About Burns Statistics       Burns Statistics is the consulting and software vehicle for Patrick Burns. You can read his blog at: http://www.portfolioprobe.com/blog Specialties are programming in the R language, quantitative finance, risk management, and solving difficult optimization problems in any field via genetic algorithms and simulated annealing. Upcoming events involving Burns Statistics History of news from Burns Statistics Some Presentations 2011 December. "Portfolio Optimisation Inside Out" 2011 August. "Random Input Testing using R" 2010 November. "Effective Backtesting" presented at The Thalesians. 2010 June. "Optimising and Constraining Portfolio Distances" or "Goldilocks and the 3 Little Pigs" (pdf) presented at The London Quant Group. 2010 May. "Portfolio Probe: Changing Fund Management" (pdf) presented at The LondonR Group. 2009 June. “A Brief Overview of R” The portion of the presentation immediately below that pertains to R. 2009 June. “Using Random Portfolios with R” presented at the Thalesians, London. A video of the lecture is available the Thalesians website. 2009 April. “Random Portfolios: Practice and Theory” (pdf) given at R/Finance 2009 Chicago. 2009 March. "3.5 Reasons to Switch from Excel to R" (pdf) presented at The LondonR Group. 2006 September. “Portfolio Analysis with Random Portfolios” (pdf) UKSIP, London. Publications See also Working Papers. Patrick Burns on Google Scholar. 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., R. Engle and J. Mezrich. (1998). Correlations and Volatilities of Asynchronous Data. The Journal of Derivatives. 5 number 4. (abstract) This is derived from Discussion Paper 97-30 at the University of California, San Diego Department of Economics Fraley, C. and P. Burns. (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. Experience Consulting Patrick has over a decade of experience as a consultant in the financial and medical industries. Assignments have included analysis of equity data with R, building GARCH modules in S, tutoring S and statistics, automated trading, risk management, and evaluating the efficacy of medical devices. Finance In addition to his consulting experience, Patrick 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. He also wrote in-house software for numerous applications including portfolio optimization and risk management. Software Development Patrick was a lead developer of S-PLUS 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. 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. Go to Burns Statistics Home.