Strategies that only take long positions in assets.
An explainable multi-agent system using fine-tuned GPT-4o models for crypto portfolio management. Specialized agents analyze news, factors, and charts, collaborate on decisions, and execute trades—outperforming benchmarks in returns, accuracy, and interpretability.
This paper introduces a multi-step prompt strategy called Classify-and-Rethink (CAR) to help ChatGPT overcome behavioral biases—especially the framing effect—in financial decision-making. Applied to gold news, CAR improves score rationality and generates higher Sharpe ratios.
This paper shows ChatGPT can act as a robo-advisor, generating stock picks from news that yield up to 3% monthly alpha, especially on political and policy-related events. Its performance beats traditional textual analysis in both U.S. and Chinese markets.
This paper introduces HAID—a novel measure that captures new information in earnings call Q&As by comparing executive answers to ChatGPT’s responses. A higher HAID predicts more trading, stronger price reactions, improved analyst forecasts, and greater liquidity.
ChatGPT-based sentiment from full earnings call transcripts predicts stock returns up to six months ahead. After its democratization, retail investors’ trading aligns more closely with AI insights—narrowing the gap with informed traders.
This paper shows that hedge funds adopting ChatGPT saw a 3–5% boost in annualized returns post-2022.
This paper introduces asset embeddings—vector representations of stocks learned from investor portfolios using techniques like BERT and Word2Vec. These embeddings outperform traditional characteristics in explaining return comovement, offering a new framework for understanding investor behavior.
ChatGPT can classify Federal Reserve policy tone and identify monetary shocks with high accuracy—matching or outperforming traditional methods. The paper shows GPT-4 can replicate expert-level reasoning, offering a powerful tool for analyzing central bank communication.
ChatGPT can classify crypto tweets into bullish or bearish and predict Bitcoin returns better than BERT or VADER. Its sentiment signals show strong predictive power for daily returns.
ChatGPT can predict future UK interest rate decisions by analyzing central bank speeches—turning policy tone into a reliable forecasting signal.
ChatGPT can turn bloated disclosures into sharp summaries. The sentiment from these summaries predicts stock returns better than traditional methods — revealing alpha in plain sight.
This paper shows that ChatGPT-3.5 can predict aggregate U.S. stock returns using WSJ headlines. DeepSeek and smaller LLMs (like BERT) do not match this predictive performance.