Long Term Update: Bottom Done.

kama
Kama Average and deviation lines – XBTUSD weekly chart

This is the main template I use with the tradingview platform, it is a weekly XBTUSD chart with the Kaufmann moving average I modified by adding the deviation lines.
These deviation lines have been appropriately calibrated according to the volatility of the underlying asset.
As you can clearly see, the market has never tested the second negative deviation line and has always reacted from the first line.
So it was also yesterday after a minimum at 9200$ where a strong reaction took place up to 11600$.

I think that this market is headed well above 20000$ in the upcoming weeks/months, for completeness a possible bearish scenario would imply first a drop down to 7500$, a subsequent reaction to 9500$-10000$ before resuming the fall to new lows. This possible bearish scenario would convince me to liquidate all the bitcoins i bought in 2014-2015 at an average price of 550$. As long XBTUSD stays above 9500$ i’m not worried for my long term position.

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Long Term Update: 2018 Outlook with entropic methods

Every beginning of a new year i post an outlook using entropic methods explained in the technical section of this blog. Here you can find the 2015, 2016 and 2017 forecast update, where you can find more information about this approach.

Updated values for bitcoin (in brackets values of last year) using daily data since August 2010 (average of 4 exchanges when possible).

 BTC/USD
Growth Factor G 1.0028 (1.0007)
Shannon Probability P 0.5384 (0.519)
Root mean square RMS (see this as volatility) 0.059 (0.045 )

Bitcoin’s entropic values versus the Usd strongly improved in 2017 but volatility increased a bit, despite this the Growth Factor (G) increased up to 1.0028% (remember that volatility is detrimental to the Growth Factor) compounded daily or 280% yearly up from 30% of 1y ago. Also the optimal fraction of your capital to invest in bitcoin improved in 2017 with a 7.7% instead of 6.4% of 1y ago.

 2018 Price forecast  Full volatility  Half volatility
Forecast using only G* ~38700$ ~38700$
Upper bound adding volatility ~121000$ ~68000$
Lower bound subtracting volatility ~12300$ ~21800$

*38700 is obtained with today price (around 13800$) times (1.0028^365)=~2.77
13800*2.77=38740, just change 365 with the number of days you prefer for a different forecast.

It’s interesting to notice that with reduced volatility the support level is above the actual quote of XBTUSD (13800$ at the moment i’m writing) because the growth factor (G) is very high and is skewing everything to the upside. If volatility stays low the uptrend should push bitcoin above 22k USD during the year without too much effort, it’s a scenario i prefer instead of wild price swings.

What went wrong in 2017?

A year ago, I forecasted a top of $2900, reached in July 2017 with an intermediate Top well ahead of the end of the year. I tried to double the volatility factor (rms) to see the next level after a reader asked me about the possibility that bitcoin was in a bubble above 2900$. The next level was around 6000$, again this new level has been broken at the end of October.
The last 2 months have been crazy and the explanation is a huge change in shift in this market happened in March 2017 (with altcoins literally exploding) that basically erased the reliability of the January 2017 forecast. I think that this year forecast should be more accurate compared to last year.

Conclusions

For this year i think that i’ll consider the support/resistance levels obtained with a full volatility value with the result to have for the whole 2018 a good probability to stay inside the 12300$-121000$ price zone.
At the same time i think that at the end of a strong buying climax period, if any, it will be wise to reduce your bitcoin investment if the price goes above 60k-70k USD.

I’m at your disposal for any questions; see you at the next update and Happy New Year!

Weekly Range Update: Bottom Done

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XBTUSD Daily Chart

XBT/USD weekly price range 14300$-17500$ | This week we return to a lower volatility level for calculating VWAP volume deviation lines, so we have a third and fourth deviation line not as far apart as they were in previous updates. The trend remains steadily UP also because the minimum done at 11000 dollars is clearly higher than that of 12 November at around 5600 dollars; I therefore expect a new maximum in the weeks to follow above 20000 dollars.

For the resistance zone the most probable range is from 17k to 21k dollars while for the support zone the range is 11000$-14300$.

The RSI oscillator has dropped almost to the oversold area with its average at about 47 that still has to turn upward to confirm a reversal in the trend.

With the other template i follow with KAMA average and deviation lines i’ve some doubts that XBTUSD will go towards the interesting long term support zone of 7500-9000 USD.

In the event of an unexpected catastrophic news, the support area on the weekly chart rises to USD 4300-5800.

Italian version here at bitchanger.com

Long Term Update: new support area

kama
Weekly Chart BTCUSD – KAMA V1.2 Average + Price Deviation Bands

This is the last version of my KAMA indicator (public at tradingview) with default settings tuned for BTCUSD weekly chart.

In the previous two occasions the first deviation line held well the drop, notice how in the recent November bottom the price was at an intermediate level between the Kama and the first negative line, an high bottom interpretable as a strong signal followed by a strong top (~19600$)

At the moment the bottom is around 11k usd, done again at an intermediate level while the 7500$-9000$ support area is defined by the 1st and 2nd deviation line.
This support area should work especially if the market goes sideways, it could be a nice zone where to buy with reduced risk of high initial drawdown.

