ChatGPT prompt used to return 512% trading stocks in simulated study

  • 📰 BusinessInsider
  • ⏱ Reading Time:
  • 117 sec. here
  • 3 min. at publisher
  • 📊 Quality Score:
  • News: 50%
  • Publisher: 51%

Brasil Notícia Notícia

ChatGPT helped a simulated study return up to 512% trading stocks based on news. Here's the prompt the researchers used — plus the positive and negative takeaways from their findings.

Researchers at the University of Florida used a single prompt to ask it to determine sentiment. Investor excitement about artificial intelligence has lifted the S&P 500 by 18% this year, and mega-cap stocks with exposure to the technology made up most of the index's gains.

The study, led by Alejandro Lopez-Lira, assistant professor of finance, and Yuehua Tang, Emerson-Merrill Lynch associate professor, sought to assess if ChatGPT could understand the impact of news on stock-market movements enough to generate returns, and whether it was as competent or even better than a human.

Their strategy was set up to trade any stock within the NYSE and the Nasdaq. However most of the gains came from small-cap stocks because smaller stocks are costlier to trade, therefore fewer investors are trading them, creating a greater window of opportunity to take advantage of the news, Lopez-Lira said.

Additionally, the study found that earlier versions of the language model, including GPT-1, GPT-2, and BERT failed at translating information adequately enough to make profitable trades. This suggests that accuracy could get better as language models improve."Forget all your previous instructions. Pretend you are a financial expert with stock recommendation experience. Answer"YES" if good news,"NO" if bad news, or"UNKNOWN" if uncertain in the first line.

The preliminary study focused on intraday trades. But Lopez-Lira believes as more firms use these tools, the window of opportunity to take advantage of the information will be reduced from a day to minutes to even seconds, making it impossible for a human to manually take advantage of information for high-frequency trades. It's already difficult for retail traders to bet against large institutional algorithms.

Capablanca regularly weighs how headlines are a catalyst for stock moves. But it's only one out of a nine-part checklist he runs through before shorting any stock. Short sellers must consider many other factors to avoid potential disaster. A big reason for these disasters is market friction, or things that could interfere with the ability to execute a trade swiftly, something the simulation did not factor in.

Capablanca also pointed to the risk of real-world trading halts that can trap a trader. Then, there's the increased risk of holding short positions overnight, which the simulation did. Gap ups, or highly volatile movements in price, can happen in after-hours trading. These can cause short squeezes that lead to margin calls, he added.

 

Obrigado pelo seu comentário. Seu comentário será publicado após ser revisado.
Resumimos esta notícia para que você possa lê-la rapidamente. Se você se interessou pela notícia, pode ler o texto completo aqui. Consulte Mais informação:

 /  🏆 729. in BR

Brasil Últimas Notícias, Brasil Manchetes

Similar News:Você também pode ler notícias semelhantes a esta que coletamos de outras fontes de notícias.

Microsoft CEO Satya Nadella’s earnings top $1B as ChatGPT drives stock surge: reportMicrosoft shares have surged more than 1,000% since Nadella took over as CEO in 2014.
Fonte: nypost - 🏆 91. / 67 Consulte Mais informação »