Googling and ARMS sentiment across economic phases and horizons: insights into Brazilian crises
DOI:
https://doi.org/10.1108/REGE-02-2025-0035Keywords:
Stock market crashes, ARMS index, Google Trends, Probit modelAbstract
PurposeThis study investigates the impact of fundamental factors (returns, liquidity, and volatility) and investor sentiment, captured through indirect (ARMS index) and direct (Google Trends search volumes of positive and negative terms) measures across the Expansion and Contraction phases and three time horizons, on the risk of stock market crashes in Brazil.
Design/methodology/approachThe analysis applies the CMAX (current index level relative to the historical maximum) method for crisis identification and the local bull-bear indicator to classify economic phases over short-, medium-, and long-term horizons. Probit models were then estimated to assess how these factors affect the likelihood of crisis occurrence.
FindingsThe results reveal that declining returns, reduced liquidity, and heightened volatility increase the probability of crisis. Investor sentiment, marked by optimism during expansions and pessimism during contractions, significantly predicts crisis risk, particularly over shorter horizons, although its effect diminishes as market fundamentals regain their influence. Notably, Google Trends exhibited strong predictive power, outperforming the ARMS index.
Practical implicationsThese findings provide timely insights for investors, analysts, and policymakers. Real-time sentiment monitoring via Google Trends supports early detection of market instability, aiding portfolio management, stress testing, and policy actions. The study also informs macroprudential regulation by incorporating behavioral indicators into systemic risk frameworks.
Originality/valueThis study is among the first to examine direct and indirect investor sentiment across economic cycles in an emerging market, offering a robust framework to anticipate crises while highlighting the societal benefits of early detection and the importance of financial literacy in curbing emotional market behavior.
Downloads
References
Aggarwal, R., Inclan, C., & Leal, R. (1999). Volatility in emerging stock markets. Journal of financial and Quantitative Analysis, 34(1), 33‑55. doi:10.2307/2676245
Amihud, Y. (2002). Illiquidity and stock returns : Cross-section and time-series effects. Journal of financial markets, 5(1), 31‑56. doi:10.1016/S1386-4181(01)00024-6
Amihud, Y., & Mendelson, H. (1986). Asset pricing and the bid-ask spread. Journal of financial Economics, 17(2), 223‑249. doi: 10.1016/0304-405X(86)90065-6
Amihud, Y., Mendelson, H., & Wood, R. (1990). Liquidity and the 1987 stock market crash. Journal of Portfolio Management, 16(3), 65‑69. doi: 10.1016/S0304-405X(97)00021-4
Bai, M., Qin, Y., & Zhang, H. (2021). Stock price crashes in emerging markets. International Review of Economics & Finance, 72, 466‑482. doi: 10.1016/j.iref.2020.12.007
Bekaert, G., Hoerova, M., & Duca, M. L. (2013). Risk, uncertainty and monetary policy. Journal of Monetary Economics, 60(7), 771‑788. doi: 10.1016/j.jmoneco.2013.06.003
Ben Yaala, S., & Henchiri, J. E. (2023). Predicting stock market crashes on the African stock markets : Evidence from log-periodic power law model. African Journal of Economic and Management Studies. doi: 10.1108/AJEMS-03-2023-0113
Ben Yaala, S., & Henchiri, J. E. (2024). Predicting stock market crashes in MENA regions : Study based on the irrationality of investor behavior and the NARX model. Journal of Financial Regulation and Compliance. doi: 10.1108/JFRC-12-2023-0201
Ben Yaala, S., & Henchiri, J. E. (2025a). Climate risks and cryptocurrency volatility : Evidence from crypto market crisis. China Finance Review International. doi: 10.1108/CFRI-09-2024-0575
Ben Yaala, S., & Henchiri, J. E. (2025b). Detecting and analyzing explosive bubbles and their relationship with volatility : Evidence from Tunisia. RAUSP Management Journal, 60(1), 86‑101. doi: 10.1108/RAUSP-05-2024-0097
Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. Journal of econometrics, 31(3), 307‑327. doi: 10.1016/0304-4076(86)90063-1
