rsiExample.py

import numpy as np
from scipy.signal import lfilter


def mySettings():

    settings = {}
    settings['markets'] = ['CASH', 'F_AD', 'F_AE', 'F_AH', 'F_AX', 'F_BC', 'F_BG', 'F_BO', 'F_BP', 'F_C',  'F_CA',
                           'F_CC', 'F_CD', 'F_CF', 'F_CL', 'F_CT', 'F_DL', 'F_DM', 'F_DT', 'F_DX', 'F_DZ', 'F_EB',
                           'F_EC', 'F_ED', 'F_ES', 'F_F',  'F_FB', 'F_FC', 'F_FL', 'F_FM', 'F_FP', 'F_FV', 'F_FY',
                           'F_GC', 'F_GD', 'F_GS', 'F_GX', 'F_HG', 'F_HO', 'F_HP', 'F_JY', 'F_KC', 'F_LB', 'F_LC',
                           'F_LN', 'F_LQ', 'F_LR', 'F_LU', 'F_LX', 'F_MD', 'F_MP', 'F_ND', 'F_NG', 'F_NQ', 'F_NR',
                           'F_NY', 'F_O',  'F_OJ', 'F_PA', 'F_PL', 'F_PQ', 'F_RB', 'F_RF', 'F_RP', 'F_RR', 'F_RU',
                           'F_RY', 'F_S',  'F_SB', 'F_SF', 'F_SH', 'F_SI', 'F_SM', 'F_SS', 'F_SX', 'F_TR', 'F_TU',
                           'F_TY', 'F_UB', 'F_US', 'F_UZ', 'F_VF', 'F_VT', 'F_VW', 'F_VX',  'F_W', 'F_XX', 'F_YM',
                           'F_ZQ']

    settings['slippage'] = 0.05
    settings['budget'] = 1000000
    settings['beginInSample'] = '20050101'
    settings['endInSample'] = '20121231'
    settings['lookback'] = 504

    return settings


def myTradingSystem(DATE, OPEN, HIGH, LOW, CLOSE, settings):
    period1 = 504

    rsi1 = RSI(CLOSE, period1)
    p = rsi1 - 50

    return p, settings


def RSI(CLOSE,period):
    closeMom = CLOSE[1:, :] - CLOSE[:-1, :]
    upPosition = np.where(closeMom >= 0)
    downPosition = np.where(closeMom < 0)

    upMoves = closeMom.copy()
    upMoves[downPosition] = 0

    downMoves = np.abs(closeMom.copy())
    downMoves[upPosition] = 0

    out = 100 - 100 / (1 + (np.mean(upMoves[-(period+1):, :], axis=0) / np.mean(downMoves[-(period+1):, :], axis=0)))

    return out


def nDayEMA(field, period):
    ep = 2.0/(period+1)
    aa = np.array([ep])
    bb = np.array([1, -(1-ep)])
    zInit = np.array(field[1, :]*(1-ep))[np.newaxis]

    out = lfilter(aa, bb, field[1:, :], zi=zInit, axis=0)
    out = out[0]

    out[:period-1, :] = np.NaN
    return out

# Evaluate trading system defined in current file.
if __name__ == '__main__':
    import quantiacsToolbox
    results = quantiacsToolbox.runts(__file__)