The Predictive Edge
Autor: | Alejandro Lopez-Lira |
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EAN: | 9781394242726 |
eBook Format: | ePUB |
Sprache: | Englisch |
Produktart: | eBook |
Veröffentlichungsdatum: | 02.07.2024 |
Untertitel: | Outsmart the Market using Generative AI and ChatGPT in Financial Forecasting |
Kategorie: | |
Schlagworte: | Market sentiment analysis; market analysis; market sentiment; investing with chatgpt; stock market analysis; securities analysis; market sentiment analysis with ai; market sentiment analysis book; market sentiment book; market sentiment guide |
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Use ChatGPT to improve your analysis of stock markets and securities
In The Predictive Edge: Outsmart the Market Using Generative AI and ChatGPT in Financial Forecasting, renowned AI and finance researcher Dr. Alejandro Lopez-Lira delivers an engaging and insightful new take on how to use large language models (LLMs) like ChatGPT to find new investment opportunities and make better trading decisions. In the book, you'll learn how to interpret the outputs of LLMs to craft sounder trading strategies and incorporate market sentiment into your analyses of individual securities.
In addition to a complete and accessible explanation of how ChatGPT and other LLMs work, you'll find:
- Discussions of future trends in artificial intelligence and finance
- Strategies for implementing new and soon-to-come AI tools into your investing strategies and processes
- Techniques for analyzing market sentiment using ChatGPT and other AI tools
A can't-miss playbook for taking advantage of the full potential of the latest AI advancements, The Predictive Edge is a fully to-date and exciting exploration of the intersection of tech and finance. It will earn a place on the bookshelves of individual and professional investors everywhere.
ALEJANDRO LOPEZ-LIRA, PHD, is an Assistant Professor of Finance at the University of Florida. His award-winning research is focused on machine learning and textual analysis and he has a lengthy background in finance from renowned institutions. He was the recipient of the 2023 BlackRock Best Paper Prize for the research underpinning this book.