## ABSTRACT This paper proposes value‐at risk (VaR) estimation methods that are a synthesis of conditional autoregressive value at risk (CAViaR) time series models and implied volatility. The appeal of this proposal is that it merges information from the historical time series and the different inf
Value at risk from econometric models and implied from currency options
✍ Scribed by James Chong
- Publisher
- John Wiley and Sons
- Year
- 2004
- Tongue
- English
- Weight
- 177 KB
- Volume
- 23
- Category
- Article
- ISSN
- 0277-6693
- DOI
- 10.1002/for.934
No coin nor oath required. For personal study only.
✦ Synopsis
Abstract
This paper compares daily exchange rate value at risk estimates derived from econometric models with those implied by the prices of traded options. Univariate and multivariate GARCH models are employed in parallel with the simple historical and exponentially weighted moving average methods. Overall, we find that during periods of stability, the implied model tends to overestimate value at risk, hence over‐allocating capital. However, during turbulent periods, it is less responsive than the GARCH‐type models, resulting in an under‐allocation of capital and a greater number of failures. Hence our main conclusion, which has important implications for risk management, is that market expectations of future volatility and correlation, as determined from the prices of traded options, may not be optimal tools for determining value at risk. Therefore, alternative models for estimating volatility should be sought. Copyright © 2004 John Wiley & Sons, Ltd.
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