More and more data are observed in form of curves. Numerous applications in finance, neuroeconomics, demographics and also weather and climate analysis make it necessary to extract common patterns and prompt joint modelling of individual curve variation. Focus of such joint variation analysis...

This paper shows how asymptotically valid inference in regression models based on the weighted least squares (WLS) estimator can be obtained even when the model for reweighting the data is misspecified. Like the ordinary least squares estimator, the WLS estimator can be accompanied by...

We investigate, if it pays off for a company to invest into complex swing option algorithms. We first introduce least squares Monte Carlo as a complex valuation algorithm and explain in detail how it works. Using a simulation study and two backtest scenarios we compare the output of this method...

Prior literature on corporate governance and performance provides mixed evidence on the impact of various corporate governance measures on performance indicators. However, most of literatures adopt the Ordinary Least Square (OLS). This method is based on the central tendency, which may not...

We show that the standard equation-by-equation OLS used in performance evaluation ignores information in the alpha population and leads to severely biased estimates for the alpha population. We propose a new framework that treats fund alphas as random effects. Our framework allows us to make...

Few would contest that teachers are a very important determinant of whether students learn in school and how to improve teacher performance has been the focus of much policy debate in rich and poor countries. This paper examines how incentives, both pecuniary and non-pecuniary, correlate with...