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Contribution Details

Type Master Thesis
Scope Discipline-based scholarship
Title Non-Parametric Estimation of State Price Densities
Organization Unit
  • Daniel Grosshans
  • Thorsten Hens
  • English
Institution University of Zurich
Faculty Faculty of Business, Economics and Informatics
Number of Pages 46
Date November 2017
Abstract Text This thesis contributes to our understanding of arbitrage-free asset pricing in incomplete markets. In particular, I present a new methodological approach to the empirical estimation of state price densities. I point out that the empirical literature has neglected incompleteness by proposing methods that are aimed to provide unique estimates of state price densities. I propose to characterize arbitrage-free prices through a system of linear inequalities. Under incompleteness, the absence of arbitrage will imply the existence of a multitude of sets of arbitrage-free prices. I will determine boundaries for the arbitrage-free option prices and the distribution of state prices and I will also propose how a unique state price density could be optimally estimated. In a last section I will address the recovery of the pricing kernel and I will show in particular how the hypothesis of a monotonically decreasing pricing kernel should be tested in the presence of market incompleteness. In particular, I do not find supporting evidence for the so-called pricing kernel puzzle.
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