We propose a new no-change benchmark to evaluate forecasts of series that are temporally aggregated. The new benchmark is the last high-frequency observation and reflects the null hypothesis that the underlying series, rather than the aggregated series, is unpredictable. Under the random walk...

I propose an alternative weighting mechanism for equity mandates based on the statistical significance of the factor loading on the benchmark. Specifically, the weight of each security entering the active portfolio is directly proportional to the t-statistic of the factor loading ($\beta$) with...

Global firms finance themselves through foreign subsidiaries, often shell companies in tax havens, which obscures their nationality in aggregate statistics. We associate the universe of traded securities with their issuer's ultimate parent and restate bilateral investment positions to better...

I show that ambiguity-averse decision functionals matched with the multiple-prior learning model are more robust to model misspecification than the standard expected utility with Bayesian learning. However, these criteria may fail to deliver robust decisions because the multiple-prior learning...

This paper proposes new estimators for the propensity score that aim to maximize the covariate distribution balance among different treatment groups. Heuristically, our proposed procedure attempts to estimate a propensity score model by making the underlying covariate distribution of different...

This paper reviews methods that have been employed to estimate poverty in contexts where household consumption data are unavailable or missing. These contexts range from completely missing and partially missing consumption data in cross-sectional household surveys, to missing panel household...

Crude oil prices are particularly volatile. Managing such price risks is vital for participants in financial markets, in particular the oil market. In the perspective of a long position, we conduct an in-depth study of popular existing statistical approaches as well as a recently developed...

Purpose: Most of the managers in business organizations do not place a great significanceover the statistical methods and statistical thinking, because they are often convinced thatstatistical thinking would not contribute towards adding any value to management and tobusiness related decision...

This study assesses the classification accuracies of two statistical methods namely, multiple discriminant analysis and logistic regression approach in default prediction. It uses a small sample of 32 India firms listed on Bombay Stock Exchange for the sample period of six years over 2010-11 to...