LCARE - Localizing Conditional Autoregressive Expectiles
| Autor: | Andrija Mihoci, Xiu Xu, Wolfgang Karl Härdle |
|---|---|
| Rok vydání: | 2015 |
| Předmět: |
Economics and Econometrics
Statistical Finance (q-fin.ST) business.industry 05 social sciences Downside risk Quantitative Finance - Statistical Finance Asset allocation 01 natural sciences FOS: Economics and business 010104 statistics & probability Portfolio insurance 0502 economics and business Econometrics Portfolio Tail risk 0101 mathematics business Finance Value at risk Risk management 050205 econometrics Quantile Mathematics Parametric statistics |
| Zdroj: | SSRN Electronic Journal. |
| ISSN: | 1556-5068 |
| DOI: | 10.2139/ssrn.3085849 |
| Popis: | We account for time-varying parameters in the conditional expectile based value at risk (EVaR) model. EVaR appears more sensitive to the magnitude of portfolio losses compared to the quantile-based Value at Risk (QVaR), nevertheless, by fitting the models over relatively long ad-hoc fixed time intervals, research ignores the potential time-varying parameter properties. Our work focuses on this issue by exploiting the local parametric approach in quantifying tail risk dynamics. By achieving a balance between parameter variability and modelling bias, one can safely fit a parametric expectile model over a stable interval of homogeneity. Empirical evidence at three stock markets from 2005- 2014 shows that the parameter homogeneity interval lengths account for approximately 1-6 months of daily observations. Our method outperforms models with one-year fixed intervals, as well as quantile based candidates while employing a time invariant portfolio protection (TIPP) strategy for the DAX portfolio. The tail risk measure implied by our model finally provides valuable insights for asset allocation and portfolio insurance. |
| Databáze: | OpenAIRE |
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