Arbeitspapier
Interquantile Expectation Regression
We propose a semiparametric estimator to determine the effects of explanatory variables on the conditional interquantile expectation (IQE) of the random variable of interest, without specifying the conditional distribution of the underlying random variables. IQE is the expected value of the random variable of interest given that its realization lies in an interval between two quantiles, or in an interval that covers the range of the distribution to the left or right of a quantile. Our so-called interquantile expectation regression (IQER) estimator is based on the GMM framework. We derive consistency and the asymptotic distribution of the estimator, and provide a consistent estimator of the asymptotic covariance matrix. Our results apply to stationary and ergodic time series. In a simulation study we show that our asymptotic theory provides an accurate approximation in small samples. We provide an empirical illustration in finance, in which we use the IQER estimator to estimate one-step-ahead daily expected shortfall conditional on previously observed daily, weekly, and monthly aggregated realized measures.
- Sprache
-
Englisch
- Erschienen in
-
Series: Tinbergen Institute Discussion Paper ; No. 17-034/III
- Klassifikation
-
Wirtschaft
Estimation: General
Semiparametric and Nonparametric Methods: General
Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
Financial Econometrics
Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
- Thema
-
quantile
interquantile expectation
regression
generalized method of moments
risk management
expected shortfall
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Barendse, Sander
- Ereignis
-
Veröffentlichung
- (wer)
-
Tinbergen Institute
- (wo)
-
Amsterdam and Rotterdam
- (wann)
-
2017
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:44 MEZ
Datenpartner
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Barendse, Sander
- Tinbergen Institute
Entstanden
- 2017
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