Modeling stock markets through the reconstruction of market processes
Abstract
There are two possible ways of interpreting the seemingly stochastic nature of financial markets: the Efficient Market Hypothesis (EMH) and a set of stylized facts that drive the behavior of the markets. We show evidence for some of the stylized facts such as memory-like phenomena in price volatility in the short term, a power-law behavior and non-linear dependencies on the returns. Given this, we construct a model of the market using Markov chains. Then, we develop an algorithm that can be generalized for any N-symbol alphabet and K-length Markov chain. Using this tool, we are able to show that it's, at least, always better than a completely random model such as a Random Walk. The code is written in MATLAB and maintained in GitHub.
Keywords
Cite
@article{arxiv.1803.06653,
title = {Modeling stock markets through the reconstruction of market processes},
author = {João Pedro Rodrigues do Carmo},
journal= {arXiv preprint arXiv:1803.06653},
year = {2018}
}
Comments
49 pages, dissertation