Offtopic: Quantitative Analysis of Altcoins, part I

In this update we will compare major altcoins towards bitcoin with the quantitative systems I use in the annual forecast that I publish in the first post of each year. Concisely we will list the volatility and gain values of these alternative assets to bitcoin. I would remind you that it is always preferable to invest in assets with low volatility and consequently high returns, volatility always deteriorates the gain of an asset.
I used weekly data, the last 52 weeks where possible. Only Bitcoin Gold hasn’t enough data for a proper computation of its quantitative values.

ALTCOIN Gain (G) Volatility (RMS)
Ethereum 0.9865 0.176
Dash 0.9862 0.188
Monero 0.979 0.1509
Litecoin 0.977 0.1511
Ethereum Classic 0.9765 0.169
Next 0.961 0.182
Ripple 0.96 0.236
Zetacash 0.951 0.1631
Stellar Lumens 0.9313 0.29
Bitcoin Cash 0.93 0.207
Qtum 0.909 0.206
Iota 0.88 0.179
Eos 0.8421 0.322
Bitcoin Gold n/a n/a

This table explains why every time you ask me an advice about altcoins, I tell you that it is better to ignore them because NO ALTCOIN shows positive gains above the unit due to the fact that they are dominated by volatility that highly reduce the final gain of the asset.
Said this, the less bad altcoins are Dash and Ethereum followed by Monero and Litecoin with a preference to these last two because of lower volatility compared to Ethereum and Dash.

A special mention to Bitcoin Cash that, considering its high market cap, both Gain and Volatility are bad.

To conclude, the big mistake is to compare altcoins to USD, in my opinion it’s wise to compare them against Bitcoin; against fiat currencies is easy to perform well.

Technical Appendix

The procedure to compute volatility and gain is always the same explained in the past:

  1. Compute log of Today bar divided by yesterday bar
  2. Average values (avg) of last 52 periods (n) (1 year using weekly data)
  3. Compute Volatility (rms)
  4. Compute price momentum probability with the formula P = (((avg / rms) – (1 / sqrt (n))) + 1) / 2
  5. Compute Gain using the formula G = ((1+rms)^P*((1-rms)^(1-P))

ITA Version here

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6 thoughts on “Offtopic: Quantitative Analysis of Altcoins, part I

  1. Awesome – will you be able to share the weekly data as a google spreadsheet thats updated daily? that would be so helpful. I’m thinking of applying my momentum tactical asset strategies (Meb Faber) that I use currently for ETFs to alt investing to see what happens. Essentially the strategy does a 4 week, 3 months, 6 months and 12 month look back on the gain, does an AVERAGE of those four numbers, and then ranks the top 3. If the gain is LESS than BTC then I will hold the asset in BTC not the alt, otherwise the top 3 (AGG3). This allows the long term trader/hodler to take advantage of the “momentum” in the alt when it goes over the BTC momentum and pull back when necessary. A slightly more aggressive variation would be to shorten the lookback periods when taking that average for the momentum (avg of 1 week, 4 weeks, 12 weeks, 36 weeks instead).

    1. I used tradingview, manually checking G and RMS values with each altcoin, a bit tedious to repeat each week not only but with tradingview you can’t export data. Using different averages timespan it’s like to apply some sort of bias towards recent data, why? theoretically you should use all the data available as more data you use as less estimation errors there are in computing the gain. That definition of “momentum” is not appropriate in my view, positive momentum when the gain is negative is merely volatility at work:) with all the risks involved but still possible to be exploited with appropriate strategies.

      NOTE: i used last 52 weeks just because with tradingview you can use only arrays of fixed size but i should have used all available data for each altcoin to further reduce measurement errors.

  2. OK thanks – maybe you can share how you do it in trading view.. Re: tactical asset allocation strategies that use moving averages, here’s a good blog I follow and a good introduction to them:
    https://investingforaliving.us/2010/11/10/reducing-risk-and-enhancing-returns-through-market-timing/

    and his other portfolio strategy page is here that has more links (e.g. to the AGG3 strategy I referenced)
    https://investingforaliving.us/portfolios/

    I am attempting to use the same kind of strategy against alts… thanks 😉

  3. Frank

    Thanks for the altcoins info Enky. Hats off. Because of the very high BTC transaction fee i have been appreciating LTC more and more right now, and i believe it’s the most undervalued coin at this moment given the recent technological upgrades and network speed. For smaller transaction values LTC is in my opinion at this moment far superior than BTC/BCH in the means of transaction fees, confirmation time and adoption. I’m using LTC for smaller payments and holding BTC as a permanent store of value. When comparing all the steps made the past years since the MtGox Drama i’m becoming more confident that we are witnessing the first steps of a revolution from the financial system. Quite a long time ago you mentioned 4000$ as good exit point for your long position regarding BTC. Did you adjust your exit strategy or do you think this will be bigger than we’ve ever could imagine and you’ve become a permahodler?

    1. Not a permahodler but as long as btcusd gain value (G) computed on the weekly chart remains positive i hold. at the moment is 1.0282 a very strong gain.

  4. Andy Grant

    This is the most accurate analysis i’ve read about altcoins ever. It should be a sticky on every reddit altcoin channel.

    The data speaks for itself and i can’t argue with that, the only thing i’d like to add is that IMHO most of the altcoin bullrun that happened in May this year was due to the escalating scaling/privacy debate around bitcoin.

    So the data on Litecoin and Monero MAY seem prettier than it actually is.

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