[Statlist] Friday, 12.05.2017 with Walter Distaso, Imeprial College

[Maurer Letizia]

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ETH and University of Zurich

Organisers:

Proff. P. Bühlmann - L. Held - T. Hothorn - M. Maathuis -
N. Meinshausen - S. van de Geer - M. Wolf
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We are glad to announce the following talk:

Friday, May 12, 2017 at 15.15h  ETH Zurich HG G 19.141
with Walter Distaso, Imperial College
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Title:

Testing for jump spillovers without testing for jumps<https://www.math.ethz.ch/sfs/news-and-events/research-seminar.html?s=fs17#e_9831>


Abstract:

The analysis of jumps spillovers across assets and markets is fundamental for risk management and portfolio diversification. This paper develops statistical tools for testing conditional independence among the jump components of the quadratic variation, which are measured as the sum of squared jump sizes over a day. To avoid sequential bias distortion, we do not pretest for the presence of jumps. We proceed in two steps. First, we derive the limiting distribution of the infeasible statistic, based on the unobservable jump component. Second, we provide sufficient conditions for the asymptotic equivalence of the feasible statistic based on realized jumps. When the null is true, and both assets have jumps, the statistic weakly converges to a Gaussian random variable. When instead at least one asset has no jumps, then the statistic approaches zero in probability. We then establish the validity of moon bootstrap critical values. If the null is true and both assets have jumps, both statistics have the same limiting distribution. in the absence of jumps in at least one asset, the bootstrap-based statistic converges to zero at a slower rate. Under the alternative, the bootstrap statistic diverges at a slower rate. Altogether, this means that the use of bootstrap critical values ensures a consistent test with asymptotic size equal to or smaller than alpha. We finally provide an empirical illustration using transactions data on futures and ETFs.


This abstract is also to be found under the following link: http://stat.ethz.ch/events/research_seminar

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