Modeling Stock Return Volatility Using Symmetric and Asymmetric Nonlinear State Space Models: Case of Tehran Stock Market

Authors

Abstract:

Volatility is a measure of uncertainty that plays a central role in financial theory, risk management, and pricing authority. Turbulence is the conditional variance of changes in asset prices that is not directly observable and is considered a hidden variable that is indirectly calculated using some approximations. To do this, two general approaches are presented in the literature of financial economics for modeling and calculating volatility. In the first approach, conditional variance is modeled as a function of the square of the past shocks of return on assets. Models of the GARCH type fall into this category. In the alternative approach, volatility is assumed to be a random variable, which evolves using nonlinear patterns of Gaussian state space. This type of model is known as Stochastic Volatility (SV).  Because, SV models include two kinds of noise processes, one for observations and another for hidden, volatility, thus, they are more realistic and more flexible in calculating volatility than GARCH type.  This study attempts to analyze the volatility in stock returns of 50 companies, which are active in Tehran Stock Market using symmetric and asymmetric methods of Stochastic Volatility, which is different in the presence of leverage effect. The empirical comparison of these two models by calculating the posterior probability of accuracy of each model using the MCMC Bayesian method represents a significant advantage of the ASV model. The results in both symmetric and asymmetric methods represent the very high stability of the volatility generated by the shocks on stock returns; therefore, the Tehran Stock market changes in returns due to this high sustainability will be predictable.

Upgrade to premium to download articles

Sign up to access the full text

Already have an account?login

similar resources

Nonlinear Model Improves Stock Return Out of Sample Forecasting (Case Study: United State Stock Market)

Improving out-of-sample forecasting is one of the main issues in financial research. Previous studies have achieved this objective by increasing the number of input variables or changing the kind of input variables. Changing the forecasting model is another possible approach to improve out-of-sample forecasting. Most researches have focused on linear models, while few have studied nonlinear mod...

full text

Empirical Study on Stock Return Volatility in China's Stock Market

Wave of financial globalization and financial innovation has brought great changes of the international financial market, the traditional measuring method is not well adapt to these new changes, this requires the presence of the new analysis method. This article will link function to copulas connect theory is introduced into the financial analysis. In this paper, the author makes an empirical a...

full text

survey the asymmetric correlation between stock return, trading volume and volatility of tehran stock exchange market (dcc-garch approach)

in this research the asymmetric and non-linear correlation between the market returns and trading volume variables has modeled with the dcc-garch approach; and the impacts of market shocks, weekend and calendar effects on the market returns and trading volume are surveyed. the estimation results of parameters of the model by the maximum likelihood method show that previous day’s market return h...

full text

Modeling Stock Market Volatility Using Univariate GARCH Models: Evidence from Bangladesh

This paper investigates the nature of volatility characteristics of stock returns in the Bangladesh stock markets employing daily all share price index return data of Dhaka Stock Exchange (DSE) and Chittagong Stock Exchange (CSE) from 02 January 1993 to 27 January 2013 and 01 January 2004 to 20 August 2015 respectively.  Furthermore, the study explores the adequate volatility model for the stoc...

full text

conditional copula-garch methods for value at risk of portfolio: the case of tehran stock exchange market

ارزش در معرض ریسک یکی از مهمترین معیارهای اندازه گیری ریسک در بنگاه های اقتصادی می باشد. برآورد دقیق ارزش در معرض ریسک موضوع بسیارمهمی می باشد و انحراف از آن می تواند موجب ورشکستگی و یا عدم تخصیص بهینه منابع یک بنگاه گردد. هدف اصلی این مطالعه بررسی کارایی روش copula-garch شرطی در برآورد ارزش در معرض ریسک پرتفویی متشکل از دو سهام می باشد و ارزش در معرض ریسک بدست آمده با روشهای سنتی برآورد ارزش د...

Effect of Oil Price Volatility and Petroleum Bloomberg Index on Stock Market Returns of Tehran Stock Exchange Using EGARCH Model

The present research aims to evaluate impacts of crude oil price return index, Bloomberg Petroleum Index and Bloomberg energy index on stock market returns of 121 companies listed in Tehran stock exchange in a 10 years' period from early 2006 to April 2016. First, explanatory variables were aligned with petroleum products index mostly due to application of dollar data. Subsequently, to check va...

full text

My Resources

Save resource for easier access later

Save to my library Already added to my library

{@ msg_add @}


Journal title

volume 11  issue 41

pages  197- 229

publication date 2020-12

By following a journal you will be notified via email when a new issue of this journal is published.

Keywords

No Keywords

Hosted on Doprax cloud platform doprax.com

copyright © 2015-2023