The Investor Social Network Sentiment, Commodity Prices and Ukrainian war impact; ‎Evidence from the S&P500 and the ESG Indexes ‎

NEIFAR, MALIKA and HarzAllah, AMIRA and Hdider, Anis (2025): The Investor Social Network Sentiment, Commodity Prices and Ukrainian war impact; ‎Evidence from the S&P500 and the ESG Indexes ‎.

Abstract

Purpose: Through an empirical analysis, taking into account of the investor social network sentiment ‎effects and the impact of fluctuations in the international prices of crude oil, natural gas and wheat on US stock ‎markets (SMs) performances, this study seeks to compare between the S&P500 and the ESG SMs behaviors ‎pre- and post-Ukrainian war declaration (PUWD). ‎ Methodology: In a first step, this study propose an original method for measuring investor ‎sentiment from tweeter in the US SM. In a second step, Student t and ANOVA tests are used ‎to prove the behavior instability of the conventional and ESG US SM, the investor sentiment ‎‎(IS), and the world economic environment. In a third step, besides the GARCH-X and the ‎augmented TGARCH-M models for a comparative analysis pre- vs PUWD, a robustness check ‎of the persistence and the asymmetry is based on the new impact curves (NICs) and the sign ‎and size bias tests is considered for the conventional US SM return (SMR) and volatility. ‎ Results: Regarding the IS SENTG (SENT) effect, results reveal significant positive effect on ‎the ESG return pre- and PUWD (S&P500 return and its volatility only PUWD). In addition, ‎the ESG return is found to have significant effect on its volatility. Finding show also that only ‎PUWD; economic factors such as the prices of raw materials have as expected significant ‎positive effects on return of the ESG (return and volatility of the S&P500) index, while the ‎market volatility (VIX) affect negatively the conventional SMR and positively its volatility ‎either pre- or PUWD. NICs and sign and size bias tests confirm graphically results about ‎S&P500. ‎ Originality: In this study, the approach used to calculate the SENT and SENTG index from ‎investors' tweets is based on combination of the BERT model of face hugging for natural ‎language processing and the python language. The S&P500 and the ESG indexes are found to ‎behave differently via different models vis à vis the investor sentiments and the geopolitical ‎and economics evolutions pre- and PUWD. ‎

• Item Type: MPRA Paper
• Language: English
• Keywords: S&P500 and ESG stock index instability; American investor sentiment on tweeter, Ukrainian ‎War; commodity prices and the VIX index; Augmented TGARCH-M model; NICs and sign ‎and size bias tests
• Subjects: G - Financial Economics > G0 - General > G02 - Behavioral Finance: Underlying Principles; G - Financial Economics > G1 - General Financial Markets > G15 - International Financial Markets

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