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...

this paper attempts to compare the forecasting performance of the arima model and hybrid arma-garch models by using daily data of the iran’s exchange rate against the u.s. dollar (irr/usd) for the period of 20 march 2014 to 20 june 2015. the period of 20 march 2014 to 19 april 2015 was used to build the model while remaining data were used to do out of sample forecasting and check the forecasti...

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...

the research problem investigated in this paper is modeling volatility and analyzing risk and return’s relationship in tehran stock exchange using garch-family models including garch(1,1), garch(2,2), egarch(1,1), pgarch(1,1), tgarch(1,1), garch(1,1)-m and cgarch(1,1). using the daily returns of tehran stock exchange companies, we focused on two portfolios of all the companies during a 10-year-...

importance of risk and uncertainty in financial markets became more apparent after financial crisis in 2007. volatility is the most important measure of risk in financial markets. thus, modeling volatility of financial markets is one of the important issues in finance and economics. in this paper first we tried to specify key features of volatility of daily returns of tehran stock exchange pric...

A key problem in financial econometrics is the modeling, estimation and forecasting of conditional return volatility and correlation. Having accurate forecasting models for conditional volatility and correlation is important for accurate derivatives pricing, risk management and asset allocation decisions. It is well known that conditional volatility and correlation are highly predictable. An in...

Modeling and forecasting volatility of capital markets has been important area of inquiry and research in financial economics with the recognition of time-varying volatility, volatility clusturing, and asymmetric response of volatility to market movements. Given the anticipated growth of the Nepalese stock market and increasing interest of investors towards investment in Nepalese stock market, ...

In recent years, authors have focused on modeling and forecasting volatility in financial series it is crucial for the characterization of markets, portfolio optimization and asset valuation. One of the most used methods to forecast market volatility is the linear regression. Nonetheless, the errors in prediction using this approach are often quite high. Hence, continued research is conducted t...

• So far we have maintained the assumption of iid data in the estimation of distributions and risk measures. However, this assumption does not hold for financial data, which are known to be intertemporally dependent, especially in the volatility. Estimation of risk measures under the assumption of iid can be viewed as unconditional estimates. In contrast, we can model the intertemporal dependen...

F orecasting the volatility of a financial asset has wide implications in finance. Conditional variance extracted from the GARCH framework could be a suitable proxy of financial asset volatility. Option pricing, portfolio optimization, and risk management are examples of implications of conditional variance forecasting. One of the most recent methods of volatility forecasting is Real...