Mariner Backtesting - TA-LIB Beta

 real = BETA(control_value, measured_value, timeperiod=5)

from cloudquant import Strategy
import talib


class TAlibExample(Strategy):


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

        def match_bar_data(control_value, measured_value):
            count = 0
            del_list = []
            for spy, symb in zip(control_value, measured_value):
                # check nan
                if symb != symb:
                    del_list.append(count)
                count += 1
            for number in del_list:
                del control_value[number]
                del measured_value[number]
            return [control_value, measured_value]

        # define a list of symbols to gather data for
        cls.symbol_list = ['WMT', 'TGT', 'AAPL', 'MSFT', 'AMZN', 'FB', 'GOOGL', 'SBUX']
        print 'Symbol\tBeta Calculation\n'

        volatility_data = {}

        bar_spy = md['SPY'].bar.daily(start=-252)
        for x in md:
            symbol = x.symbol
            if symbol in cls.symbol_list:


                bar = md[symbol].bar.daily(start=-252, include_empty=True)
                bar_len = len(bar.high)

                match_up = match_bar_data(bar_spy.close, bar.close)
                spy = match_up[0]
                cur_symbol_close = match_up[1]

                if bar_len > 0:
                    timeperiod = 250
                    if bar_len < 250:
                        timeperiod = bar_len
                    calc_beta = talib.BETA(spy, cur_symbol_close, timeperiod=timeperiod)[-1]
                    volatility_data[symbol] = calc_beta

        print 'Volatile Symbols:'
        for symbol in volatility_data:
            if volatility_data[symbol] > 1:
                print '%s\t%s' % (symbol, volatility_data[symbol])

        print '\nNon-Volatile Symbols:'
        for symbol in volatility_data:
            if volatility_data[symbol] < 1:
                print '%s\t%s' % (symbol, volatility_data[symbol])