A Statistical Analysis of Cryptocurrencies, Stephen Chan et al, JRFM, May 2017
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?
Thank you very much for this article.
Thanks, I'd like to see how many on Steemit are into this level of analysis.
That article has only been downloaded some 300 times in the 20 days since pub, so pretty small niche interest.
But I'm not sure charting works until one's analysed which charts are valid for cryptos.
People usually don't like to put too much effort into their investment decisions, I guess. Many made quite a decent profit without caring at all about statistics. ;-)
By the way: Are you one of the authors of this paper?
Sure, a rising market can be forgiving :-)
I can see asset managers don't yet have a language for cryptos.
No, I'm not one of the authors.
I'll bet if you re-post this you will get a lot more response than last month. I am interested to understand more.