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.



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

Technical Update: KAMA, an underrated indicator

Kama moving average is a very interesting filtering technique developed by P.Kaufman.
This moving average has been designed to account for market noise or volatility, KAMA will closely follow prices when swings are small and the noise is low, instead when the price swings widen KAMA will adjust trying to follow prices from a greater distance. This trend-following indicator can be used to identify the overall trend, time turning points and filter price movements when the market is flat avoiding annoying whipsaw false signals trades.

At the moment i’m working on a modified version of this indicator with the help of the tradingview online platform, i added deviation lines from the KAMA average and settings have been optimized to better track XBTUSD price movements on daily and weekly chart.

Here’s an example of this indicator applied to a weekly chart of XBTUSD with some comments.

It’s evident that when the market is flat the KAMA average is relatively stable without giving false signals, when this happens you can try to trade deviation lines to catch bottoms or tops.

About this week the secondary positive deviation line is around 3200$, should you go short at that level? Well is at your own risk to trade against the main tendency that now is bullish, instead you might follow the trend buying at the midline or below it, i’m enough sure that today sell-off is healthy and the price was just moving back to the midline point (KAMA average) from the first positive deviation line.

Beware that because of very large price variation during the same bar the KAMA and its deviation lines can change a bit. The indicator is available for free at, just look for “KAMA – Enky v1.0”.

Your feedback is highly appreciated and will help me improving this trading tool.

Offtopic: Cacoethes scribendi

“Cacoethes scribendi” or translated from Latin to english “a burning desire to write”, writing always of bitcoin sometimes is boring, today i show you the template i use with metatrader 4 applied to other assets like stocks, indexes and altcoin.

I already explained that an idea that i like is to do a price regression of our asset using a filter that eliminates all cycles below 30-40 periods with the intent to extract the underlying long term trend, then you can try to earn some money trading the secondary cycles that move the price up and down inside the price channel.

SP500/N100 weekly chart


Mid channel line color is white thus this market is neutral the ideal situation to trade the price levels, at the moment there could be a short opportunity, stoploss above the dotted positive deviation line.


Similar situation for the nasdaq 100 index.



The big drop of the Brexit is clearly visible, the pound should stay above 1.29, it’s the moment to buy with a stoploss below 1.28

Nikkei 225


Nikkei is short for Japan’s Nikkei 225 Stock Average, it is a price-weighted index comprised of Japan’s top 225 blue-chip companies traded on the Tokyo Stock Exchange. The Nikkei is equivalent to the Dow Jones Industrial Average Index in the United States.
In this mothky chart is visibile the big rise fueled by the quantitative easing of the Japan Central Bank and the subsequent drop after flirting with the resistance at 21000.
At the moment it is holding above the first negative deviation line, i don’t see any trading opportunity.



On the weekly chart the tendency is neutral, midline color is white, ideal to trade secondary cycles like the one that pushed down Tesla below 150 usd and below our support, a very good trading opportunity, it is possible also to trade the dotted levels but they are less safe.



Daily chart of ferrari (RACE ticker), after an interesting double bottom on the support this stock trended higher above the resistance after the earnings.
I think we are seeing a buying climax and in this situations is smart to sell the good news, i see a short trade opportunity here but it’s wise to wait some weak signals from this stock before going on.

Nintendo and the Pokemon Go Bubble


No comment here, the bubble is evident but this stock is still hovering above midline and the long term trend is bullish. Again a nice double bottom at the support.



Last five years of Apple in this monthly chart, here the support levels worked almost perfectly. Apple is losing some steam as the midline color is white, neutral long term tendency despite you can see a sequence of higher highs and lows. The stock reacted from the dotted line at around 90 usd but i’m not sure is going up yet, the trading opportunity here is a test at 75-80 usd this year or the next one.

ETCUSD – Hourly chart


Hourly chart of ethereum classic, again bubbles are clearly visible. Some congestion outside the upper solid deviation line it’s the warning signal, be prepared to open a short. Now volatility is a bit lower and this altcoin is moving inside the dotted deviation lines. I see a buying opportunity once 1.85 usd is tested.


This price channel indicator is an improvement of the classic bollinger bands indicator, what i don’t like of the bollinger bands is the wrong way to compute the upper and lower bands that might lead to very misleading values sometimes as i explained at the end of this old article. To keep things simple i omitted to include some timing indicators, for example adding the Walter Bressert DSS oscillator with ethereum classic we have:


Clean cycles togheter with a correct approach to spot support/resistance levels and you have a decent guide to follow. This oscillator is configured using 9 periods and 5 periods for a second pass smoothing.



Thank You

Since May 2016 I’ve seen a strong Bitcoin price rally after the breakout of the $500 resistance.

“Move fast for profit regardless security and customer satisfaction” may be applied to companies but not for a true decentralized cryptocurrency like Bitcoin.

I want to thank Bitcoin Core for the very conservative approach to its development. Core has been doing a supreme job maintaining the reference client, making sure that the network is running smoothly and insuring that the 11 billions $ market cap doesn’t decline due to bugs in the software because of developers negligency like happened today to another altcoin.

Thanks again for doing a great job.

Project maintainers


  • Dr. Pieter Wuille

  • Cory Fields

  • Gregory Maxwell

  • Luke-Jr

  • Jorge Timón

  • Peter Todd

  • Patrick Strateman

  • Dr. Johnson Lau

  • Suhas Daftuar

  • ฿tcDrak

  • Michael Ford

  • paveljanik

OFFTOPIC: a quick view of an altcoin

This is an attempt to forecast where the next big movement will end of this altcoin, an altcoin that recently is getting lot of unjustified attention from the bitcoin community. I don’t know if people is bored of bitcoin and is trying to pursuit a “get rich quick scheme” pumping their bitcoins in this altcoin, aniway it is not the purpose of this article to prove it or not.

