Quantum Temporal Convolutional Neural Networks for Cross-Sectional Equity Return Prediction: A Comparative Benchmark Study
“We conduct a comprehensive benchmarking study on the JPX Tokyo Stock Exchange dataset and evaluate predictions through long-short portfolio construction using out-of-sample Sharpe ratio as the primary performance metric.”
AssetEquities
StrategyMachine learningportfolio optimization
TechniqueFeedforward networkconvolutional network
ClaimSharpe ratioexcess return
Also stated: Long-short, Price and volume, out-of-sample test
Missing from abstract: benchmark, costs, multiple testing, universe
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