This paper shows that the framework proposed by Barberis and Huang (2009) to incorporate narrow framing and loss aversion into dynamic models of portfolio choice and asset pricing can be extended to also account for probability weighting and for a value function that is convex on losses and...

Although firms devote a great deal of resources to promoting high ethical standards, little is known about how deceptive information transmission affects behavior in these environments. We find evidence for ripple effects of deceptive reporting—that victims of lies pay lies forward—and show...

This paper analyzes the role played by financial assets, direct real estate, and the Fama and French factors in explaining EREIT returns and examines the usefulness of these variables in forecasting returns. Four models are analyzed and their predictive potential is assessed by comparing three...

We analyze the impacts of alternative submarket definitions when predicting house prices in a mass appraisal context, using both ordinary least squares (OLS) and geostatistical techniques. For this purpose, we use over 13,000 housing transactions for Louisville, Kentucky. We use districts...

It is well known that the class of strong (Generalized) AutoRegressive Conditional Heteroskedasticity (or GARCH) processes is not closed under contemporaneous aggregation. This paper provides the dynamics followed by the aggregate process when the individual persistence parameters are drawn from...

We augment the existing literature using the Log-Periodic Power Law Singular (LPPLS) structures in the log-price dynamics to diagnose financial bubbles by providing three main innovations. First, we introduce the quantile regression to the LPPLS detection problem. This allows us to disentangle...

Structured additive regression (STAR) models are a rich class of regression models that include the generalized linear model (GLM) and the generalized additive model (GAM). STAR models can be fitted by Bayesian approaches, component-wise gradient boosting, penalized least-squares, and deep...

We develop new higher-order asymptotic techniques for the Gaussian maximum likelihood estimator of the parameters in a spatial panel data model, with fixed effects, time-varying covariates, and spatially correlated errors. We introduce a new saddlepoint density and tail area approximation to...

We develop a dynamic model of corporate investment and financing decisions in which corporate insiders have superior information about the firm's growth prospects. We show that firms with positive private information can credibly signal their type to outside investors using the timing of...

In this study, we examine the rationale that informed traders use in choosing various financial instruments in order to speculate on the volatility of the underlying asset, here a common stock. Using a continuous-time trading model, we demonstrate that the quality of the private information...