Statistical Models Commons^™

Sparse Model Selection Using Information Complexity, Yaojin Sun

Doctoral Dissertations

This dissertation studies and uses the application of information complexity to statistical model selection through three different projects. Specifically, we design statistical models that incorporate sparsity features to make the models more explanatory and computationally efficient.

In the first project, we propose a Sparse Bridge Regression model for variable selection when the number of variables is much greater than the number of observations if model misspecification occurs. The model is demonstrated to have excellent explanatory power in high-dimensional data analysis through numerical simulations and real-world data analysis.

The second project proposes a novel hybrid modeling method that utilizes a mixture …

Essays In Financial Economics: Announcement Effects In Fixed Income Markets, James J. Forest

Doctoral Dissertations

ABSTRACT ESSAYS IN FINANCIAL ECONOMICS: ANNOUNCEMENT EFFECTS IN FIXED INCOME MARKETS PHD IN FINANCE MAY 2018 JAMES J FOREST B.A., FRAMINGHAM STATE UNIVERSITY M.S., NORTHEASTERN UNIVERSITY Ph.D., UNIVERSITY OF MASSACHUSETTS – AMHERST Directed by: Professor Hossein B. Kazemi This dissertation demonstrates the use of empirical techniques for dealing with modeling issues that arise when analyzing announcement effects in fixed income markets. It describes empirical challenges in achieving unbiased and efficient parameter estimates and shows the importance of modelling a wide range of macroeconomic announcement effects to avoid omitted variable bias. Employing techniques common in Macroeconomics, financial market researchers are better …