Market Sentiment and Stock Market Volatility: Evidence from Tehran Stock Exchange

Document Type : Research Paper


Associate Professor, Department of Finance, Faculty of Islamic Studies and Management, Imam Sadiq University, Tehran, Iran


This study aimed to evaluate the significance and severity of the relationship between market sentiment and the volatility of the Tehran Stock Exchange Price Index (TEPIX). We drew on the principal component analysis (PCA) to provide a composite sentiment index using a set of proxies. In addition, ARIMA-E-GARCH hybrid models were applied to model the volatility of the TEPIX and other control variables. Subsequently, GLS regression was used to measure the impact of market sentiment and the control variables variation on the volatility of the TEPIX. The findings showed that the influences of optimistic and pessimistic sentiment on the volatility of TEPIX were both statistically significant and respectively, negative and positive. However, the severity of these negative and positive effects was slight. Furthermore, we found that the stock exchange volatility was highly affected by the volatility of the inflation and the liquidity much more than the other variables such as optimistic and pessimistic sentiment.


Main Subjects

Article Title [فارسی]

گرایش احساسی بازار و نوسان بازار سهام: شواهدی از بورس اوراق بهادار تهران

Author [فارسی]

  • محمد توحیدی
دانشیار گروه مالی، دانشکده معارف اسلامی و مدیریت، دانشگاه امام صادق (ع)، تهران، ایران
Abstract [فارسی]

این پژوهش معناداری و شدت رابطه میان گرایش احساسی سرمایه‌گذاران و نوسان شاخص قیمت بورس اوراق بهادار تهران (TEPIX) را می‌سنجد. برای انجام این مهم، ابتدا یک شاخص ترکیبی گرایش احساسی و متشکل از یک‌سری متغیرهای احساسی با استفاده از روش تحلیل مؤلفه‌های اساسی (PCA) استخراج می‌شود. سپس از طریق مدل‌های ترکیبی ARIMA-E-GARCH، تلاطم شاخص قیمت بورس اوراق بهادار تهران و سایر متغیرهای کنترل مدل‌سازی می‌شود. در نهایت برای سنجش اثر گرایش احساسی سرمایه‌گذاران و نوسان سایر متغیرهای کنترل بر نوسان شاخص قیمت بورس اوراق بهادار تهران از رگرسیون GLS استفاده می‌شود. نتایج گویای آن است که اثر  احساسات خوش‌بینانه و بدبینانه بر روی نوسان شاخص قیمت بورس اوراق بهادار تهران هر دو معنادار و به ترتیب منفی و مثبت، اما شدت تأثیر اندک است. افزون بر آن، یافته‌ها نشان می‌دهد نوسان شاخص سهام بیشتر متأثر از نوسان متغیرهایی چون تورم و نقدینگی است.

Keywords [فارسی]

