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iamraa/quantrum.roc200.py

Last active Jul 29, 2018
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Quantrum ROC(200) & KST strategy test
import talib # библиотека для технического анализа
import numpy as np
# функция, выполняемая перед началом тестирования
def initialize(context):
# сохраняем актив, с которым будем работать
context.asset = symbol('SPY')
context.strategy = 'roc_sma'
set_benchmark(symbol('SPY'))
# ставим событие для ребалансировки на открытии рынка
schedule_function(rebalance, date_rules.every_day(), time_rules.market_open())
# ежедневная ребалансировка
def rebalance(context, data):
# история для расчета средних за последние 400 торговых дней
price_hist = data.history(context.asset, 'close', 400, '1d')
# стратегия
if context.strategy == 'price_sma200':
# средние: длинная и короткая
ma_long = talib.SMA(price_hist, timeperiod=200)
ma_short = price_hist
# сигнал на положении
allow = ma_short[-1] >= ma_long[-1]
elif context.strategy == 'roc200':
price_hist = data.history(context.asset, 'close', 400, '1d')
ma_long = talib.ROC(price_hist, timeperiod=200)
# сигнал на положении
allow = 0 < ma_long[-1]
record(roc=ma_long[-1])
elif context.strategy == 'roc200smooth':
# средние: длинная и короткая
roc200 = talib.ROC(price_hist, timeperiod=200)
ma_long = (roc200 + np.roll(roc200, 1)*2 + np.roll(roc200, 2)*2 + np.roll(roc200, 3)) / 6
# сигнал на положении
allow = 0 < ma_long[-1]
record(sroc=ma_long[-1])
elif context.strategy == 'tsi':
prices = data.history(context.asset, ['open', 'high', 'low', 'close'], 400, '1d')
tsi = get_tsi(prices, 10, 50) # 10, 50
roc200 = talib.ROC(price_hist, timeperiod=200)
for_sign = roc200.copy()
tsi *= np.sign(for_sign)
ma_long = tsi
# сигнал на положении
allow = 0.5 < ma_long[-1]
record(tsi=ma_long[-1])
elif context.strategy == 'kst':
prices = data.history(context.asset, ['close'], 400, '1d')
kst, kst_signal = get_kst(prices, [10, 15, 20, 30], [10, 10, 10, 15], 9)
# сигнал на положении
allow = 0. <= kst[-1]
record(kst=kst[-1])
elif context.strategy == 'kst_signal':
prices = data.history(context.asset, ['close'], 400, '1d')
kst, kst_signal = get_kst(prices, [10, 15, 20, 30], [10, 10, 10, 15], 9)
# сигнал на положении
allow = 0. <= (kst - kst_signal)[-1]
record(kst_hist=(kst - kst_signal)[-1])
elif context.strategy == 'roc_sma':
prices = data.history(context.asset, ['close'], 400, '1d')
roc_sma = talib.SMA(talib.ROC(prices.close, timeperiod=5), timeperiod=200)
# сигнал на положении
allow = 0. <= roc_sma[-1]
record(roc_sma=roc_sma[-1])
elif context.strategy == 'roc5x200':
ma_short = talib.ROC(price_hist, timeperiod=5)
ma_long = talib.ROC(price_hist, timeperiod=200)
# сигнал на положении
allow = 0 < ma_short[-1] - ma_long[-1]
record(rocx=ma_short[-1] - ma_long[-1])
elif context.strategy == 'sma50_sma200':
# средние: длинная и короткая
ma_long = talib.SMA(price_hist, timeperiod=200)
ma_short = talib.SMA(price_hist, timeperiod=50)
# сигнал на пересечении
#allow = ma_short[-1] >= ma_long[-1] and ma_short[-1] < ma_long[-1]
# сигнал на положении
allow = 0 < ma_short[-1] - ma_long[-1]
else:
print('Неизвестная стратегия')
return
record(allow=allow, price=price_hist[-1])
# проверяем возможность торговли активом
if data.can_trade(context.asset):
if allow:
# покупаем актив на 100% портфеля, если разрешено
order_target_percent(context.asset, 1.)
else:
order_target_percent(context.asset, 0.)
def get_tsi(df, short, long):
ratio = (df.close - df.close.shift(short)).abs() / talib.ATR(df.high.values, df.low.values, df.close.values, timeperiod=short)
tsi = talib.SMA(talib.SMA(ratio.values, timeperiod=short), timeperiod=long) - 1 # substruct 1
tsi[tsi < 0] = 0
#print("Min: {0} Max: {1}".format(tsi[~np.isnan(tsi)].min(), tsi[~np.isnan(tsi)].max()))
return tsi
def get_kst(df, roc, sma, signal):
kst = None
for i, v in enumerate(roc):
data = talib.SMA(talib.ROC(df.close, timeperiod=v), timeperiod=sma[i])
if kst is None:
kst = data * (i + 1)
else:
kst += data * (i + 1)
return kst, talib.SMA(kst, timeperiod=signal)
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