In the late 80s, we at Olsen coined the term high frequency finance to describe our scientific approach to finance and economics. We later published a book, Introduction to High Frequency Finance, that describes the new field. High frequency finance firstly deals with collecting as much information as possible; in particular storing all tick by tick market data, then in a second step studying the detailed statistical properties of the data; describing the economic processes and later based on these observations develop models to explain the observed phenomena. In biology, this approach has a long tradition. Biologists in the field of systematics have literally for centuries specialized in carefully describing the plants and only after completing this step have they moved on to introduce a systematic approach to categorize the species.
In economics the traditional methodology of research is to first formulate a general hypothesis and then to prove the conjecture. The debate of the efficient-market hypothesis is an example of this approach: researchers put forward the hypothesis stating that a market is efficient only if all known information is reflected in the market prices. The hypothesis was introduced because researchers believed that markets could only fulfill their role of ensuring an optimal allocation of resources, if all information was reflected in the market prices. The hypothesis of market efficiency spurred a large debate, which was not as rewarding as expected because the evidence was indecisive.
The debate of efficient-market hypothesis was motivated by a desire to prove that financial markets are indeed efficient in allocating resources. So in this sense, prior political beliefs impacted the research agenda. High frequency finance takes a different tack. There is no prior hypothesis: the collected data has to speak for itself. The researcher is open to surprise and has no hidden agenda.
Our recent discovery of 17 new scaling laws illustrates the methodology, we would have never predicted the existence of so many scaling laws and were completely surprised by the results. As soon as we had made the discovery, it opened the door to improve our technology of how we compute volatility and design trading models. We succeeded in our research, because we were open to surprise and had spent a lot of time studying the detailed properties of the empirical data. Economic phenomena are highly complex and subtle. If we start off with constraining objectives, we may miss the point and go off on a tangent.
The approach of high frequency finance has an apparent disadvantage: the reality of economics is far more complex than we would ever expect and the dream of a rapid answer to an economic problem is an illusion; we have to acknowledge that a lot of work is required before we can hope to solve a particular issue. What do you prefer, a solution that seems to solve all the issues, but is crap, or spend more time to discover a durable answer?
High frequency finance goes beyond econophysics, a relatively new interdisciplinary research field that applies theories and methods used in physics and other natural sciences and relies heavily on validating its results with empirical data. High frequency finance is agnostic: the discipline starts with data collection and then iteratively generalizes the observed phenomena to discover appropriate explanations. We seek inspiration in other sciences, not just natural science, but are always looking for bespoke solutions that go to the heart of the problem and rely on a minimum of prior assumptions.
The current crisis is a wake up call to break the shackles of economics. High frequency finance shows the way forward: What is now needed is to make the financial resources available for the many researchers worldwide that are eager to dive into the masses of economic and financial data and unlock their secrets.
Author: Richard B. Olsen, Founder and CEO of Olsen Ltd
October 7th, 2009 | High frequency finance, News | RSS feed