A model of financial asset price determination is proposed that incorporates flat trading features into an e¡é cient price process. The model involves the superposition of a Brownian semimartin- gale process for the efficient price and a Bernoulli process that determines the extent of flat...

A recursive regression methodology is used to analyze the bubble characteristics of various fi- nancial time series during the subprime crisis. The methods provide a technology for identifying bubble behavior and consistent dating of their origination and collapse. Seven relevant financial...

A new methodology is proposed to estimate theoretical prices of financial contin- gent claims whose values are dependent on some other underlying financial assets. In the literature, the preferred choice of estimator is usually maximum likelihood (ML). ML has strong asymptotic justification but...

Some limit theory is developed for estimators suggested in Phillips, Wu and Yu (2009) for dating bubble pheonoma in time series data. The models involve mildly explosive autoregressions and the tests rely on right sided recursive unit root tests. The estimates locate the origination and collapse...

This paper examines how volatility responds to return news in the context of stochastic volatility (SV) using a nonparametric method. The correlation structure in the classical leverage SV model is generalized based on a linear spline. In the new model the correlation between the return...

This paper develops a new methodology for estimating and testing conditional factor models in finance. We propose a two-stage procedure that naturally unifies the two existing approaches in the finance literature–the parametric approach and the nonparametric approach. Our combined approach...

The asymptotic distributions of the least squares estimator of the mean reversion parameter (κ) are developed in a general class of diffusion models under three sampling schemes, namely, longspan, in-fill and the combination of long-span and in-fill. The models have an affine structure in the...

In this paper a method is developed and implemented to provide the simulated maximum likelihood estimation of latent diffusions based on discrete data. The method is applicable to diffusions that either have latent elements in the state vector or are only observed at discrete time with a noise....

The paper proposes a new class of continuous-time asset pricing models where negative jumps play a crucial role. Whenever there is a negative jump in asset returns, it is simultaneously passed on to diffusion variance and the jump intensity, generating self-exciting co-jumps of prices and...

Hypothesis testing using Bayes factors (BFs) is known not to be well dened under the improper prior. In the context of latent variable models, an additional problem with BFs is that they are difficult to compute. In this paper, a new Bayesian method, based on decision theory and the EM...