This paper examines how individual religiosity at the top level of organizations affects the quality of their disclosure practices, as measured by the readability of annual reports. Our paper extends the recent accounting and finance literature that moves away from a location-based measure to an...

This study analyzes the volatility spillover effects in the US stock market (S&P500) and cryptocurrency market (BGCI) using intraday data during the COVID-19 pandemic. As the potential drivers of portfolio diversification, we measure the asymmetric volatility transmission on both markets. We...

Building on an economic model of rational Bitcoin mining, we measured the carbon footprint of Bitcoin mining power consumption using feed-forward neural networks. We found associated carbon footprints of 2.77, 16.08 and 14.99 MtCO2e for 2017, 2018 and 2019 based on a novel bottom-up approach,...

Machine learning in finance has been on the rise in the past decade. The applications of machine learning have become a promising methodological advancement. The paper's central goal is to use a metadata-based systematic literature review to map the current state of neural networks and machine...

In some applications of supervised machine learning, it is desirable to trade model complexity with greater interpretability for some covariates while letting other covariates remain a "black box". An important example is hedonic property valuation modeling, where machine learning techniques...

The use of machine learning (ML) methods has been widely discussed for over a decade. The search for the optimal model is still a challenge that researchers seek to address. Despite advances in current work that surpass the limitations of previous ones, research still faces new challenges in...

A constant in the business world is the frequent movement of customers joining or abandoning companies’ services and products. The customer is one of the company’s most important assets. Reducing the customer abandonment rate has become a matter of survival and, at the same time, the most...

Historically, exchange rate forecasting models have exhibited poor out-of-sample performances and were inferior to the random walk model. Monthly panel data from 1973 to 2014 for ten currency pairs of OECD countries are used to make out-of sample forecasts with artificial neural networks and...

Climate change, green consumers, energy security, fossil fuel divestment, and technological innovation are powerful forces shaping an increased interest towards investing in companies that specialize in clean energy. Well informed investors need reliable methods for predicting the stock prices...

In Canada, financial advisors and dealers are required by provincial securities commissions and self-regulatory organizations-charged with direct regulation over investment dealers and mutual fund dealers-to respectively collect and maintain know your client (KYC) information, such as their age...