def capital_for_given_parameters_type4(countrynum, bestFA, numOfObserv, threshold, listOfParams, numOfBestStrategy, closePriceList, closePriceSeries, highPriceSeries, lowPriceSeries, interpolatedRates, daysTillExpiration, vixList, daysOfExpiration):
'''This function calculates capital dynamics based on parameters from training part. Also it gives best train strategy Sharpe ratio as well as best test Sharpe ratio (to check whether best train strategy is also best in the test sample).
:bestFA: list with FA indicator determined by condition based on train part output
:numOfObserv: hom much data to use in test part
:threshold: parameter when index is considered overbought. It is given from test part
:listOfParams: periods of TA indicators to use to check
:numOfBestStrategy: index for the best option strategy from training part (0 is atm put)
:closePriceList: B&H part of portfolio
:closePriceSeries, highPriceSeries, lowPriceSeries: data to use for TA signals calculation
:interpolatedRates, daysTillExpiration, vixList, daysOfExpiration: is as in options calculation part
:output: three variables with capital and Sharpe ratios
'''
futuresPrice = futures_price(interpolatedRates[-numOfObserv:], daysTillExpiration[-numOfObserv:], list(closePriceSeries)[-numOfObserv:])
daysToRenewInit = new_futures_dates(daysOfExpiration[-numOfObserv:], futuresPrice)
condFARaw = [1 if x>threshold else (float('nan') if pd.isna(x) else 0) for x in bestFA][-numOfObserv:]
eMACond = EMA_sign(closePriceSeries, int(listOfParams[0]), int(listOfParams[1]))[-numOfObserv:]
fAPlusEMA = get_condition_type4(condFARaw, eMACond)
fAPlusTA = [x*y for x, y in zip(fAPlusEMA,eMACond)]
datesTuple = dates_tuple(fAPlusTA, daysTillExpiration[-numOfObserv:], daysOfExpiration[-numOfObserv:], daysToRenewInit[-numOfObserv:])#daysToRenewFinal, daysToSellFInal, daysToHoldOptions, daysForOptionCalculation respectively
optionStrategies = calculate_strategies(countrynum,interpolatedRates[-numOfObserv:], daysTillExpiration[-numOfObserv:], futuresPrice, vixList[-numOfObserv:], datesTuple[0], datesTuple[1], datesTuple[3])
fAPortfolio1 = first_portfolios_with_given_options(closePriceList[-numOfObserv:], datesTuple[2], datesTuple[0], datesTuple[1], optionStrategies)
aDCond = AD_sign(highPriceSeries, lowPriceSeries, 5, 34, int(listOfParams[2]))[-numOfObserv:]
fAPlusAD = get_condition_type4(condFARaw, aDCond)
fAPlusTA = [x*y for x, y in zip(fAPlusAD,aDCond)]
datesTuple = dates_tuple(fAPlusTA, daysTillExpiration[-numOfObserv:], daysOfExpiration[-numOfObserv:], daysToRenewInit[-numOfObserv:])
optionStrategies2 = calculate_strategies(countrynum,interpolatedRates[-numOfObserv:], daysTillExpiration[-numOfObserv:], futuresPrice, vixList[-numOfObserv:], datesTuple[0], datesTuple[1], datesTuple[3])
fAPortfolio2 = portfolios_with_given_options(fAPortfolio1, datesTuple[2], datesTuple[0], datesTuple[1], optionStrategies2)
