This paper investigates the forecasting accuracy of alternative time series models when augmented with partial least-squares (PLS) components extracted from economic data, such as Federal Reserve Economic Data, well Monthly Database (FRED-MD). Our results indicate that PLS FRED-MD data reduce error linear models, ARIMA and SARIMA, but produce poor forecasts during high-volatility periods. In co...

this paper examines the impact of 2005 presidential election of iran on the tehran stock exchange volatility as a political shock. it uses garch family (fiegarch, egarch, and garch) and markov regime switching (mrs) models as the analytical frameworks for the main the stock daily prices index. our findings confirm statistical validity of arima – fiegarch-x and ar(1) mrs as appropriate specifica...

Modelling and forecasting volatility of a financial time series has been significant area research in recent years, owing to the fact that is regarded as an essential notion many economic applications. Because not directly observable, analysts are especially eager obtain accurate estimation this conditional variance process. As result, number models have developed specifically suited estimate i...

AbstractThe Islamic stock index is a composite of stocks listed on the Indonesia Stock Exchange (IDX). Therefore, expected to have low volatility and be resistant possible financial crisis. This study aims see whether lower than conventional during Covid-19 The data taken daily closing for JKSE JII period March 1, 2020, April 30, 2022, with total 532 observations. model used ARMA/ ARIMA which t...