Category: Long Term Trading

Long Term Update: 2026 Outlook with entropic methods

On By CryptoAdvisorIn Long Term Trading10 Comments

Every year i post an outlook using entropic methods explained in the technical section of this blog. Here you can find the 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023, 2024 and 2025 forecast update, where you can find more information about this approach.

Updated values for bitcoin (in brackets values of 2025) using daily data since August 2010 (from now on I will use only BITSTAMP data, as today there are not many differences between major Bitcoin exchanges.).

   BTC/USD
Growth Factor G 1.00094 (1.00099 )
Shannon Probability P (see this as entropy) 0.5217 (0.5295 )
Root mean square RMS (see this as volatility) 0.045 (0.047)

The entropy levels of Bitcoin against the USD showed no improvement in 2025. The Growth Factor (G) dropped a bit to 1.00094% daily compounded, equivalent to about 41% annually. The optimal portion of your total wealth to allocate to Bitcoin is now 4.3% (~0.5217*2=1.0434 – 1 = 0.0434 or ~4%) and it went down a bit due to a flat year.

“For those who may have forgotten, the Shannon Probability measures the persistence of Bitcoin’s price movement, indicating the likelihood that the asset will experience a positive trend. A value of 0.52 suggests that, out of 100 days, Bitcoin is likely to show an upward movement on 52 days, and either a decline or no significant movement on the remaining 48 days.”

Bitcoin’s historical volatility dropped slightly this year, the only positive development amid otherwise challenging data, and aligns with expectations for a maturing asset in terms of capitalization. However, as noted in updates over the past two years, the pace of decline has slowed considerably, and volatility remains substantially higher than that of other assets, underscoring Bitcoin’s persistent nature as a highly speculative investment.

 
 2026 Price forecast  Full Historical Volatility  Half Historical Volatility
Forecast using only G* or Growth Factor ~124,000$ ~124,000$
Upper bound adding volatility ~292,000$ ~190,500$
Lower bound subtracting volatility ~52,700$ ~80,800$

*124,100 $ is obtained with 1st January as a starting price (around 87890$) times (1.00094^365)=~1.41   |  87890*1.41=~124000$, just change 365 with the number of days you prefer for a different forecast.

What happened in 2025? 

In this 2025 this market went up but failed to break through the equilibrium point that I calculate every year in January, which was set at around $132,000. The market corrected down to the annual support calculated with half historical volatility at about $85,000. As shown for those who follow me on Twitter, there were also weekly supports from my deviation bands at around $83,000. Considering that the updated forecast for 2026 still includes $80,800 as support, the area between 80 and 90 thousand dollars remains an interesting support zone.

I was hoping for something better this year, at least a quick visit above $132,000, but that didn’t happen. For this year, the directional bias remains unclear, though key levels are well-defined., but the support zone at around $53,000 remains very interesting, it’s both the last level of this year’s forecast and also a support from my monthly deviation bands calculated from the KAMA average. I refer you to my latest post on Twitter.

Conclusions

After holding my long position for nearly three years, initiated in February 2023 at approximately $22,500, this is a good moment to reassess the risk/reward profile at current levels.

The 2025 data tells a nuanced story, while Bitcoin delivered positive returns, the entropic indicators showed marginal deterioration. The Growth Factor declined and Shannon Probability dropped , these aren’t alarm signals, but they suggest that the statistical edge has weakened a bit compared to when I entered the position.

At current prices around $88,000, I’m sitting on roughly 290% gains. My approach for 2026 is conditional.

If $80,000 breaks down decisively, I will take profits. This level represents both the lower bound of my half-volatility forecast and a psychologically significant threshold. Even at $80k, I’d be locking in approximately 255% gains, a reasonable exit after a historically strong run.

My reentry target would be the $50,000–55,000 zone. This area aligns with both the full-volatility lower bound at $52,700 and my monthly KAMA deviation bands. 

On the other hand, if $132,000 breaks to the upside, I will hold and reassess at the upper bound levels. This is not a bearish call, it’s risk management after a successful multi-year trade. The data doesn’t justify aggressive positioning in either direction at these levels.

Feel free to reach out with any questions, and I’ll see you in the next update. Happy New Year!

Charts

Bitcoin’s cumulative volatility follows a compelling logarithmic decay curve, at the current trajectory, convergence with typical US equity volatility levels is still 15 to 20 years out. A reminder that, as an asset class, Bitcoin remains in its infancy.
Projected levels for 2026
Here’s what happened in 2025, where the market failed to move above the equilibrium point calculated using only the Growth Factor (G).

