Nonparametric transition based-tests for Markov processes in financial econometrics

非参数模型的识别和规范在资产定价和风险管理中起着至关重要的作用。研究人员的目标是使用非参数估计的转移密度和转移分布来研究一些重要的模型规范问题。该方法将许多看似不相关的模型辨识问题集成到一个共同的范例中，通过将它们框定为对在观测频率上采样的潜在过程的转移密度或分布的各种限制。这将为分析其他类似问题提供丰富的框架。通过估计零假设和替代假设下的转移密度和分布，将提出并研究适当的检验统计量。检验的性质包括渐近零分布和幂函数，并将通过精心设计的模拟进行分析。将对各种方法的相对优点进行严格的审查。研究人员将仔细研究在经验金融学中经常出现的几个检验问题。研究人员打算发展金融计量经济学前沿领域出现的新技术和新理论。研究人员将为经济学和金融计量经济学中的模型规格问题开发模型和尖端技术。这些问题的共同特征是，股票和利率的动态很难确定，因此当代的非参数技术特别适合于这些问题。所提出的技术和结果将对经验金融学中的资产定价、投资组合配置、风险管理和其他问题产生重大影响。该项目将通过与本科生和研究生密切合作、创建数据集和开发公开可用的计算机代码来整合研究和教育。博士后研究员和代表不足的群体将被背叛，作为我们研究调查的一部分。结果将通过在研讨会、会议、专业协会会议上的演讲和通过互联网广泛传播。

Nonparametric model identification and specification play a critical rolein asset pricing and risk management. The objective of the investigators isto study a number of important model specification problems usingnonparametrically estimated transition densities and transitiondistributions. The proposed method integrates a number of seeminglyunrelated model identification problems into a common paradigm, by framingthem as various restrictions on the transition density or distribution ofthe underlying process, sampled at the observation frequency. This willprovide a rich framework for analyzing other similar problems. Byestimating the transition density and distribution under null andalternative hypotheses, appropriate test statistics will be proposed and investigated. Theproperties of the tests includeboth the asymptotic null distributions and power functions and will alsobe analyzed via carefully designed simulations. The relative merits ofvarious methods will be critically examined. Several testing problemsarising frequently in the empirical finance will be carefullyinvestigated.The investigators intend to develop new techniques and theories that arisefrom frontiers of financial econometrics. The investigators will developmodels and cutting-edge technologies for model specification problems ineconomics and financial econometrics. Common characteristics of theseproblems are that the dynamics of stocks and interest rates are hard tospecify and hence contemporary nonparametric techniques are particularlypowerful for these problems. The proposed techniques and results will havestrong impact on assest pricing, portfolio allocations, risk managementsand other problems in empirical finance. The project will integrateresearch and education by working closely with both undergraduate andgraduate students, creating datasets and developing publicly availablecomputer code. Postdoctoral fellows and underrepresented groups will betrained as a part of our research investigation. The results will bedisseminated broadly through presentations at seminars, conferences,professional association meetings and via internet.