Abnormal Real Operations, Real Earnings Management, and Subsequent Crashes in Stock Prices
Review of Quantitative Finance and Accounting,
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 (DROs) from industry norms is shown to be positively associated with their future crash risk. This association is incremental to that between discretionary accruals (DAs) and crash risk found by prior studies. Moreover, after Sarbanes–Oxley Act (SOX) of 2002, DRO’s predictive power for crash risk strengthens substantially, while DA’s predictive power essentially dissipates. These results are consistent with the prior finding that managers shift from accrual earnings management to REM after SOX. We further develop a suspect-firm approach to capture firms’ use of DRO for REM purposes. This analysis shows that REM-firms experience a significant increase in crash risk in the following year. These findings suggest that the impact of DRO on crash risk is at least partially through REM.
The Impact of Dark Trading and Visible Fragmentation on Market Quality
Review of Finance,
Two important characteristics of current equity markets are the large number of competing trading venues with publicly displayed order books and the substantial fraction of dark trading, which takes place outside such visible order books. This article evaluates the impact on liquidity of dark trading and fragmentation in visible order books. Dark trading has a detrimental effect on liquidity. Visible fragmentation improves liquidity aggregated over all visible trading venues but lowers liquidity at the traditional market, meaning that the benefits of fragmentation are not enjoyed by investors who choose to send orders only to the traditional market.
Spillover Effects among Financial Institutions: A State-dependent Sensitivity Value-at-Risk Approach
Journal of Financial and Quantitative Analysis,
In this paper, we develop a state-dependent sensitivity value-at-risk (SDSVaR) approach that enables us to quantify the direction, size, and duration of risk spillovers among financial institutions as a function of the state of financial markets (tranquil, normal, and volatile). For four sets of major financial institutions (commercial banks, investment banks, hedge funds, and insurance companies) we show that while small during normal times, equivalent shocks lead to considerable spillover effects in volatile market periods. Commercial banks and, especially, hedge funds appear to play a major role in the transmission of shocks to other financial institutions.