Research Interests
My research interests center around multivariate time series. My current research involves incorporating regularization methods into a vector autoregression framework [1], [2]. My other projects are oriented toward financial applications, specifically non-Gaussian measures of dependence in finance [3] and estimating windows of local stationarity of stock returns in a pairs trading application [4]. Through my research, I've gained a great deal of insight as to R software development as well as high performance statistical computing.
Education
Cornell University
PhD. Statistics
University of Wisconsin-Madison
M.S. Economics
American University
B.S. Economics, B.S. Mathematical Statistics
B.S. Economics, B.S. Mathematical Statistics
2016
2010
2009
Publications
| [1] | VARX-L Structured Regularization for Large Vector Autoregression. International Journal of Forecasting, 2017. |
| [2] | Hierarchical Vector Autoregressions. , 2014. |
| [3] | Non-Gaussian Measures of Statistical Dependence. In Financial Signal Processing and Machine Learning, Wiley |
| [4] | Locally stationary vector processes and adaptive multivariate modeling. In Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on, pages 8722-8726, 2013. |
Honors and Awards
Applied Finance with R Conference: Best Student Paper Award
2015
Structured Regularization for Large Vector Autogressions with Exogenous Variables
Google Summer of Code Fellowship
2014
Mentoring organization: R-Project
Project: Dimension Reduction Methods for Multivariate Time Series
Amazon
2014
AWS in Education Research Grant
Cornell University
2011
University Fellowship
University of Wisconsin-Madison
2010
Economics Department Scholarship
American University
2009
Summa Cum Laude, Phi Beta Kappa, University Honors
Professional Experience
A quantitative hedge fund
May-August 2015
Quantitative Analyst Intern
Zurich Insurance Group
May-August 2011
Predictive Modeling Intern