|52 week change||815.15%|
|52 week high||30,244.10|
|52 week low||3122.58|
|Average bid/ask spread||1.03%|
|Year to date change||310.44%|
|Month to date change||4.73%|
|#||Name||Price||Market cap||Change (day)|
|#||Name||Price||Market cap||Change (24h)|
The top 30 cryptocurrencies by adjusted market capitalization are automatically selected and included in the index. All the so called “stable coins”, which are pegged to a fiat currency, are not taken into consideration. To calculate the weights for each cryptocurrency, the adjusted market capitalization must first be calculated. Market capitalization is not computed as some instantaneous number – the volatility in the cryptocurrency market is such that this would destabilize the index composition too much. Instead, the CCi30 uses an exponentially weighted moving average of the market capitalization. The weighted average Market Capitalization helps smooth the volatility to give the most accurate portrait of market capitalization at any given point. The formula used to derive market capitalization is:
where M(t) is the actual market cap at time t, M* is our adjusted market cap, and α is the decay rate of the exponential moving average, set with an halfilfe of 3 days.
The number of constituents was set at 30 because it is the minimum number necessary to be statistically significant. The use of more constituents would generate higher fees with no significant improvement to performance and any less than thirty would risk reduced performance, insufficient diversification, compromised statistical significance, and missed opportunities to pick the next rising star.
By taking the top 30 cryptocurrencies, the CCi30 captures a very high percentage of the cryptocurrency market capitalization. With this scope, the index statistically represents the entire cryptocurrency market with a confidence level of 99% and a confidence interval of 1.11. In other words, the margin of error of the index value as an indicator of the market is just 1.11%.
The weight of each constituting cryptocurrency is measured by the square root of its adjusted market capitalization, so at time t, the weight of the cryptocurrency 0 will be:
where Mi* is the adjusted market capitalization of a specified cryptocurrency at time t.
The square root function was chosen as a hybrid that most accurately weights the constituents based on the current conditions of the cryptocurrency market.
A simple market capitalization weighted index would be dominated by the top two cryptocurrencies, while a more slowly decaying weighting, or in the extreme case, equal weighing, would give too much weight to the tiny, illiquid cryptocurrencies at the bottom of the range.
In order to accurately capture the movements of the market, no caps or floors are implemented upon the weights of the cryptocurrencies.
Between rebalancing dates, the index value is defined as:
Where It is the value of the index at time t, Wj is the weight of the jth name in the index, and Pj is the price of the jth name as a function of time.
On rebalancing dates, the weights are normalized in such a way that the index value is the same, whether it is computed with old or with new weights.
The index is calculated in realtime. All values refer to the close of the previous day, considered to be at 0000 GMT.
Not too surprisingly, the index is a better investment vehicle than Bitcoin itself, and a much safer approach than trying to pick single coins. Investing in the index allows to profit from the unforecastable raise of some cryptocurrencies, while limiting the losses deriving from the fall of others.
The CCi30 is the most accurate instrument for measuring the whole cryptocurrencies market, and the Blockchain sector in general. It represents a useful tool for investors, a benchmark for traders and asset managers, a replicable index for passive funds and ETFs. In short, it is the industry standard for cryptocurrencies.
* The Sharpe-Rivin ratio is a development of the Sharpe ratio formula by Prof. Igor Rivin. It serves as a more accurate way of measuring risk-adjusted returns. For more information you can read this paper.
CCi30Ⓡ was created and is maintained by an independent team of mathematicians, quants and fund managers lead by Igor Rivin, Professor of Mathematics at Temple University and Regius Professor of Mathematics at St. Andrews University, and Carlo Scevola, economist and president of CS&P. Robert Davis, Engineer, IT expert and programmer, is responsible for technology.
The CCi30 index is currently used by several financial institutions as the benchmark for their investment strategies.
A free license is available for academic and research use. A realtime API and various data analysis tools are included in the commercial license.