系统源代码发布v2.4供下载，带年化32.1%策略，简化GUI逻辑

年化42.86%，比基准的12.86高出不少，回撤才9.43%，还是比较稳健的。

策略核心代码如下：我们使用KNN算法，大家可以考虑替换成SVM，或者树模型lightGBM。

class MLTrainOnceStrategy(Strategy):
    price_delta = .004  # 0.4%

    def init(self):
        # Init our model, a kNN classifier
        self.clf = KNeighborsClassifier(7)

        # Train the classifier in advance on the first N_TRAIN examples
        df = self.data.df.iloc[:N_TRAIN]
        X, y = get_clean_Xy(df)
        self.clf.fit(X, y)

        # Plot y for inspection
        self.I(get_y, self.data.df, name='y_true')

        # Prepare empty, all-NaN forecast indicator
        self.forecasts = self.I(lambda: np.repeat(np.nan, len(self.data)), name='forecast')

    def next(self):
        # Skip the training, in-sample data
        if len(self.data) < N_TRAIN:
            return

        # Proceed only with out-of-sample data. Prepare some variables
        high, low, close = self.data.High, self.data.Low, self.data.Close
        current_time = self.data.index[-1]

        # Forecast the next movement
        X = get_X(self.data.df.iloc[-1:])
        forecast = self.clf.predict(X)[0]

        # Update the plotted "forecast" indicator
        self.forecasts[-1] = forecast

        # If our forecast is upwards and we don't already hold a long position
        # place a long order for 20% of available account equity. Vice versa for short.
        # Also set target take-profit and stop-loss prices to be one price_delta
        # away from the current closing price.
        upper, lower = close[-1] * (1 + np.r_[1, -1] * self.price_delta)

        if forecast == 1 and not self.position.is_long:
            self.buy(size=.2, tp=upper, sl=lower)
        elif forecast == -1 and not self.position.is_short:
            self.sell(size=.2, tp=lower, sl=upper)

        # Additionally, set aggressive stop-loss on trades that have been open
        # for more than two days
        for trade in self.trades:
            if current_time - trade.entry_time > pd.Timedelta('2 days'):
                if trade.is_long:
                    trade.sl = max(trade.sl, low)
                else:
                    trade.sl = min(trade.sl, high)