Strategies focused on US-listed assets.
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.
GPT-4 can create alpha. By simply prompting it with price and volume definitions, it generates factors that deliver Sharpe ratios up to 4.49 and annual returns up to 66%—without using any financial data.
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.
ChatGPT can generate profitable day trading signals by analyzing real-time Twitter news and selecting stock tickers to buy and sell. The strategy earns significant intraday alpha, especially from short positions, even without firm-specific prompts.
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 extract forward-looking investment signals from earnings calls. The paper shows that its investment score predicts firm capex up to 9 quarters ahead and negatively forecasts future stock returns—revealing information not yet priced by markets.
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.
Can ChatGPT predict stocks? Yes—GPT-4 applied to headlines yields a high-Sharpe intraday strategy with 650%+ returns. Predictive power emerges only in large models.
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.
This paper shows that a simple, model-free valuation approach using all available accounting data can identify stock mispricing. A strategy that buys underpriced and sells overpriced firms earns **4–10% alpha per year**, outperforming many known anomalies—even without complex valuation models.