The paper aims to model and forecast the volatility in the stocks traded at the Karachi Stock Exchange before and during the recent financial crisis using the GARCH, EGARCH and GJR-GARCH models. We find the stock return volatility to be characterized by clustering and displaying asymmetries. Results point to the capability of the EGARCH(1,1) model at forecasting for both periods lending support to the use of GARCH family of models for emerging markets during crisis. We find evidence for a synthetically constructed index based on trading volume capturing the volatility structure of the market as well as that based on market capitalization which has important implications for investors.Rad ima za cilj stvoriti model i predvidjeti volatilnost ...
In this paper, The GARCH (1,1) model is presented and some results for the existence and uniqu...
Abstract: This study looks into the relationship between stock returns and volatility in South Afric...
This study estimates the volatility of Pakistani and leading foreign stock markets. Daily data are u...
This paper compares and estimates standard and asymmetric GARCH models with daily returns data of th...
We investigate the daily volatility and Value-at-Risk (VaR) forecasts for the Karachi Stock Exchange...
We investigate the daily volatility and Value-at-Risk (VaR) forecasts for the Karachi Stock Exchange...
Volatility is unobservable and an indispensible contribution to the pricing models and for risk mana...
This paper examines sector specific volatility in order to determine how different sectors respond t...
Engle (1982) introduced the autoregressive conditionally heteroskedastic model for quantifying the c...
This paper examines sector specific volatility in order to determine how different sectors respond t...
Analysis of time series is used to develop simple models which can forecast, interpret, and analyze ...
Economic decisions are modeled based on perceived distribution of the random variables in the future...
This study aimed at understanding the volatility of Dhaka Stock Exchange (DSE). The daily and monthl...
AbstractThis paper models time-varying volatility in one of the Indian main stock markets, namely, t...
The modelling of market returns can be especially problematical in emerging and frontier financial m...
In this paper, The GARCH (1,1) model is presented and some results for the existence and uniqu...
Abstract: This study looks into the relationship between stock returns and volatility in South Afric...
This study estimates the volatility of Pakistani and leading foreign stock markets. Daily data are u...
This paper compares and estimates standard and asymmetric GARCH models with daily returns data of th...
We investigate the daily volatility and Value-at-Risk (VaR) forecasts for the Karachi Stock Exchange...
We investigate the daily volatility and Value-at-Risk (VaR) forecasts for the Karachi Stock Exchange...
Volatility is unobservable and an indispensible contribution to the pricing models and for risk mana...
This paper examines sector specific volatility in order to determine how different sectors respond t...
Engle (1982) introduced the autoregressive conditionally heteroskedastic model for quantifying the c...
This paper examines sector specific volatility in order to determine how different sectors respond t...
Analysis of time series is used to develop simple models which can forecast, interpret, and analyze ...
Economic decisions are modeled based on perceived distribution of the random variables in the future...
This study aimed at understanding the volatility of Dhaka Stock Exchange (DSE). The daily and monthl...
AbstractThis paper models time-varying volatility in one of the Indian main stock markets, namely, t...
The modelling of market returns can be especially problematical in emerging and frontier financial m...
In this paper, The GARCH (1,1) model is presented and some results for the existence and uniqu...
Abstract: This study looks into the relationship between stock returns and volatility in South Afric...
This study estimates the volatility of Pakistani and leading foreign stock markets. Daily data are u...