Machine learning (ML) is a novel method that has applications in asset pricing and that fits well within the problem of measurement in economics. Unlike econometrics, ML models are not designed for parameter estimation and inference, but similar to econometrics, they address, and may be better...

Due to the non-normality of stock returns, nonparametric rank tests are gaining accceptance relative to parametric tests in financial economics event studies. In rank tests, financial assets’ multiple day cumulative abnormal returns (CARs) are replaced by cumulated ranks. This paper proposes...

Using a large database of U.S. seasoned equity offering (SEO) announcements from 2010 to 2015, we examine the effects of several explanatory variables-firm specific, macroeconomic, fixed income, and stock market variables-on the announcement period abnormal stock returns and on the longer-run...

Cross-border acquisitions by Indian companies have increased tremendously, especially during the last two decades, and the pharmaceutical industry is one of the top acquiring industries. This study verifies the relationship between cross-border acquisitions and shareholders’ wealth in the...

In this paper, we estimate the dynamic impact of unconventional monetary policy in the US on international REITs. Unlike existing studies which are limited to conventional policy tools and undertake a static approach, we use an event study approach and estimate a time-varying parameter model to...

We estimate how an acquiring firm's risk changes depending on whether the market initially judges the acquisition to be neutral, strongly negative, or strongly positive for the shareholders of the acquiring firm. We found that for an average neutral acquisition, the annualized standard deviation...

The purpose of this paper is to approach the way investors perceive the risk associated with unexpected environmental disasters. For that reason, we examine certain types of natural and technological disasters, also known as “na-tech”. Based on the existing relevant literature and historical...

The current study investigates the connectedness between US COVID-19 news, Dowes Jones Index (DJI), green bonds, gold, and bitcoin prices for the period 22 January 2020-3 August 2021. The study has employed wavelet coherency, the continuous wavelet transform, and the wavelet-based Granger...

The aftermath of the COVID-19 pandemic is not limited to human lives and health sectors. It has also changed social and economic aspects of the world. This study investigated the Islamic stock market's reaction and changes in volatility before and during this pandemic. The market model of event...

By employing the modified net buying pressure as a measure of informed option trading, this study tested whether option trading around quarterly earnings announcements is either directionally motivated and/or volatility motivated. We found evidence that is consistent with the idea that option...