Mariner Backtesting - Strategy.on_strategy_start()

Strategy Start Event

on_strategy_start() is called on the first instantiation for the class.

 @classmethod
def on_strategy_start(cls,
                      md,
                      service,
                      account):
    pass

• Test script uses data in StatData in is_symbol_qualified and its data to qualify each symbol.

 symbol,company_name,security_type,primary_exchange,sector,industry,previous_day_volume,adv10,adv30,previous_close,beta,beta2
APD,AIR PRODS & CHEMS INC,OrdinaryShares,N,Basic Material,Chemicals-Specialty,858082.0,996092,898543,155.89,1.208,1.23919
HW,HEADWATERS INC,OrdinaryShares,N,Consumer Cyclical,Bldg-Constr Prds/Misc,438424.0,517816,609371,18.6,1.7849,1.74121
HOG,HARLEY DAVIDSON INC,OrdinaryShares,N,Consumer Cyclical,Leisure-Products,1930811.0,2424363,2488764,52.33,1.1354,1.80105
USB,US BANCORP DEL,OrdinaryShares,N,Financial,Banks-Super Regional,7203005.0,5555187,5327973,43.84,0.7962,1.34894
ULTA,ULTA SALON COSMETCS & FRAG I,OrdinaryShares,Q,Retail,Retail-Specialty,1246789.0,1522229,802796,254.09,0.6278,0.73014
ULTI,ULTIMATE SOFTWARE GROUP INC,OrdinaryShares,Q,Technology,Computer Sftwr-Enterprse,121181.0,218459,247742,211.96001,1.2676,1.32008
UBSH,UNION BANKSHARES CORP NEW,OrdinaryShares,Q,Financial,Banks-Southeast,121299.0,132288,111614,27.1,1.1489,1.45813
ULTR,ULTRAPETROL BAHAMAS LTD,OrdinaryShares,Q,Transportation,Transportation-Ship,99678.0,152145,286023,0.331,2.667,3.50239
UVV,UNIVERSAL CORP VA,OrdinaryShares,N,Consumer Staple,Tobacco,67094.0,101279,149420,60.64,1.1796,0.57873
UHAL,AMERCO,OrdinaryShares,Q,Capital Equipment,Comml Svcs-Leasing,66608.0,63376,62815,336.97,1.527,1.05692

 from cloudquant.interfaces import Strategy

class StatCheck(Strategy):

    @classmethod
    def on_strategy_start(cls, md, service, account):

        # create a list of dictionaries from the user_data file
        # the headers will be used as the keys
        # each row will have its own dictionary
        temp_file = service.read_file('StatData', format='csv')

        # populate class variable (dictionary)
        cls.stats = {}

        # for each dictionary created for each row:
        for row in temp_file:

            # save the data from the file to a class variable based on symbol
            # access the symbol from the 'symbol' key in row, row['symbol']
            cls.stats[row['symbol']] = row

        # print the cls.stats keys, which are symbols
        print 'symbol list:', cls.stats.keys(), '\n\n'

    @classmethod
    def is_symbol_qualified(cls, symbol, md, service, account):
        # qualify all of the symbols from the file
        return symbol in cls.stats.keys()

    # called at the beginning of each instance
    def on_start(self, md, order, service, account):
        # print the symbol
        print 'in on_start for ' + self.symbol

        # print the data for the current symbol
        print self.__class__.stats[self.symbol]

        # check the previous close on file vs the current previous close
        # access the previous close from the dictionary
        print 'Previous Close:', md.stat.prev_close, '\tPrevious Close From File:', \
            self.__class__.stats[self.symbol]['previous_close'], '\n'

        service.terminate()

Console

symbol list: ['UBSH', 'HOG', 'ULTA', 'UHAL', 'USB', 'ULTI', 'HW', 'UVV', 'ULTR', 'APD']

in on_start for APD
{'sector': 'Basic Material', 'previous_close': 155.89, 'industry': 'Chemicals-Specialty', 'security_type': 'OrdinaryShares', 'beta': 1.208, 'primary_exchange': 'N', 'adv10': 996092, 'previous_day_volume': 858082.0, 'company_name': 'AIR PRODS & CHEMS INC', 'adv30': 898543, 'symbol': 'APD', 'beta2': 1.23919}
Previous Close: 149.550003052   Previous Close From File: 155.89 

in on_start for HOG
{'sector': 'Consumer Cyclical', 'previous_close': 52.33, 'industry': 'Leisure-Products', 'security_type': 'OrdinaryShares', 'beta': 1.1354, 'primary_exchange': 'N', 'adv10': 2424363, 'previous_day_volume': 1930811.0, 'company_name': 'HARLEY DAVIDSON INC', 'adv30': 2488764, 'symbol': 'HOG', 'beta2': 1.80105}
Previous Close: 60.8100013733   Previous Close From File: 52.33 

in on_start for HW
{'sector': 'Consumer Cyclical', 'previous_close': 18.6, 'industry': 'Bldg-Constr Prds/Misc', 'security_type': 'OrdinaryShares', 'beta': 1.7849, 'primary_exchange': 'N', 'adv10': 517816, 'previous_day_volume': 438424.0, 'company_name': 'HEADWATERS INC', 'adv30': 609371, 'symbol': 'HW', 'beta2': 1.74121}
Previous Close: 23.5799999237   Previous Close From File: 18.6 

