ChatGPT as Stock Sentiment Analyst

Can advanced natural language processing models such as ChatGPT extract sentiment from firm news headlines that usefully predicts associated next-day stock returns? In their April 2023 paper entitled “Can ChatGPT Forecast Stock Price Movements? Return Predictability and Large Language Models”, Alejandro Lopez-Lira and Yuehua Tang test the ability of ChatGPT to predict next-day returns of individual stocks via analysis of relevant article and press release headlines from RavenPack, a leading provider of news sentiment data. They pre-process the headlines to ensure unique content and high relevance to a specific firm. They next instruct ChatGPT to designate whether each headline is good, bad or irrelevant for firm stock price, as follows:

“Forget all your previous instructions. Pretend you are a financial expert. You are
a financial expert with stock recommendation experience. Answer “YES” if good
news [+1], “NO” if bad news [-1} , or “UNKNOWN” if uncertain in the first line [0]. Then
elaborate with one short and concise sentence on the next line. Is this headline
good or bad for the stock price of _company_name_ in the _term_ term?”

They then compute a ChatGPT score for each stock in the news (averaging if there is more than one headline for a firm) and relate all stock scores to stock returns lagged by one day. They further compare predictive powers of ChatGPT sentiment scores to those provided by RavenPack. Using daily returns for a broad sample of U.S. common stocks and daily news headlines from RavenPack during October 2021 (post-training period for ChatGPT) through December 2022, they find that: (more…)