the research problem investigated in this paper is modeling volatility and analyzing risk and return’s relationship in tehran stock exchange using garch-family models including garch(1,1), garch(2,2), egarch(1,1), pgarch(1,1), tgarch(1,1), garch(1,1)-m and cgarch(1,1). using the daily returns of tehran stock exchange companies, we focused on two portfolios of all the companies during a 10-year-...

This paper investigates the dynamic relationship between volatility, volume and open interest in CSI 300 futures market using asymmetric GARCH model, Granger causality test, variance decomposition and impulse response function based on 1-min data. ARMA-EGARCH model is employed and find that both contemporaneous and lagged volume is positively related to volatility, and current open interest has...

Over the past years, cryptocurrencies have drawn substantial attention from media while attracting many investors. Since then, cryptocurrency prices experienced high fluctuations. In this paper, we forecast high-frequency 1 min volatility of four widely traded cryptocurrencies, i.e., Bitcoin, Ethereum, Litecoin, and Ripple, by modeling to select best model. We propose various generalized autore...

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...

F orecasting the volatility of a financial asset has wide implications in finance. Conditional variance extracted from the GARCH framework could be a suitable proxy of financial asset volatility. Option pricing, portfolio optimization, and risk management are examples of implications of conditional variance forecasting. One of the most recent methods of volatility forecasting is Real...

Se analiza el contagio en volatilidad entre los mercados cambiarios y de valores México Brasil enero/2000 a noviembre/2020. La metodología incluye modelos GARCH univariados: GARCH, APARCH, EGARCH TARCH para análisis la las series multivariados GARCH: DCC ADCC, medir co-movimientos condicional del mercado capitales cambiario, permitiendo determinar existencia contagio. observa que, brasileño, co...

Recent research suggests that long memory can be caused by regime switching and is easily confused with it. However, if the causes of confusion were properly controlled, they could distinguished. Motivated this idea, our study aims to distinguish between financial volatility. We firstly modeled volatility using Fractionally Integrated Exponential GARCH (FIEGARCH) Markov Regime-Switching EGARCH ...