We study the impact of firms’ abnormal business operations on their future crash risk in stock prices. Computed based on real earnings management (REM) models, firms' deviation in real operations from industry norms (DRO) is shown to be positively associated with their future crash risk. This association is incremental to that between discretionary accruals (DA) and crash risk found by prior st...

One of the most important duties of financial economy is modeling and forecasting the volatilities of price of risky assets. From analysts and policy makers’ view, price volatility is a key variable contributing to perception of market volatilities. Therefore, analysts need to have an appropriate of forecast of price volatility as a necessary input to perform duties such as risk management, por...

This study uses 462,678 monthly observations of US-listed firms for the period 1990–2018 to document a strong positive relationship between short-term changes in financial distress risk and future stock price crashes. result is economically significant as one interquartile increase main explanatory variable any month increases probability crash by 8.33% relative its mean value. The findings wit...

After credit risk, liquidity risk is probably the next most important risk faced by the finance industry; and yet the study of liquidity is far less advanced. This may be in part due to the fact that there is no agreed definition of what liquidity is, even in qualitative terms; everyone would agree that the effect of illiquidity is to make it difficult or costly to trade large volumes of the un...

Keeping a basic tenet of economic theory, rational expectations, we model the nonlinear positive feedback between agents in the stock market as an interplay between nonlinearity and multiplicative noise. The derived hyperbolic stochastic finite-time singularity formula transforms a Gaussian white noise into a rich time series possessing all the stylized facts of empirical prices, as well as acc...