kAMACond = KAMA_sign(closePriceSeries, 10, 2, 30, int(listOfParams[3]))[-numOfObserv:]
fAPlusKAMA = get_condition_type4(condFARaw, kAMACond)
fAPlusTA = [x*y for x, y in zip(fAPlusKAMA,kAMACond)]
datesTuple = dates_tuple(fAPlusTA, daysTillExpiration[-numOfObserv:], daysOfExpiration[-numOfObserv:], daysToRenewInit[-numOfObserv:])
optionStrategies3 = calculate_strategies(countrynum,interpolatedRates[-numOfObserv:], daysTillExpiration[-numOfObserv:], futuresPrice, vixList[-numOfObserv:], datesTuple[0], datesTuple[1], datesTuple[3])
fAPortfolio3 = portfolios_with_given_options(fAPortfolio2, datesTuple[2], datesTuple[0], datesTuple[1], optionStrategies3)
mACDCond = MACD_sign(closePriceSeries, 26, 12, int(listOfParams[4]))[-numOfObserv:]
fAPlusMACD = get_condition_type4(condFARaw, mACDCond)
fAPlusTA = [x*y for x, y in zip(fAPlusMACD,mACDCond)]
datesTuple = dates_tuple(fAPlusTA, daysTillExpiration[-numOfObserv:], daysOfExpiration[-numOfObserv:], daysToRenewInit[-numOfObserv:])
optionStrategies4 = calculate_strategies(countrynum,interpolatedRates[-numOfObserv:], daysTillExpiration[-numOfObserv:], futuresPrice, vixList[-numOfObserv:], datesTuple[0], datesTuple[1], datesTuple[3])
fAPortfolio4 = portfolios_with_given_options(fAPortfolio3, datesTuple[2], datesTuple[0], datesTuple[1], optionStrategies4)
tRIXCond = TRIX_sign(closePriceSeries, int(listOfParams[5]))[-numOfObserv:]
fAPlusTRIX = get_condition_type4(condFARaw, tRIXCond)
fAPlusTA = [x*y for x, y in zip(fAPlusTRIX,tRIXCond)]
datesTuple = dates_tuple(fAPlusTA, daysTillExpiration[-numOfObserv:], daysOfExpiration[-numOfObserv:], daysToRenewInit[-numOfObserv:])
optionStrategies5 = calculate_strategies(countrynum,interpolatedRates[-numOfObserv:], daysTillExpiration[-numOfObserv:], futuresPrice, vixList[-numOfObserv:], datesTuple[0], datesTuple[1], datesTuple[3])
fAPortfolio5 = portfolios_with_given_options(fAPortfolio4, datesTuple[2], datesTuple[0], datesTuple[1], optionStrategies5)#this is the final set of portfolios for given FA condition type, given FA indicator value, set of TA indicators
fASharpeRatiosVector = sharpe_ratios_vector(fAPortfolio5)
bestTrainStrategyCapital = list(fAPortfolio5.iloc[:,numOfBestStrategy])
bestTrainStrategySharpe = float(fASharpeRatiosVector.iloc[numOfBestStrategy,0])
bestTestSharpe = float(fASharpeRatiosVector.max())
return bestTrainStrategyCapital, bestTrainStrategySharpe, bestTestSharpe
def capital_for_given_parameters_type5(countrynum, numOfObserv, listOfParams, numOfBestStrategy, closePriceList, closePriceSeries, highPriceSeries, lowPriceSeries, interpolatedRates, daysTillExpiration, vixList, daysOfExpiration):
'''This function calculates capital dynamics based on parameters from training part. Also it gives best train strategy Sharpe ratio as well as best test Sharpe ratio (to check whether best train strategy is also best in the test sample).
