SmartETF

SocGen and the Perception of Risk

As you touch in the last sentence the root of the problem is in measuring/understandin... risk. The problem is deeper than the realizing most traders don't know Value-at-Risk (VaR) or Standard Deviation (σ); it didn't seem to help LTCM. The problem stems from the foundation of risk measurement, Normal Distributions. All three popular risk modeling techniques (VaR, Standard Deviation, Semi-Variance) are all measuring risk using a normal distribution (arithmetic calculation); this is the flaw (should be a Stable Distribution which is logarithmic).

Using a normal distribution the probability of return at 1σ is 68.3%, 2σ is 95.4% and 3σ is 99.7%; so what is 5σ? The odds of a 5 sigma event are one in 7000 years! In reality they occur every 3-4 years on average and we have had many outliers outside the sacred 3σ level many times in the past 12 months. Furthermore, a 22σ event like the 87’ crash should occur once in three lifetimes of the universe. Normal distributions are the staple at all the major financial and educational institutions and professional associations like PRMIA, GARP, CFP, FPA and IMCA.

Had these managers used Stable Distributions they could have seen the actual risk more accurately; especially in conjunction with Student-t and through more sophisticated data management techniques such as GARCH (Generalized Auto-Regressive Conditional Heteroscedasticity).

It’s time for risk managers and money managers to open there ears, the oracles of these original models and techniques are claiming its time to change. William Sharpe states “the CAPM Theory is ready for a makeover”, “tail-risk is ignored by Mean-Variance Analysis”, and “the new approach doesn’t rely on a normal distribution”. Benoit Mandelbrot, co-founder of Chaos Theory and creator of Fractal Geometry, combines the best of breed mathematics to create Extreme Value Theory; a substantial upgrade in risk measurement and portfolio optimization. Maybe its time to revamp what we teach and preach!