Mariner Backtesting - TA-LIB Index of highest value over a specified period

MAXINDEX

 

 integer = MAXINDEX(close, timeperiod=30)

Plot

Index of highest value over a specified period

Working Example

 from cloudquant.interfaces import Strategy
from collections import OrderedDict
import ktgfunc
import talib

class WE_MAXINDEX(Strategy):

    def on_start(self, md, order, service, account):
        # symbol and timestamp
        print(self.symbol + ":  " + service.time_to_string(service.system_time))
        daily_bars = md.bar.daily(start=-100)
        close = daily_bars.close
        integer = talib.MAXINDEX(close, timeperiod=30)

        # get the date values
        dates = service._context.market._storage.market_hours.keys()
        dateList = []
        for date in dates:
           dateList.append(str(date.strftime('%Y-%m-%d')))
        dates = sorted(dateList, reverse=True)[1:101]
        dates.sort()

        dict = OrderedDict()
        dict['date'] = dates
        dict['close'] = close
        dict['integer'] = integer
        symbol = 'MAXINDEX: ' + self.symbol
        print ktgfunc.talib_table(symbol, 1, dict)

Console

MSFT:  2017-02-09 09:30:00.000000
MAXINDEX: MSFT
Input Output
date close integer
2016-09-16 56.87 0.00
2016-09-19 56.55 0.00
2016-09-20 56.43 0.00
2016-09-21 57.37 0.00
2016-09-22 57.43 0.00
2016-09-23 57.04 0.00
2016-09-26 56.52 0.00
2016-09-27 57.56 0.00
2016-09-28 57.64 0.00
2016-09-29 57.01 0.00
2016-09-30 57.21 0.00
2016-10-03 57.03 0.00
2016-10-04 56.86 0.00
2016-10-05 57.25 0.00
2016-10-06 57.35 0.00
2016-10-07 57.41 0.00
2016-10-10 57.65 0.00
2016-10-11 56.81 0.00
2016-10-12 56.73 0.00
2016-10-13 56.54 0.00
2016-10-14 57.03 0.00
2016-10-17 56.84 0.00
2016-10-18 57.27 0.00
2016-10-19 57.14 0.00
2016-10-20 56.87 0.00
2016-10-21 59.26 0.00
2016-10-24 60.59 0.00
2016-10-25 60.58 0.00
2016-10-26 60.22 0.00
2016-10-27 59.70 26.00
2016-10-28 59.47 26.00
2016-10-31 59.52 26.00
2016-11-01 59.40 26.00
2016-11-02 59.03 26.00
2016-11-03 58.81 26.00
2016-11-04 58.32 26.00
2016-11-07 60.01 26.00
2016-11-08 60.06 26.00
2016-11-09 59.77 26.00
2016-11-10 58.31 26.00
2016-11-11 58.62 26.00
2016-11-14 57.73 26.00
2016-11-15 58.87 26.00
2016-11-16 59.65 26.00
2016-11-17 60.64 44.00
2016-11-18 60.35 44.00
2016-11-21 60.86 46.00
2016-11-22 61.12 47.00
2016-11-23 60.40 47.00
2016-11-25 60.53 47.00
2016-11-28 60.61 47.00
2016-11-29 61.09 47.00
2016-11-30 60.26 47.00
2016-12-01 59.20 47.00
2016-12-02 59.25 47.00
2016-12-05 60.22 47.00
2016-12-06 59.95 47.00
2016-12-07 61.37 57.00
2016-12-08 61.01 57.00
2016-12-09 61.97 59.00
2016-12-12 62.17 60.00
2016-12-13 62.98 61.00
2016-12-14 62.68 61.00
2016-12-15 62.58 61.00
2016-12-16 62.30 61.00
2016-12-19 63.62 65.00
2016-12-20 63.54 65.00
2016-12-21 63.54 65.00
2016-12-22 63.55 65.00
2016-12-23 63.24 65.00
2016-12-27 63.28 65.00
2016-12-28 62.99 65.00
2016-12-29 62.90 65.00
2016-12-30 62.14 65.00
2017-01-03 62.58 65.00
2017-01-04 62.30 65.00
2017-01-05 62.30 65.00
2017-01-06 62.84 65.00
2017-01-09 62.64 65.00
2017-01-10 62.62 65.00
2017-01-11 63.19 65.00
2017-01-12 62.61 65.00
2017-01-13 62.70 65.00
2017-01-17 62.53 65.00
2017-01-18 62.50 65.00
2017-01-19 62.30 65.00
2017-01-20 62.74 65.00
2017-01-23 62.96 65.00
2017-01-24 63.52 65.00
2017-01-25 63.68 89.00
2017-01-26 64.27 90.00
2017-01-27 65.78 91.00
2017-01-30 65.13 91.00
2017-01-31 64.65 91.00
2017-02-01 63.58 91.00
2017-02-02 63.17 91.00
2017-02-03 63.68 91.00
2017-02-06 63.64 91.00
2017-02-07 63.43 91.00
2017-02-08 63.34 91.00