res.status_code in [403]:
+                if res.status_code in [400]:
+                    raise e
+                elif retry and res.status_code in [403]:
                     self.relogin_oauth2()
 
 

fast_arrow/option_strategies/iron_condor.py

@@ -58,6 +58,8 @@ def generate_by_deltas(cls, options,
         - set delta for inner leg of the call credit spread (eg, 0.1)
         """
 
+        raise Exception("Not Implemented starting at the 0.3.0 release")
+
         #
         # put credit spread
         #

fast_arrow/option_strategies/vertical.py

@@ -21,8 +21,8 @@ def gen_df(cls, options, width, spread_type="call", spread_kind="buy"):
         # get CALLs or PUTs
         options = list(filter(lambda x: x["type"] == spread_type, options))
 
-        coef = (1 if spread_kind == "sell" else -1)
-        shift = width * -1
+        coef = (1 if spread_type == "put" else -1)
+        shift = width * coef
 
         df = pd.DataFrame.from_dict(options)
         df['expiration_date'] = pd.to_datetime(df['expiration_date'], format="%Y-%m-%d")
@@ -34,17 +34,22 @@ def gen_df(cls, options, width, spread_type="call", spread_kind="buy"):
         for k,v in df.groupby("expiration_date"):
             sdf = v.shift(shift)
 
-            df.loc[v.index, "strike_price_shifted"]     = sdf["strike_price"]
-            df.loc[v.index, "delta_shifted"]            = sdf["delta"]
-            df.loc[v.index, "volume_shifted"]           = sdf["volume"]
-            df.loc[v.index, "open_interest_shifted"]    = sdf["open_interest"]
-            df.loc[v.index, "instrument_shifted"]       = sdf["instrument"]
+            df.loc[v.index, "strike_price_shifted"] = sdf["strike_price"]
+            df.loc[v.index, "delta_shifted"] = sdf["delta"]
+            df.loc[v.index, "volume_shifted"] = sdf["volume"]
+            df.loc[v.index, "open_interest_shifted"] = sdf["open_interest"]
+            df.loc[v.index, "instrument_shifted"] = sdf["instrument"]
+            df.loc[v.index, "adjusted_mark_price_shift"] = sdf["adjusted_mark_price"]
 
             if spread_kind == "sell":
-                df.loc[v.index, "margin"] = sdf["strike_price"] - v["strike_price"]
+                df.loc[v.index, "margin"] = abs(sdf["strike_price"] - v["strike_price"])
             else:
                 df.loc[v.index, "margin"] = 0.0
 
-            df.loc[v.index, "premium_adjusted_mark_price"] = (sdf["adjusted_mark_price"] - v["adjusted_mark_price"]) * coef
+            if spread_kind == "buy":
+                df.loc[v.index, "premium_adjusted_mark_price"] = (v["adjusted_mark_price"] - sdf["adjusted_mark_price"])
+            elif spread_kind == "sell":
+                df.loc[v.index, "premium_adjusted_mark_price"] = (sdf["adjusted_mark_price"] - v["adjusted_mark_price"])
+
 
         return df