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SUMMARY:The Pricing Kernel Anomaly: the Case of the Information that did n
 ot Bark
DTSTART:20151022T120000
DTEND:20151022T130000
DTSTAMP:20260406T063903Z
UID:f8c18fe54a6f0ff82070837c0126a39460e2d127113be1a4935ae6a3
CATEGORIES:Conferences - Seminars
DESCRIPTION:Carlo SALA (PhD student\, Università della Svizzera italiana)
 \nThis paper provides an empirical study on the conditioning of the inform
 ation in the estimation of the pricing kernel. Although the neoclassical t
 heory requires the pricing kernel to be a monotonically decreasing functio
 n\, recent empirical studies found several violations: at the extremes as 
 well as in the central part of the functional. Since Jackwerth (2000)\, th
 is is known as the "pricing kernel puzzle". While the risk-neutral moments
  extracted from option surfaces are by construction forward looking\, the 
 ones obtainable from historical returns are only partially informative\, t
 hus suboptimal with respect to investors' future beliefs. This underestima
 tion of the physical ltration produces a disalignment with respect to the 
 full conditioning of the information set as required by the neoclassical t
 heory.  Empirically it turns out that most of papers present in literatur
 e are then aected by a non-homogeneity bias. We propose a new exible and h
 ighly informative non-parametric method to estimate a non-stationary and f
 ully-conditional physical measure. Exploiting the informational content of
  the implied moments of option prices\, the proposed measure embeds the mi
 ssing forward looking information necessary to produce a time-varying and 
 fully-conditional physical measure. A natural approach to exploit simultan
 eously multiple data and provide statistical inference is the Dirichlet pr
 ocess. Using the precision parameter of the Dirichlet process as a proxy f
 or the missing information\, we calibrate it with respect to the daily liq
 uidity of the options in the market. The obtained density is a mixture of 
 the  two measures and combines the prior forward looking information avai
 lable from option data with the historical background provided by stock re
 turns. The new  measure is then used to investigate the pricing kernel mo
 notonicity.
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STATUS:CONFIRMED
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