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University of Minnesota - Twin Cities Curriculum Vitae Fall 2016

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Page 1: University of Minnesota - Twin Cities Curriculum Vitae Fall 2016

University of Minnesota - Twin CitiesDepartment of Economics Placement Director4-101 Hanson Hall Manuel Amador1925 Fourth Street South (612) 624-4060 orMinneapolis, Minnesota 55455 (612) 204-5781U.S.A. [email protected]

Placement Coordinator(612) 625-6353 Catherine Bach(612) 624-0209 FAX (612) 625-6859

[email protected]

Curriculum VitaeFall 2016

ALEXANDER GARIVALTIS

Personal DataAddress Contact Information4-101 Hanson Hall Cell: (612) 800-24181925 Fourth Street South E-mail: [email protected], MN 55455 URL: garivaltis.weebly.com

Citizenship: USA

Major Fields of Concentration

Financial Econometrics, Algorithmic Game Theory, Computational Economics

EducationDegree Field Institution YearPh.D. Economics University of Minnesota (expected) 2017M.A. Economics University of Minnesota 2015M.S. Mathematics Northern Illinois University 2011B.S. Mathematics Northern Illinois University 2010

DissertationTitle: “Essays on Universal Portfolios”Dissertation Advisors: Professor Aldo Rustichini and Professor David RahmanExpected Completion: Summer 2017

References

Professor Aldo Rustichini (612) 625-4816 Department of [email protected] University of Minnesota

4-101 Hanson HallProfessor David Rahman (612) 625-3525 1925 Fourth Street South

[email protected] Minneapolis, MN 55455

Professor Jan Werner (612) [email protected]

Page 2: University of Minnesota - Twin Cities Curriculum Vitae Fall 2016

Curriculum VitaeGarivaltis

Page 2

Honors and Awards

2013 - 2015 Distinguished Teaching Award, Department of Economics, University of Minnesota,Minneapolis, Minnesota

2012 CLA Graduate Fellowship, Department of Economics, University of Minnesota, Minneapolis,Minnesota

Teaching Experience

2015 - 2017 Instructor, Department of Economics, University of Minnesota, Minneapolis, Minnesota.Taught Principles of Microeconomics and the Major Project Seminar.

2015 - 2016 Writing Assistant, Department of Economics, University of Minnesota, Minneapolis, Minnesota.Writing Assistant for Growth and Development and the Major Project Seminar.

2013 - 2015 Teaching Assistant, Department of Economics, University of Minnesota, Minneapolis,Minnesota. Led recitation sections for Intermediate Microeconomics, Principles ofEconometrics, and Introduction to Econometrics.

Papers

“Learning to Trade Prophetically,” job market paper.

Work in Progress

“Kelly Gambling on Hidden Markov Models of Stock Price Fluctuations”

Computer Skills

Fortran, C/C++, MATLAB, Stata/Mata, LaTeX, Python, Mathematica, Maple

Abstracts

“Learning to Trade Prophetically”

I consider an algorithmic trader who tries to approximate the performance of a “prophet” that sees the future, butis restricted to constant portfolio rebalancing rules. Nature picks daily stock prices that maximize the prophet’sexcess log-wealth in the long run; the trader plays a robust strategy that minimizes this spread in the worst case.Amazingly, the excess growth rate of the prophet’s capital converges uniformly to 0. The subgame perfectequilibrium has a closed form that is practical to compute, even in a setting with many assets. I generalize the gameto incorporate arbitrary linear constraints on nature’s moves. This bolsters real-world performance, as certain typesof extreme fluctuation are basically known a priori to be impossible. I backtest the algorithm on historical stockprices.

“Kelly Gambling on Hidden Markov Models of Stock Price Fluctuations”

Leonard Baum’s seminal (1970) paper on Hidden Markov Models (HMMs) promised an application to “stockmarket behavior” in a future paper with James Simons, but it never appeared. Famously, Simons founded the hedgefund company Renaissance Technologies in 1982. I backtest a Kelly (conditionally log-optimal) gambling procedureon historical stock prices that is perpetually guessing the hidden market sentiment (Bullish, Bearish, Neutral). Thestate is persistent, but not observed directly — it must be inferred (along with HMM parameters) from signals like

Page 3: University of Minnesota - Twin Cities Curriculum Vitae Fall 2016

Curriculum VitaeGarivaltis

Page 3

volume, returns, intraday range, weather, and so forth. The algorithm watches for short-term anomalies and tries toreject the random walk hypothesis in favor of an HMM. Some versions of the system are able to smell a rat duringthe financial crisis of 2007-2009.