Creation of Advanced Trading Systems

Creation of Advanced Trading Systems

event_note 26.07.2019

Overseeing the asset management is being taken over by trading systems based on data analysis, artificial intelligence, machine-learning methods, predominantly the neural networks. Robotic trading based on algorithms will outperform man. Do you have the feeling you have already read this somewhere? Most likely yes, recently, there have been a lot of marketing materials and academic publications issued, focusing on modern technologies enforcement into financial assets management.

The articles have a very similar structure – initially, they list “breaking-through” discoveries in the field of information technologies and data analysis, not forgetting to name magical words such as “artificial intelligence”, “data analysis”, “neural networks” etc. The readers are further introduced to the advantages these technologies bring in comparison to the financial assets management by a man of flesh and bones. These articles and publication materials are very similar in trying to get out the most of the upsurge of modern technologies. Thereafter, in most cases, there is information about the author’s individual solution or service and, there, the magical words start disappearing or they appear vaguely and on a general level. When such promoted services or solutions are investigated into greater detail, more or less the same approaches which can be handled by a better-developed spreadsheet editor are seen. The message could be conveyed roughly like this: “There are brilliant tools which are gaining ground in the asset management, we deal with them… but eventually, we still do the techniques which can be managed by a “better excel” because it is just enough for us.” It is a practical example of what is nowadays called buzzword. Most of the current solutions offered in the market say: “We need to follow the technological development and we are unique in this owing to our approach… as a result, we fill our portfolio with shares of excellent technological companies (e.g. A, B, C) and the following year we exchange them for X, Y, Z.” The point is that from the global view, these changes are only cosmetic and the high dependency on the global market development remains.

Yes, there are companies that really work on this basis and use a “state-of-art” approach which they successfully apply in practice. The pace is set by companies such as the US Renaissance or Two Sigma. They, however, never spread these words and what they show are real results. Why would we be using the top-notch technologies if they did not deliver an added value in the form of better results? This mind-set is so intuitive and straightforward that it is partly in contradiction with our rooted habits – for example, the dependency of strategy profits on the global stock market development. If a trading strategy is correlated with the activity of underlying assets or with stock index S&P500, it is not good and this strategy must be immediately adjusted or is completely removed from further development – this fact is researched in the first set of tests in the new trading system which is being developed.

The point of such an approach is an effort to maintain high stability, not higher profitability. Mathematically speaking, the optimisation problem is not maximising the profit but minimising the risk. The pursuit of maximal profit is the subject of many statistical delusions and mathematical paradoxes that lurk at each of research steps from the historical bias, overfitting, high degree of correlation with the global financial market up to the uncontrollable degree of risk. In the moment of reaching risk control, the trading system gains a truly powerful tool in the form of stability. Therefore, profit is “only” the function of available capital and willingness to undertake risks.

The basic optimisation condition is the starting point for a long journey of research and development which results in a viable and autonomous trading system.

In the end, a person enters the whole process as a checker and “maintenance man” of such a trading system. No strategy can run in the real environment without maintenance and calibration. This role is still held by man as well as the role of a checker. State-of-art technologies work as a good technical tool for achieving all goals – these technologies are faster, more accurate, more computing-efficient but they can never solve everything for man, they cannot define a problem and they cannot solve a wrongly defined problem.

Michal Dufek, Head of Financial Research Software Development