We survey the main applications of algorithmic (Kolmogorov) complexity to the problem of price dynamics in financial markets. We stress the differences between these works and put forward a general algorithmic framework in order to highlight its potential for financial data analysis. This...

We explore the potential benefits of a series of existing and new non-parametric convex and non-convex frontier-based fund rating models to summarize the information contained in the moments of the mutual fund price series. Limiting ourselves to the traditional mean-variance portfolio setting,...

Since the first multi-agents based market simulations in the nineties, many different artificial stock market models have been developped. There are mainly used to reproduce and understand real markets statistical properties such as fat tails, volatility clustering and positive auto-correlation...