Forecasting volatility using range data: analysis for emerging equity markets in Latin America
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.
Volume (Year): 22 (2012)
Issue (Month): 6 (March)
|Contact details of provider:|| Web page: http://www.tandfonline.com/RAFE20|
|Order Information:||Web: http://www.tandfonline.com/pricing/journal/RAFE20|
When requesting a correction, please mention this item's handle: RePEc:taf:apfiec:v:22:y:2012:i:6:p:461-470. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Michael McNulty)
If references are entirely missing, you can add them using this form.