Take the AI make money for you with " AI and Financial Markets "

The application of AI technology to financial markets has become a focal point due to advancements in information processing, particularly deep learning. This Special Issue on “AI and Financial Markets” comprises ten articles that explore various facets of this dynamic field. It aims to inspire both researchers and practitioners in financial technology by presenting a range of innovative studies.

The first group of articles focuses on machine learning applications ([1–4]). Suimon et al. [1] use an autoencoder to develop a three-factor model of the Japanese yield curve. Yono et al. [2] create a model to measure macroeconomic uncertainty based on news text. Zengeler and Handmann [3] apply deep reinforcement learning to high-frequency trading of index contracts. Zhang and Hamori [4] combine machine learning with traditional economic models to assess their predictive superiority over a random walk.

The second section features agent-based artificial market simulations ([5,6]). Hirano et al. [5] model continuous double auction markets with three types of trading agents to analyze the effects of capital adequacy ratio regulation. Maeda et al. [6] develop a framework for training deep reinforcement learning models in agent-based price–order–book simulations.

The third category includes papers on other novel approaches ([7–9]). Kim et al. [7] employ the hidden Markov model to identify asset phases and propose a price trend-based investment strategy. Yue et al. [8] outline a network model for non-banking financial institutions in Romania. Vezeris et al. [9] implement a Turtle rule-based trading system to test its efficiency with selected assets.

Finally, Deng’s [10] conceptual paper introduces the Artificial Intelligence BlockCloud (AIBC), a large-scale decentralized ecosystem that integrates AI and blockchain technology for cost-effective computing and storage resource sharing.

These articles collectively address various aspects of AI and financial markets, offering valuable insights and serving as a rich resource for further exploration in financial technology.