Risk assessment
Our fund is managed electronically and watched continuously by several assistants. Every trader has clear positions limits and a clearly established risk/return goals. Quantitative Risk assessment techniques are used in order to simulate VaR and control the third and fourth moments of funds returns distribution, as well as globally, keeping track of diversification and antidiversification effects.
The abundance of information that circulates through the markets is one of the main characteristics of the financial markets. An efficient use of active management is impossible without the quantitative processing of these data in a special way.
Using advanced quantitative models means taking objective view of information, same facts being dealt with in the same way. The use of such formal decision-support tools keeps the fund returns systematic and makes it able to get the most from all the available information. A framework of forecasts creation made using a handful of variables, paying a close attention to risk managment when constracting portfolios, and endeavouring to implement strategies efficiently while cutting costs is both cogent and effective. The model approach is the most effective when it is underpinned by economic and financial theory. With the theoretical grounding, it is possible to make sense of the data collected on the market. The black-box sysndrome, whereby a steasy stream of information is analysed without prior critical analysis is not synonymous with quantitative trading.
Knowing what models can't do is as important to understand as what it produces. Knowing if the perspective recommendations are relevant in a particular maket context is also very imporant. All this makes quantitative management successive.
A quant will always seek to interpret the flow of information moving the market. This objective is a view of the challenges involved and keeps the choice of tools of painstaking priority.