Common Market Practice
The backbone of quantitative finance is the so-called Brownian Motion which can be viewed as a temporal concatenation of normal distributions. Inherent to this approach are assumptions of symmetry, thin tails, and outlier sensitivity etc., all of which do not typically align with reality.
The normal distribution is symmetric, and if centred at the current point of the market, it would imply that the probability of a rising and likewise of a falling market is 50%. That is, directional forecasts for future market behaviour would simply be equivalent to a random toss of a coin. The use of such a distribution to calculate things such as Value at Risk is, likewise, fraught with difficulties.
In the context of risk management the shortcomings of such a model are so pronounced that specialists within universities, banks and insurance companies all over the world have exerted much effort to find adequate techniques or alternatives to better capture market uncertainty. Although some of these endeavours appear to have generated more satisfactory models in the short term, over the long term many of them have proved to be unstable and thus unreliable.
The Efficient Market Hypothesis states that if all relevant information has been incorporated into a financial market efficiently, then changes in market prices will be purely random and unpredictable. Despite its abstract appeal, the Efficient Market Hypothesis has been shown to be an unwarranted assumption that is inapplicable in many real world markets.
Such features suggest that a fresh alternative to current practice is required if market behaviour is to be captured adequately.
Read more: Overcoming Market Challenges