Machine Learning and Big Data with kdb+/q

CHAPTER 29Econophysics: The Agent‐Based Computational Models

In this chapter, we step outside the main scope of this book and illustrate the usage of q for the analysis of models in the econophysics domain. This field is a fusion between theories developed in physics on the problems in social sciences and in particular in economics and financial economics. The emergence of econophysics dates back to the 1990s when some models from statistical physics were used to analyse data from stock markets. A very nice introduction of the methods from this period can be found in a seminal review by Mantegna and Stanley (1999). The main reason why the field itself appeared is likely due to the emergence of a large amount of financial data which required statistical methods to analyse them.

It is worth stressing that the influence of physics on finance appears before the 1990s. Among many achievements, we may recall the utility‐based theory developed by Bernoulli (2011), the theory of gravity of international trade developed by a trained physicist and a first laureate in Nobel Prize in Economics Jan Tinbergen, Tinbergen and Hekscher (1962), or the apparent resemblance of the famous Black–Scholes equation and the heat equation used for a long time in physics to describe heat conductors. The trend in merging physics and finance was further shown by awarding the econophysicist Jean‐Phillippe Bouchaud as Quant of the Year for 2016.

In terms of the equations, the most prominent trace of physics ...