wassname/options_backtester
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rebalance modified

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Camilo1704
2020-03-12 19:00:53 -03:00
parent e16dc77508
commit f23aa0ee01
2 changed files with 1428 additions and 34 deletions
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2legs_example.ipynb
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backtester/backtester.py
+54 -34
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@@ -116,7 +116,8 @@ class Backtest:
bar = pyprind.ProgBar(len(stock_dates), bar_char='█')
for date, stocks, options in data_iterator:
if date in rebalancing_days:
if (date in rebalancing_days):
previous_rb_date = rebalancing_days[rebalancing_days.get_loc(date) -
1] if rebalancing_days.get_loc(date) != 0 else date
self._update_balance(previous_rb_date, date, self._stocks_data, self._options_data)
@@ -173,26 +174,37 @@ class Backtest:
sma_days (int): SMA window size
"""
# Sell all the options currently in the inventory
self._sell_options(options, date)
self._execute_option_exits(date, options)
stock_capital = self._current_stock_capital(stocks)
total_capital = self.current_cash + stock_capital
options_capital = self._current_options_capital(options)
total_capital = self.current_cash + stock_capital + options_capital
options_allocation = self.allocation['options'] * total_capital
#buy stocks
stocks_allocation = self.allocation['stocks'] * total_capital
# Clear inventories
self._initialize_inventories()
self._stocks_inventory = pd.DataFrame(columns=['symbol', 'price', 'qty'])
self._buy_stocks(stocks, stocks_allocation, sma_days)
self._execute_option_entries(date, options, options_allocation)
stock_capital = self._current_stock_capital(stocks)
stocks_value = sum(self._stocks_inventory['price'] * self._stocks_inventory['qty'])
options_value = sum(self._options_inventory['totals']['cost'] * self._options_inventory['totals']['qty'])
self.current_cash = stocks_allocation - stock_capital
# Update current cash
self.current_cash = total_capital - options_value - stocks_value
# exit/enter contracts
if self.allocation['options'] * total_capital >= options_capital:
self._execute_option_entries(date, options, options_allocation - options_capital)
else:
to_sell = options_capital - options_allocation
options_value = self._get_current_option_quotes(options)
self._sell_some_options(date, to_sell, options_value)
options_value = self._current_options_capital(options)
value = self._get_current_option_quotes(options)
#current cash due to options added _execute_option_entries or _options_to_sell
def _sell_options(self, options, date):
# This method essentially recycles most of the code in the filter_exits method in Strategy.
# The whole thing needs a refactor.
@@ -229,6 +241,23 @@ class Backtest:
self.trade_log = self.trade_log.append(candidates, ignore_index=True)
self.current_cash -= sum(total_costs)
def _sell_some_options(self, date, to_sell, options_value):
sold = 0
values_by_row = [0] * len(options_value[0])
for i in range(len(self._options_strategy.legs)):
values_by_row += options_value[i]['cost'].values # sum in each row all the values in the leg
for i, (contract_per_row, inventory_row) in enumerate(zip(values_by_row, self._options_inventory.iterrows())):
if to_sell - sold < -contract_per_row * inventory_row[1]['totals']['qty']:
qty_to_sell = to_sell // contract_per_row
self._options_inventory.at[i, ('totals', 'date')] = date
self._options_inventory.at[i, ('totals', 'qty')] += qty_to_sell
sold -= (qty_to_sell * contract_per_row)
self.current_cash = to_sell - sold
def _current_stock_capital(self, stocks):
"""Return the current value of the stocks inventory.
@@ -246,25 +275,15 @@ class Backtest:
return (current_stocks[self._stocks_schema['adjClose']] * current_stocks['qty']).sum()
def _current_options_capital(self, options):
# Currently unused method
total_cost = 0.0
for leg in self._options_strategy.legs:
current_options = self._options_inventory[leg.name].merge(options,
how='left',
left_on='contract',
right_on=self._options_schema['contract'])
price_col = (~leg.direction).value
try:
cost = current_options[price_col].fillna(
0.0).iloc[0] * self._options_inventory['totals']['qty'].values[0] * self.shares_per_contract
if price_col == 'bid':
total_cost += cost
else:
total_cost -= cost
except IndexError:
total_cost += 0.0
return total_cost
options_value = self._get_current_option_quotes(options)
values_by_row = [0] * len(options_value[0])
if len(options_value[0]) != 0:
for i in range(len(self._options_strategy.legs)):
values_by_row += options_value[i]['cost'].values
total = -sum(values_by_row * self._options_inventory['totals']['qty'].values)
else:
total = 0
return total
def _buy_stocks(self, stocks, allocation, sma_days):
"""Buys stocks according to their given weight, optionally using an SMA entry filter.
@@ -384,7 +403,8 @@ class Backtest:
# Update options inventory, trade log and current cash
self._options_inventory = self._options_inventory.append(entries, ignore_index=True)
self.trade_log = self.trade_log.append(entries, ignore_index=True)
self.current_cash -= sum(total_costs)
self.current_cash += options_allocation - sum(total_costs * qty)
def _execute_option_exits(self, date, options):
"""Exits option positions according to `self._options_strategy`.
@@ -421,7 +441,7 @@ class Backtest:
# Append the 'totals' column to exit_candidates
qtys = self._options_inventory['totals']['qty']
total_costs = sum([exit_candidates[l.name]['cost'] for l in self.legs])
total_costs = sum([exit_candidates[l.name]['cost'] for l in self._options_strategy.legs])
totals = pd.DataFrame.from_dict({'cost': total_costs, 'qty': qtys, 'date': date})
totals.columns = pd.MultiIndex.from_product([['totals'], totals.columns])
exit_candidates = pd.concat([exit_candidates, totals], axis=1)