Matthew Sekerke

Matthew Sekerke

Matthew Sekerke is a Bates Group expert and consultant with over fifteen years of financial services industry experience. A capable quant, modeler and programmer, he has earned advanced degrees in Economics, Mathematics and Finance. Mr. Sekerke is the author of Bayesian Risk Management: A Guide to Model Risk and Sequential Learning in Financial Markets (Wiley Finance, 2015), a critical essay on how financial time series models break down over time, and what can be done to monitor and manage the associated operational risks.


Credentials

Experience

Ndogenous, President, 2017-Present

Johns Hopkins Institute for Applied Economics, Global Health, and the Study of Business Enterprise, Fellow,2016-Present

PwC, Director, 2015-2017

Alvarez & Marsal, Senior Director, 2012-2015

Navigant Economics, Associate Director, 2008-2012

Chicago Partners, Consultant, 2004-2008

Prof. Steve H. Hanke, Johns Hopkins University, Chief of Staff/Research Associate, 2000-2003

Education

Durham University Business School, Ph.D. in Economics, expected 2021

Columbia University Fu Foundation School of Engineering, M.S. in Applied Mathematics, expected 2021

University of Chicago Booth School of Business, M.B.A. in Analytic Finance, Econometrics & Statistics, Entrepreneurship, Accounting, and Finance (with Honors), 2012

Johns Hopkins University, M.A., History, 2007

Johns Hopkins University, B.A., Mathematics & Economics (dual major), 2004

Professional Memberships

American Economic Association (AEA)

American Finance Association (AFA)

Society for Industrial and Applied Mathematics (SIAM)

Institute of Electrical and Electronics Engineers (IEEE)

CFA Charterholder

Global Association of Risk Professionals

  • Certified Energy Risk Professional (ERP) – 2011: covers energy risk in physical and financial markets
  • Certified Financial Risk Manager (FRM) – 2010: covers spectrum of risk management and capital regulation
Skills

Computing:

  • Python (numpy, scipy, pandas, scikit-learn, statsmodels, TensorFlow)
  • R (survival, mstate, various econometrics and Bayesian inference toolkits, visualization/choropleths)
  • MATLAB (predictive Bayesian model programming, especially for Bayesian Risk Management; optimization)
  • SAS (macro programming, SAS/STAT, relational databases, workflow management with Enterprise Manager)
  • Less frequent: Stata, Eviews (econometrics), VBA (data transformation), SQL Server (relational databases)

Languages:

  • German (high proficiency)
  • French
  • Italian
  • Spanish
  • Portuguese (reading proficiency)
Automat:ee