Using a battery of look-ahead-bias free measures of accruals quality (AQ), we find a strong and long lasting negative relation between future returns and AQ. In decile portfolios that rank on AQ, a hedge portfolio that goes long in the lowest decile and short in the highest decile generates an...

In this paper, we propose the use of static and dynamic copulas to study the leverage effect in the S&P 500 index. Copula models can conveniently separate the leverage effect from the marginal distributions of the return and its volatility. Daily volatility is proxied by a measure of realized...

This paper studies stochastic conditional duration models with a mixture of distribution processes for financial asset's transaction data. The mixture component distributions include exponential, gamma and Weibull. The models allow for a correlation between the observed durations and the...

This paper extends a stochastic conditional duration (SCD) model for financial transaction data to allow for correlation between error processes or innovations of observed duration process and latent log duration process with the aim of improving the statistical fit of the model. Suitable...

This paper proposes a threshold stochastic conditional duration (TSCD) model to capture the asymmetric property of financial transactions. The innovation of the observable duration equation is assumed to follow a threshold distribution with two component distributions switching between two...

Traditionally stationarity refers to shift invariance of the distribution of a stochastic process. In this paper, we rediscover stationarity as a path property instead of a distributional property. More precisely, we characterize a set of paths denoted as A, which corresponds to the notion of...

Volatility clustering is a well-known stylized feature of financial asset returns. This paper investigates asymmetric pattern in volatility clustering by employing a univariate copula approach of Chen and Fan (2006). Using daily realized kernel volatilities constructed from high frequency data...

This paper proposes a threshold stochastic conditional duration (SCD) model for financial data at the transaction level. In addition to assuming that the innovations of the duration process follow a threshold distribution with positive support, we also assume that the latent first-order...

This study develops a corporate bankruptcy classification model from a sample of 258 bankrupt and non-bankrupt companies, covering the period 1986-2008. Instead of depending on traditional ratios, it uses a simple exponential function-based algorithm to improve the stability of financial data....

Previous research claims that industry-relative financial ratios are more stable than unadjusted ratios. Yet, most bankruptcy studies continue to use unadjusted financial ratios to develop bankruptcy-prediction models. In re-examining whether industry-relative ratios are actually more stable, we...