There are no guarantees that the market will stay sideways enough to test that support area but strategically isn’t a bad move to buy inside it with a stoploss below 7000$.

Quantitative Analysis of Altcoins, part III

In part I and II I did a quantitative analysis on altcoins and possible strategies on how to capitalize on their weakness compared to bitcoin.

In Part III we will see how to allocate a portfolio starting with Fiat currencies.

In the table below you will find cryptos with relative gains (G) and volatility (RMS) against the dollar using all the historical data available, as data source was mainly used  poloniex and bittrex exchanges, for bitcoin has been used Bitstamp.

In red the cryptocurrencies with negative Gain against the USD.

Cryptocurrency  Gain (G) Volatility (RMS)
Bitcoin 1.0045 0.0796
Ethereum 1.0033 0.0863
Ethereum Classic 1.0031 0.076
BCash 1.0029 0.1535
Eos 1.0024 0.1355
Dash 1.0013 0.0894
Monero 1.0007 0.0781
Stellar Lumens 1.0005 0.1207
Ripple 1.0004 0.1115
Iota 0.9984 0.127
Qtum 0.9979 0.1224
Litecoin 0.9976 0.095
Bitcoin Gold 0.9966 0.0983
Next 0.9954 0.11
Zetacash 0.9902 0.1104

It’s pretty obvious that i’ll not consider any crypto with negative Gain and Bitcoin is clearly the winner with the best Gain and low volatility compared to the rest. I exclude also all the crypto with positive Gain but with high volatility because the main objective is to allocate a portfolio with the lowest possible volatility.

The remaining crypto are:

  1. Bitcoin
  2. Ethereum
  3. Ethereum Classic
  4. Dash
  5. Monero

Ideally it should be allocated the same amount of money on each asset but to compute the fraction of your capital to put on each asset i use the same formula seen in Part I & II.

F = 2P - 1

Where F is the optimal fraction of your capital to wage in a single trade and P the persistence or Shannon Probability, concepts already explained in Part I & II.

Cryptocurrency  Persistence (P) Fraction of your capital to wage (F)
Bitcoin 0.55 10%
Ethereum 0.5441 9%
Ethereum Classic 0.5317 6%
Dash 0.535 7%
Monero 0.5286 6%

Thanks to the formula F=2P-1 I know how much to wage on each crypto for a total of around 40% of your capital to invest in crypto. The remaining 60% could be invested in traditional stuff of your choice (equities, bonds, real estate). But let see in detail a simple portfolio management strategy.

Simple Portfolio Management Strategy

  1. Maintain about ten, or more, equities in the portfolio.
  2. Maintain about equal asset allocation between the ten equities.
  3. Consider the investment horizon from one to four calendar years.
  4. Be skeptical of investing in assets with less than a two and a half year history with a minimum of four and a half years.

Four simple policies listed in order of importance, and the second policy is the one that makes the money or the “engine” of the strategy. A short investment horizon is mandatory because “risk management” is an important part of financial engineerin g and given enough time, no matter how small the risk, it will bite.

At the moment there aren’t ten cryptocurrencies that satisfy my needs in terms of Gain (G) and Volatility (RMS) so I have to find a compromise, using only five crypto and, personally, i prefer to don’t maintain an equally asset allocation among all cryptos because there is a huge difference in terms of size between Bitcoin and the others. Another issue is that many altcoins have less then 2 years of history because this new sector is relatively new so it is difficult to respect rule number 4.

Another important concept is how frequent to balance the portfolio. Doing it every day is really not necessary for the casual long term investor. An interesting choice is to rebalance asset allocation if there is an asset that exceed all the others by 5-10%. Basically when one asset increased in value more than the others, money should be removed from the investment, and re-invested in all the others thus defending the gains through investment diversification.

Aggressive Portfolio

Aggressive Asset Allocation with ~40% in crypto (click to enlarge)

The suggested asset allocation is intended as very aggressive having almost 40% allocated in cryptocurrencies, I would advise not to follow this if you are over 65 or if you have a family with kids. In this case I would suggest a maximum of 10% invested in cryptocurrencies (e.g. 6% Bitcoin, 4% Ethereum or 6% Bitcoin, 2% Dash, 2% Monero).

In the case of a very conservative asset allocation, for who has a very low risk tolerance, I would not go beyond 5% allocated in cryptocurrencies.

Personally i’ve a very high aggressive asset allocation but I’ve all the time and experience to follow carefully my Portfolio and to act accordingly to new information on a daily basis.

In the future i might publish other updates about the subject with updated quantitative data on altcoins/bitcoin.

 

 

Weekly Range Update: CBOE/CME is coming!

bitstampUSD 1 Day #1 2017-12-10 23_03_45.582
XBTUSD Daily Chart

XBT/USD weekly price range 11500$-19100$ | The resistance zone for this week is very wide but less than the previous week and ranges from 17500 to 19100 dollars, the support area around the 2nd deviation line, from 11500 to 11300 dollars.

