Forecasting exchange rate volatility using autoregressive random variance model

Mike K. P. SO, K. LAM, Wai Keung LI

Research output: Contribution to journalArticles

17 Citations (Scopus)

Abstract

Recently, as an alternative to the GARCH model, the autoregressive random variance (ARV) model has been gaining popularity in the modelling of changing volatility, mainly because of the capability in capturing the stochastic nature of volatility. This article highlights the ARV model as an alternative to the GARCH model in modelling volatility. The main focus is to compare the two models in forecasting exchange rate volatility. Although the two approaches generally give close forecasting performance, the ARV method provides a notable improvement in Canadian/ Dollar and Australian/Dollar. The outstanding performance seems to be related to the 'volatility of volatility', i.e. the volatility changes from day to day. Copyright © 1999 Taylor & Francis.
Original languageEnglish
Pages (from-to)583-591
JournalApplied Financial Economics
Volume9
Issue number6
DOIs
Publication statusPublished - 1999

Citation

So, M. K. P., Lam, K., & Li, W. K. (1999). Forecasting exchange rate volatility using autoregressive random variance model. Applied Financial Economics, 9(6), 583-591. doi: 10.1080/096031099332032

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