Long Term Update: 2025 Outlook with entropic methods

On By CryptoAdvisorIn Long Term Trading18 Comments

Every year i post an outlook using entropic methods explained in the technical section of this blog. Here you can find the 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023 and 2024 forecast update, where you can find more information about this approach.

Updated values for bitcoin (in brackets values of 2024) using daily data since August 2010 (from now on I will use only BITSTAMP data, as today there are not many differences between major Bitcoin exchanges.).

   BTC/USD
Growth Factor G 1.00099 (1.00099 )
Shannon Probability P (see this as entropy) 0.5295 (0.5224 )
Root mean square RMS (see this as volatility) 0.047 (0.047)

The entropy levels of Bitcoin against the USD showed no significant improvement in 2024. The Growth Factor (G) remained steady at 1.00099% daily compounded, equivalent to about 44% annually. The optimal portion of your total wealth to allocate to Bitcoin increased to 6% (~0.5295*2=1.0448 – 1 = 0.059 or ~6%), driven by a year-long upward trend in Bitcoin’s price, which boosted the Shannon Probability from 0.522 to nearly 0.53, an improvement, but still modest.

“For those who may have forgotten, the Shannon Probability measures the persistence of Bitcoin’s price movement, indicating the likelihood that the asset will experience a positive trend. A value of 0.53 suggests that, out of 100 days, Bitcoin is likely to show an upward movement on 53 days, and either a decline or no significant movement on the remaining 47 days.”

Bitcoin’s historical volatility has remained relatively unchanged this year, aligning with the average recorded since the inception of its historical data in August 2010. Currently, it remains stable at a comparatively high level, particularly when measured against traditional assets such as gold, stocks, bonds, and forex currencies, refer to the chart at the end of this post for more details.

As i said in my last year update it seems that a volatility plateau has been identified, and it is notably substantial higher compared to other assets. This suggests that Bitcoin continues to be a highly speculative asset as its volatility is still too high to be considered a viable reserve asset for central banks, despite increasing recent discussions around its potential in this role. 

 2025 Price forecast  Full Historical Volatility  Half Historical Volatility
Forecast using only G* or Growth Factor ~132,300$ ~132,300$
Upper bound adding volatility ~328,000$ ~209,300$
Lower bound subtracting volatility ~52,300$ ~85,100$

*132,300$ is obtained with 1st January as a starting price (around 91900$) times (1.00099^365)=~1.44   |  91900*1.44=~132300$, just change 365 with the number of days you prefer for a different forecast.

What happened in 2024? 

A year ago, I predicted an upper boundary of $151,000 using full historical volatility and approximately $96,000 using half of that volatility. These targets were calculated based on the opening price on January 1, 2024, which was around $44,000. The calculated support levels were $24,900 and $39,000.

The year turned out to be overwhelmingly positive, with Bitcoin surpassing the initial calculated resistance of $96,000. This reflects notable strength in the uptrend, as BTCUSD reached an all-time high of $108,300 in December. The most probable resistance level of $96,000 held true, as the year-end price stayed below it, which aligns with expectations.

Looking ahead to 2025, I will focus on levels calculated using reduced volatility (half the historical value) since this approach often yields more reliable results. This gives us a key support level at $85,000, which is highly significant. If Bitcoin spends too much time below $85,000 during 2025, it may signal the end of the uptrend that began from the $16,000 low in 2022.

In a bearish scenario, should it materialize, I would anticipate a potential low in the $50,000 range during 2025.

Conversely, if Bitcoin holds consistently above $85,000, the first major resistance to watch is around $210,000. This could mark the end of the current uptrend that started in 2022 and would represent a strong peak. Any value exceeding $210,000 should be considered a clear speculative bubble. I do not expect the upper limit of $328,000 to be breached throughout 2025.

Conclusions

For this year, I may consider taking profits on my position if the market shows signs of weakness below the critical $85,000 level. As a reminder, I initiated my bullish position in February 2023 at approximately $22,500.

I also recommend cautious long-term trading strategies this year. The growing speculation around Bitcoin as a potential reserve asset for central banks could lead to a spectacular market top. In that scenario, preliminary support levels for 2026, calculated using a starting price of $91,900 on January 1, 2024, and a two-year window, suggest potential declines between $54,000 and $100,000. If Bitcoin reaches a significant top, potentially at or above $200,000, these levels become plausible targets for a subsequent correction in 2026. These values are provided as a preview to illustrate possible directions, but only if such a dramatic peak occurs this year.

