Sentiment as a Brake, Not a Signal: A Profit-at-Risk and Placebo Attribution of Affective Features in Equity Trading Systems

Trading systems increasingly use the affective content of financial text to size positions, assuming that sentiment carries information a price-based model lacks. We ask whether that assumption survives a falsification test. Using more than three million social-media and news messages scored for sentiment, sarcasm and emotion, we compare three strategies differing only in their affective input: technical indicators alone, technical indicators plus sentiment, and a content-free placebo whose feature matches sentiment's statistical profile but carries no meaning. Each is evaluated on return relative to tail risk across a bull and a bear year. Sentiment does not improve how the system trades; it changes how much. It acts almost entirely as a brake on exposure, pulling the strategy out of a rising market and cutting its participation in a falling one. The placebo is decisive: compared on common trading days, which holds the exposure difference aside, a meaningless feature performs as well as real sentiment, with no significant daily difference in either regime. What looks like skill is reduced exposure, not better timing. Any textual feature proposed for a trading system should therefore be tested against a distribution-matched placebo, compared at equal exposure, and judged on profit-at-risk rather than raw return.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-09-24
DOI
https://doi.org/10.5281/zenodo.22104248
Primary Topic
Financial Markets and Investment Strategies
Type
preprint
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preprint

Sentiment as a Brake, Not a Signal: A Profit-at-Risk and Placebo Attribution of Affective Features in Equity Trading Systems

Younès Lahrichi, Saïd Achchab, Abdelkhaleq El Haddad
Zenodo (CERN European Organization for Nuclear Research)
Financial Markets and Investment Strategies
preprint

Sentiment as a Brake, Not a Signal: A Profit-at-Risk and Placebo Attribution of Affective Features in Equity Trading Systems

Younès Lahrichi, Saïd Achchab, Abdelkhaleq El Haddad
preprint en

Abstract

Trading systems increasingly use the affective content of financial text to size positions, assuming that sentiment carries information a price-based model lacks. We ask whether that assumption survives a falsification test. Using more than three million social-media and news messages scored for sentiment, sarcasm and emotion, we compare three strategies differing only in their affective input: technical indicators alone, technical indicators plus sentiment, and a content-free placebo whose feature matches sentiment's statistical profile but carries no meaning. Each is evaluated on return relative to tail risk across a bull and a bear year. Sentiment does not improve how the system trades; it changes how much. It acts almost entirely as a brake on exposure, pulling the strategy out of a rising market and cutting its participation in a falling one. The placebo is decisive: compared on common trading days, which holds the exposure difference aside, a meaningless feature performs as well as real sentiment, with no significant daily difference in either regime. What looks like skill is reduced exposure, not better timing. Any textual feature proposed for a trading system should therefore be tested against a distribution-matched placebo, compared at equal exposure, and judged on profit-at-risk rather than raw return.

Zenodo (CERN European Organization for Nuclear Research)
Mohammed V University (MA), Institut Supérieur de Commerce et d'Administration des Entreprises (MA), ISCA Technologies (United States) (US)
Financial Markets and Investment Strategies
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Sentiment as a Brake, Not a Signal: A Profit-at-Risk and Placebo Attribution of Affective Features in Equity Trading Systems — Younès Lahrichi, Saïd Achchab, et al. · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS