The Value of Econophysics

This text is written for Marginalia, a magazine published by university students.

Marginaria Web Page(http://ronsetsu-marginalia.blogspot.nl/)

“What econophysics means?” I have to answer this question before explaining the value of econophysics because you can’t understand the value of anything if you don’t know it. Evonophysics is a relatively new domain and its researchers come from many different fields, such as physics, economics, engineering, mathematics, information and so on, therefore the definition of it is not explicit. So I propose the objectives of econophysics and define econophysics as a science aiming it. There are, for examples, (1) to find statistical features called stylized facts that come from big data that you couldn’t have got before (big means high frequency or minute detailed, such as 1 nanosecond financial market trading data, all companies transactions relationship, and so on), (2) to describe the mechanism emerging stylized fact by using simple microscopic or mesoscopic model like agent based model (ABM) and (3) to extend the realm of physics to be able to discuss the systems composed of not only particles that always behave same if the condition is the same but also agents that behave differently even if the condition is the same because of agents’ learning, adopting and evolution. 

 The biggest defect of economics is relying too much on mathematics. It means that every economical phenomena should be described by mathematics makes economics unrealistic. Mathematics only deal with perfect deterministic situations or perfect random situations. If you use mathematics in the mixture situations of deterministic and random, you can get only very abstract or trivial conclusions (such as bubbles must crash eventually) and cannot discuss real-worlds problems. To avoid this, economist have made “good-looks” assumptions like people behave in order to maximize his/her utility with perfect rationality and solve economic problems with such assumptions. One of the typical cases of this is efficient market theory (EMH). It says that price movements obey independent Gaussian distribution because people trade stocks based on its theoretical price (fundamental price) determined by the external news such as company’s achievement and external news will come unexpectedly because expected news is taken into account immediately and loses its value. So this statement means that everybody behave rationally and nobody knows the future. It sounds good. However, it cannot explain fat tail, one of the stylized facts that means large fluctuations obey power law distribution and thus occur more frequently than Gaussian. This typical examples are large crashes, such as Wall Street Crash (1929), Black Monday (1987), Lehman Shock (2008) and so on. Gaussian distribution says large crashes never happen, but in reality, it is not the case. In conclusion, what I want to say in this paragraph is that mathematics is useful, but sometimes you idealize problem too much to contain important features in order to solve it mathematically.

 So what we should do solve this problem? Econophysicists uses mainly ideas come from non-equilibrium statistical mechanics, complex systems theory, synergetics. The key is in the mesoscopic level connecting micro and macro because there are no other economics domain dealing with mesoscopic. It is true that one of the EMH defects, perfect rationality is also criticized by behavioral economics that assumes people have bounded rationality, but it is only the microscopic level and not suitable to discuss macroscopic economic phenomena. Then, what is the best way to tackle mesoscopic? I think it is ABM. ABM can realize mesoscopic mechanics by emergence and downward causation. Emergence means interactions among microscopic agents make macroscopic orders or structures. Downward causation is each agent who often has bounded rationality learn from macroscopic environment that are formed by emergence and change the way how to behave. This micro-macro loop is essential because it can generate stable and non-equilibrium states that are often seen in the real world, but traditional economics, such as evolutionary game theory cannot reproduce. Roughly speaking, an equilibrium state is like a ball in a valley. This is stable because if a ball moves, immediately returns the center of a valley. So its state is frozen. In contrast, stable non-equilibrium state is a sand pile. You drop sands, a sand pile emerges and gains its height. Then, the height of a sand pile will go to infinity? This answer is clearly no. Avalanches sometimes occur and the height goes down. So this system is stable not because its state is frozen but because it always moves. Economic phenomena are not frozen, but dynamical so that you can look them as stable non-equilibrium than equilibrium and this is explained by econophysics.

 In conclusion, the value of econophysics is to capture economic phenomena without failing there non-equilibrium features. And what’s more, I expect the development of experimental econophysics established by Ji-Ping Huang. It has a great potential to combine econophysics and laboratory experiments. In Japan, Yu Chen, an associate professor of The University of Tokyo studies it.