That said, I remain firmly confident in the $85,000 support level as a key indicator of the current uptrend’s strength. Regardless of the various scenarios discussed, keep this level in mind as your primary reference point.

As for the upper boundary, I believe it is highly improbable to reach or surpass $328,000 during 2025.

Feel free to reach out with any questions, and I’ll see you in the next update. Happy New Year!

Charts

Bitcoin’s cumulative volatility as expected is dropping every year and is stabilizing towards a value that is still a bit high compared to other traditional assets (stocks, gold, bonds range from 0.01 to 0.03) but the very high average returns of btc compensate the high volatility. The values represent the root mean square of logarithmic returns of bitcoin daily data.
Projected levels for 2025
Here’s what happened in 2024, where the market spent a lot of time around the equilibrium point calculated using only the Growth Factor (G).

Long Term Update: 2024 Outlook with entropic methods

On By CryptoAdvisorIn Long Term Trading19 Comments

Every year i post an outlook using entropic methods explained in the technical section of this blog. Here you can find the 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022 and 2023 forecast update, where you can find more information about this approach.

Updated values for bitcoin (in brackets values of 2023) using daily data since August 2010 (from now on I will use only BITSTAMP data, as today there are not many differences between major Bitcoin exchanges.).

   BTC/USD
Growth Factor G 1.00099 (1.00090 )
Shannon Probability P (see this as entropy) 0.52237 (0.5214 )
Root mean square RMS (see this as volatility) 0.0471 (0.049)

The entropy values of Bitcoin versus the USD have experienced a slight improvement in 2023. The Growth Factor (G) has marginally risen to 1.00099% compounded daily or 144% per year, surpassing the 139% observed one year ago. The optimal fraction of your total wealth to invest in Bitcoin has also slightly elevated to 4.5% (~0.52237*2=1.04475 – 1 = 0.04475 or ~4.5%), a figure that can still be rounded to 5%, similar to last year’s recommendation.

The volatility of Bitcoin has not exhibited an increase this year, considering the average value since the inception of its historical series in August 2010. Currently, it maintains a stable position at a relatively high value when compared to other assets such as gold, stocks, bonds, and forex currencies.

It seems that a volatility plateau has been identified, and it is notably substantial higher compared to other assets. This suggests that Bitcoin continues to be a highly speculative asset. In the year 2023, the growth factor of BTCUSD still outperforms traditional markets significantly, except for the Shannon Probability, which aligns closely with that of the US stock market (around 0.52). This implies that, on average, out of 100 days, an asset rises for 52 days and declines for 48 days.

 2024 Price forecast  Full Historical Volatility  Half Historical Volatility
Forecast using only G* or Growth Factor ~61,400$ ~61,400$
Upper bound adding volatility ~151,000$ ~96,000$
Lower bound subtracting volatility ~24,900$ ~39,000$

*61400 is obtained with 1st January as a starting price (around 42650$) times (1.00099^365)=~1.44   |  42650*1.44=~61400$, just change 365 with the number of days you prefer for a different forecast.

What happened in 2023? 

A year ago, I predicted an upper boundary of $58,000 using full volatility and about $36,500 using half of historical volatility, these two targets were calculated based on the opening price on January 1, 2023, which was around $16,500. The calculated support levels were $9,100 and $14,500. 
The year has proven positive, surpassing the initial calculated resistance level of $36,500, which coincided with the monthly KAMA average. This signals a notable strength in the uptrend, with BTCUSD transitioning from a position of weakness to one of strength by rising above the monthly average.

Conclusions

For this year, it might be a smart move to also consider a lower value for volatility, let’s say 25% of the historical volatility, as I don’t expect a new all-time high but rather a consolidation phase a few months before, during, and after the halving. Therefore, determining a resistance level at around $77,000, calculated with a precise 1/4 of historical volatility—a method I don’t typically employ but find plausible for this year. This is due to my belief that it might be challenging for the volatility to remain high for a significant amount of time, making it less likely for BTC to surpass this $77,000 level.

I might consider taking profit if the market shows signs of weakness around this level. I remind you guys that I had opened a bullish position in February 2023 at approximately $22,500.

