@inproceedings{linhares-pontes-etal-2025-backtesting,
title = "Backtesting Sentiment Signals for Trading: Evaluating the Viability of Alpha Generation from Sentiment Analysis",
author = "Linhares Pontes, Elvys and
Gonz{\'a}lez-Gallardo, Carlos-Emiliano and
Bordea, Georgeta and
G Moreno, Jose and
Ben Jannet, Mohamed and
Zhao, Yuxuan and
Doucet, Antoine",
editor = "Bechet, Fr{\'e}d{\'e}ric and
Chifu, Adrian-Gabriel and
Pinel-sauvagnat, Karen and
Favre, Benoit and
Maes, Eliot and
Nurbakova, Diana",
booktitle = "Actes de la session industrielle de CORIA-TALN 2025",
month = "6",
year = "2025",
address = "Marseille, France",
publisher = "ATALA {\textbackslash}{\textbackslash}{\&} ARIA",
url = "https://aclanthology.org/2025.jeptalnrecital-industrielle.2/",
pages = "17--32",
language = "fra",
abstract = "Sentiment analysis, widely used in product reviews, also impacts financial markets by influencing asset prices through microblogs and news articles. Despite research in sentiment-driven finance, many studies focus on sentence-level classification, overlooking its practical application in trading. This study bridges that gap by evaluating sentiment-based trading strategies for generating positive alpha. We conduct a backtesting analysis using sentiment predictions from three models (two classification and one regression) applied to news articles on Dow Jones 30 stocks, comparing them to the benchmark Buy{\&}Hold strategy. Results show all models produced positive returns, with the regression model achieving the highest return of 50.63{\%} over 28 months, outperforming the benchmark Buy{\&}Hold strategy. This highlights the potential of sentiment in enhancing investment strategies and financial decision-making."
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<abstract>Sentiment analysis, widely used in product reviews, also impacts financial markets by influencing asset prices through microblogs and news articles. Despite research in sentiment-driven finance, many studies focus on sentence-level classification, overlooking its practical application in trading. This study bridges that gap by evaluating sentiment-based trading strategies for generating positive alpha. We conduct a backtesting analysis using sentiment predictions from three models (two classification and one regression) applied to news articles on Dow Jones 30 stocks, comparing them to the benchmark Buy&Hold strategy. Results show all models produced positive returns, with the regression model achieving the highest return of 50.63% over 28 months, outperforming the benchmark Buy&Hold strategy. This highlights the potential of sentiment in enhancing investment strategies and financial decision-making.</abstract>
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%0 Conference Proceedings
%T Backtesting Sentiment Signals for Trading: Evaluating the Viability of Alpha Generation from Sentiment Analysis
%A Linhares Pontes, Elvys
%A González-Gallardo, Carlos-Emiliano
%A Bordea, Georgeta
%A G Moreno, Jose
%A Ben Jannet, Mohamed
%A Zhao, Yuxuan
%A Doucet, Antoine
%Y Bechet, Frédéric
%Y Chifu, Adrian-Gabriel
%Y Pinel-sauvagnat, Karen
%Y Favre, Benoit
%Y Maes, Eliot
%Y Nurbakova, Diana
%S Actes de la session industrielle de CORIA-TALN 2025
%D 2025
%8 June
%I ATALA \textbackslash\textbackslash& ARIA
%C Marseille, France
%G fra
%F linhares-pontes-etal-2025-backtesting
%X Sentiment analysis, widely used in product reviews, also impacts financial markets by influencing asset prices through microblogs and news articles. Despite research in sentiment-driven finance, many studies focus on sentence-level classification, overlooking its practical application in trading. This study bridges that gap by evaluating sentiment-based trading strategies for generating positive alpha. We conduct a backtesting analysis using sentiment predictions from three models (two classification and one regression) applied to news articles on Dow Jones 30 stocks, comparing them to the benchmark Buy&Hold strategy. Results show all models produced positive returns, with the regression model achieving the highest return of 50.63% over 28 months, outperforming the benchmark Buy&Hold strategy. This highlights the potential of sentiment in enhancing investment strategies and financial decision-making.
%U https://aclanthology.org/2025.jeptalnrecital-industrielle.2/
%P 17-32
Markdown (Informal)
[Backtesting Sentiment Signals for Trading: Evaluating the Viability of Alpha Generation from Sentiment Analysis](https://aclanthology.org/2025.jeptalnrecital-industrielle.2/) (Linhares Pontes et al., JEP/TALN/RECITAL 2025)
ACL