## Abstract To support the development of hydrogen production by high temperature electrolysis using solid oxide electrolysis cells (SOECs), the effects of operating conditions on the performance of the SOECs were investigated using a one‐dimensional model of a cathode‐supported planar SOEC stack.
A Study of Value-at-Risk Based on M-Estimators of the Conditional Heteroscedastic Models
✍ Scribed by Farhat Iqbal; Kanchan Mukherjee
- Publisher
- John Wiley and Sons
- Year
- 2011
- Tongue
- English
- Weight
- 119 KB
- Volume
- 31
- Category
- Article
- ISSN
- 0277-6693
- DOI
- 10.1002/for.1224
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✦ Synopsis
ABSTRACT
In this paper, we investigate the performance of a class of M‐estimators for both symmetric and asymmetric conditional heteroscedastic models in the prediction of value‐at‐risk. The class of estimators includes the least absolute deviation (LAD), Huber's, Cauchy and B‐estimator, as well as the well‐known quasi maximum likelihood estimator (QMLE). We use a wide range of summary statistics to compare both the in‐sample and out‐of‐sample VaR estimates of three well‐known stock indices. Our empirical study suggests that in general Cauchy, Huber and B‐estimator have better performance in predicting one‐step‐ahead VaR than the commonly used QMLE. Copyright © 2011 John Wiley & Sons, Ltd.
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