The effect of size and intensity of price jumps on forecasting index volatility in Tehran Stock Exchange

Subject Areas : Journal of Investment Knowledge

mohsen rajab boloukat ¹ (PhD Student of Financial Management, South Tehran Branch, Islamic Azad University, Tehran, Iran)
ali baghani ² (Assistant Professor, Department of Accounting, South Tehran Branch, Islamic Azad University, Tehran, Iran)
Ali Najafi Moghadam ³ (Assistant Professor, Department of Accounting, South Tehran Branch, Islamic Azad University, Tehran, Iran)
fatemeh sarraf ⁴ (Assistant Professor, Department of Accounting, South Tehran Branch, Islamic Azad University, Tehran, Iran)
norouz noorolahzadeh ⁵ (Assistant Professor, Department of Accounting, South Tehran Branch, Islamic Azad University, Tehran, Iran)

Received: 2021-04-14 Accepted : 2021-06-22 Published : 2024-09-22

Keywords: Forecasting, realized volatility, Jump, Hawkes process,

Abstract :

It is very important to distinguish how the volatility in the return of assets occur. For this reason, in recent years, realized volatility and frequencies of daily volatility recognition studies have been developed. This study uses stock prices of 30 big companies of Tehran Stock Exchange during the years 1390 (2011) to 1394 (2016) and calculates the realized stock volatility during trading days using the HAR-CJ model to examine the effect of size and intensity of price jumps in predicting index volatility. The results showed that the development of HAR-CJ and HAR-RV-CJ models using the size and intensity of jump did not have a significant effect on improving the index volatility prediction but, to a small extent, the model prediction performance Adjusts for index volatility. Also, using intraday jumps instead of daily jumps, does not improve the performance of the prediction model.

References:

• پوریعقوبی هادی، اشرفی یکتا (1399)، سرایت­پذیری تلاطم بازده میان صنایع مختلف بازار سرمایه ایران، فصلنامه علمی پژوهشی دانش سرمایه­گذاری، 9(34)، 293-277.


• دوستیان رحمان و همکاران (1400)، سرایت­پذیری تلاطم شرطی بازده در بانکهای پذیرفته شده در بورس اوراق بهادار، فصلنامه علمی پژوهشی دانش سرمایه­گذاری، 10(37)، 178-159.


• قاضی فینی سیدرضا، پناهیان حسین (1398)، پیش بینی و مدل­سازی تلاطم بازدهی سهام در بورس اوراق بهادار تهران با استفاده از مدل­های GARCH، فصلنامه علمی تحقیقات حسابداری و حسابرسی، 11(43)، 70-55.


• پاکیزه، کامران، (1390)، تلاطم و بازده (شواهدی از بورس اوراق بهادار تهران و بورس های بین الملل) فصلنامه علمی پژوهشی تحقیقات مدل سازی اقتصادی ، شماره دوم.


• Andersen, T. G., Bollerslev, T, and F.X. Diebold and Labys, P. (2003), The distribution of exchange rate volatility, Journal of the American Statistical Association, vol. 96, pp. 42–55, 2003.


• Andersen, T. G., Bollerslev, T., Dobrev, D. )2007(, No-arbitrage semimartingale restrictions for continuous-time volatility models subject to leverage effects, jumps and i.i.d. noise: Theory and testable distributional implications. Journal of Econometrics 138 (1), 125-180


• Andersen, T. G., Bollerslev, T, and F.X. Diebold. (2007a), Roughing it up: Including jump components in the measurement, modelling and forecasting of return volatility. Review of Economics and Statistics, 89:701-720.


• Andersen, T. G., Bollerslev, T, and Dobrev, D. (2007b), No-arbitrage semi-martingale restrictions for ncontinuous-time volatility models subject to leverage e_ects, jumps and i.i.d. noise: Theory and testable distributional implications. Journal of Econometrics 138: 125–80


• Andersen, T.G., Bollerslev, T, Dobrev, D., (2007c), No-arbitrage semi-martingale restrictions for continuous-time volatility models subject to leverage effects, jumps and i.i.d. noise: Theory and testable distributional implications. Journal of Econometrics 138, 125–180.


• Barndorff-Nielsen, Ole E., and Shephard, N. (2004), Power and bipower variation with stochastic volatility and jumps. Journal of Financial Econometrics 2: 1–37.


• Barndorff-Nielsen, Ole E., and Shephard, N. (2006), Econometrics of testing for jumps in financial economics using bipower variation. Journal of Financial Econometrics 4: 1–30.


• Bollerslev, T, and Ghysels, E. (1997), Periodic autoregressive conditional heteroscedasticity. Journal of Business and Economic Statistics, 14:139–151.


• Buncic, D; I.M. Gisler, K, (2017), The role of Jumps and Leverage in forecasting Volatility in International Equity Markets, Journal of International Money and Finance VOL August 9.


• Corsi, F.(2009), A Simple Approximate Long-memory Model of Realized Volatility, Journal of Financial Econometrics, Vol. 7, 174-196.


• Corsi, Fulvio and Roberto Ren´o (2012), Discrete-time volatility forecasting with persistent leverage effect and the link with continuous-time volatility modeling, Journal of Business and Economic Statistics, 30(3), 368–380.


• Délèze, F. Hussain, S.M, (2013), Information Arrival, Jumps and Cojumps in European Financial Markets: Evidence using tick by tick data.


• Diebold F.X. and Mariano, R.S (1995), Comparing predictive accuracy. Journal of Business and Economics Statistics, 13:253–263.


• Jurdi, D.J., (2020), Intraday Jumps, Liquidity, and U.S. Macroeconomic News: Evidence from Exchange Traded Funds, Journal of Risk and Financial Management, 2020, 13, 118


• Lahaye, J., Laurent, S., Neely, C.J., (2011), Jumps, Cojumps and Macro Announcements. Journal of Applied Econometrics 26, 893–921.


• Lee, S. S., Mykland, P.A., (2008), Jumps in financial markets: A new nonparametric test and jump dynamics. Review of Financial Studies 21 (6), 2535-2563.


• Műller, U. Dacorogna, M. Davé, R. Olsen, R. Pietet,O. and Weizsacker, J. von. (1997), Volatilities of different time resolutions – analysing the dynamics of market components, Journal of Empirical Finance , vol. 4, pp. 213–239.


• Patton, A. (2011), Volatility forecast comparison using imperfect volatility proxies. Journal of Econometrics, 160:246–256.


• Seda,P. (2012), Performance of Heterogeneous Autoregressive Models of Realized Volatility: Evidence from U.S. Stock Market, International Journal of Economics and Management Engineering, Vol:6, No:12, 2012


• West, K.D. (1996), Asymptotic inference about predictive ability. Econometrica, 64:1067–1084.