Mariner Backtesting - TA-LIB Rate of change ratio: (real/prevPrice)

ROCR

Rate of change ratio: (price/prevPrice)

ROCR

 real = ROCR(close, timeperiod=10)

Plot

Rate of change ratio: (price/prevPrice)

Working Example

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

class WE_ROCR(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
        real = talib.ROCR(close, timeperiod=10)

        # 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['real'] = real
        symbol = 'ROCR: ' + self.symbol
        print ktgfunc.talib_table(symbol, 1, dict)

Console

MSFT:  2017-02-09 09:30:00.000000
ROCR: MSFT
Input Output
date close real
2016-09-16 56.87 nan
2016-09-19 56.55 nan
2016-09-20 56.43 nan
2016-09-21 57.37 nan
2016-09-22 57.43 nan
2016-09-23 57.04 nan
2016-09-26 56.52 nan
2016-09-27 57.56 nan
2016-09-28 57.64 nan
2016-09-29 57.01 nan
2016-09-30 57.21 1.01
2016-10-03 57.03 1.01
2016-10-04 56.86 1.01
2016-10-05 57.25 1.00
2016-10-06 57.35 1.00
2016-10-07 57.41 1.01
2016-10-10 57.65 1.02
2016-10-11 56.81 0.99
2016-10-12 56.73 0.98
2016-10-13 56.54 0.99
2016-10-14 57.03 1.00
2016-10-17 56.84 1.00
2016-10-18 57.27 1.01
2016-10-19 57.14 1.00
2016-10-20 56.87 0.99
2016-10-21 59.26 1.03
2016-10-24 60.59 1.05
2016-10-25 60.58 1.07
2016-10-26 60.22 1.06
2016-10-27 59.70 1.06
2016-10-28 59.47 1.04
2016-10-31 59.52 1.05
2016-11-01 59.40 1.04
2016-11-02 59.03 1.03
2016-11-03 58.81 1.03
2016-11-04 58.32 0.98
2016-11-07 60.01 0.99
2016-11-08 60.06 0.99
2016-11-09 59.77 0.99
2016-11-10 58.31 0.98
2016-11-11 58.62 0.99
2016-11-14 57.73 0.97
2016-11-15 58.87 0.99
2016-11-16 59.65 1.01
2016-11-17 60.64 1.03
2016-11-18 60.35 1.03
2016-11-21 60.86 1.01
2016-11-22 61.12 1.02
2016-11-23 60.40 1.01
2016-11-25 60.53 1.04
2016-11-28 60.61 1.03
2016-11-29 61.09 1.06
2016-11-30 60.26 1.02
2016-12-01 59.20 0.99
2016-12-02 59.25 0.98
2016-12-05 60.22 1.00
2016-12-06 59.95 0.99
2016-12-07 61.37 1.00
2016-12-08 61.01 1.01
2016-12-09 61.97 1.02
2016-12-12 62.17 1.03
2016-12-13 62.98 1.03
2016-12-14 62.68 1.04
2016-12-15 62.58 1.06
2016-12-16 62.30 1.05
2016-12-19 63.62 1.06
2016-12-20 63.54 1.06
2016-12-21 63.54 1.04
2016-12-22 63.55 1.04
2016-12-23 63.24 1.02
2016-12-27 63.28 1.02
2016-12-28 62.99 1.00
2016-12-29 62.90 1.00
2016-12-30 62.14 0.99
2017-01-03 62.58 1.00
2017-01-04 62.30 0.98
2017-01-05 62.30 0.98
2017-01-06 62.84 0.99
2017-01-09 62.64 0.99
2017-01-10 62.62 0.99
2017-01-11 63.19 1.00
2017-01-12 62.61 0.99
2017-01-13 62.70 1.00
2017-01-17 62.53 1.01
2017-01-18 62.50 1.00
2017-01-19 62.30 1.00
2017-01-20 62.74 1.01
2017-01-23 62.96 1.00
2017-01-24 63.52 1.01
2017-01-25 63.68 1.02
2017-01-26 64.27 1.02
2017-01-27 65.78 1.05
2017-01-30 65.13 1.04
2017-01-31 64.65 1.03
2017-02-01 63.58 1.02
2017-02-02 63.17 1.01
2017-02-03 63.68 1.01
2017-02-06 63.64 1.01
2017-02-07 63.43 1.00
2017-02-08 63.34 0.99