Offtopic: Quantitative Analysis of Altcoins, part II

In part I, I did a quick analysis of altcoins compared to XBT, this time i’m going to check their performance using all available data of each altcoin since inception date using daily data instead of weekly to improve the granularity of the analysis because, the finer the granularity of the analysis, the better the insights for understanding the characteristic of the asset.

ALTCOIN Gain (G) Volatility (RMS)
Ethereum      0.998               0.072
Monero      0.996               0.073
Next      0.995               0.074
Dash      0.993               0.111
Litecoin      0.991               0.115
Ethereum Classic      0.990               0.084
Stellar Lumens      0.987               0.135
Eos      0.981               0.126
Iota      0.979               0.117
Bitcoin Cash      0.977               0.161
Ripple      0.975               0.187
Zetacash      0.947               0.201
Qtum      0.912               0.265
Bitcoin Gold      0.740*               0.570*

*Note that because of the very short size of the Bitcoin Gold dataset, its Gain (G) and volatility might change a lot in the long run.

If I were forced to assemble a portfolio of altcoins, i’ll probably opt for low volatility alts, like Ethereum, Monero, Next and Ethereum Classic. Eventually I would add Dash and Litecoin because by increasing the number of assets as a result I will reduce the final volatility of the portfolio.
At the end of this post you will find what i’d actually do if asked to diversify an initial capital of bitcoins.

To give you an idea of the Gain (G), you have to power this number to the number of days interested, for example (G)^365 will give you the average value of your asset in 1 calendar year.

For Ethereum is:

0.998^365 = 0.4815

or a 52% expected decrease in value towards XBT in 365 days.

How Much to allocate individually on each altcoin?

This is a simple question with a simple answer, the formula to obtain the fraction of your capital to wage on a particular asset is:

F = 2P - 1

Where P is the Shannon Probability and F the optimal fraction of your capital to wage. The Shannon probability of a time series is the likelihood that the value of the time series will increase in the next time interval. The Shannon probability is measured using the average, avg, and root mean square (volatility), rms, of the normalized increments of the time series as i explained in previous udpates.

For Monero is:

F = 2 * 0.4953 - 1 = -0.0096 or ~1% as an optimal fraction to wage

For Ethereum is:

F = 2 * 0.5079 – 1 = 0.0158 or 1.6% as an optimal fraction of your capital

Monero has both the Persistence and Gain negative but what about Ethereum? How is it possible to have a positive persistence and negative Gain (G = 0.998)?

Well the point is that an asset’s gain in value can be negative, even though the likelihood of an up movement is greater than 50% or 0.50 (in this case 0.5079). How can the time average of something be positive, and result in negative values?

It may seem counter intuitive, but just because the average daily gain in value of an asset is positive, is not sufficient evidence that the asset’s value will increase or be a decent investment.

Do we really see asset class with these kinds of price characteristics?

The answer is that we do. During the dotcom equities bubble of the 2000, about half of the equities had these characteristics; many were to fall the hardest, too. I think the same about many altcoins/ICO, they will end badly in comparison to Bitcoin.

This is why a possible asset allocation might be to go short against Altcoins with a fraction of your Bitcoins (says 10% shorting 5 crypto); it is a strategy that might suffer some losses in the short term if you are unlucky with volatility going against you, but it will surely win in the long run.

In the upcoming PART III – We will better understand how to assemble a portfolio of cryptocurrencies starting with EURO or USD instead of Bitcoin and it’s intended for who hasn’t yet invested in any Crypto.

 

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