Blood, Sweat and Cheers: Absurdist Crime Films and Contemporary Society

Within the crime film tradition there is a plethora of sub-genres all of which relate to crime and its consequences. However, directors Joel and Ethan Coen, Quentin Tarantino and David Lynch, all of whom create plots around crime and criminality, have been difficult to pin down and attribute to any given sub-genre. This thesis demonstrates that an absurdist philosophy can be used to effectively examine the content of the previously mentioned filmmakers. Through an analysis of these filmmakers and their better known works compelling evidence is revealed suggesting that these filmmakers may all belong to the emerging crime film sub-genre known as absurdist crime films.

Forecasting the Yield Curve of Government Bonds: A Comparative Study

For the past 20 years, researchers have applied the Kalman filter to the modeling and forecasting the term structure of interest rates. Despite its impressive performance in in-sample fitting yield curves, little research has focused on the out-of-sample forecast of yield curves using the Kalman filter. The goal of this thesis is to develop a unified dynamic model based on Diebold and Li (2006) and Nelson and Siegel’s (1987) three-factor model, and estimate this dynamic model using the Kalman filter. We compare both in-sample and out-of-sample performance of our dynamic methods with various other models in the literature. We find that our dynamic model dominates existing models in medium- and long-horizon yield curve predictions. However, the dynamic model should be used with caution when forecasting short maturity yields