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Lassoing the HAR model: A Model Selection Perspective on Realized Volatility Dynamics

Audrino, Francesco; Knaus, Simon - School of Economics and Political Science, Universität … - 2012

absolute shrinkage and selection operator (lasso) which should identify the aforementioned model. We prove that the lasso …. The HAR model is not recovered by the lasso on real data. This, together with an empirical out-of-sample analysis that … shows equal performance of the HAR model and the lasso approach, leads to the conclusion that the HAR model may not be the …

Persistent link: https://www.econbiz.de/10010593816

Essays in computational statistics with applications to volatility forecasting and forecast combination

Knaus, Simon D. - 2014

Der erste Aufsatz der vorliegenden Dissertation untersucht die Dynamik der realisierten Volatilität. Ein erfolgreiches Model in diesem Bereich ist das sogenannte heterogene auto-regressive Modell (HAR), das konzeptionell einfach und gut für Vorhersagen geeignet ist. Eine neue Herangehensweise...

Persistent link: https://www.econbiz.de/10010350528

Beating the simple average : egalitarian LASSO for combining economic forecasts

Diebold, Francis X.; Shin, Minchul - 2017

Persistent link: https://www.econbiz.de/10011770567

A state space model for Berlin house prices

Schulz, Rainer; Werwatz, Axel - 2001

How risky are investments in residential real estate? To answer this question, information is needed about the behavior of house prices. The hedonic methodology has become a standard approach for modelling the prices of heterogeneous assets. Although intuitively appealing, it is often criticized...

Persistent link: https://www.econbiz.de/10010310353

Consistent preordering with an estimated criterion function, with an application to the evaluation and comparison of volatility models

Hansen, Peter Reinhard; Lunde, Asger - 2003

When alternatives are compared using an estimated criterion function, this may introduce a discrepancy between the true and the estimated criterion. In this paper, we consider a situation where a preordering (ranking) of stochastic sequences is defined from expected loss/gain, using a parametric...

Persistent link: https://www.econbiz.de/10010318932

Secondary Analysis of Case-Control Studies in Genomic Contexts

Carroll, Raymond J. (contributor) - 2010

This dissertation consists of five independent projects. In each project, a novelstatistical method was developed to address a practical problem encountered in genomiccontexts. For example, we considered testing for constant nonparametric effectsin a general semiparametric regression model in...

Persistent link: https://www.econbiz.de/10009464885

Model selection criteria in the presence of missing data based on the Kullback-Leibler discrepancy

Sparks, JonDavid - 2009

An important challenge in statistical modeling involves determining an appropriate structural form for a model to be used in making inferences and predictions. Missing data is a very common occurrence in most research settings and can easily complicate the model selection problem. Many useful...

Persistent link: https://www.econbiz.de/10009466074

Evaluation of Dynamic Stochastic General Equilibrium Models Based on Distributional Comparison of Simulated and Historical Data

Corradi, Valentina; Swanson, Norman R. - 2003

We take as a starting point the existence of a joint distribution implied by different dynamic stochastic general equilibrium (DSGE) models, all of which are potentially misspecified. Our objective is to compare "true" joint distributions with ones generated by given DSGEs. This is accomplished...

Persistent link: https://www.econbiz.de/10010263218

Improving the pricing of options: a neural network approach

Anders, Ulrich; Korn, Olaf; Schmitt, Christian - 1996

In this paper we apply statistical inference techniques to build neural network models which are able to explain the prices of call options written on the German stock index DAX. By testing for the explanatory power of several input variables serving as network inputs, some insight into the...

Persistent link: https://www.econbiz.de/10010299651

Model selection in neural networks

Anders, Ulrich; Korn, Olaf - 1996

In this article we examine how model selection in neural networks can be guided by statistical procedures such as hypotheses tests, information criteria and cross validation. The application of these methods in neural network models is discussed, paying attention especially to the identification...

Persistent link: https://www.econbiz.de/10010299652