Nonparametric model identification and specification play a critical role in asset pricing and risk management. The objective of the investigators is to study a number of important model specification problems using nonparametrically estimated transition densities and transition distributions. The proposed method integrates a number of seemingly unrelated model identification problems into a common paradigm, by framing them as various restrictions on the transition density or distribution of the underlying process, sampled at the observation frequency. This will provide a rich framework for analyzing other similar problems. By estimating the transition density and distribution under null and alternative hypotheses, appropriate test statistics will be proposed and investigated. The properties of the tests include both the asymptotic null distributions and power functions and will also be analyzed via carefully designed simulations. The relative merits of various methods will be critically examined. Several testing problems arising frequently in the empirical finance will be carefully investigated.

The investigators intend to develop new techniques and theories that arise from frontiers of financial econometrics. The investigators will develop models and cutting-edge technologies for model specification problems in economics and financial econometrics. Common characteristics of these problems are that the dynamics of stocks and interest rates are hard to specify and hence contemporary nonparametric techniques are particularly powerful for these problems. The proposed techniques and results will have strong impact on assest pricing, portfolio allocations, risk managements and other problems in empirical finance. The project will integrate research and education by working closely with both undergraduate and graduate students, creating datasets and developing publicly available computer code. Postdoctoral fellows and underrepresented groups will be trained as a part of our research investigation. The results will be disseminated broadly through presentations at seminars, conferences, professional association meetings and via internet.

Agency
National Science Foundation (NSF)
Institute
Division of Mathematical Sciences (DMS)
Type
Standard Grant (Standard)
Application #
0532370
Program Officer
Mary Ann Horn
Project Start
Project End
Budget Start
2005-09-01
Budget End
2009-08-31
Support Year
Fiscal Year
2005
Total Cost
$399,999
Indirect Cost
Name
Princeton University
Department
Type
DUNS #
City
Princeton
State
NJ
Country
United States
Zip Code
08540