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| import pandas as pd | |
| from ib_insync import Future, IB, Forex | |
| from syscore.objects import missing_data | |
| ## MODIFY SO RETURNS *ALL* RELEVANT STUFF! | |
| ## DO A FULL RUN WITH *ALL* INSTRUMENTS INCLUDING MISSING SGX | |
| ## DOUBLE CHECK ALL FIGURES | |
| def identify_duplicates(ib, symbol, exchange): | |
| print("%s %s" % (symbol, exchange)) | |
| future = Future(symbol=symbol, exchange = exchange) | |
| contracts = ib.reqContractDetails(future) | |
| if len(contracts)==0: | |
| print("Missing data for %s/%s" % (symbol, exchange)) | |
| return missing_data | |
| list_of_ccy= [contract.contract.currency for contract in contracts] | |
| list_of_multipliers = [contract.contract.multiplier for contract in contracts] | |
| unique_list_of_ccy = list(set(list_of_ccy)) | |
| unique_list_of_multipliers= list(set(list_of_multipliers)) | |
| if len(unique_list_of_multipliers)>1: | |
| print("%s/%s more than one multiplier %s" % | |
| (symbol, exchange, str(unique_list_of_multipliers))) | |
| multiplier = str(unique_list_of_multipliers) | |
| else: | |
| multiplier = unique_list_of_multipliers[0] | |
| if len(unique_list_of_ccy)>1: | |
| print("%s/%s more than one currency %s" % | |
| (symbol, exchange, str(unique_list_of_multipliers))) | |
| currency = str(unique_list_of_ccy) | |
| else: | |
| currency = unique_list_of_ccy[0] | |
| return [symbol, exchange, currency, multiplier] | |
| import numpy as np | |
| def get_stats_for_data_row(ib, data_row, all_fx_rates): | |
| list_of_contracts = get_list_of_contracts(ib, | |
| data_row.Symbol, | |
| data_row.Exchange, | |
| data_row.Currency, | |
| data_row.Multiplier) | |
| if len(list_of_contracts)==0: | |
| print("Couldn't get list of contracts for %s" % str(data_row)) | |
| return missing_data | |
| list_of_market_data = \ | |
| get_list_of_market_data_for_list_of_contract_details(ib, | |
| list_of_contract_details=list_of_contracts) | |
| highest_volume_index, contracts_per_day = contract_with_highest_volumes(list_of_market_data) | |
| true_multiplier = adjust_multiplier(data_row.Multiplier, | |
| list_of_contract_details = list_of_contracts, | |
| highest_volume_index = highest_volume_index) | |
| print("Adjusted multiplier from %f to %s" % (float(data_row.Multiplier), | |
| true_multiplier)) | |
| dollar_volume = \ | |
| normalised_volume_for_list_of_market_data(list_of_market_data=list_of_market_data, | |
| highest_volume_index=highest_volume_index, | |
| multiplier=true_multiplier, | |
| all_fx_rates=all_fx_rates, | |
| currency=data_row.Currency) | |
| risk_per_contract = get_risk_per_contract_in_dollars(list_of_market_data=list_of_market_data, | |
| highest_volume_index=highest_volume_index, | |
| all_fx_rates=all_fx_rates, | |
| multiplier=true_multiplier, | |
| currency=data_row.Currency) | |
| risk_adjusted_cost, slippage = risk_adjusted_cost_and_slippage_per_trade(ib, | |
| list_of_market_data=list_of_market_data, | |
| list_of_contract_details=list_of_contracts, | |
| highest_volume_index=highest_volume_index, | |
| commission=data_row.Commission, | |
| multiplier =true_multiplier | |
| ) | |
| pattern = expiry_pattern_string(list_of_market_data=list_of_market_data, | |
| list_of_contract_details=list_of_contracts) | |
| return [data_row.Symbol, | |
| data_row.Exchange, | |
| data_row.Multiplier, | |
| data_row.Currency, | |
| dollar_volume, | |
| risk_adjusted_cost, | |
| risk_per_contract, | |
| contracts_per_day, | |
| true_multiplier, | |
| data_row.Commission, | |
| slippage, | |
| pattern] | |
| def get_list_of_contracts(ib, symbol, exchange, currency, multiplier): | |
| multiplier = float(multiplier) | |
| if multiplier<1.0: | |
| use_multiplier = str(multiplier) | |
| else: | |
| use_multiplier = str(int(multiplier)) | |
| future = Future(symbol=symbol, | |
| exchange=exchange, | |
| currency=currency, | |
| multiplier=use_multiplier) | |
| list_of_contract_details = ib.reqContractDetails(future) | |
| list_of_contract_details_valid = remove_expired_contracts(list_of_contract_details) | |
| return list_of_contract_details_valid | |
| def remove_expired_contracts(list_of_contract_details): | |
