Month: March 2011

Legends of the Monte Carlo Technique

A recent blog in Investment Week that mentioned the history of Monte Carlo simulation and its use in finance led me to take a harder look at what I thought I knew about how financial risk analysis was launched.

I had long believed that Monte Carlo simulation was developed by a team working at Los Alamos Scientific Laboratory during the 1940s.  The blog mentioned Stanislaw Ulam playing solitaire. Both turned out to be true.  Ulam was part of the team working on nuclear weapons at Los Alamos, and he prefaced his own account of his inspiration from solitaire by saying,"After spending a lot of time trying to estimate them by pure combinatorial calculations, I wondered whether a more practical method than "abstract thinking" might not be to lay it out say one hundred times and simply observe and count the number of successful plays. This was already possible to envisage with the beginning of the new era of fast computers. . . ."  He and John von Neumann began to work on the calculations that eventually became essential to the Manhattan Project. 

So far, so true.  But how did Monte Carlo simulation enter the finance arena?  The blog fast forwards thirty years to 1976 and Roger G. Ibbotson and Rex A. Sinquefield with their publication of "Stocks, Bonds, Bill, and Inflation: Simulations of the Future."

True––but not so fast.  In the intervening years and especially during the 1950s, there was considerable development and dissemination of Monte Carlo simulation technique by the U.S. Air Force and the Rand Corporation.  This brought the technique closer to the realm of finance, but we’re not there yet.  

The earliest publication I can dig up on Monte Carlo and financial risk simulation is David B. Hertz’s "Risk Analysis in Capital Investment," published in the Harvard Business Review in 1964.

Harvard Biz
From Harvard Business Review, circa 1964

Okay, the 1960s.  That still leaves unattended by history almost fifty years, the advent of desktop computing, the commercialization of Monte Carlo software, acceleration through parallel computing, and the wafting up on the horizon of cloud computing.

So, in the words of too many finance journals, "more research is necessary."


Revenues are not the only ‘profit’ to consider when investing in rail travel

Slovakian RailThe UK government has just launched its consultation on the proposed high-speed rail line between London and Birmingham, which will cut the journey time by around 50 minutes if it goes ahead.  Opponents of the scheme believe the £17 billion it is forecast to cost would be better spent updating the West Coast mainline, while supporters say it will be a major boost for the UK economy.

Faced with its own investment dilemma, the Slovak Rail Company (SRC) used @RISK to model potential train travel over the next 30 years. The organisation knew that if it was to continue to provide a viable rail transport system, its rolling stock required modernisation, with end-of-life vehicles being replaced by double-deck electric or diesel units.  However, a key risk in undertaking this task was that the dwindling passenger numbers opting for rail travel would result in revenues not being high enough to warrant the investment in new carriages.

@RISK was first used to ascertain whether buying new rolling stock would have a positive or negative outcome on SRC’s revenues.  But SRC also believed its revised strategy of new carriages and upgraded timetables would make train travel more attractive (compared to travel by car which was seeing a seven to eight percent increase per year).  Therefore it also used @RISK to investigate the socio-economic impact of people taking more journeys by train.

Despite some uptake in passenger journeys as a result of new rail carriages, the revenue modelling showed that the rail company would not be profitable and the system would therefore need subsidies.  However, using risk analysis to investigate the socio-economic impact of the investment showed that the rail upgrade was worthwhile because it resulted in advantages in terms of better quality journeys, fewer car accidents and less pollution.

As a result of SRC using @RISK to inform its decision-making process, the European Union and Slovakian Ministry of Transport (who are co-funding the project with SRC) approved the investment in new rolling stock.  Some carriages are now in operation, and all 32 new units will be in use by 2013.

Craig Ferri
EMEA Managing Director of Risk & Decision Analysis

March 2011 – Worldwide Training Schedule

Palisade Training services show you how to apply @RISK and the DecisionTools Suite to real-life problems, maximizing your software investment. All seminars include free step-by-step books and multimedia training CDs that include dozens of example models.

North America
Houston, TX: 15-16 March 2011
Decision-Making and Quantitative Risk Analysis using @RISK

Amsterdam: 29-30 March 2011
2011 Palisade Risk Conference

São Paulo, Brasil: 29 a 31 de março de 2011
Avaliação do Risco para Usuários do @RISK e DecisionTools Suite

Buenos Aires, Argentina: 21 al 23 de marzo de 2011
Evaluación de Riesgo para Usuarios Principiantes/Intermedios

Melbourne: 30-31 March 2011
Decision-Making and Quantitative Risk Analysis using @RISK