In this project, I attempt to obtain an effective strategy for trading a collec- tion of 27 financial futures based solely on their past trading data. All of ...

In this paper, we demonstrate how a well-established machine learning-based statistical arbitrage strategy can be successfully transferred from equity to ...

In this paper, we demonstrate how a well-established machine learning-based statistical arbitrage strategy can be successfully transferred from equity to ...

This study aims to model and forecast the market price of commodity futures and to discover more profitable investment strategies for futures trading.

4 апр. 2024 г. · AI's role in futures trading will not just be about automating tasks—it may provide new ways to predict and react to price action in real time ...

Artificial intelligence in futures trading relies heavily on machine learning algorithms to analyze historical data, identify patterns, and make predictions.

In this paper, we demonstrate how a well-established machine learning-based statistical arbitrage strategy can be successfully transferred from equity to ...

23 июл. 2024 г. · Algorithmic trading: Traders can use machine learning algorithms to develop automated trading systems that make trades based on predefined rules ...

12 мар. 2024 г. · The new ML initiative aims to offer retail traders and buy-side firms, including proprietary trading firms and hedge funds, unprecedented tools for identifying ...

1 мар. 2024 г. · This paper proposes a novel intraday algorithmic trading system for volatile commodity futures markets based on a Deep Q-network (DQN) algorithm and its robust ...