Return Predictability News Today

The AI revolution drove frenzied investment in both private and public companies and captured the public’s imagination in 2023. Transformational consumer products like ChatGPT are powered by Large Language Models (LLMs) that excel at modeling sequences of tokens that represent words or parts of words [2]. Amazingly, structural understanding

AI is reshaping all industries as it captivates the public with its limitless potential. Many in financial services have strong reservations about the technology, but it is here and is not going away. How can banks harness the opportunities of AI, from reducing costs to maximizing the customer experience, while managing its shortcomings?

A ground-breaking study investigates.

The two researchers who authored a recent paper discuss what the chatbot can and can't do when it comes to investing.

ChatGPT was even able to explain its classifications of Fed policy statements in a way that resembled the central bank’s own analyst, who also interpreted the language to act as a human benchmark for the study

Two new papers have been published this month that deployed the artificial intelligence chatbot in market-relevant tasks — one in deciphering whether Federal Reserve statements were hawkish or dovish, and one in determining whether headlines were good or bad for a stock.

The first wave of academic research applying the artificial intelligence bot to finance reveals it can also tell whether the Federal Reserve is being hawkish.

The first wave of academic research applying ChatGPT to the world of finance is arriving - and judging by early results, the hype of the past few months is justified.

Research showed ChatGPT can pull off similar tasks without even being specifically trained

This paper studies a portfolio choice problem of a utility-maximizing investor with return predictability and small liquidity costs. By adopting a logarithmic-return assumption, our asymptotic expansion around small liquidity costs provides the closed-form expressions for the first-order approximation of the value function and the associated almost-optimal trading strategy. The almost-optimal trading strategy indicates that the investor should trade toward the optimal frictionless portfolio, ins...