This coffeesode explores using AI models to predict stock prices. The discussion focuses on a study that used five years of historical stock data to train AI models and then tested their predictive stock market accuracy. The conversation also discusses a trading simulation, employing the most accurate model (linear regression), demonstrating significant profit generation in various scenarios. The speakers acknowledge limitations and suggest future research directions to enhance AI's predictive capabilities, such as incorporating financial reports and news data. The overall finding is that AI models show potential for profitable stock investment strategies.

Reference-
Shiburam, D. (2024) Applying AI Models for Stock Investment Decisions. Open Journal o f Applied Sciences, 14, 3061-3068. https://doi.org/10.4236/ojapps.2024.1411201

DISCLAIMER: This podcast was generated fully or in parts using AI technologies such as synthetic voice generation. AI may still sometimes give inaccurate responses, so you may want to confirm any facts independently. This conversation does not constitute financial, investment, or other professional advice. Any information provided herein is for informational purposes only and should not be construed as a recommendation or solicitation to engage in any specific investment activity. Listeners are advised to seek independent professional advice before making any financial decisions.

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