Mariner Backtesting - TA-LIB Relative Strength Index

RSI

 

 real = RSI(close, timeperiod=14)

Plot

Relative Strength Index

Working Example

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

class WE_RSI(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.RSI(close, timeperiod=14)

        # 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 = 'RSI: ' + self.symbol
        print ktgfunc.talib_table(symbol, 1, dict)

Console

MSFT:  2017-02-09 09:30:00.000000
RSI: 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 nan
2016-10-03 57.03 nan
2016-10-04 56.86 nan
2016-10-05 57.25 nan
2016-10-06 57.35 54.72
2016-10-07 57.41 55.28
2016-10-10 57.65 57.53
2016-10-11 56.81 48.27
2016-10-12 56.73 47.49
2016-10-13 56.54 45.62
2016-10-14 57.03 51.09
2016-10-17 56.84 48.96
2016-10-18 57.27 53.54
2016-10-19 57.14 52.05
2016-10-20 56.87 48.91
2016-10-21 59.26 67.24
2016-10-24 60.59 73.04
2016-10-25 60.58 72.93
2016-10-26 60.22 69.13
2016-10-27 59.70 63.85
2016-10-28 59.47 61.65
2016-10-31 59.52 61.95
2016-11-01 59.40 60.70
2016-11-02 59.03 56.87
2016-11-03 58.81 54.66
2016-11-04 58.32 49.92
2016-11-07 60.01 62.05
2016-11-08 60.06 62.34
2016-11-09 59.77 59.43
2016-11-10 58.31 47.70
2016-11-11 58.62 50.01
2016-11-14 57.73 44.10
2016-11-15 58.87 51.91
2016-11-16 59.65 56.39
2016-11-17 60.64 61.32
2016-11-18 60.35 59.21
2016-11-21 60.86 61.71
2016-11-22 61.12 62.95
2016-11-23 60.40 57.39
2016-11-25 60.53 58.11
2016-11-28 60.61 58.57
2016-11-29 61.09 61.34
2016-11-30 60.26 54.55
2016-12-01 59.20 47.35
2016-12-02 59.25 47.70
2016-12-05 60.22 54.09
2016-12-06 59.95 52.18
2016-12-07 61.37 60.15
2016-12-08 61.01 57.53
2016-12-09 61.97 62.26
2016-12-12 62.17 63.17
2016-12-13 62.98 66.71
2016-12-14 62.68 64.25
2016-12-15 62.58 63.41
2016-12-16 62.30 61.01
2016-12-19 63.62 67.30
2016-12-20 63.54 66.60
2016-12-21 63.54 66.60
2016-12-22 63.55 66.65
2016-12-23 63.24 63.45
2016-12-27 63.28 63.69
2016-12-28 62.99 60.56
2016-12-29 62.90 59.59
2016-12-30 62.14 51.95
2017-01-03 62.58 55.51
2017-01-04 62.30 52.83
2017-01-05 62.30 52.83
2017-01-06 62.84 57.42
2017-01-09 62.64 55.28
2017-01-10 62.62 55.05
2017-01-11 63.19 59.98
2017-01-12 62.61 53.55
2017-01-13 62.70 54.37
2017-01-17 62.53 52.49
2017-01-18 62.50 52.15
2017-01-19 62.30 49.81
2017-01-20 62.74 54.62
2017-01-23 62.96 56.85
2017-01-24 63.52 61.97
2017-01-25 63.68 63.31
2017-01-26 64.27 67.81
2017-01-27 65.78 75.94
2017-01-30 65.13 67.98
2017-01-31 64.65 62.75
2017-02-01 63.58 52.96
2017-02-02 63.17 49.76
2017-02-03 63.68 53.52
2017-02-06 63.64 53.19
2017-02-07 63.43 51.36
2017-02-08 63.34 50.56