A CNN-GRU hybrid is claimed to outperform standalone CNN and GRU for market sentiment and risk prediction, but the reported metrics are in-sample only.
Application of Black-Litterman Bayesian in Statistical Arbitrage
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abstract
\begin{abstract} In this paper, we integrated the statistical arbitrage strategy, pairs trading, into the Black-Litterman model and constructed efficient mean-variance portfolios. Typically, pairs trading underperforms under volatile or distressed market condition because the selected asset pairs fail to revert to equilibrium within the investment horizon. By enhancing this strategy with the Black-Litterman portfolio optimization, we achieved superior performance compared to the S\&P 500 market index under both normal and extreme market conditions. Furthermore, this research presents an innovative idea of incorporating traditional pairs trading strategies into the portfolio optimization framework in a scalable and systematic manner.
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Integrative Analysis of Financial Market Sentiment Using CNN and GRU for Risk Prediction and Alert Systems
A CNN-GRU hybrid is claimed to outperform standalone CNN and GRU for market sentiment and risk prediction, but the reported metrics are in-sample only.