| list_of_contract_details_valid = [contract_detail | |
| for contract_detail in list_of_contract_details | |
| if contract_still_valid(contract_detail)] | |
| return list_of_contract_details_valid | |
| def contract_still_valid(contract_details): | |
| expiry_as_str = contract_details.contract.lastTradeDateOrContractMonth | |
| expiry_as_date = datetime.datetime.strptime(expiry_as_str, '%Y%m%d') | |
| if expiry_as_date>datetime.datetime.now(): | |
| return True | |
| else: | |
| return False | |
| def get_list_of_market_data_for_list_of_contract_details(ib, list_of_contract_details): | |
| list_of_market_data = [ib.reqHistoricalData(contract_details.contract, | |
| durationStr='20 D', | |
| barSizeSetting='1 day', | |
| endDateTime='', | |
| whatToShow='TRADES', | |
| useRTH=True) | |
| for contract_details in list_of_contract_details] | |
| return list_of_market_data | |
| def adjust_multiplier(raw_multiplier, | |
| list_of_contract_details, | |
| highest_volume_index): | |
| raw_multiplier_as_float = float(raw_multiplier) | |
| priceMagnifier = get_price_magnifier(list_of_contract_details, | |
| highest_volume_index=highest_volume_index) | |
| adjusted_multiplier = raw_multiplier_as_float / priceMagnifier | |
| return adjusted_multiplier | |
| def get_price_magnifier(list_of_contract_details, | |
| highest_volume_index): | |
| relevant_contract_details = list_of_contract_details[highest_volume_index] | |
| priceMagnifier = relevant_contract_details.priceMagnifier | |
| return priceMagnifier | |
| def normalised_volume_for_list_of_market_data(list_of_market_data, | |
| highest_volume_index, | |
| multiplier, | |
| currency, | |
| all_fx_rates): | |
| adv_highest_volume = average_volumes_by_contract(list_of_market_data)[highest_volume_index] | |
| daily_stdev = price_standard_deviation_for_contract_with_highest_volume(highest_volume_index, | |
| list_of_market_data) | |
| risk_per_contract_usd = get_risk_per_contract_in_dollars(list_of_market_data=list_of_market_data, | |
| highest_volume_index=highest_volume_index, | |
| multiplier=multiplier, | |
| currency=currency, | |
| all_fx_rates=all_fx_rates) | |
| volume_in_dollar_risk = adv_highest_volume * risk_per_contract_usd | |
| print("Highest volume %f Risk per contract %f Volume in dollar risk %f" % | |
| (adv_highest_volume, daily_stdev, volume_in_dollar_risk)) | |
| return volume_in_dollar_risk | |
| def get_risk_per_contract_in_dollars(list_of_market_data, | |
| highest_volume_index, | |
| currency, | |
| all_fx_rates, | |
| multiplier | |
| ): | |
| risk_per_contract = get_risk_per_contract(list_of_market_data=list_of_market_data, | |
| highest_volume_index=highest_volume_index, | |
| multiplier=multiplier) | |
| fx_rate = all_fx_rates[currency] | |
| return fx_rate*risk_per_contract | |
| def get_risk_per_contract(list_of_market_data, | |
| highest_volume_index, | |
| multiplier): | |
| daily_stdev = price_standard_deviation_for_contract_with_highest_volume(highest_volume_index=highest_volume_index, | |
| list_of_market_data=list_of_market_data) | |
| risk_per_contract = 16* daily_stdev * multiplier | |
| return risk_per_contract | |
| def risk_adjusted_cost_and_slippage_per_trade(ib, | |
| list_of_contract_details, | |
| list_of_market_data, | |
| highest_volume_index, | |
| multiplier, | |
| commission): | |
| risk_per_contract = get_risk_per_contract(list_of_market_data=list_of_market_data, | |
| multiplier=multiplier, | |
| highest_volume_index=highest_volume_index) | |
| spread = spread_for_contract_with_highest_volume(ib, | |
| highest_volume_index, | |
| list_of_contract_details=list_of_contract_details) | |
| slippage = spread/2 | |
| cost_per_trade = commission + multiplier*slippage | |
| cost_per_trade_SR = cost_per_trade / risk_per_contract | |
| print("Risk per contract %f Spread %f Commission %f Cost per trade SR %f" | |
| % (risk_per_contract, spread, commission, cost_per_trade_SR)) | |
| return cost_per_trade_SR, slippage | |
| def expiry_pattern_string(list_of_market_data, | |
| list_of_contract_details): | |
| list_of_average_volumes = average_volumes_by_contract(list_of_market_data) | |
| highest_volume = np.nanmax(list_of_average_volumes) | |
