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trendFollowing.py
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65 lines (48 loc) · 2.43 KB
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### Quantiacs Trend Following Trading System Example
# import necessary Packages below:
import numpy
def myTradingSystem(DATE, OPEN, HIGH, LOW, CLOSE, VOL, exposure, equity, settings):
''' This system uses trend following techniques to allocate capital into the desired equities'''
nMarkets = CLOSE.shape[1]
periodLonger = 200
periodShorter = 40
# Calculate Simple Moving Average (SMA)
smaLongerPeriod = numpy.nansum(CLOSE[-periodLonger:, :], axis=0)/periodLonger
smaShorterPeriod = numpy.nansum(CLOSE[-periodShorter:, :], axis=0)/periodShorter
longEquity = smaShorterPeriod > smaLongerPeriod
shortEquity = ~longEquity
pos = numpy.zeros(nMarkets)
pos[longEquity] = 1
pos[shortEquity] = -1
weights = pos/numpy.nansum(abs(pos))
return weights, settings
def mySettings():
''' Define your trading system settings here '''
settings = {}
# S&P 100 stocks
settings['markets']=['CASH','AAPL','ABBV','ABT','ACN','AEP','AIG','ALL',
'AMGN','AMZN','APA','APC','AXP','BA','BAC','BAX','BK','BMY','BRKB','C',
'CAT','CL','CMCSA','COF','COP','COST','CSCO','CVS','CVX','DD','DIS','DOW',
'DVN','EBAY','EMC','EMR','EXC','F','FB','FCX','FDX','FOXA','GD','GE',
'GILD','GM','GOOGL','GS','HAL','HD','HON','HPQ','IBM','INTC','JNJ','JPM',
'KO','LLY','LMT','LOW','MA','MCD','MDLZ','MDT','MET','MMM','MO','MON',
'MRK','MS','MSFT','NKE','NOV','NSC','ORCL','OXY','PEP','PFE','PG','PM',
'QCOM','RTN','SBUX','SLB','SO','SPG','T','TGT','TWX','TXN','UNH','UNP',
'UPS','USB','UTX','V','VZ','WAG','WFC','WMT','XOM']
# Futures Contracts
settings['markets'] = ['CASH', 'F_AD', 'F_BO', 'F_BP', 'F_C', 'F_CC', 'F_CD',
'F_CL', 'F_CT', 'F_DX', 'F_EC', 'F_ED', 'F_ES', 'F_FC', 'F_FV', 'F_GC',
'F_HG', 'F_HO', 'F_JY', 'F_KC', 'F_LB', 'F_LC', 'F_LN', 'F_MD', 'F_MP',
'F_NG', 'F_NQ', 'F_NR', 'F_O', 'F_OJ', 'F_PA', 'F_PL', 'F_RB', 'F_RU',
'F_S', 'F_SB', 'F_SF', 'F_SI', 'F_SM', 'F_TU', 'F_TY', 'F_US', 'F_W',
'F_XX', 'F_YM']
settings['beginInSample'] = '20120506'
settings['endInSample'] = '20140506'
settings['lookback'] = 2
settings['budget'] = 10**6
settings['slippage'] = 0.05
return settings
# Evaluate trading system defined in current file.
if __name__ == '__main__':
import quantiacsToolbox
results = quantiacsToolbox.runts(__file__)