Document Type : Research Article


1 Postdoc of Finance, Faculty of Economics, University of Tehran, Tehran, Iran

2 Ph.D. in Financial Management, Faculty of Management, University of Tehran, Tehran, Iran

3 Postdoc of Finance, Hankuk University of Foreign Studies, Seoul, South Korea


According to the literature on risk, bad news induces higher volatility than good news. Although parametric procedures used for conditional variance modeling are associated with model risk, this may affect the volatility and conditional value at risk estimation process either due to estimation or misspecification risks. For inferring non-linear financial time series, various parametric and non-parametric models are generally used. Since the leverage effect refers to the generally negative correlation between an asset return and its volatility, models such as GJRGARCH and EGARCH have been designed to model leverage effects. However, in some cases, like the Tehran Stock Exchange, the results are different in comparison with some famous stock exchanges such as the S&P500 index of the New York Stock Exchange and the DAX30 index of the Frankfurt Stock Exchange. The purpose of this study is to show this difference and introduce and model the "reversed leverage effect bias" in the indices and stocks in the Tehran Stock Exchange.


[1] Abdelaal, M. A. (2011). Modelling and Forecasting Time Varying Stock Return Volatility in the Egyptian Stock Market. International Research Journal of Finance and Economics, 78, 96{113.
[2] Andreea-Cristina P, Stelian S. (2017). Empirical Results of Modeling EUR/RON Exchange Rate using ARCH, GARCH, EGARCH, TARCH and PARCH models. Romanian Statistical Review, 65 (1), 57{72.
[3] Arbel, A. and P. J. Strebel, (1983). Pay Attention to Neglected Firms, Journal of Portfolio Management, 9, 37{42.
[4] Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroscedasticity. Journal of Econometrics, 31 (3), PP. 307-327.
[5] Cao, L and F.E.H. Tay, (2001). Financial forecasting using support vector machines, Neural Comput. Appl., 10, 184{192.
[6] Coffie, W., Tackie, G., Bedi, I. and F.Aboagye-Otchere. (2017). Alternative Models for the Conditional Hetroscedasticity and the Predictive Accuracy of variance Models-Emprical Evidence from East and North Africa Stock Markets, Journal of Accounting and Finance, 17(2).
[7] Conrad, J., Cornell, B., Landsman, W.R., (2002). When is bad news really bad news?, Journal of Finance, 57(6), 2507{2532.
[8] De Bondt, W. and Thaler, R. (1985). Does the stock market overreact?, Journal of Finance, 40 (30), 793{805.
[9] Dritsaki, Ch. (2017). An empirical Evaluation in GARCH Volatility Modeling: Evidence from the Stockholm Stock Exchange. Journal of Mathematical Finance,7, 366{390.
[10] Fama, E. (1970), Efficient Capital Markets: A Review of Theory and Empirical Work, Journal of Finance, 25, 383-417.
[11] Finnerty, J., (1976). Insiders and market efficiency. Journal of Finance, 31,1141{1148.
[12] Friedmann, R., Sanddorf-Kohle, W.G, (2002). Volatility Clustering and Non-
trading Days in Chinese Stock Markets. Journal of Economics and Business,5(4), P. 193217.
[13] Glosten, L., Jagannathan, R. and Runke, D, (1993). Relationship between the expected value and the volatility of the nominal excess return on stocks.
[14] Gultekin,M.N. and Gultekin,N.B, (1983). Stock market seasonality: International evidence. Journal of Finance Economics, 12, 469-482.
[15] Guo,Z. (2017a). Models with short-term variations and long-term dynamics in risk management of commodity derivatives. ZBW-Leibniz Information Centre for Economics. Standard-Nutzungsbedingungen: Die Dokumente auf EconStor durfen.
[16] Guo, Z.-Y. (2017b). GARCH models with fat-tailed distributions and the Hong Kong stock market returns. International Journal of Business and Management,12(9).
[17] Henry, O., (1988). Modelling the Asymmetry of Stock Market Volatility. Applied Financial Economics, 8(2), 145{153.
