Nonparametric Specification Testing for Continuous-Time Models with Applications to Term Structure of Interest Rates

By Yongmiao Hong. 2005

294 citations recorded by the source corpus.

Subfields: Finance, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/7cec226324b27cbded900c949e3f5141bccc4771

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Citations in the corpus

On Time-Varying Factor Models: Estimation and Testing ∗ (2017, background): “For example, Moon and Weidner (2015) demonstrate that the first part of A.4(i) can be satisfied for various processes; Su et al. (2015) verify similar conditions to those in A.”
Default and Recovery Implicit in the Term Structure of Sovereign CDS Spreads (2008, methodology): “, Huang and Huang (2000) and Berndt, Douglas, Duffie, Ferguson, and Schranzk (2004)), it is plausible that (risk-neutral) loss rates are indeed much larger for highly rated countries like Korea or Mexico.”
Likelihood-based scoring rules for comparing density forecasts in tails (2011, methodology): “2 Alternative test statistics based on the PIT are developed in Berkowitz (2001); Bai (2003); Bai and Ng (2005); Hong and Li (2005); Li and Tkacz (2006), and Corradi and Swanson (2006a), mainly to counter the problems caused by parameter estimation uncertainty and the assumption of correct dynamic…”
Numerical simulation of a strongly nonlinear Ait-Sahalia-type interest rate model (2011, background): “However, Hong and Li [ 15 ] developed the so called omnibus nonparametric specification test for continuous-time models based on the transition density function, which, unlike the marginal density used by Ait-Sahalia, captures the full dynamics of continuous process.”
Bias in the estimation of the mean reversion parameter in continuous time models (2012, unknown): “E-mail address: yujun@smu.edu.sg. include Chan et al. (1992), Aït-Sahalia (1996a,b), Dai and Singleton (2000), and Hong and Li (2005).”
A Bayesian approach to bandwidth selection for multivariate kernel regression with an application to state-price density estimation (2009, background): “Major applications of this approach have focused on option pricing (Aı̈t-Sahalia and Lo, 1998; Broadie, Detemple, Ghysels and Torres, 2000; Aı̈t-Sahalia and Duarte, 2003; among others), value-at-risk estimation (see, for example, Aı̈t-Sahalia and Lo, 2000), modelling financial crashes (Fernandes, 20”
Testable Implications of Affine Term Structure Models (2011, unknown): “A broad class of finance models posit that P nt = E t (M t+1 P n−1,t+1 ) for some pricing kernel M t+1 .”
Nonparametric Transition-Based Tests for Jump Diffusions (2009, unknown): “This feature is also shared by the test statistic T4 of Hong and Li (2005) [see Figure 6(a), in which the null distribution is supposed to be uniform].”
Bitcoin and global financial stress: A copula-based approach to dependence and causality in the quantiles (2018, unknown): “N The second approach is the out-of-sample approach of Hong and Li (2005), called the Granger causality in distribution (GCD), which captures the Granger causality in distributions in each conditional quantile.”
Nonparametric inference with generalized likelihood ratio tests (2007, methodology): “11 3.1 GLR statistic The basic idea of the GLR test can be transparently illustrated in terms of likelihood as follows.”
Jackknifing Bond Option Prices (2005, unknown): “Important contributions include Chan et al. (1992) and Aı̈t-Sahalia (1996a, 1996b), Stanton (1997), Bandi and Phillips (2002), Bandi (2002), and Hong and Li (2005), to mention only a few.”