The skewness in physical distributions of equity index returns and the implied volatility skew in the risk neutral measure are subjects of extensive academic research. Much attention is now being focused on models that are able to capture time-varying conditional skewness and kurtosis. For this reason normal mixture GARCH(1,1) models have become very popular in financial econometrics. We introd...

Forecasting Value-at-Risk (VaR) for financial portfolios is a staggering task in financial risk management. The turmoil in financial markets as observed since September 2008 called for more complex VaR models, as ”standard” VaR approaches failed to anticipate the collective market movements faced during the financial crisis. Hence, recent research on portfolio management mainly focussed on mode...

In this study, the volatility of two Asian stock markets, Bursa Malaysia and Singapore Exchange, is estimated. The analysis used data on daily closing prices indices respective markets between July 1, 2019 August 31, 2020. sample split into subsample periods: Pre-COVID-19 pandemic during COVID-19 pandemic. We estimated a standard GARCH, GARCH-M, TGARCH, EGARCH PGARCH model for each subsample. c...

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...

Related commodity markets have two characteristics: (i) they may be expected to follow similar volatility processes; (ii) such markets are frequently represented by a market aggregate or index. Indices are used to represent the performance and aggregate time series properties of a group of markets. An important issue regarding the time series properties of an index is how the index reflects the...

After the so-called Asia crisis in the summer of 1997 the nancial markets were shaken by increased volatility transmission around the world. Therefore, in this paper we will analyse the daily exchange rates in New York, Germany, and Japan for the period of 2 years (June 21, 1996 to June 22, 1998). We estimate a VAR-GARCH in mean model and estimate the multivariate volatility e ects between the ...

This paper considers a multivariate t version of the Gaussian dynamic conditional correlation (DCC) model proposed by Engle (2002), and suggests the use of devolatized returns computed as returns standardized by realized volatilities rather than by GARCH type volatility estimates. The t-DCC estimation procedure is applied to a portfolio of daily returns on currency futures, government bonds and...

S tock returns of companies listed on the stock exchange is one of the most important criteria in assessing the macroeconomic. This study investigates the effect of exchange rate Volatility on the stock exchange Returns of D8 countries. It takes monthly data during the period (2008:1-2015:6) constituting 90 observations. At first we used Panel-GARCH model to estimate Exchange Rate Vo...

Long memory (long-term dependence) of volatility counts as one of the ubiquitous stylized facts of financial data. Inspired by the long memory property, multifractal processes have recently been introduced as a new tool for modeling financial time series. In this paper, we propose a parsimonious version of a bivariate multifractal model and estimate its parameters via both maximum likelihood an...

In this chapter we use particle filtering methods to estimate volatility and examine volatility dynamics for three financial time series during the early part of the current credit crisis. We compare estimates from a pure stochastic volatility model, a stochastic volatility model with jumps and a Garch model to each other and to the market volatilities implied by actual option prices. Our three...