What Can Be Learned from Inverse Statistics? View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2010

AUTHORS

Peter Toke Heden Ahlgren , Henrik Dahl , Mogens Høgh Jensen , Ingve Simonsen

ABSTRACT

One stylized fact of financial markets is an asymmetry between the most likely time to profit and to loss. This gain–loss asymmetry is revealed by inverse statistics, a method closely related to empirically finding first passage times. Many papers have presented evidence about the asymmetry, where it appears and where it does not. Also, various interpretations and explanations for the results have been suggested. In this chapter, we review the published results and explanations. We also examine the results and show that some are at best fragile. Similarly, we discuss the suggested explanations and propose a new model based on Gaussian mixtures. Apart from explaining the gain–loss asymmetry, this model also has the potential to explain other stylized facts such as volatility clustering, fat tails, and power law behavior of returns. More... »

PAGES

247-270

References to SciGraph publications

Book

TITLE

Econophysics Approaches to Large-Scale Business Data and Financial Crisis

ISBN

978-4-431-53852-3
978-4-431-53853-0

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-4-431-53853-0_13

DOI

http://dx.doi.org/10.1007/978-4-431-53853-0_13

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1052756678


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