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

• Autores: Manabu Asai, Iván Brugal
• Localización: Applied financial economics, ISSN 0960-3107, Vol. 22, Nº. 4-6, 2012, págs. 461-470
• Idioma: inglés
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• Resumen

  • 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.