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...

We decompose UK market volatility into shortand long-run components using EGARCH component model and examine the cross-sectional prices of the two components. Our empirical results suggest that these two components are significantly priced in the cross-section and the negative risk premia are consistent with the existing literature. The Fama-French three-factor model is improved by the inclusio...

Data finansial yang mengikuti deret waktu memiliki keragaman atau volatilitas setiap waktunya tidak konstan. Keadaan ini disebut sebagai heteroskedastisitas. Metode dapat menyelesaikan masalah tersebut adalah Autoregressive Conditional Heteroscedasticity (ARCH)/Generalized (GARCH). Namun, ARCH/GARCH mengatasi beberapa kasus seperti perbedaan dalam nilai leverage effect. Sehingga dilakukan pemod...

A comprehensive comparison of the volatility predictive abilities different classes time-varying models is considered. The include exponential GARCH (EGARCH) and stochastic (SV) using daily returns, heterogeneous autoregressive (HAR) model realized (RV) EGARCH (REGARCH) SV (RSV) both. All are extended to accommodate well-known phenomenon in stock markets a negative correlation between today’s r...

During the past decades, seasonal autoregressive integrated moving average (SARIMA) had become one of a prevalent linear models in time series and forecasting. Empirical research advocated that forecasting with non-linear can be an encouraging alternative to traditional models. Linear are often compared mixed conclusions terms superiority performance. Therefore, aim this study is build early wa...

abstract: with regard to the basel committee’s emphasis on the necessity of using 10-day value-at-risk (var) internal models in order to determine minimum market risk capital requirements, and downsides of the square-root-of-time rule, our purpose is to produce more accurate forecasts of the multi-period var using sixteen models for three stock indices, the tepix, nasdaq, and ftse. the results,...

This paper investigates the issue of co-movement and interaction among the monetary, foreign exchange and stock markets by employing the data from China’s financial markets. Based on the ICA-EGARCH-M model, we explore the volatility spillover effects so as to illustrate the overall co-movements across financial markets. Furthermore, in order to observe the multi-market dynamic relationship vari...

This paper focuses on the selection and comparison of alternative non-nested volatility models. We review the traditional in-sample methods commonly applied in the volatility framework, namely diagnostic checking procedures, information criteria, and conditions for the existence of moments and asymptotic theory, as well as the out-of-sample model selection approaches, such as mean squared error...