Trading Financial Markets successfully
During the GFC almost all models used to quantify risk failed badly. Not only did they not anticipate the risk, the size of the market moves were simply beyond the scope of these models, not to mention that they failed to foreshadow the wide and very sudden changes that occurred. Given that so many financial institutions had to be rescued, regulation of the entire industry, especially in the US and in Europe, has been tightened and is being tightened still further. The purpose is to strengthen the equity base of financial institutions and to ensure prudent management of funds.
The implication is that the requirements in areas such as risk and asset management will substantially increase, thus demanding much more reliable forecasts of chance and risk. This, in turn, would not only lead to improved hedging techniques but also result in better return optimisation.
QanSystem is in stark contrast to common market practice, which assumes normally distributed data and Brownian motion, ignoring bank-specific adjustments to make their models correspond a bit more with reality. This implies that QanSystem facilitates exploitation of arbitrage opportunities against positions taken by competitors such as banks and other market participants, including insurance companies, hedge funds, mutual funds and asset management companies, using standard methods.
We believe that none of the models known and applied in finance today adequately describe reality. We therefore use non-parametric techniques, with no model or any other assumptions, to forecast market direction, to price options, and much more. This is a mathematically intricate task and, to our knowledge, has not been accomplished previously. With our approach, we are able to capture not only regular market behaviour more realistically but also to uncover very unfamiliar patterns. For example, a highly asymmetric distribution could reflect a strong directional bias suggesting limited market potential in one direction as opposed to possibly huge movements in the opposite direction.