Comparison between Information Theoretic Measures to Assess Financial Markets

Using transfer entropy to measure information flows between financial markets

We use transfer entropy to quantify information flows between financial markets and propose a suitable bootstrap procedure for statistical inference. Transfer entropy is a model-free measure designed as the Kullback-Leibler distance of transition probabilities. Our approach allows to determine, measure and test for information transfer without being restricted to linear dynamics. In our empiric...

Markets for Financial Information

An algorithmic information-theoretic approach to the behaviour of financial markets

Using frequency distributions of daily closing price time series of several financial market indices, we investigate whether the bias away from an equiprobable sequence distribution found in the data, predicted by algorithmic information theory, may account for some of the deviation of financial markets from log-normal, and if so for how much of said deviation and over what sequence lengths. We...

Information Dispersion in Financial Markets

Public disclosures can level information asymmetry in financial markets by removing informed traders’ advantage, or can exacerbate asymmetry by further increasing these traders’ knowledge of the firm. This study finds evidence of the latter phenomenon in earnings conference calls, where management releases new information, and financial analysts on the call immediately respond and question mana...

Information Communication in Financial Markets∗

Empirical evidence shows word-of-mouth communication has real effects on trading patterns in financial markets. On top of that, the social network through which the information conveys also plays a crucial role. We propose a framework that allows informed traders to directly and truthfully communicate information in four major social interaction structures represented by circle, tree, star and ...