Brito, A. D. (2024). Instability of returns and liquidity during the Covid-19 pandemic : Evidence from the brazilian stock market. Revista de Administração da UFSM, 17(2), e3. doi:10.5902/1983465984713
Cao, J., He, G., & Jiao, Y. (2025). Too sensitive to fail : The impact of sentiment connectedness on stock price crash risk. Entropy, 27(4), 345. doi: 10.3390/e27040345
Carosia, A. E. de O., da Silva, A. E. A., & Coelho, G. P. (2025). Predicting the Brazilian Stock Market with Sentiment Analysis, Technical Indicators and Stock Prices : A Deep Learning Approach. Computational Economics, 65(4), 2351‑2378. doi: 10.1007/s10614-024-10636-y
Choudhry, T. (1996). Stock market volatility and the crash of 1987 : Evidence from six emerging markets. Journal of International money and Finance, 15(6), 969‑981. doi: 10.1016/S0261-5606(96)00036-8
Da, Z., Engelberg, J., & Gao, P. (2011). In Search of Attention. The Journal of Finance, 66(5), 1461‑1499. doi: 10.1111/j.1540-6261.2011.01679.x
Da, Z., Engelberg, J., & Gao, P. (2015). The sum of all FEARS investor sentiment and asset prices. The Review of Financial Studies, 28(1), 1‑32. doi: 10.1093/rfs/hhu072
De Long, J. B., & Shleifer, A. (1991). The stock market bubble of 1929 : Evidence from clsoed-end mutual funds. The Journal of Economic History, 51(3), 675‑700. https://ms.mcmaster.ca/~grasselli/DeLongShleifer91.pdf
Fang, W. (2001). Stock return process and expected depreciation over the Asian financial crisis. Applied Economics, 33(7), 905‑912. doi: 10.1080/00036840122487
Forero-Laverde, G. (2018). A New Indicator for Describing Bull and Bear Markets. EHES Working Papers in Economic History. https://www.econstor.eu/handle/10419/247059
Gao, Z., Ren, H., & Zhang, B. (2020). Googling investor sentiment around the world. Journal of Financial and Quantitative Analysis, 55(2), 549‑580. [suspicious link removed]
Grigoryev, L. M., & Starodubtseva, M. F. (2021). Brazil in the 21st century : A difficult path. Russian Journal of Economics, 7(3), 250‑268. doi: 10.32609/j.ruje.7.78432
Hadhri, S., & Ftiti, Z. (2019). Commonality in liquidity among Middle East and North Africa emerging stock markets : Does it really matter? Economic Systems, 43(3‑4), 100699.
Karasan, A., Alp, O. S., & Weber, G.-W. (2025). Machine learning approach to stock price crash risk. Annals of Operations Research. doi: 10.1007/s10479-025-06596-7
Nguyen, A. T., & Nguyen, N. T. (2024). How does investor sentiment affect stock market crash risk? Evidence from Asia-Pacific markets. Cogent Economics & Finance, 12(1), 2422959. doi: 10.1080/23322039.2024.2422959
Nguyen, H. T., & Nguyen, H. T. N. (2024). Stock price crash risk, liquidity and institutional blockholders : Evidence from Vietnam. Journal of Economics and Development, 26(3), 174‑188. doi: 10.1108/JED-09-2023-0177
Pan, W.-F. (2020). Does Investor Sentiment Drive Stock Market Bubbles? Beware of Excessive Optimism! Journal of Behavioral Finance, 21(1), 27‑41. doi: 10.1080/15427560.2019.1587764
Pindyck, R. S. (1983). Risk, inflation, and the stock market. National Bureau of Economic Research Cambridge, Mass., USA. https://www.nber.org/papers/w1186
Rodriguez-Nieto, J. A., & Mollick, A. V. (2021). The US financial crisis, market volatility, credit risk and stock returns in the Americas. Financial Markets and Portfolio Management, 35(2), 225‑254. doi: 10.1007/s11408-020-00369-x
Tabash, M. I., Chalissery, N., Nishad, T. M., & Al-Absy, M. S. M. (2024). Market shocks and stock volatility : Evidence from emerging and developed markets. International Journal of Financial Studies, 12(1), 2. doi: 10.3390/ijfs12010002
TENG, Chia-Chen, WU, Wei-Shao, et YANG, J. Jimmy. Investor Sentiment and Stock Market Crashes a Heliobiological Perspective. doi: 10.2139/ssrn.4188543
Wu, B., Cai, Y., & Zhang, M. (2021). Investor sentiment and stock price crash risk in the Chinese stock market. Journal of Mathematics, 2021, 1‑10. doi: 10.1155/2021/6806304
Zouaoui, M., Nouyrigat, G., & Beer, F. (2011). How Does Investor Sentiment Affect Stock Market Crises? Evidence from Panel Data. Financial Review, 46(4), 723‑747. doi: 10.1111/j.1540-6288.2011.00318.x
Published
Issue
Section
License
Copyright (c) 2026 Sirine Ben Yaala, Jamel Eddine Henchiri

This work is licensed under a Creative Commons Attribution 4.0 International License.