Search Results - subject:"volatility forecasting."

Are RiskMetrics forecasts good enough? Evidence from 31 stock markets

McMillan, David G.; Kambouroudis, Dimos - In: International Review of Financial Analysis 18 (2009) 3, pp. 117-124

, a straightforward volatility forecasting exercise and a Value-at-Risk exceptions forecasting competition. Our results …

Persistent link: https://www.econbiz.de/10004973401

Intra-daily information of range-based volatility for MEM-GARCH

Lam, K.P.; Ng, H.S. - In: Mathematics and Computers in Simulation (MATCOM) 79 (2009) 8, pp. 2625-2632

Conventional GARCH modeling formulates an additive-error mean equation for daily return and an autoregressive moving-average specification for its conditional variance, without much consideration on the effects of intra-daily data. Using Engle’s multiplicative-error model (MEM) formulation,...

Persistent link: https://www.econbiz.de/10010748948

Modeling Jump and Continuous Components in the Volatility of Oil Futures

Tseng, Tseng-Chan; Chung, Huimin; Huang, Chin-Sheng - In: Studies in Nonlinear Dynamics & Econometrics 13 (2009) 3, pp. 1671-1671

In this study, we use the 'heterogeneous autoregressive' (HAR) model and replace all squared returns with a squared range to estimate realized range-based volatility (RRV) forecasts for oil futures prices. Our findings demonstrate that the HAR-RRV models, involving volatility measures with a...

Persistent link: https://www.econbiz.de/10005046514

Forecasting Volatility under Fractality, Regime-Switching, Long Memory and Student-t Innovations

Lux, Thomas; Morales-Arias, Leonardo - Institut für Weltwirtschaft (IfW) - 2009

We examine the performance of volatility models that incorporate features such as long (short) memory, regime-switching and multifractality along with two competing distributional assumptions of the error component, i.e. Normal vs Student-t. Our precise contribution is twofold. First, we...

Persistent link: https://www.econbiz.de/10005011993

Volatility Forecasting Models and Market Co-Integration: A Study on South-East Asian Markets

Febrian, Erie; Herwany, Aldrin - Center for Economics and Development Studies, Fakultas … - 2009

Volatility forecasting is an imperative research field in financial markets and crucial component in most financial … effectiveness of the contending models of statistical and econometric volatility forecasting in the three South-east Asian prominent … then used to assess the markets cointegration. We find that the best volatility forecasting models for JKSE, KLSE, and STI …

Persistent link: https://www.econbiz.de/10005013937

The skew pattern of implied volatility in the DAX index options market

Muzzioli, Silvia - Dipartimento di Economia "Marco Biagi", Università … - 2009

The aim of this paper is twofold: to investigate how the information content of implied volatility varies according to moneyness and option type and to compare the latter option based forecasts with historical volatility in order to see if they subsume all the information contained in the...

Persistent link: https://www.econbiz.de/10008506814

Forecasting daily volatility with intraday data

Frijns, Bart; Margaritis, Dimitris - In: The European Journal of Finance 14 (2008) 6, pp. 523-540

The aim of this paper is to assess to what extent intraday data can explain and predict end-of-the-day volatility. Using a realized volatility measure as proposed by Andersen, T., T. Bollerslev, F. Diebold, and P. Labys. 2001. The distribution of realized exchange rate volatility. Journal of the...

Persistent link: https://www.econbiz.de/10005471842

How has volatility in metals markets changed?

Watkins, Clinton; McAleer, Michael - In: Mathematics and Computers in Simulation (MATCOM) 78 (2008) 2, pp. 237-249

Within the industrial metals industry, there has been a great deal of interest surrounding trends in metals market volatility over time. This paper uses a rolling AR(1)-GARCH(1,1) model to estimate and forecast the volatility processes for daily returns on the futures prices of two important...

Persistent link: https://www.econbiz.de/10010749874

Volatility forecasting: the jumps do matter

Corsi, Fulvio; Pirino, Davide; Renò, Roberto - Dipartimento di Economia Politica e Statistics, … - 2008

This study reconsiders the role of jumps for volatility forecasting by showing that jumps have positive and mostly …

Persistent link: https://www.econbiz.de/10005766526

ARFIMAX and ARFIMAX-TARCH realized volatility modeling

Degiannakis, Stavros - In: Journal of Applied Statistics 35 (2008) 10, pp. 1169-1180

ARFIMAX models are applied in estimating the intra-day realized volatility of the CAC40 and DAX30 indices. Volatility clustering and asymmetry characterize the logarithmic realized volatility of both the indices. The ARFIMAX model with time-varying conditional heteroskedasticity is the best...

Persistent link: https://www.econbiz.de/10005639750