  • گرایش احساسی بازار
  • معامله اختلال‌زا
  • نوسان قیمت سهام
  • مالی رفتاری
  • شاخص قیمت بورس اوراق بهادار تهران (TEPIX)
Abdelhédi-Zouch, M., Abbes, M. B., & Boujelbène, Y. (2015). Volatility spillover and investor sentiment: Subprime crisis. Asian Academy of Management Journal of Accounting & Finance, 11(2), 1–16.
Antoniou, C., Doukas, J. A., & Subrahmanyam, A. (2015). Investor sentiment, beta, and the cost of equity capital. Management Science, 62(2), 347–367.
Audrino, F., Sigrist, F., & Ballinari, D. (2020). The impact of sentiment and attention measures on stock market volatilityInternational Journal of Forecasting, 36(2), 334-357.
Aydogan, B. (2017). Sentiment dynamics and volatility of international stock markets.  Eurasian Business Review, 7 (3), 407–419.
Aziz Khan, M., & Ahmad, E. (2018). Measurement of investor sentiment and its bi-directional contemporaneous and lead–lag relationship with returns: Evidence from Pakistan. Sustainability, MDPI, Open Access Journal, 11(1), 1-20.
Bahloul, W., & Bouri, A. (2016). The impact of investor sentiment on returns and conditional volatility in US futures markets. Journal of Multinational Financial Management, 36(1), 89–102.
Baker, M., & Stein, J. (2002). Market liquidity as a sentiment indicator. Journal of Financial Markets, 7, 271-299.
Baker, M., & Wurgler, J. (2006). Investor sentiment and the cross-section of stock returns. Journal of Finance, 61, 1645-1680.
Baker, M., & Wurgler, J. (2007). Investor sentiment in the stock market. Journal of Economics Perspectives, 21(2), 129–151.
Barber, B. M., Odean T., & Zhu, N. (2006). Do noise traders move markets? [Paper presentation]. EFA Zurich Meetings.,
Barberis, N., & Thaler, R. (2003). A survey of behavioral finance. In Nicholas Barberis and Richard Thaler (Eds.)…, Handbook of the economics of finance (Vol. 1, pp. 1053-1128). Elsevier …
Beaumont, R., Daele, M., Frijns, B., & Lehnert, T. (2005). …: On individual and institutional noise trading. Working Paper, Maastricht University.
Beer, F., & Zouaoui, M. (2013). Measuring investor sentiment in the stock market. Journal of Applied Business Research. 29 (1), 51-68…
Black, F. (1986). Noise. Journal of Finance41(3), 529-543.
Bollerslev, T., & Wooldridge, J. M. (1992). Quasi-maximum likelihood estimation and inference in dynamic models with time-varying covariances. Econometric Reviews, 11(2), 143-172.
Box, G. E. P., & Jenkins, G. M. (1976). Time series analysis: Forecasting and control (Revised ed.). Holden Day.
Brown, G. W. (1999). Volatility, sentiment, and noise traders. Financial Analysts Journal, 55(2), 82–90.
Brown, G. W., & Cliff, M. T. (2004). Investor sentiment and the near-term stock market. Journal of Empirical Finance11(1), 1–27.
Brown, G. W., & Cliff, M. T. (2005). Investor sentiment and asset valuation. Journal of Business, 78(2), 405-440.
Campbell, J. Y., & Kyle, A. S. (1993). Smart money, noise trading and stock price behavior. The Review of Economic Studies, 60(1), 1–34.
Campbell, J.Y., Lettau, M., Malkiel, B.G. & Xu, Y. (2001), Have Individual Stocks Become More Volatile? An Empirical Exploration of Idiosyncratic Risk. The Journal of Finance, 56 (1), 1-43.
Chakravarty, S. (2001). Stealth trading: Which traders’ trades move stock prices. Journal of Financial Economics, 61, 289-307.
Chen, C., Hu, J., Meng, Q., & Zhang, Y. (2011). Short-time traffic flow prediction with ARIMA-GARCH model [Paper presentation]. 2011 IEEE Intelligent Vehicles Symposium (IV), Baden-Baden, Germany.
Chen, H., Chong, T., Tai, L., & She, Y. (2013). MPRA Paper 54150: A principal component approach to measuring investor sentiment in China. University Library of Munich.
Chi, L., & Zhuang, X. (2011). A study on the relationship between investor sentiment and the stock market returns in China-based on panel data model. Management Review, 6, 41–48.
