The volatility clustering often seen in financial data has increased the interest of researchers in applying good models to measure and forecast stock returns. This paper aims to model the volatility for daily and weekly returns of the Portuguese Stock Index PSI-20. By using simple GARCH, GARCH-M, Exponential GARCH (EGARCH) and Threshold ARCH (TARCH) models, we find support that there are significant asymmetric shocks to volatility in the daily stock returns, but not in the weekly stock returns. We also find that some weekly returns time series properties are substantially different from properties of daily returns, and the persistence in conditional volatility is different for some of the sub-periods referred. Finally, we compare the fo...
Volatility plays a key role in asset and portfolio management and derivatives pricing. As such, accu...
The main motive of this study is to investigate the use of ARCH model for forecasting volatility of ...
Volatility forecasting in an important area of research in financial markets and immense effort expe...
The volatility clustering often seen in financial data has increased the interest of researchers in ...
The volatility clustering often seen in financial data has increased the interest of researchers in ...
Modelling and forecasting stock market volatility has been one of the most important topics in finan...
The aim of this work project is to find a model that is able to accurately forecast the daily Value-...
Engle (1982) introduced the autoregressive conditionally heteroskedastic model for quantifying the c...
In this paper we apply volatility forecasting models based on past measures of risk and some ARCH cl...
Volatility is arguably one of the most important measures in financial economics since it is often u...
This paper focuses on the performance of various Garch models, were Arch model s not dismissed in te...
We tested different GARCH models in modeling the volatility of stock returns in London Stock Exchang...
In this paper we aim to test the usefulness of two variants of Generalized Autoregressive Conditiona...
This paper empirically investigates the volatility pattern of Indian stock market based on time seri...
This paper studies the performance of GARCH model and its modifications, using the rate of returns f...
Volatility plays a key role in asset and portfolio management and derivatives pricing. As such, accu...
The main motive of this study is to investigate the use of ARCH model for forecasting volatility of ...
Volatility forecasting in an important area of research in financial markets and immense effort expe...
The volatility clustering often seen in financial data has increased the interest of researchers in ...
The volatility clustering often seen in financial data has increased the interest of researchers in ...
Modelling and forecasting stock market volatility has been one of the most important topics in finan...
The aim of this work project is to find a model that is able to accurately forecast the daily Value-...
Engle (1982) introduced the autoregressive conditionally heteroskedastic model for quantifying the c...
In this paper we apply volatility forecasting models based on past measures of risk and some ARCH cl...
Volatility is arguably one of the most important measures in financial economics since it is often u...
This paper focuses on the performance of various Garch models, were Arch model s not dismissed in te...
We tested different GARCH models in modeling the volatility of stock returns in London Stock Exchang...
In this paper we aim to test the usefulness of two variants of Generalized Autoregressive Conditiona...
This paper empirically investigates the volatility pattern of Indian stock market based on time seri...
This paper studies the performance of GARCH model and its modifications, using the rate of returns f...
Volatility plays a key role in asset and portfolio management and derivatives pricing. As such, accu...
The main motive of this study is to investigate the use of ARCH model for forecasting volatility of ...
Volatility forecasting in an important area of research in financial markets and immense effort expe...