Value at risk from econometric models and implied from currency options
Article Abstract:
The daily exchange rate value at risk estimates derived from econometric models are compared with those implied by the prices of the traded options. Univariate and multivariate GARCH models are employed in parallel with simple historical and exponentially weighted moving average methods. In stable conditions, implied model overestimates value at risk, hence over-allocating capital while it is less responsive than the GARCH type models during volatile periods, leading to under-allocation of capital and risk of failures. Market expectations of future volatility, as determined from the prices of traded options, may not be the optimal tools to determine value at risk.
Publication Name: Journal of Forecasting
Subject: Mathematics
ISSN: 0277-6693
Year: 2004
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Smooth transition exponential smoothing
Article Abstract:
New Adaptive Exponential Smoothing method surpasses the existing Adaptive Exponential Method and Constant Parameter Methods when the estimation and evaluation samples both contain a level shift or an outlier while considering a simulated data. Existing Adaptive method drawbacks like unstable forecasts and poor performance are also overcome. The new method is analogous to the old and we can model a smoothing parameter as a logistic function of the variables specified by the users ( smooth transition model) also the empirical study made using monthly time series found the results to be accurate.
Publication Name: Journal of Forecasting
Subject: Mathematics
ISSN: 0277-6693
Year: 2004
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Daily volatility forecasts: reassessing the performance of GARCH Models
Article Abstract:
The accurate measurement and forecasting of volatility plays an important role in the execution and evaluation of asset and derivative pricing models. A method for estimating true volatility based on cumulative squared return from intra day is proposed and discussed. The failure of GARCH (Generalized Autoregressive Conditional Heteroskedasticity) models in providing effective forecasts of volatility is discussed in detail.
Publication Name: Journal of Forecasting
Subject: Mathematics
ISSN: 0277-6693
Year: 2004
User Contributions:
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