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Dependence of stock returns in bull and bear markets
Dobrić, Jadran; Frahm, Gabriel; Schmid, Friedrich - 2007
Pearson's correlation coefficient is typically used for measuring the dependence structure of stock returns. Nevertheless, it has many shortcomings often documented in the literature. We suggest to use a conditional version of Spearman's rho as an alternative dependence measure. Our approach is...
Persistent link: https://www.econbiz.de/10003875336
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Jump-robust volatility estimation using nearest neighbor truncation
Andersen, Torben; Dobrev, Dobrislav; Schaumburg, Ernst - 2010
We propose two new jump-robust estimators of integrated variance based on highfrequency return observations. These MinRV and MedRV estimators provide an attractive alternative to the prevailing bipower and multipower variation measures. Specifically, the MedRV estimator has better theoretical...
Persistent link: https://www.econbiz.de/10008657195
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Parametric estimation : finite sample theory
Spokojnyj, Vladimir G. - 2011
The paper aims at reconsidering the famous Le Cam LAN theory. The main features of the approach which make it different from the classical one are: (1) the study is non-asymptotic, that is, the sample size is fixed and does not tend to infinity; (2) the parametric assumption is possibly...
Persistent link: https://www.econbiz.de/10009379449
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Increasing weather risk : fact of fiction?
Wang, Weining; Bobojonov, Ihtiyor B.; Härdle, Wolfgang; … - 2011
It is an undisputed fact that weather risk increases over time due to climate change. However, qualification of this statement with regard to the type of weather risk and geographical location is needed. We investigate the application of novel statistical tools for assessing changes in weather...
Persistent link: https://www.econbiz.de/10009379509
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Penalized sieve estimation and inference of semi-nonparametric dynamic models : a selective review
Chen, Xiaohong - 2011
two-step estimators and their consistent variance estimators. Examples from dynamic asset pricing, nonlinear spatial VAR …, semiparametric GARCH, and copula-based multivariate financial models are used to illustrate the general results. -- Nonlinear time … ; Semiparametric two-step ; Nonlinear ill-posed inverse ; Mixtures ; Conditional moment restrictions ; Nonparametric endogeneity …
Persistent link: https://www.econbiz.de/10009230387
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TVICA - time varying independent component analysis and its application to financial data
Chen, Ray-Bing; Chen, Ying; Härdle, Wolfgang - 2011
series that are neither Gaussian distributed nor stationary. Independent component analysis (ICA) method can be used to …) method. Compared to a static ICA, the dynamic TVICA provides good performance both in simulation and real data analysis. The …. -- Adaptive Sequential Testing ; Independent Component Analysis ; Local Homogeneity ; Signal Processing ; Realized Volatility. …
Persistent link: https://www.econbiz.de/10009266846
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Large vector auto regressions
Song, Song; Bickel, Peter J. - 2011
One popular approach for nonstructural economic and financial forecasting is to include a large number of economic and financial variables, which has been shown to lead to significant improvements for forecasting, for example, by the dynamic factor models. A challenging issue is to determine...
Persistent link: https://www.econbiz.de/10009266948
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The merit of high-frequency data in portfolio allocation
Hautsch, Nikolaus; Kyj, Lada M.; Malec, Peter - 2011
This paper addresses the open debate about the effectiveness and practical relevance of highfrequency (HF) data in portfolio allocation. Our results demonstrate that when used with proper econometric models, HF data offers gains over daily data and more importantly these gains are maintained...
Persistent link: https://www.econbiz.de/10009306337
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The merit of high-frequency data in portfolio allocation
Hautsch, Nikolaus; Kyj, Lada M.; Malec, Peter - 2011
This paper addresses the open debate about the usefulness of high-frequency (HF) data in large-scale portfolio allocation. Daily covariances are estimated based on HF data of the S&P 500 universe employing a blocked realized kernel estimator. We propose forecasting covariance matrices using a...
Persistent link: https://www.econbiz.de/10009308302
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Shortcomings of a parametric VaR approach and nonparametric improvements based on a non-stationary return series model
Gürtler, Marc; Rauh, Ronald - 2009 - This Version: 2009-09-09
A non-stationary regression model for financial returns is examined theoretically in this paper. Volatility dynamics are modelled both exogenously and deterministic, captured by a nonparametric curve estimation on equidistant centered returns. We prove consistency and asymptotic normality of a...
Persistent link: https://www.econbiz.de/10009487233