About

Burns Statistics

Burns Statistics develops rigorous statistical methods and software for portfolio optimization, risk analysis, and performance attribution.

Experience

Consulting

Pat has worked, mainly in finance, for over thirty years both as a consultant and an employee. We are currently not in the market for new consulting jobs.

Software development

Pat was a lead developer of S-PLUS, the precursor to the R language, in its early years. His tasks included adding functionality (such as principal components and robust estimation in several settings), finding and fixing bugs, and documentation. He has been a user of R for over 25 years.

Finance

Years ago Pat was an employee of Schroder Salomon Smith Barney (Citigroup) in London for four years. While there, he developed statistical models for equities — both client-facing and proprietary. More recently Pat has been an employee of Manulife Investment Management in its investment risk and construction solutions team. During the interim there were years of consulting to various financial firms.

Education

In 1988 Patrick received a PhD in statistics from the University of Washington in Seattle. His thesis topic was the robust analysis of designed experiments — that is, developing techniques that perform well even when outliers exist in the data.

Specialties include:

  • Programming in the R language
  • Statistics, including quantitative finance
  • Solving difficult problems via heuristic optimization (genetic algorithms and simulated annealing).

Portfolio probe

Portfolio Probe is software that does two things:

  • generates random portfolios
  • does portfolio optimization

Random portfolios will transform the fund management industry.  They:

  • provide information about fund performance that is actually useful
  • help improve the strategies of funds
  • have many other possible uses

Publications

  • Burns, P. (2012). Tao Te Programming.
  • Burns, P. (2009, 2011). The R Inferno.

  • Burns, P. (2007). Bullseye. Professional Investor, March issue.
    A very similar version is available as Dart to the Heart.

  • Burns, P. (2007). Random Portfolios for Performance Measurement. Appears in Optimisation, Econometric and Financial Analysis, E. Kontoghiorghes and C. Gatu, eds. Springer.
    This is based on the working paper Performance Measurement via Random Portfolios but has some additional material.

  • Burns, P. (2000). Constructing Multinational Macroeconomic Factor Models: Experience from Europe. Journal of Asset Management, 1 #2, p121–131.
  • Burns, P. (1998). S Poetry.

  • Burns, P., Engle, R., & Mezrich, J. (1998). Correlations and Volatilities of Asynchronous Data. The Journal of Derivatives, 5 number 4.
    This is derived from Discussion Paper 97-30 at the University of California, San Diego Department of Economics.

  • Fraley, C. and Burns, P. (1995). Large-scale Estimation of Variance and Covariance Components. SIAM Journal on Scientific and Statistical Computing, 16, number 1.

  • Burns, P. (1991). A Graphical Display for Choosing a Transformation. Proceedings of the 23rd Symposium of the Interface: Computing Science and Statistics, p42–45.

  • Burns, P. (1990). The L1 Solution Set in Two-way Tables. Utilitas Mathematica, 37 p233–250.