Less is more: AI Decision-Making using Dynamic Deep Neural Networks for Short-Term Stock Index Prediction

TL;DR

This paper presents a multi-agent deep learning model for short-term stock index prediction that outperforms passive strategies and traditional machine learning models, achieving higher profitability with lower market exposure.

Contribution

Introduces a novel multi-agent deep learning approach for trading in futures markets, demonstrating superior performance and reduced risk compared to passive and conventional models.

Findings

Model A outperforms passive investment and traditional ML models.

Achieves higher profitability with only 41.95% market exposure.

Demonstrates top quartile performance among US Large Cap active funds.

Abstract

In this paper we introduce a multi-agent deep-learning method which trades in the Futures markets based on the US S&P 500 index. The method (referred to as Model A) is an innovation founded on existing well-established machine-learning models which sample market prices and associated derivatives in order to decide whether the investment should be long/short or closed (zero exposure), on a day-to-day decision. We compare the predictions with some conventional machine-learning methods namely, Long Short-Term Memory, Random Forest and Gradient-Boosted-Trees. Results are benchmarked against a passive model in which the Futures contracts are held (long) continuously with the same exposure (level of investment). Historical tests are based on daily daytime trading carried out over a period of 6 calendar years (2018-23). We find that Model A outperforms the passive investment in key performance metrics, placing it within the top quartile performance of US Large Cap active fund managers. Model A also outperforms the three machine-learning classification comparators over this period. We observe that Model A is extremely efficient (doing less and getting more) with an exposure to the market of only 41.95% compared to the 100% market exposure of the passive investment, and thus provides increased profitability with reduced risk.