Chowdhury, S. S., Sharmin, R., & Rahman, M. (2014). Effect of sentiment on the Bangladesh stock market returns [Paper presentation]. 12th EBES Conference, Nanyang Technological University, Singapore.
Chu, Y., Hirshleifer, D., & Ma, L. (2017). The causal effect of limits to arbitrage on asset pricing anomalies. NBER Working Papers 24144, National Bureau of Economic Research Inc. 1-61.
Chuang, W. J., Ouyang, L. Y., & Lo, W. C. (2010). The impact of investor sentiment on excess returns: A Taiwan stock market case. International Journal of Information & Management Sciences, 21(1), 13–28.
Chuangxia H., Xin Y., Xiaoguang Y., & Hu, S. (2014). An empirical study of the effect of investor sentiment on returns of different industries. Mathematical Problems in Engineering, 45, 1-11
Chung, J., Choe, H., & Kho, B. C. (2009). The impact of day-trading on volatility and liquidity. Asia-Pacific Journal of Financial Studies, 38, 237-275.
Da, Z., Larrain, B., Sialm, C., & Tessada, J. (2015). Working Paper No. 22161: Price pressure from coordinated noise trading: Evidence from pension fund reallocations (pp. 1–48). Cambridge, MA: National Bureau of Economic Research, Inc.
Danthine, J. P., & Moresi, S. (1993). Volatility, information and noise trading. European Economic Review, Elsevier, 37(5), 961-982.
DeLong, J. B., Shleifer, A., Summers, L. H., & Waldmann, R. J. (1990). Noise trader risk in financial markets. Journal of Political Economy, 98(4), 703-738.
Devault, L., Sias, R., & Starks, L. (2019). Sentiment metrics and investor demand. The Journal of Finance74(2), 985–1024.
Dimic, N., Neudl, M., Orlov, V., & Äijö. J. (2018). Investor sentiment, soccer games and stock returns. Research in International Business and Finance, 43, 90–98
Doojin R., Hyeyoen K., & Heejin Y. (2017). Investor sentiment, trading behavior and stock returns. Applied Economics Letters, 24(12), 826–830.
Dunham, L. M., & Garcia, J. (2021). Measuring the effect of investor sentiment on liquidity. Managerial Finance, 47(1), 59-85.
Fama, E. (1970). Efficient capital markets: A review of theory and empirical work. The Journal of Finance, 25(2), 383-417.
Ferreira, T. S. V., Machado, M. A. V., & Silva, P. Z. P. (2021). Asymmetric impact of investor sentiment on Brazilian stock market volatility. Revista de Administração Mackenzie, 22(4), 1–28.
Foucault, T., Sraer, D., & Thesmar, D. (2011). Individual investors and volatility, Working paper. The Journal of Finance, 66 (4), 1369-1406.
Frazzini, A., & Lamont, O. A. (2005). NBER Working Paper No 11526: Dumb money: Mutual fund flows and the cross-section of stock returns (pp. 1–35). Cambridge, MA: National Bureau of Economic Research.
Glushkov, D. (2006). Sentiment beta.
Haritha, P. H., & Rishad, A. (2020). An empirical examination of investor sentiment and stock market volatility: Evidence from India. Finance Innovation, 6(34), 1-15 …
He, G., Zhu, S., & Gu, H. (2020). The nonlinear relationship between investor sentiment, stock return, and volatility. Discrete Dynamics in Nature and Society, 2020 (1), 1-11
Heejin Y., Doojin, R., & Doowon, R. (2017). Investor sentiment, asset returns and firm characteristics: Evidence from the Korean Stock Market. Investment Analysts Journal, 46(2), 132-147.
Herve, F., Zouaoui, M., & Belvaux, B. (2019). Noise traders and smart money: Evidence from online searches. Economic ModellingElsevier, 83 (8), 141-149 …, 1–25.
Hong, H., & Stein, J. C. (2007). Disagreement and the stock market. Journal of Economic Perspectives, 21(2), 109–128. 
Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica47(2), 263-291.
Kapoor, S., & Prosad, J. M. (2017). Behavioural finance: A review. Procedia Computer Science, 122(1), 50–54.
