Mariner Backtesting - TA-LIB Linear Regression Angle

LINEARREG_ANGLE

 real = LINEARREG_ANGLE(close, timeperiod=14)

Plot

Linear Regression Angle

Plot

Linear Regression Angle

Working Example

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

class WE_LINEARREG_ANGLE(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.LINEARREG_ANGLE(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 = 'LINEARREG_ANGLE: ' + self.symbol
        print ktgfunc.talib_table(symbol, 1, dict)

Console

MSFT:  2017-02-09 09:30:00.000000
LINEARREG_ANGLE: 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 1.70
2016-10-06 57.35 1.83
2016-10-07 57.41 1.33
2016-10-10 57.65 0.78
2016-10-11 56.81 0.32
2016-10-12 56.73 -0.02
2016-10-13 56.54 -1.21
2016-10-14 57.03 -2.46
2016-10-17 56.84 -2.20
2016-10-18 57.27 -0.89
2016-10-19 57.14 -0.88
2016-10-20 56.87 -0.98
2016-10-21 59.26 2.59
2016-10-24 60.59 7.40
2016-10-25 60.58 11.90
2016-10-26 60.22 15.12
2016-10-27 59.70 16.91
2016-10-28 59.47 18.21
2016-10-31 59.52 17.73
2016-11-01 59.40 16.30
2016-11-02 59.03 13.31
2016-11-03 58.81 10.20
2016-11-04 58.32 5.42
2016-11-07 60.01 3.78
2016-11-08 60.06 1.29
2016-11-09 59.77 -2.96
2016-11-10 58.31 -5.79
2016-11-11 58.62 -5.36
2016-11-14 57.73 -5.92
2016-11-15 58.87 -4.58
2016-11-16 59.65 -2.61
2016-11-17 60.64 0.56
2016-11-18 60.35 3.05
2016-11-21 60.86 5.93
2016-11-22 61.12 8.16
2016-11-23 60.40 8.30
2016-11-25 60.53 7.34
2016-11-28 60.61 9.10
2016-11-29 61.09 11.55
2016-11-30 60.26 11.89
2016-12-01 59.20 7.74
2016-12-02 59.25 3.98
2016-12-05 60.22 -0.09
2016-12-06 59.95 -3.07
2016-12-07 61.37 -2.53
2016-12-08 61.01 -1.14
2016-12-09 61.97 1.18
2016-12-12 62.17 4.37
2016-12-13 62.98 9.00
2016-12-14 62.68 11.29
2016-12-15 62.58 13.09
2016-12-16 62.30 14.08
2016-12-19 63.62 17.50
2016-12-20 63.54 18.73
2016-12-21 63.54 17.40
2016-12-22 63.55 15.15
2016-12-23 63.24 13.07
2016-12-27 63.28 9.79
2016-12-28 62.99 7.79
2016-12-29 62.90 4.55
2016-12-30 62.14 1.37
2017-01-03 62.58 -0.76
2017-01-04 62.30 -1.92
2017-01-05 62.30 -3.48
2017-01-06 62.84 -4.24
2017-01-09 62.64 -5.92
2017-01-10 62.62 -5.24
2017-01-11 63.19 -3.53
2017-01-12 62.61 -2.68
2017-01-13 62.70 -1.42
2017-01-17 62.53 -0.81
2017-01-18 62.50 0.00
2017-01-19 62.30 0.14
2017-01-20 62.74 1.00
2017-01-23 62.96 0.82
2017-01-24 63.52 2.18
2017-01-25 63.68 3.04
2017-01-26 64.27 4.52
2017-01-27 65.78 8.93
2017-01-30 65.13 11.15
2017-01-31 64.65 11.96
2017-02-01 63.58 11.63
2017-02-02 63.17 9.50
2017-02-03 63.68 8.18
2017-02-06 63.64 6.24
2017-02-07 63.43 3.60
2017-02-08 63.34 0.19