Unlocking Earnings Calls: Leveraging AI Tools to Forecast U.S. Election Outcomes

Elections attract significant global interest, but forecasting outcomes accurately poses challenges. Experts often rely on historical and economic data, polls, and political strategies, yet these methods have limitations. This article introduces a novel approach to gauge election sentiments by analyzing public statements from company leaders. LSEG developed a prediction tool, the MarketPsych Transcript Analytics (MTA), which harnesses AI sentiment analysis to evaluate earnings call transcripts. By employing natural language processing, MTA identifies subtle shifts in executive language rather than just counting keywords. The method tracks mentions of candidates’ names in the 20 days leading up to elections, revealing that the eventual winner’s name is typically mentioned more frequently than their opponent’s across the last six U.S. presidential elections. This innovative technique may offer predictive insights that surpass conventional polling methods, providing an earlier glimpse into voter sentiment and election trends.

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