A dominating shark in the wide, open sea…

Posted on June 20, 2011 by Xiang

A strong, powerful predator in the seawaters, such as a shark, can do great damage to the other species living in the same habitat.

The same principle can be applied to our topic of discussion: high frequency trading (this will be my continuing topic for the near future). The shark here is high frequency trading, the sea being the financial markets, and the other species sharing the same habitat with the shark as all other trading participants within the market. Just as a hungry shark would effortlessly hunt down and consume, not one, or two, or three, but a whole shoal of its prey, the high frequency trading practitioners are just as hungry in the markets when it comes to volume. And my gosh are they hungry! Not only are high frequency firms dissatisfied with a dominating statistic of 70% of the overall volume in the U.S. equities market, they are now accounting for a third of all trading activity in the European markets. And it isn’t just in the developed markets that high frequency trading takes place nowadays. Emerging markets such as Brazil, Mexico and China are all engaging in such activity as well.

The operation of high frequency trading is based on rapid trading of thousands of orders systematically and automatically by computers that analyse instantaneous changes in prices and quotes.  This often results in other participants in the market, such as retail and institutional investors, chasing artificial prices, in the sense that these will not be the eventual prices at which their orders will be executed. Reasonably, debates about this topic materialized and evolved until a popular argument was formed that high frequency trading holds an “unfair” advantage.  This extra feature that other traders in the market don’t possess, namely speed, has been listed top of the pile in “unfair” advantage. But is it really unfair in the sense that other traders have not deployed enough capital to be able to implement the same technology within their corporation? Or is it unfair because high frequency traders are soaking up all the liquidity and quotes?

And so the controversy continues and grows….

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Importance of Quantitative Modelling

Posted on May 9, 2011 by Aqeela

Why quantitative modelling is important for research and financial sector?

Market competition and recent progress in data collection and data storage techniques have increased the importance of quantitative modelling. Modelling has become an important part of research and development across many fields of study, having evolved from a tool to a discipline in less than two decades. There is the need to give an overview of quantitative analysis methods and models, as quantitative modelling enables banks and insurance companies to devise their own specific risk models. It facilitates them to model changing economic and regulatory landscapes quickly and economically. Recently, quantitative modelling has received a lot of attention in the financial sector. Modelling framework and software tools enhance the performance of business. Quantitative models provide diagramming techniques to document business process for growth.

Most people are not experts in predicting the outcomes of the systems governed by stochastic process and quantitative modelling. Although many software tools exist to model such processes, hardly any attention is paid to the analysis of quantitative aspects to support or optimise the outcomes.

A substantial number of users don`t have confidence in the assumptions of the models. High quality solutions are often misused and may create other problems (e.g. making the organisation more resistant to the introduction of future changes).

In the current era, when new financial modelling and mathematical finance techniques appear, one of the first questions inevitably is: why one more and which one quantitative model in particular? The answer springs directly from job experience of mathematicians working as quantitative analysts in financial institutions. Indeed, one of the major challenges any financial engineer has to cope with is the practical implementation of mathematical models for pricing derivative securities.

The method “Monte Carlo Simulation” calculates the value that is at risk of being lost from a change in interest rates using Monte Carlo simulations. This method enables financial institutions to compute the sensitivity of a single instrument or an entire portfolio to any number of interest rate changes.

One of the most important quantitative models is “Interest Rate Modelling”. This enables the financial market practitioners, academics and research students to develop their own interest rate models to price bonds and derivatives using existing models, and to design generic pricing frameworks.

OptiRisk Systems, in collaboration with Fraunhofer ITWM & CARISMA, organises training workshops to provide the deep knowledge on Monte Carlo Methods and Interest Rate Modelling, which is required by financial consultants as well as academics.

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