Quantitative Trading of Bollinger Band Channel Breakouts Using the Generalized Autoregressive Conditional Heteroskedasticity Stock Selection Model
Proposing a quantitative investment strategy that integrates the generalized autoregressive conditional heteroskedasticity model for volatility stock selection,Bollinger Band channel breakout timing,and average true range(ATR)dynamic stop-loss.Firstly,30 stocks with the highest future volatility for the upcoming week are predictd using the generalized autoregressive conditional heteroskedasticity(GARCH)model to construct a stock pool.Secondly,the Bollinger Bands indicator for timing is used to capture price trend changes.Lastly,the stop-loss level based on the ATR indicator it adjusted to protect capital.Through multiple backtests,optimal parameters were determined.The results demonstrate the strategy's performance across various market environments,showcasing its risk-avoidance capabilities in bear markets,profit-making abilities in bull and sideways markets,and stable excess returns.The comprehensive use of volatility stock selection,price breakout,and dynamic stop-loss strategies offers investors an effective quantitative investment solution.
quantitative investmentvolatilitygeneralized autoregressive conditional heteroskedasticity(GARCH)modelBollinger band channeldynamic stop-loss
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维普
