SNB researchers test LLM-based FX trading strategy
Meta’s Llama 3.1 comes out top predicting G10 currency sentiment based on news articles
Researchers from the Swiss National Bank have shown how a trading strategy that uses fine-tuned large language models (LLMs) to analyse sentiment in the foreign exchange market could outperform traditional language-based artificial intelligence methods.
The authors of the SNB working paper, Daniele Ballinari and Jessica Maly, suggest that by fine-tuning LLMs to better understand the jargon of FX markets, trading strategies can be created based on the sentiment they detect.
LLMs “provide innovative
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