Here there is the weekly chart with logscale for the price axis.I highlighted the first big up movement and the subsequent price drop, a perfect 62%  fibonacci retracement down from the top to 0.015 btc/unit. Assuming that the current bullish movement will be of the same size of the previous one using a logarithmic scale the target should be at 0.135 Btc/Unit. There would be price retracements for sure before reaching such an optimistic target therefore a more likely long term top could be the point half way between our initial target and the bottom used as a starting point for our forecast. As indicated in the chart this potential resistance level is around 0.047 Btc/unit. IMO it would be a decent point where to open a short position because it is above the previous high of 0.035 Btc/unit and in a strong uptrend i’d prefer to avoid to open a short position from a lower high. In any case it is better to confirm the trade with a bearish signal with an oscillator of your choice.



Technical update: Consolidation Breakout Trading System

Today after many years i’ve reinstalled Metastock Professional, i was curious to see if there was some old Expert Advisors giving good result with bitcoin and i’ve found this one: “Consolidation Breakout” from Trading Systems Analysis Group.

Basically it works with volatility breakouts to identify entry/exit points and while this system uses John Bollinger’s Bollinger Bands and Welles Wilder’s Average True Range indicator, it is not linked to the methods of those two authors.
It’s based upon a strict observation of the Bollinger Band width compressing/decompressing (a method used by many traders) around the prices until the distance between the upper and lower bands is less than 1 ¾ times the 1 period average true range; it then looks for a breakout in either direction of the Bollinger Bands to capture the movement of the breakout. Once a position is entered, it looks to cross the 20-period simple moving average to exit the position but any other money management approach can be used for the exit.

I attach below the above expert advisor applied to a daily bitcoin chart. It works fairly well when volatility is high enough, even with less volatility performances aren’t so bad without substantial losses.
At the moment the system is flat and exited a short position on 4 Sept. at $231.

I’d like to add that because bitcoin recently has been very boring from now on there will be updates about Currencies, Equities and Gold, all instruments that i trade regularly with my btc broker since September 2012.

OFFTOPIC: Donations

First of all I’d like thank everyone for contributing to this blog with donations since 2011; said this I kindly ask you to don’t send donations less than 0.01 bitcoins because there are problems with coinbase to process transactions below 0.01 btcs. I already reported this issue to coinbase technical stuff, i’m waiting an answer.

Thank You

OFFTOPIC: join ##btctrading on freenode

The #btctrading IRC channel

##btctrading is a place where many traders hang out and discuss about bitcoin market analysis. The community in ##btctrading will be mostly the same community that you’ll find here in the comments.

Download an IRC Client

A popular open-source option for Windows / Linux is Xchat:
Mac users might want to consider Colloquy:

Connect to the FreeNode Network

Once you install the application you’ll want to connect to the FreeNode network. is a network that is very popular with open-source development communities. Most web-development frameworks have an IRC channel on FreeNode so we’re in good company.

To connect to FreeNode set your IRC client to connect to the server by setting it in the client’s user-interface or by entering the following line in the input box:

Join ##btctrading

From there you can join the btctrading channel using either the IRC client’s user-interface or by entering the following line in the input box:

/join ##btctrading

Again I please everyone to join the unofficial channel using the double # as prefix (##btctrading), thanks.
Why? well because of freenode rules on primary channels at the moment i decided not to use #btctrading, more here.

Time is running out

I report  an analysis that take an historical perspective of the XBT/USD, using MtGox data for the period before the inception date of the Bitstamp exchange. The effort of this short analisys is to understand how much it’ll last the current decline in prices started 5 months ago.

I reported here all the most important past swings of this market, not always considering the absolute highs and lows but the upward and downward phases of the market which can include periods of sideways activity.

The earliest days

In 2010 the main exchange was MtGox, it opened in July but available data starts from 17 August.
Up to the first days of october the price stayed flat at $0.06 then rised significantly to $0.50 the 7 November. A correction followed with a low at $0.17 after 32 days.

The next swing carried bitcoin from 17 cents up to $1.09 (9 Feb. 2011) and again a correction, longer this time, 54 days down to 56 cents, it was april 2011.

The First wave

Everyone here probably remember the insane upswing that went from below 1$ up to 32$ of  June 2011, from this top bitcoin entered a bear market that lasted 162 days, till november 2011 where it bottomed out at $1.99

From this bottom a new upswing happened up to $7.2 (8 Jan ’12) , again similar in length to the previous ones: 52 days. This market then stayed sideways for 145 days, when the first days of June a new uptrend moved bitcoin up to $15.4, in August ’12 after 77 days. For the second time in a year we have had another phase of  flatness prices that lasted 139 days similar the previous one of 145 days.

The second wave

The first days of 2013 another upleg started from $13 up to $266; 97 days the longest upswing ever for bitcoin. After a period of huge volatility till July of the same year , prices stabilized at around 100-120 dollars and this consolidation ended 12 October after 185 days. So far we have had 6 consolidations with an average duration of 126 days or 158 days without considering the earliest days of bitcoin.

The last wave

This is the latest part with the solid rise from 140 dollars of October ’13 up to $1163, the bitstamp all time high done 49 days later. Since then 156 days are passed and comparing this value with past values i believe that the actual consolidation phase is coming to an end.

Eventually this correction might last as the previous one that lasted 185 days, this will project the end of the actual correction phase something around June 2014, one month from now.
Beware that this forecast doesn’t necessarily means that a new bottom will develop because as i said earlier i haven’t considered absolute bottoms in calculating the duration of all the past price consolidations; it just means that probably during next June a new uptrend will start.

Time will tell.