Arbeitspapier
lCARE: localizing conditional autoregressive expectiles
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.
- Sprache
-
Englisch
- Erschienen in
-
Series: SFB 649 Discussion Paper ; No. 2015-052
- Klassifikation
-
Wirtschaft
Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
Model Construction and Estimation
Financial Forecasting and Simulation
- Thema
-
expectiles
tail risk
local parametric approach
risk management
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Xu, Xiu
Mihoci, Andrija
Härdle, Wolfgang Karl
- Ereignis
-
Veröffentlichung
- (wer)
-
Humboldt University of Berlin, Collaborative Research Center 649 - Economic Risk
- (wo)
-
Berlin
- (wann)
-
2015
- Handle
- Letzte Aktualisierung
- 10.03.2025, 11:43 MEZ
Datenpartner
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Xu, Xiu
- Mihoci, Andrija
- Härdle, Wolfgang Karl
- Humboldt University of Berlin, Collaborative Research Center 649 - Economic Risk
Entstanden
- 2015
Ähnliche Objekte (12)
lCARE – localizing Conditional AutoRegressive Expectiles
Evaluating models of autoregressive conditional duration
Multivariate autoregressive conditional heteroskedasticity with smooth transitions in conditional correlations
Singular conditional autoregressive Wishart model for realized covariance matrices
A (semi-)parametric functional coefficient autoregressive conditional duration model
Transformed Polynomials for Nonlinear Autoregressive Models of the Conditional Mean
Option pricing under linear autoregressive dynamics, heteroskedasticity, and conditional leptokurtosis
The conditional autoregressive wishart model for multivariate stock market volatility
Modeling autoregressive conditional skewness and kurtosis with multi-quantile CAViaR
Quasi-maximum likelihood estimation in generalized polynomial autoregressive conditional heteroscedasticity models
Predicting bid-ask spreads using long memory autoregressive conditional poisson models
Localizing Multivariate CAViaR
lCARE – localizing Conditional AutoRegressive Expectiles
Evaluating models of autoregressive conditional duration
Multivariate autoregressive conditional heteroskedasticity with smooth transitions in conditional correlations
Singular conditional autoregressive Wishart model for realized covariance matrices
A (semi-)parametric functional coefficient autoregressive conditional duration model
Transformed Polynomials for Nonlinear Autoregressive Models of the Conditional Mean
Option pricing under linear autoregressive dynamics, heteroskedasticity, and conditional leptokurtosis
The conditional autoregressive wishart model for multivariate stock market volatility
Modeling autoregressive conditional skewness and kurtosis with multi-quantile CAViaR
Quasi-maximum likelihood estimation in generalized polynomial autoregressive conditional heteroscedasticity models
Predicting bid-ask spreads using long memory autoregressive conditional poisson models
Localizing Multivariate CAViaR
lCARE – localizing Conditional AutoRegressive Expectiles
Evaluating models of autoregressive conditional duration
Multivariate autoregressive conditional heteroskedasticity with smooth transitions in conditional correlations
Singular conditional autoregressive Wishart model for realized covariance matrices
A (semi-)parametric functional coefficient autoregressive conditional duration model
Transformed Polynomials for Nonlinear Autoregressive Models of the Conditional Mean
Option pricing under linear autoregressive dynamics, heteroskedasticity, and conditional leptokurtosis
The conditional autoregressive wishart model for multivariate stock market volatility
Modeling autoregressive conditional skewness and kurtosis with multi-quantile CAViaR
Quasi-maximum likelihood estimation in generalized polynomial autoregressive conditional heteroscedasticity models
Predicting bid-ask spreads using long memory autoregressive conditional poisson models