Probability Theory

The corner stones of quantitative finance are extremely statistical, and obviously along side it mathematical. Using various techniques involving intense probability theory such as Markov Chains- strategies are developed, whether it be StatArb (statistical arbitrage being long on certain securities and short on others), price pattern detection or using the infamous Monte Carlo Simulation to calculate random sample paths of a given security based on underlying fundamental conditions such as interest rates.
Seemingly most of these methods are used today by massive hedge funds that are often leveraged more than 15:1 on the sole basis of a "superior model" or a "cant fail" strategy, lacking the adequate risk management to protect them from any "black swan event".

Enter Paul Wilmott, a modern day quant genius. He has developed the CQF or Certificate in Quantitative Finance and has for many years warned the market of a "mathematical led meltdown". The 2007-08 crisis springs to mind with specific reference to CDO's and the repackaging of mortgages solely developed by mathematicians.

Post crisis Mr Wilmott has developed a "Financial Modelers Manifesto", containing a hipocratic oath that embodies the problems we face with regards to the power and clout these big hedge funds have, however with power comes responsibility. Taken from the Manifesto, the hipocratic oath is as follows:

~ I will remember that I didn't make the world, and it doesn't satisfy my equations.

~ Though I will use models boldly to estimate value, I will not be overly impressed by mathematics.

~ I will never sacrifice reality for elegance without explaining why I have done so.

~ Nor will I give the people who use my model false comfort about its accuracy. Instead, I will make explicit its assumptions and oversights.

~ I understand that my work may have enormous effects on society and the economy, many of them beyond my comprehension.

One has to agree there is a place in this world for financial modeling, however to confuse the model with real life and try to model human behavior is to assume the human race obeys mathematical rules....absurd!


Again one has to look at success rates of traders. Sure some of them have had a good run, but 98% of them have not been able to sustain a long successful track record and the inevitable blow up occurs. These big players often double up on bets going against them, never practicing sound risk management principles. The phrase 'Stop Loss' springs to mind.


If we consider a sample of 10 000 traders, assuming there is a 50% chance of making a profit or loss per year we find after 1 year we only have 5000 traders left in the black, 2500 traders after two years, 1250 after three years, 625 after four and only 312 successful successful traders after the fifth year. Not very impressive is it?


Survival of the fittest or survival of the safest? 

Great risk offers great reward but it also offers unemployment. There is a culture within financial markets that does not account for risk related returns. Maybe we should change the scale?


The Young Economist