Financial analysts assume that the reliability of predictions derived from regression analysis improves with sample size. This is generally true because larger samples tend to produce less noisy results than smaller samples. But this is not always the case. Some observations are more relevant...

It is common practice to forecast social, political, and economic outcomes by polling people about their intentions. This approach is direct, but it can be unreliable in settings where it is hard to identify a representative sample, or where subjects have an incentive to conceal their true...

Investors sometimes have strong convictions that a distinctive economic regime will prevail in the period ahead and therefore would like to form a portfolio that reflects the expected returns, standard deviations, and correlations of assets during such a regime. To do so, they typically isolate...

Chapter 1. Introduction -- Part I -- Chapter 2. Production Economics and Economic Efficiency (Mónica Meireles) -- Chapter 3. Data Envelopment Analysis: A Review and Synthesis (Ana S. Camanho) -- Chapter 4. Stochastic Frontier Analysis: A Review and Synthesis (Mara Madaleno) -- Part II --...

In this paper, we run regression analyses to explain voluntary turnover intentions with data from more than 5,000 employees and with about 250 explanatory variables. The findings of our multi-factor approach highlight the fact that previous empirical research might have over-estimated the impact...

Random forests are invariant and robust estimators that can fit complex interactions between input data of different types and binary, categorical, or continuous outcome variables, including those with multiple dimensions. In addition to these desirable properties, random forests impose a...

In view of the failure of high profile companies like Circuit City and Linens n Things, Financial distress or bankruptcy prediction has generated much interest recently. This research develops and tests a model for the prediction of bankruptcy of retail firms. We use accounting variables such as...

This report focuses on the forecast of the number of monthly cross-border deals in the European Union. We propose a new model to improve the forecasting properties of a count model of Foreign Direct Investment deals in EU, by taking into account past trends in high-frequency (daily) deal data...

A common problem in applied regression analysis is that covariate values may be missing for some observations but imputed values may be available. This situation generates a trade-off between bias and precision: the complete cases are often disarmingly few, but replacing the missing observations...

Many sophisticated investors rely on scenario analysis to select a portfolio. These investors define prospective economic scenarios, assign probabilities to them, translate the scenarios into expected asset class returns, and select the portfolio with the highest expected return or expected...