Clearly, intraday volatility from tomorrow will increase due to the impact of CME and CBOE futures, so there may be very good buying opportunities if the price were to fall below $11500 for short periods of time. Given that the arrival of derivatives is not an unexpected news and I don’t expect any kind of impact on the current bullish trend, what we will see will only be an increase in intraday volatility as already proven in the past by academic studies.

Also this week to compensate for record volatility levels I refined again the coefficients to calculate the various VWAP deviation levels so as to have greater consistency with other indicators I use.

The RSI oscillator is always clearly overbought even if it has downloaded a little while keeping always above the threshold of 70; as long as there is this great force this oscillator will remain constantly above 70 and therefore it must always be contextualized the reading of RSI according to the condition of the market, today still in extreme force.

In the event of an unexpected catastrophic news, the support area on the weekly chart rises to 4100-5300 USD.

ITA Version here

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.

 

Weekly Range Update: again at resistance

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XBTUSD Daily Chart – VWAP Levels

XBT/USD weekly price range 10500$-14400$ | The resistance zone for this week is very wide and ranges from 12000$ to 17000$ and is defined by the 2nd and 4th deviation line, we start the week again near a resistance but I think it is possible to reach 14400$ with a maximum peak at 17000$ eventually the week later near the CME bitcoin futures debut.

To compensate for higher levels of volatility I have increased the coefficients to calculate the various levels of VWAP price deviation lines so as to have greater consistency with other indicators that I use to compute volatility, supports and resistances; all this to ensure a good correlation between the different approaches I use.

We are very unbalanced to the upside and I don’t expect significant declines for this reason the support area is more narrow and ranges from 9250 to 10500 dollars just above the 1st deviation line.

The RSI oscillator is always clearly overbought with its average being saturated well above the threshold level of 70; these two conditions do not preclude a further push of the market at $14000 and until I see a slowdown on the weekly chart I will continue to ignore this oscillator.

In the event of an unexpected catastrophic news, the support area on the weekly chart is updated to 3600-4500 USD.

ITA version here.

Weekly Range Update: at resistance

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XBTUSD Daily Chart – VWAP and dev. levels

XBT/USD weekly price range 7600$-10700$ | The 2-month VWAP is now at 6600$, the resistance zone ranges from 9600$ to 10700$ and is defined by the 3rd and 4th price deviation line.
XBTUSD begins the week at a resistance level, however this pair has proven that it is not impossible to reach the fourth positive deviation line above VWAP, it has already happened on November 8th.

The support area ranges from 6600$ to 7600$ and is defined by VWAP and the 1st deviation line.

In the event of a strong profit taking, I think it is very difficult to see a test down to the VWAP at 6600$, given the enormous strength of this market is much more likely that the support level at 7600$ will hold.

The RSI oscillator is clearly overbought with its average just above the threshold level of 70; these two conditions do not preclude a further boost of the market up to 10700$.

In the event of an unexpected catastrophic news, the support area on the weekly chart is updated to 3700-4400 USD.

ITA version here.

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

Weekly Range Update

XBTUSD dailychart
XBTUSD dailychart

XBT/USD weekly price range 6800$-8600$ | This week the 2-month VWAP updates to 6100$ from last week’s 4800$; new data is replacing the old ones and it may happen that you have some slight changes on the price level of the reference average.

The resistance zone ranges from 8600$ to 9800$ and is defined by the 2nd and 3rd deviation line of the 2-month VWAP.

The support area ranges from $6100 to $6800 and is defined by VWAP and an intermediate level between the VWAP and the 1st deviation line.

I think it is very difficult to see a test down to the VWAP at $6100, if there were to be some profit taking the market should not fall below $6800, considering that the RSI oscillator turned upside without testing the oversold area i still believe that this market will go over 8000$ eventually after a small correction towards our first support at 6800$.

The other template I use on Tradingview with KAMA average and deviation levels is very similar to this one; the weekly KAMA is at 5800$ not far from the 6100$ of the 2-month VWAP.
The resistance zone is 8000$-9300$, slightly lower than the one presented with this update of 8600$-9800$.
Basically we have a decent correlation between the two templates (VWAP using Sierrachart and KAMA using Tradingview. com)

In the event of an unexpected catastrophic news, the support area on the weekly chart is updated to 3200-4000 USD.

ITA Version Here.

Short Term Update

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Updated Weekly Range Levels

Given the good price reaction from the 5400$ bottom, I decided to update the price levels for this week to 6250$-7600$ with an extreme to $9000.

As I often say, the higher the bottom, the higher the chance is that the following top is very high and could be between 9000 and 10000 dollars, we have seen that the market almost never reaches the fourth VWAP deviation line so let’s say that a good top could be around 9000$.

The ALMA moving average isn’t yet bullish but it’s close to reverse its direction while the RSI failed to reach oversold territory and this means that the market remains very strong despite all the FUD of last week.