Signal source for QuantX

BollingerBand.py

    def _mavg_signal(data):
        ....
        # bollinger band %B day 20
        c = data["close_price_adj"].fillna(method='ffill')
        m20 = c.rolling(window=20, center=False).mean()
        s20 = c.rolling(window=20, center=False).std()
        ub = m20 + s20 * 2
        lb = m20 - s20 * 2
        pb = (c - lb) / (ub - lb)
        ....
        return {
            ....
            "UpperBB:price":ub,
            "LowerBB:price":lb,
            "BB %B:ratio":pb,
            ....
        }

macd.py

    def macd(values, short_period, long_period, signal_period):
        shorts = values.ewm(span=short_period).mean()
        longs = values.ewm(span=long_period).mean()
        _macd = shorts - longs
        return _macd, _macd.ewm(span=signal_period).mean()

rsi.py

      def rsi(data, period):
        diff = data.diff(1)
        pos = diff.clip_lower(0).ewm(alpha=1/period).mean()
        neg = diff.clip_upper(0).ewm(alpha=1/period).mean()
        return pos / (pos - neg)
      

StochasticOscillatorSample.py

    def _mavg_signal(data):
        ....
        close = data["close_price_adj"]
        l14 = data["low_price_adj"].rolling(window=14).min()
        h14 = data["high_price_adj"].rolling(window=14).max()
        pk  = 100 * ((close - l14) / (h14 - l14))
        pd  = pk.rolling(window=3).mean()
        ....
        return {
            ....
            "%K:ratio": pk,
            "%D:ratio": pd,
            ....
        }