| volumes_as_proportion = [volume / highest_volume for volume in list_of_average_volumes] | |
| list_pattern = ["%s:%.2f" % (contract_details.contract.lastTradeDateOrContractMonth, | |
| volume_proportion) | |
| for contract_details, volume_proportion in | |
| zip(list_of_contract_details, | |
| volumes_as_proportion)] | |
| return ",".join(list_pattern) | |
| def contract_with_highest_volumes(list_of_market_data): | |
| list_of_average_volumes = average_volumes_by_contract(list_of_market_data) | |
| highest_volume = max(list_of_average_volumes) | |
| highest_volume_index = list_of_average_volumes.index(highest_volume) | |
| return highest_volume_index, highest_volume | |
| def average_volumes_by_contract(list_of_market_data): | |
| list_of_average_volumes = [volume_for_a_contract(market_data_for_contract) | |
| for market_data_for_contract in list_of_market_data] | |
| return list_of_average_volumes | |
| def price_standard_deviation_for_contract_with_highest_volume(highest_volume_index, | |
| list_of_market_data): | |
| list_of_closing_prices = [daily_data.close for daily_data in list_of_market_data[highest_volume_index]] | |
| std_dev = np.nanstd(list_of_closing_prices) | |
| return std_dev | |
| import datetime | |
| def spread_for_contract_with_highest_volume(ib, | |
| highest_volume_index, | |
| list_of_contract_details): | |
| contract = list_of_contract_details[highest_volume_index].contract | |
| start = '' | |
| end = datetime.datetime.now() | |
| ticks = ib.reqHistoricalTicks(contract, start, end, 1000, 'BID_ASK', useRth=False) | |
| list_of_spreads = [spread_on_tick(tick) for tick in ticks] | |
| return np.nanmedian(list_of_spreads) | |
| def spread_on_tick(tick): | |
| if np.isnan(tick.priceAsk) or np.isnan(tick.priceBid): | |
| return np.nan | |
| if tick.priceAsk<=0: | |
| return np.nan | |
| if tick.priceBid<=0: | |
| return np.nan | |
| if tick.priceBid>tick.priceAsk: | |
| return np.nan | |
| return tick.priceAsk - tick.priceBid | |
| def volume_for_a_contract(market_data_for_contract): | |
| list_of_volumes = [data_for_day.volume for data_for_day in market_data_for_contract] | |
| return np.nanmean(list_of_volumes) | |
| def get_all_fx_rates(ib, new_market_data_pd): | |
| list_of_fx_codes = list(set(list(new_market_data_pd.Currency.values))) | |
| dict_of_codes_and_prices = dict( | |
| [ | |
| (code, get_fx_for_code(ib, code)) | |
| for code in list_of_fx_codes | |
| ] | |
| ) | |
| return dict_of_codes_and_prices | |
| def get_fx_for_code(ib, fx_code, invert=False): | |
| if fx_code=="USD": | |
| return 1.0 | |
| if invert: | |
| forex = Forex('USD%s' % fx_code) | |
| else: | |
| forex = Forex('%sUSD' % fx_code) | |
| data = ib.reqHistoricalData(forex, durationStr='5 D', barSizeSetting='1 day', endDateTime='', whatToShow='MIDPOINT', useRTH=True) | |
| if len(data)==0: | |
| if invert: | |
| raise Exception("Can't get price for %s" % fx_code) | |
| return get_fx_for_code(ib, fx_code, invert=True) | |
| data_prices = [data_object.close for data_object in data] | |
| avg_price = np.nanmean(data_prices) | |
| if avg_price==0.0: | |
| raise Exception("Couldn't get price for %s" % fx_code) | |
| if invert: | |
| return 1.0/avg_price | |
| return avg_price | |
| ib=IB() | |
| ib.connect('127.0.0.1', 4001, clientId=13) | |
| new_market_data_pd = pd.read_csv('/home/rob/private/projects/new_markets/with_unique_identifers.csv') | |
| all_fx_rates = get_all_fx_rates(ib, new_market_data_pd) | |
| new_market_data_with_stats = [] | |
| for row_data in new_market_data_pd.iterrows(): | |
| print("Getting data for %s" % str(row_data[1])) | |
| new_data = get_stats_for_data_row(ib, row_data[1], all_fx_rates=all_fx_rates) | |
| if new_data is missing_data: | |
| continue | |
| new_market_data_with_stats.append(new_data) | |
| new_market_data_with_stats_pd = pd.DataFrame(new_market_data_with_stats) | |
| new_market_data_with_stats_pd.columns = ['Symbol', 'Exchange', 'Currency', 'Multiplier', | |
| 'Risk Volume $', 'Cost SR', '$ Risk per contract', | |
| 'Contracts per day', 'My multiplier', | |
| 'Commission', 'Slippage price units', | |
| 'Pattern'] | |
| new_market_data_with_stats_pd.to_csv('/home/rob/with_stats.csv') | |
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