7/10/19: Bitcoin, ethereum and ripple: a fractal and wavelet analysis

Myself and Professor Shaen Corbet of DCU have a new article on the LSE Business Review site covering our latest published research into cryptocurrencies valuations and dynamics: https://blogs.lse.ac.uk/businessreview/2019/10/07/bitcoin-ethereum-and-ripple-a-fractal-and-wavelet-analysis/.

The article profiles in non-technical terms our paper "Fractal dynamics and wavelet analysis: Deep volatility and return properties of Bitcoin, Ethereum and Ripple" currently in the process of publication with the The Quarterly Review of Economics and Finance (link here).

10/1/16: Tsallis Entropy: Do the Market Size and Liquidity Matter?

Updated version of our paper:
Gurdgiev, Constantin and Harte, Gerard, Tsallis Entropy: Do the Market Size and Liquidity Matter? (January 10, 2016), is now available at SSRN: http://ssrn.com/abstract=2507977.

Abstract:      
One of the key assumptions in financial markets analysis is that of normally distributed returns and market efficiency. Both of these assumptions have been extensively challenged in the literature. In the present paper, we examine returns for a number of FTSE 100 and AIM stocks and indices based on maximising the Tsallis entropy. This framework allows us to show how the distributions evolve and scale over time. Classical theory dictates that if markets are efficient then the time variant parameter of the Tsallis distribution should scale with a power equal to 1, or normal diffusion. We find that for the majority of securities and indices examined, the Tsallis time variant parameter is scaled with super diffusion of greater than 1. We further evaluated the fractal dimensions and Hurst exponents and found that a fractal relationship exists between main equity indices and their components.