An important concern is that algorithms can inadvertently discriminate against minority groups and reinforce existing inequality. Typically, the worry is that when classification algorithms are trained on a dataset that itself reflects bias this may reinforce bias. However, in the world of...

There exists significant hype regarding how much machine learning and incorporating social media data can improve forecast accuracy in commercial applications. To assess if the hype is warranted, we use data from the film industry in simulation experiments that contrast econometric approaches...

The principal objective of this research study was to investigate the impact of the Great Economic Recession of 2008 on national banks' equity investment valuations and create an empirical model for predicting national banks' financial failure in the United States. The focal period of the study...

Forecasting returns for the Artificial Intelligence and Robotics Index is of great significance for financial market stability, and the development of the artificial intelligence industry. To provide investors with a more reliable reference in terms of artificial intelligence index investment,...

Academics and practitioners have long recognized the importance of a firm’s industry membership in explaining its financial performance. Yet, contrary to conventional wisdom, recent research shows that industry-specific profitability forecasting models are not better than economy-wide models....

We study the coordination problem of a two-firm supply chain in which firms simultaneously choose a capacity before demand is realized. We focus on the role that (a lack of) common knowledge of demand forecasts has on firms' ability to align their capacity decisions. When forecasts are not...

The scientific community has demonstrated that for the bankruptcy prediction, different techniques have different advantages on different data sets and different feature selection approaches. This subject has attracted a lot of research interests as it is one of the major preoccupation of...

We investigate the circumstances in which business cycle forecasting is beneficial for business by addressing both the short-run and the long-run aspects. For an assessment of short-run forecasting we make a distinction between using publicly available information of cycle probabilities and the...

In this paper we develop a sales forecasting model for a small sized business unit focused on exports. Through a choice of internal explanatory variables in the organization we develop an econometric sales forecasting method, and compare its outputs with simpler univariate forecasting techniques...

The aim of this paper is to present corporate default prediction models constructed in the specific market conditions that prevail in the Republic of Serbia, and to compare their prediction accuracy with the most frequently used model – Altman's Z-score. Many authors have constructed models...