:No FA is required as the system is based purely on TA indicators:
:numOfObserv: hom much data to use in test part
:listOfParams: periods of TA indicators to use to check
:numOfBestStrategy: index for the best option strategy from training part (0 is atm put)
:closePriceList: B&H part of portfolio
:closePriceSeries, highPriceSeries, lowPriceSeries: data to use for TA signals calculation
:interpolatedRates, daysTillExpiration, vixList, daysOfExpiration: is as in options calculation part
:output: three variables with capital and Sharpe ratios
'''
futuresPrice = futures_price(interpolatedRates[-numOfObserv:], daysTillExpiration[-numOfObserv:], list(closePriceSeries)[-numOfObserv:])
daysToRenewInit = new_futures_dates(daysOfExpiration[-numOfObserv:], futuresPrice)
eMACond = EMA_sign(closePriceSeries, int(listOfParams[0]), int(listOfParams[1]))[-numOfObserv:]
datesTuple = dates_tuple(eMACond, daysTillExpiration[-numOfObserv:], daysOfExpiration[-numOfObserv:], daysToRenewInit[-numOfObserv:])#daysToRenewFinal, daysToSellFInal, daysToHoldOptions, daysForOptionCalculation respectively
optionStrategies = calculate_strategies(countrynum,interpolatedRates[-numOfObserv:], daysTillExpiration[-numOfObserv:], futuresPrice, vixList[-numOfObserv:], datesTuple[0], datesTuple[1], datesTuple[3])
fAPortfolio1 = first_portfolios_with_given_options(closePriceList[-numOfObserv:], datesTuple[2], datesTuple[0], datesTuple[1], optionStrategies)
aDCond = AD_sign(highPriceSeries, lowPriceSeries, 5, 34, int(listOfParams[2]))[-numOfObserv:]
datesTuple = dates_tuple(aDCond, daysTillExpiration[-numOfObserv:], daysOfExpiration[-numOfObserv:], daysToRenewInit[-numOfObserv:])
optionStrategies2 = calculate_strategies(countrynum,interpolatedRates[-numOfObserv:], daysTillExpiration[-numOfObserv:], futuresPrice, vixList[-numOfObserv:], datesTuple[0], datesTuple[1], datesTuple[3])
fAPortfolio2 = portfolios_with_given_options(fAPortfolio1, datesTuple[2], datesTuple[0], datesTuple[1], optionStrategies2)
kAMACond = KAMA_sign(closePriceSeries, 10, 2, 30, int(listOfParams[3]))[-numOfObserv:]
datesTuple = dates_tuple(kAMACond, daysTillExpiration[-numOfObserv:], daysOfExpiration[-numOfObserv:], daysToRenewInit[-numOfObserv:])
optionStrategies3 = calculate_strategies(countrynum,interpolatedRates[-numOfObserv:], daysTillExpiration[-numOfObserv:], futuresPrice, vixList[-numOfObserv:], datesTuple[0], datesTuple[1], datesTuple[3])
fAPortfolio3 = portfolios_with_given_options(fAPortfolio2, datesTuple[2], datesTuple[0], datesTuple[1], optionStrategies3)
mACDCond = MACD_sign(closePriceSeries, 26, 12, int(listOfParams[4]))[-numOfObserv:]
datesTuple = dates_tuple(mACDCond, daysTillExpiration[-numOfObserv:], daysOfExpiration[-numOfObserv:], daysToRenewInit[-numOfObserv:])
optionStrategies4 = calculate_strategies(countrynum,interpolatedRates[-numOfObserv:], daysTillExpiration[-numOfObserv:], futuresPrice, vixList[-numOfObserv:], datesTuple[0], datesTuple[1], datesTuple[3])
fAPortfolio4 = portfolios_with_given_options(fAPortfolio3, datesTuple[2], datesTuple[0], datesTuple[1], optionStrategies4)
tRIXCond = TRIX_sign(closePriceSeries, int(listOfParams[5]))[-numOfObserv:]
datesTuple = dates_tuple(tRIXCond, daysTillExpiration[-numOfObserv:], daysOfExpiration[-numOfObserv:], daysToRenewInit[-numOfObserv:])
optionStrategies5 = calculate_strategies(countrynum,interpolatedRates[-numOfObserv:], daysTillExpiration[-numOfObserv:], futuresPrice, vixList[-numOfObserv:], datesTuple[0], datesTuple[1], datesTuple[3])
fAPortfolio5 = portfolios_with_given_options(fAPortfolio4, datesTuple[2], datesTuple[0], datesTuple[1], optionStrategies5)#this is the final set of portfolios for given FA condition type, given FA indicator value, set of TA indicators
fASharpeRatiosVector = sharpe_ratios_vector(fAPortfolio5)
bestTrainStrategyCapital = list(fAPortfolio5.iloc[:,numOfBestStrategy])
bestTrainStrategySharpe = float(fASharpeRatiosVector.iloc[numOfBestStrategy,0])
bestTestSharpe = float(fASharpeRatiosVector.max())
return bestTrainStrategyCapital, bestTrainStrategySharpe, bestTestSharpe