Pricing Kernel Puzzles
Nonparametric estimation of the pricing kernel has led to a "puzzle", that challenged finance principles. The apparent non monotonicity of the empirical pricing kernel has been addressed as improper use of past and future observations. A new CDI spline based smoothing technique-reflecting the forward looking information sets-puts the estimated pricing kernel into a seemingly theory compatible shape. Our findings, though, show equivalence between the two techniques. We discover that CDI cannot be fully consistent since it relies on averaging in an almost constant stochastic dynamics world. Empirical insights rather point to economic phenomena and not to technical flaws.
Wolfgang Karl HÄRDLE attained his Dr. rer. nat. in Mathematics at Universität Heidelberg in 1982 and in 1988 his habilitation at Universität Bonn. He is Ladislaus von Bortkiewicz Professor of Statistics at Humboldt-Universität zu Berlin and the director of the Sino German Graduate School (洪堡大学 + 厦门大学) IRTG1792 on “High dimensional non stationary time series analysis”. He directs IDA Institute for Digital Assets,
University of Economic Studies, Bucharest, RO. His research focuses on data analytics, dimension reduction and quantitative finance. He has published over 30 books and more than 300 papers in top statistical, econometrics and finance journals. He is highly ranked and cited on Google Scholar, REPEC and SSRN. He has professional experience in financial engineering, S.M.A.R.T. (Specific, Measurable, Achievable, Relevant, Timely) data analytics, machine learning and cryptocurrency markets. He has created the www.quantlet.com platform, a cryptocurrency index, CRIX www.royalton-crix.com He is 玉山学者 (Yushan Scholar), web page hu.berlin/wkh