in on_start for UBSH
{'sector': 'Financial', 'previous_close': 27.1, 'industry': 'Banks-Southeast', 'security_type': 'OrdinaryShares', 'beta': 1.1489, 'primary_exchange': 'Q', 'adv10': 132288, 'previous_day_volume': 121299.0, 'company_name': 'UNION BANKSHARES CORP NEW', 'adv30': 111614, 'symbol': 'UBSH', 'beta2': 1.45813}
Previous Close: 35.8600006104   Previous Close From File: 27.1 

in on_start for UHAL
{'sector': 'Capital Equipment', 'previous_close': 336.97, 'industry': 'Comml Svcs-Leasing', 'security_type': 'OrdinaryShares', 'beta': 1.527, 'primary_exchange': 'Q', 'adv10': 63376, 'previous_day_volume': 66608.0, 'company_name': 'AMERCO', 'adv30': 62815, 'symbol': 'UHAL', 'beta2': 1.05692}
Previous Close: 372.059997559   Previous Close From File: 336.97 

in on_start for ULTA
{'sector': 'Retail', 'previous_close': 254.09, 'industry': 'Retail-Specialty', 'security_type': 'OrdinaryShares', 'beta': 0.6278, 'primary_exchange': 'Q', 'adv10': 1522229, 'previous_day_volume': 1246789.0, 'company_name': 'ULTA SALON COSMETCS & FRAG I', 'adv30': 802796, 'symbol': 'ULTA', 'beta2': 0.73014}
Previous Close: 251.13999939    Previous Close From File: 254.09 

in on_start for ULTI
{'sector': 'Technology', 'previous_close': 211.96001, 'industry': 'Computer Sftwr-Enterprse', 'security_type': 'OrdinaryShares', 'beta': 1.2676, 'primary_exchange': 'Q', 'adv10': 218459, 'previous_day_volume': 121181.0, 'company_name': 'ULTIMATE SOFTWARE GROUP INC', 'adv30': 247742, 'symbol': 'ULTI', 'beta2': 1.32008}
Previous Close: 190.399993896   Previous Close From File: 211.96001 

in on_start for USB
{'sector': 'Financial', 'previous_close': 43.84, 'industry': 'Banks-Super Regional', 'security_type': 'OrdinaryShares', 'beta': 0.7962, 'primary_exchange': 'N', 'adv10': 5555187, 'previous_day_volume': 7203005.0, 'company_name': 'US BANCORP DEL', 'adv30': 5327973, 'symbol': 'USB', 'beta2': 1.34894}
Previous Close: 52.0400009155   Previous Close From File: 43.84 

in on_start for UVV
{'sector': 'Consumer Staple', 'previous_close': 60.64, 'industry': 'Tobacco', 'security_type': 'OrdinaryShares', 'beta': 1.1796, 'primary_exchange': 'N', 'adv10': 101279, 'previous_day_volume': 67094.0, 'company_name': 'UNIVERSAL CORP VA', 'adv30': 149420, 'symbol': 'UVV', 'beta2': 0.57873}
Previous Close: 60.9000015259   Previous Close From File: 60.64

• Iterate over md to create a symbol list.

 from cloudquant.interfaces import Strategy


class CreatingSymbolList(Strategy):


    @classmethod
    def on_strategy_start(cls, md, service, account):

        # initialize symbol list variable
        cls.symbol_list = []

        # iterate over the market data
        for md_info in md:

            symbol = md_info.symbol
            # if the symbols' exchange is NYSE Arca and the average volume is over 20 million
            if md_info.stat.exchange == 'P' and md_info.stat.avol > 20000000:
                # add the symbol to the symbol list after it met the if condition
                cls.symbol_list.append(symbol)

        # print the length of the symbol list
        print 'cls.symbol_list:', len(cls.symbol_list)
        print cls.symbol_list, '\n\n'

    @classmethod
    def is_symbol_qualified(cls, symbol, md, service, account):
        # qualifies all symbols in cls.symbol_list
        return symbol in cls.symbol_list

    def on_start(self, md, order, service, account):
        # print the symbol, and the current method
        print self.symbol + '\t' + 'in on_start'

        service.terminate()

Console

cls.symbol_list: 11
['SPY', 'DGAZ', 'GDX', 'JNUG', 'EEM', 'XLF', 'IWM', 'USO', 'NUGT', 'VXX', 'EFA']

DGAZ    in on_start
EEM in on_start
EFA in on_start
GDX in on_start
IWM in on_start
JNUG    in on_start
NUGT    in on_start
SPY in on_start
USO in on_start
VXX in on_start
XLF in on_start

• No return value.
• Has access to system objects: md, service and account.
• Class method - @classmethod.
• Use cls to access/assign class variables (compared to reading/assigning class variable in an instance method self.__class__.CLASS_VARIABLE).
• This is a good place to read in user data that can be accessed in in_symbol_universe()/is_symbol_qualified() or on_start().