[18] Hirshleifer, D. (2001). Investor psychology and asset pricing. The Journal of Finance, 56 (4), 1533{98.
[19] Kahneman, D.; Tversky, A. (1973). On the psychology of prediction. Psycholog-ical Review, 80 (4), 237{251.
[20] keim.d. (1985). Dividend yield and stock returns. J Fin Econ, 14, 473-489.
[21] Kothary, S.P., Shu, S., Wysocki, P., (2009). Do managers withhold bad news?, Journal of Accounting Research, 47(1),241-276.
[22] Ikenberry, D., Rankine, G., & Stice, E. (1996). What do stock splits really signal?, Journal of Financial and Quantitative Analysis, 31(3), 357-374.
[23] Intaz, A., Subhrabaran D. & Niranjan R. (2016). Stock Market Volatility, Firm Size and Returns: A Study of Automobile Sector of National Stock Exchange in India, INTERNATIONAL JOURNAL OF INNOVATIVE RESEARCH & DE- VELOPMENT, 5(4), 272{281.
[24] Leuz, C., Schrand, C., (2009). Disclosure and the cost of capital: Evidence from rms response to the Enron shock. SSRN e-library.
[25] Liu, H., Hung, J. (2010). Forecasting S&P-100 stock index volatility: The role of volatility asymmetry and distributional assumption in GARCH models, Expert Systems with Applications, 37(7), 4928-4934.
[26] Litzenberger, R. and Krishna R. (1982) .The Effects of Dividends on Common Stock Prices: Tax Effects or Information Effects?, Journal of Finance, 37, 429-443.
[27] Mehrara, M., Abduli Q., (2008).The role of good and bad news in the Iran stock returns volatilities, Iranian Economic Researches, 8(26), 25-40.
[28] Nelson, D.B. and Cao, C.Q. (1992). Inequality Constraints in the Univariate GARCH Model, Journal of Business and Economic Statistics, 10 (3), pp. 229-235.
[29] Nelson, D.B., (1991). Conditional heteroscedasticity in Asset Returns: A New Approach. Econometrica, 59(3), 347370.
[30] Pagan, A.R., Schwert, G.W., (1990). Alternative Models for Conditional Stock Volatility. Journal of Econometrics, 45(6),267290.
[31] Pallier, Gerry; Wilkinson, Rebecca; Danthiir, Vanessa; Kleitman, Sabina; Knezevic, Goran; Stankov, Lazar; Roberts, Richard D. (2002). The Role of Individual Differences in the Accuracy of Con dence Judgments. The Journal of General Psychology, 129 (3), 257299.
[32] Sarkar, S., Banerjee, A. (2006). Modeling daily volatility of the Indian stock market using intra-day data. Indian Institute of Management Calcutta, Working Paper Series, 1{32.
[33] Schwert, G.W., (1989), Why Does Stock Market Volatility Change Over Time?,Journal of Finanace, 44, 1115-1153.
[34] Taylor, S. J., (1986). Modelling  nancial time series. New York: Wiley. Telmoudi, F., EL Ghourabi, M., & Limam, M. (2016). On conditional risk estimation considering model risk, Journal of Applied Statistics, 43(8), 1386-1399.
[35] Tripathy, N., Prakash, A. and Arora, M. (2009). Trading Volume, Volatility and Leverage, A Dynamic Analysis of the Indian Stock Market.
[36] Tversky, A.; Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases. Science, 185.
[37] Zhang , x. (2006). Modeling and simulation of value at risk in the  nance Market area. louisiana tech university, 276-280.
[38] Zi-Yi Guo. (2017). GARCH Models with Fat-Tailed Distributions and the Hong Kong Stock Market Returns, International Journal of Business and Management,12(9).
[39] Black, F., (1976). Studies of stock price volatility changes, In: Proceedings of the 1976 Meetings of the American Statistical Association, 171{181.
[40] Christie, A. A., (1982). The stochastic behavior of common stock variances: Value, leverage and interest rate effects, Journal of Financial Economics, 10,407{432.
[41] Nelson, D. B., (1991). Conditional heteroskedasticity in asset returns: A new approach, Econometrica, 59, 347{370.
[42] Engle, R. F., Ng, V. K., (1993). Measuring and testing the impact of news on volatility. The Journal of Finance, 48,1749{1778.
[43] Yu, J., (2005). On leverage in a stochastic volatility model, Journal of Econometrics, 127, 165{178.