Forecasting volatility using range data: analysis for emerging equity markets in Latin America

• Published in: Applied financial economics Vol. 22; no. 6; pp. 461 - 470
• Main Authors: Asai, Manabu, Brugal, Iván
• Format: Journal Article
• Language: English
• Published: Routledge 01-03-2012; Taylor and Francis Journals
• Series: Applied Financial Economics
• Subjects: Argentina; Autoregressive Moving Average models; Brazil; Capital market; Empirical research; Financial analysis; Forecasting techniques; heterogeneous autoregressive models; Latin America; leverage effects; Mexico; range; Stock exchange; U.S.A; Value at risk; Vector-autoregressive models; Volatility
• ISSN: 0960-3107; 1466-4305
• DOI: 10.1080/09603107.2011.617694

The article suggests a simple but effective approach for estimating value-at-risk thresholds using range data, working with the filtered historical simulation. For this purpose, we consider asymmetric heterogeneous Autoregressive Moving Average (ARMA) model for log-range, which captures the leverage effects and the effects from daily, weekly and monthly horizons. The empirical analysis on stock market indices on the US, Mexico, Brazil and Argentina shows that 1% and 5% Value at Risk (VaR) thresholds based on one-step-ahead forecasts of log-range are satisfactory for the period includes the global financial crisis.