There might be one reason why you’re bad at poker: you’re not playing it often enough. What if you could play a thousand rounds of poker, record every possible combination of cards and then calculate your average of losses and gains? Random numbers, like the value of cards you are dealt in a game of poker, play a central role in Monte Carlo methods. The method is even named after the famous Monte Carlo Casino in Monaco, where the uncle of one of the method’s inventors often gambled.
“Monte Carlo methods” is an umbrella term for a variety of mathematical techniques that have one thing in common: creating order from chaos by simulating as many outcomes as possible and calculating an expected average outcome. Their appeal stems from the fact that they can universally be applied to systems and models. They have been used in a variety of fields, such as in the natural sciences to simulate the evolution of galaxies or in the field of artifical intelligence to let computers make intelligent decisions in chess. The financial markets are a great field to apply the methods: with their millions of worldwide transactions everyday in New York, Tokyo or London and the countless variations of financial products, uncertainty is high and bad decisions can cost a lot of money.
Options are one of the many different financial products: they are contracts that grant the right to sell or buy an underlying asset for a specified price to the owner of the option. Monte Carlo methods can help to determine an average value of an options contract. First of all, a computer simulation calculates thousands of random yet possible price paths for the underlying asset – for instance a company’s stock that can gain or loose value. Every one of the price paths has a “payoff”, the difference between the price of the option and the value of the asset. From all these possible payoffs, the average value of the option can be generated. Based on these calculations, a reasoned decision can be made whether to buy an option or not. These steps can be used to calculate all kinds of uncertain outcomes: the prices of products in fluctuating markets like oil or to determine the risk of a bank defaulting.
Study Monte Carlo Methods with us!
Our MOOC “Monte Carlo Methods in Finance”, taught by Prof. Alberto Suarez from the Universidad Autónoma de Madrid, gives an introduction to the concepts of this technique and applies them to the pricing of European and Asian-style options. It teaches important basic concepts and skills like generating random numbers and simulations, how simple derivative products are priced and you will work with the Black-Scholes model, a mathematical model that describes financial markets. The course will also explore more advanced facets and applications, like the pricing of exotic options and modeling and quantifying financial risk in Octave. Octave is a free alternative to the industry-standard MATLAB, and most programs are portable from Octave to MATLAB.
You can already pre-enrol on our website and we will keep you posted on any updates until the course starts in January 2014. If you feel that you lack some of the business basics, you can also take our courses Introduction to Business Studies (German) and Marketing Fundamentals (German).