So, if you follow me on Twitter you may have noticed that I Tweeted about a term by the name of EconoPhysics. I was asking if anyone had ever heard of the term or done any research on the subject, I did not receive any replies. Thus, I wanted to write this post to explain and give a brief overview of my research thus far within this new, innovative study that is making it’s debut in the economics field today. But first, a little background. Econophysics is essentially the combination of ‘statistical physics’ and ‘economics’ into one study, really interesting, I know. The article I was reading alot of today defines it as: “econophysics refers to the extension of physics to the study of problems generally considered as falling within the sphere of economics.” (The Emergence of Econophysics: A New Approach in Modern Financial Theory). There is a lot more to it than that but that’s the basics of the study. The controversy in this study is as follows: It contradicts much of what people consider absolute truths about the financial markets, such as: the efficient market hypothesis. 

I am researching this topic for a paper in my English class this semester. The requirements were to find a scientific editorial to write a subject out and after a lot of searching I found myself in front of an article by the name of ‘Econophysicists Matter‘, you can view this editorial via this link: Immediately after seeing this title I wanted to investigate, at a minimum, how they related the two concepts (that being economics and physics), because at it’s core, I love the idea of such integration. As I started my research and began to read a couple of those really technical scholarly articles about the subject, it dawned on me that what they were talking about really was (in some way) the foundation to using technical analysis for analyzing the price trends. The econophysicists used historical price data determine the probability of a future move through the creation of formulas that I could not (and likely never will) understand.

At this point, my excitement in the subject grew even greater and I surprisingly found myself enjoying the reading of a scholarly article. One of the major take-aways from the article I read the most of was as follows:

“Moreover, one specific probability distribution plays a key role in the history of the discipline: Gaussian distribution (also known as normal distribution). This distribution underlies the creation of the majority of theories and models from the mainstream: the efficient market hypothesis, modern portfolio theory, CAPM, and the Black and Scholes model. We can therefore consider this distribution as a constituent of financial economics. But econophysics rejects the idea that financial distributions must be described only with a Gaussian distribution,-‘ and, as we explain in the section 3, this rejection characterizes the emergence of econophysics.” (The Emergence of Econophysics: A New Approach in Modern Financial Theory)

And the same concept continued later in the article:

“However, from the time the first statistical databases of prices were constructed in the early twentieth century, some authors noted that the distributions were leptokurtic.’^ This characteristic of statistical distribution was incompatible with Gaussian distribution [normal distributions], and mathematical and statistical work to model leptokurtic distribution appeared later.^^ At that time, while specialists were able to identify a non-Gaussian phenomenon, they had no statistical tools for dynamic analysis of observations of this kind. Non-Gaussian distribution was then only a matter of observation, and it was not modeled by a specific statistical framework.” (The Emergence of Econophysics: A New Approach in Modern Financial Theory)

Okay, to decode what this means isn’t too terribly challenging. Essentially, it is saying that the economic theory, that so many people believe, is the foundation of how the stock market ‘moves’ may not be the ‘actual’ reason for the moves. Or in other words, we have been using out-dated information and basing our investment decisions on a theoretical explanation of how the market moves (in a normal distribution). This implies that the investment theories that were developed from this theoretical explanation my not be exactly accurate in terms of their accuracy (i.e the efficient market hypothesis), and if you are a behavioral finance market participant, you consequently cannot believe in this hypothesis. Below is picture of the difference between a normal distribution and a leptokurtic distribution, the difference is subtle, but massive when applied to the overall implications of the stock market.

Leptokurtic vs Normal Distribution

To summarize in a succinct manner, IF  these new found distributions are in fact accurate in terms of their representation of how the market moves, it undermines all arguments for the truth of the efficient market hypothesis. Further more, it undermines a lot of what we make think is factual in the market-place. The theory is taboo, but if true, the ramifications are immense and every investment advisor must consider why they choose the strategy in which they do, what is their statistical foundation for such a strategy, what is the mathematical evidence for pursuing such a strategy, these are all important questions the advisor must answer if one is going to truly understand the foundations of their strategy towards this (obviously) unknowable, untamable, immensely complex beast called the market.

Obviously, I am far from an expert on the subject and over the next few weeks I hope to learn more. I woke up this morning not knowing a thing about this subject, so I think I have come a long way in a day. Regardless, I plan to post more on this subject as I learn more about it for my personal english paper on the subject. Until then, some further resources on the subject:


A Video:


Wikipedia (good for a brief definition):

A Google Search, of course :: Google Search already made

Efficient Market Hypothesis Refuted By EconoPhysics?