Koski, J., & Rice, E., & Tarhouni, A. (2004). Noise trading and volatility: Evidence from day trading and message boards. Capital Markets: Market Microstructure eJournal. Available at SSRN: or Electronic Journal, …
Kumari, J., & Mahakud, J. (2016). Investor sentiment and stock market volatility: Evidence from India. Journal of Asia-Pacific Business, 17(2), 173–202.
Kurov, A. (2008). Investor sentiment, trading behavior and informational efficiency in index futures markets. Financial Review, 43, 107-127.
Kurov, A., & Lasser, D. (2004). Price dynamics in the regular and E-mini futures markets. Journal of Financial and Quantitative Analysis, 39, 365–384.
Kyrolainen, P. (2007). Day trading and stock price volatility. Journal of Economics and Finance, 32(1), 75–89.
Lee, W. Y., Jiang, C. X., & Indro, D. C. (2002). Stock market volatility, excess returns, and the role of investor sentiment. Journal of Banking & Finance26, 2277-2299       
Lei, Y.  (2005). the trading volume trend, investor sentiment, and stock returns". LSU Doctoral Dissertations. Available at
Lin, M. (2009). Sentiment on cross-sectional stock returns and volatility. Investment Management and Financial Innovations, 6(1), 54-75. …
Lin, M., Sias, R., & Wei, Z. (2019). The survival of noise traders: Evidence from peer-to-peer lending. Research Paper No. 18-22, Georgia: Georgia Tech Scheller College of Business. Information Systems & Economics E-Journal, …, 18–22.
Ling, D. C., & Naranjo, A., & Scheick, B. (2010). Investor sentiment and asset pricing in public and private markets [Paper presentation]. 46th Annual AREUEA Conference.
Liu, H., & Shi, J. (2013). Applying ARMA-GARCH approaches to forecasting short-term electricity prices. Energy Economics, 37, 152-166.
Liu, S. (2015). Investor sentiment and stock market liquidity. Journal of Behavioral Finance16(1), 51-67.
Lu, X. & Lai, K. (2012). Relationship between stock indices and investors’ sentiment index in Chinese financial market. System Engineering Theory and Practice, 32(3), 621–629.
Mahesh, K. T. (2005). Forecasting exchange rate: A univariate out of sample approach (Box-Jenkins Methodology). The IUP Journal of Bank Management, 4, 60-74.
Maitra, D., & Dash, S. R. (2017). Sentiment and stock market volatility revisited: A time–frequency domain approach. Journal of Behavioral and Experimental Finance, 15, 74–91.
Mazviona, B. W. (2015). Measuring investor sentiment on the Zimbawe stock exchange. Asian Journal of Economic Modelling, 3(2), 21-32.
Naik, P. K., & Padhi, P. (2016). Investor sentiment, stock market returns and volatility: Evidence from national stock exchange of India. International Journal of Management Practice, 9(3), 213–237.
Nasiri, M., Sarraf, F., Nourollahzadeh, N., Hamidian, M., & Noorifard, Y. (2021). Modeling asset pricing using behavioral variables: Fama-Macbeth approach. Iranian Journal of Management Studies, 14(3), 547-564.
Nelson, D. B.  (1991), Conditional heteroscedasticity in asset returns: A new approach. Econometrica59(2), 347-370
Nofsinger, J. R., & Sias, R. W. (1999). Herding and feedback trading by institutional and individual investors. Journal of Finance, 54(6), 2263–2295.
Pei-En, L. (2019). The empirical study of investor sentiment on stock return prediction. International Journal of Economics and Financial Issues, 9(2), 119-124
Piccoli, P., da Costa, N.C.A., Jr., da Silva, W.V. & Cruz, J.A.W. (2018), Investor sentiment and the risk–return tradeoff in the Brazilian market. Accounting and Finance, 58 (1), 599-618.
Podolski, E., Kalev, P. S., & Duong, H. N. (2009). Deafened by noise: Do noise traders affect volatility and returns? [Paper presentation]. 21st Australasian Finance and Banking Conference.
