We develop a discrete-time affine stochastic volatility model with time-varying conditional skewness (SVS). Importantly, we disentangle the dynamics of conditional volatility and conditional skewness in a coherent way. Our approach allows current asset returns to be asymmetric conditional on...

Lawsuits brought pursuant to section 10(b) of the Securities and Exchange Act depend on the reliability of a statistical tool called an event study to adjudicate issues of reliance, materiality, loss causation, and damages. Although judicial acceptance of the event study technique is pervasive,...

Following recent advances in the non-parametric realized volatility approach, we separately measure the discontinuous jump part of the quadratic variation process for individual stocks and incorporate it into heterogeneous autoregressive volatility models. We analyze the distributional...

Using a sample of 97 stock return anomalies, we find that anomaly returns are 50% higher on corporate news days and are 6 times higher on earnings announcement days. These results could be explained by dynamic risk, mispricing via biased expectations, and data mining. We develop and conduct...

The issue of long memory, though has important theoretical and practical implications, has not received much attention in India. This article examines the issue of long memory in mean of the stock returns by employing a set of sophisticated time-series tests including a bias reduced log...

This paper investigates the robustness of existing long-run event study methodologies using the Asia-Pacific security market data. In doing so, the study employs the buy-and-hold abnormal return approach and the calendar time portfolio method to measure the return anomalies. Since each of these...

The speed of convergence of the truncated realized covariance to the integrated covariation between the Brownian parts of two semimartingales is heavily influenced by the presence of infinite activity jumps with infinite variation. Namely, the two small jumps processes play a crucial role...

This is the second paper presenting noise-reduced, stable correlations for long-term risk measurement. We smooth time series using Singular Spectrum Analysis (SSA) and then form the correlations from these smoothed time series. These correlations have superior time stability and are cleaned of...

This paper finds positive evidence of return predictability and investment gains for individual corporate bonds for an extended period from 1973 to 2017. Our sample consists of both public and private company bond observations. We have implemented multiple machine learning methods and designed a...