Article very recently published to find the most accurate model to describe cryptocurrency volatility. Somewhat relevant given the recent flash-crashes.
Abstract: We analyze statistical properties of the largest cryptocurrencies (determined by market capitalization), of which Bitcoin is the most prominent example. We characterize their exchange rates versus the U.S. Dollar by fitting parametric distributions to them. It is shown that returns are clearly non-normal, however, no single distribution fits well jointly to all the cryptocurrencies analysed. We find that for the most popular currencies, such as Bitcoin and Litecoin, the generalized hyperbolic distribution gives the best fit, while for the smaller cryptocurrencies the normal inverse Gaussian distribution, generalized t distribution, and Laplace distribution give good fits. The results are important for investment and risk management purposes.
The smaller cryptocurrencies analysed are Ripple, Monero, Dash, MaidSafeCoin, and Dogecoin. To put the article in context, "Bitcoin is shown to exhibit the properties of both standard financial assets but also speculative assets, which fuel further discussion on whether Bitcoin should be classed as a currency, asset or an investment vehicle." Volatility is an important measure in how to class cryptocurrencies in terms of investments and trading.
If you appreciate this kind of statistical analysis as an aid to trading, or as a predictive guide to how institutions are going to manage this new asset class, the full article is free online at:
A Statistical Analysis of Cryptocurrencies, Stephen Chan, Jeffrey Chu, Saralees Nadarajah, and Joerg Osterrieder, Journal of Risk and Financial Management 2017, 10(2), 12; doi:10.3390/jrfm10020012.
Has anybody run a similar analysis with the price of STEEM?