Rahman, M. A., Shien, L. K., & Sadique, M. S. (2013). Swings in sentiment and stock returns: Evidence from a frontier market. International Journal of Trade, Economics & Finance, 4(6), 347–363.
Rupande, L., Muguto, H. T., & Muzindutsi, P. (2019). Investor sentiment and stock return volatility: Evidence from the Johannesburg Stock Exchange. Cogent Economics & Finance, 7(1),1-16…
Schmeling, M. (2007). Institutional and individual sentiment: Smart money and noise trader risk? International Journal of Forecasting, 23(1), 127–145.  
Schneller, D., Heiden, S., & Hamid, A. (2018). Home is where you know your volatility: Local investor sentiment and stock market volatility. German Economic Review, 19(2), 209-236.
Shefrin, H. M., & Statman, M. (1984). Explaining investor preference for cash dividends. Journal of Financial Economics, 13(2), 253–282. 
Shen, J., Yu, J., & Zhao, S. (2017). Investor sentiment and economic forces. Journal of Monetary Economics, 86(1), 1–21. 
Shleifer, A., & Summers, L. H. (1990). The noise trader approach to finance. Journal of Economic Perspectives, 4(2), 19–33.
Shleifer, A., Vishny, R. (1997). The limits of arbitrage. Journal of Finance52, 35–55.
Simon, S., & Violet, L. (2015). On the relationship between investor sentiment, VIX and trading volume. Risk Governance and Control: Financial Markets & Institutions, 5 (4), 114-122. … 
Tan, Z., Zhang, J., Wang, J., & Xu, J. (2010). Day-ahead electricity price forecasting using wavelet transform combined with ARIMA and GARCH models. Applied Energy, 87, 3603-3610.
Tetlock, P. C. (2007). Giving content to investor sentiment: The role of media in the stock market. Journal of Finance, 62(3), 1139–1168.
Uygur, U., & Tas, O.  (2012). Modeling the effects of investor sentiment and conditional volatility in international stock markets. Journal of Applied Finance & Banking2(5), 239-260.
Verma, R., & Soydemir, G. (2009). The impact of individual and institutional investor sentiment on the market price of risk. Quarterly Review of Economics & Finance, 49(3), 1129–1145.
Verma, R., & Verma, P.  (2006). Noise trading and stock market volatility. Journal of Multinational Financial Management17(3), 231-243.
Wang, F. (2009). Informed arbitrage with speculative noise trading. Journal of Banking & Finance, 34, 304-313.
Willman, P., Fenton, M., Nicholson, N., & Soane, E. (2006). Noise trading and the management of operational risk: Firms, traders and irrationality in financial markets. Journal of Management Studies, 43(6), 1357-1374
Ya’Cob, N. (2019). Have sentiments influenced malaysia’s stock market volatility during the 2008 crisis? Journal of Reviews on Global Economics, Lifescience Global, 8, 755-766.
Yang, Y., & Copeland, L. (2014). Cardiff Economics Working Papers E2014/12: The effects of sentiment on market return and volatility and the cross-sectional risk premium of sentiment-affected volatility. Cardiff University, Cardiff Business School, Economics Section.
Yaziz S. R., Azizan N. A., Zakaria R., & Ahmad M. H. (2013). The performance of hybrid ARIMA-GARCH modeling in forecasting gold price [Paper presentation]. 20th International Congress on Modelling and Simulation, Adelaide, Australia.
Yu J., Huang, H. H., & Hsu, S. W.  (2014). Investor sentiment influence on the risk-reward relation in the Taiwan stock market. Emerging Markets Finance and Trade, 50, 174-188.
Yu, J., & Yuan, Y. (2011). Investor Sentiment and the Mean-Variance Relation. Journal of Financial Economics, 100 (2), 367-381.
Zhou Zou, B., He, D., & Sun, Z. (2006). Traffic predictability based on ARIMA/GARCH model. In: Nejat Ince, A., Topuz, E. (eds) Modeling and Simulation Tools for Emerging Telecommunication Networks. Springer, Boston, MA, 101-121 and Simulation Tools for Emerging Telecommunication Networks, …, 101-121.