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...

We provide a fresh look at the performance of the stock prices of firms that launched an IPO between 2009 and 2019 and assess the role of their size, age and sector in affecting future performance. We utilize data about 1611 IPOs spanning 11 economic sectors using the event study method. We...

This paper analyzes stock returns for biotechnology firms after initial public offering (IPO) and explores the effect of social media-specifically, Twitter-on these returns. The results indicate positive yet insignificant cumulative average abnormal returns (CAARs) of 1.97% in the first 25 days...

This paper aims to investigate the effect of audit committee ethnicity, as part of the diverse cultures in Malaysia, on analysts' forecast accuracy. In addition, this study investigates further the interactions between the unique cultures in Malaysia and earnings management to determine whether...

Banks' credit scoring models are required by financial authorities to be explainable. This paper proposes an explainable artificial intelligence (XAI) model for predicting credit default on a unique dataset of unsecured consumer loans provided by a Norwegian bank. We combined a LightGBM model...

Considering the inferior volatility tracking capability of the point-data-based models, we propose using the more informative price interval data and building interval regression models for volatility forecasting. To characterize the heterogeneity of the market and the nonlinearity of...

The recent financial crisis proved that financial contagion could spread among countries resulting in disruptive effects. In this paper, by modeling and simulating banking system behavior and linkages across countries, we assess, based on data from the BIS and IMF, the possible outcome of...

Theoretically, accounting earnings could be used to estimate the intrinsic value of equity. If accounting earnings could be predicted accurately, then, so could be the value of equity, thereby, creating much less risk in equity investment. However, earnings surprises are common, and therefore so...

The COVID-19 pandemic disrupts capital markets and confuses decision makers. This event represents an opportunity to better understand how financial analysts forecast earnings. We focus on forecasts for Real Estate Investment Trusts (REITs) in the United States, since REITs are relatively...

This paper aims to contribute to the existing literature in portfolio management and strategy by investigating the performance, diversification, and hedging benefits arising from integrating Sharia-compliant stocks into a conventional portfolio. Thus, this paper tests the performance of a...