Stochastic Oscillator Strategy

Explanation & Rationale

The Stochastic Oscillator Strategy identifies potential momentum reversals by measuring the relative position of a stock’s closing price within its recent high-low range. A buy signal occurs when the %K line crosses above the %D line in the oversold zone (below 20), suggesting a potential upward reversal, while a short signal is triggered when %K crosses below %D in the overbought zone (above 80), indicating a possible downward reversal. This strategy helps traders capitalize on short-term shifts in market momentum by filtering out extreme price conditions.

Code

'''
Stochastic Oscillator Strategy.

Buy when the %K line crosses above the %D line below 20 (oversold condition).
Short when the %K line crosses below the %D line above 80 (overbought condition).
This strategy helps capture momentum reversals.
Learn more @ docs.ubacktest.com/examples/other-indicators/stochastic
'''

import pandas as pd
import numpy as np

def calculate_stochastic_oscillator(data, window=14):

    low_min = data['low'].rolling(window=window).min()
    high_max = data['high'].rolling(window=window).max()

    stoch_k = 100 * (data['close'] - low_min) / (high_max - low_min)
    stoch_d = stoch_k.rolling(window=3).mean()  # 3-day moving average of %K
    return stoch_k, stoch_d

def strategy(data):
    data['%K'], data['%D'] = calculate_stochastic_oscillator(data)

    # Generate signals based on stochastic crossover
    data['signal'] = np.nan
    data.loc[(data['%K'] < 20) & (data['%K'] > data['%D']), 'signal'] = 1  # Buy signal
    data.loc[(data['%K'] > 80) & (data['%K'] < data['%D']), 'signal'] = -1  # Short signal

    return data