Python算法交易

掌握向量化回测

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data['position'] = np.sign(data['return'].rolling(momentum).mean())

data['strategy'] = data['position'].shift(1) * data['return']

# determine when a trade takes place

data.dropna(inplace=True)

trades = data['position'].diff().fillna(0) != 0

# subtract transaction costs from return when trade takes place

data['strategy'][trades] -= self.tc

data['creturns'] = self.amount * data['return'].cumsum().apply(np.exp)

data['cstrategy'] = self.amount * \

data['strategy'].cumsum().apply(np.exp)

self.results = data

# absolute performance of the strategy

aperf = self.results['cstrategy'].iloc[-1]

# out-/underperformance ...