Furthermore, I have cautious long-term trading recommendations for you this year. The hype surrounding ETFs might culminate in a “sell on news” scenario on the day the ETF gets approved. There’s a possibility of subsequent gradual declines in Bitcoin prices toward calculated support levels for the next year, ranging between $24,000 and $39,000. Don’t forget that the most probable support area is around the monthly Kama, which is inside the support windows for this year ($24,900-$39,000).

Instead of anticipating any catastrophic scenarios this year, in contrast to the previous year, which appeared more susceptible to bearish scenarios, I maintain my view of the $24,900 support as very solid.

About the upper bound i’ve to admit that it is very unlikely to reach and/or break $151,000 during 2024.

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

Charts

Bitcoin’s cumulative volatility as expected is dropping every year and is stabilizing towards a value that is still a bit high compared to other traditional assets (stocks, gold, bonds range from 0.01 to 0.03) but the very high average returns of btc compensate the high volatility. The values represent the root mean square of logarithmic returns of bitcoin daily data.
The first lower monthly kama average price band will probably slowly reach the $25,000 support level during the 2023.
I’ve added the equilibrium point computed using the G growth factor at $61,400.
The chart is monthly and begins at the end of November ’22 bottom.

Long Term Update: The Big Picture part II

On By CryptoAdvisorIn Long Term Trading, Short Term Trading10 Comments
BTCUSD Monthly Chart Jan 2021 to present day

For all my Italian followers, I am pleased to announce that my analysis are now available in Italian on bit-reminder.com. This Italian website, which I collaborate with, is a valuable resource for those interested in the cryptocurrency world, with lots of information and a technical analysis section authored by me. In addition to covering Bitcoin, from time to time I also discuss some altcoins using the same approach, utilizing the CRSI oscillator and KAMA price bands. You can find the Italian version of this article on that website as well.

Since I last made my prediction in February, Bitcoin has continued to rise and is now approaching the resistance level of $36,000. However, bitcoin is hesitating just below this critical level of $36,000 without a clear breakout. The modified RSI oscillator is approaching the overbought level, so probably we are two to three months from a top.

Based on the Kama average levels, my earlier prediction of a target range of at least $36,000 with a maximum potential upside of $58,000 still stands. However, given the current market conditions, it’s difficult to say whether we will see a new intermediate top this year. However, there is still a significant portion of May left, so it will be interesting to see how the market develops in the coming weeks and if there is enough fuel to approach $36,000 before end of June and possibly break it to hope to see $50,000 by the end of the year.

Short Term View

BTCUSD Daily Chart


For those who follow me on Twitter, they already know about the situation in the short term. Since the market’s corrected inversion on April 25th, it has been weak and moving sideways. There is a possibility that it might drop to $25900, which could result in my CRSI becoming oversold and recharging itself, potentially leading to a new short-term buy signal.

Long Term Update: 2023 Outlook with entropic methods

On By CryptoAdvisorIn Long Term Trading7 Comments

I will be busy in the coming days, so the yearly update for 2023 is being released early.

Every year i post an outlook using entropic methods explained in the technical section of this blog. Here you can find the 2015, 2016, 2017, 2018, 2019, 2020, 2021, and 2022 forecast update, where you can find more information about this approach.

Updated values for bitcoin (in brackets values of 2022) using daily data since August 2010 (from now on I will use only BITSTAMP data, as today there are not many differences between major Bitcoin exchanges.).

   BTC/USD
Growth Factor G 1.00090 (1.00130)
Shannon Probability P (see this as entropy) 0.5214 (0.5254)
Root mean square RMS (see this as volatility) 0.049 (0.049)

The entropy values of Bitcoin versus the USD have remained relatively consistent in 2022. The Growth Factor (G) has decreased slightly to 1.00090% compounded daily or 139% per year, which is less than the 168% seen one year ago. The optimal fraction of your total wealth to invest in Bitcoin has slightly decreased to 4.3% (~0.5214*2=1.0428 – 1 = 0.0428 or 4.3%, which is still roundable to 5% like last year).
The volatility of Bitcoin, unlike in previous years, has not decreased this year if we consider the average value from the beginning of the historical series, around August 2010 and it appears that for now, it remains stable at a fairly high value when compared to other assets such as gold, stocks, bonds, and forex currencies.
Despite a challenging year in 2022, the BTCUSD growth factor is still much better than traditional markets, except for the Shannon Probability, which still matches that of the US stock market (around 0.52). This means that on average, out of 100 days, an asset goes up 52 days and down for 48 days. 

 2023 Price forecast  Full Historical Volatility  Half Historical Volatility
Forecast using only G* ~23,000$ ~23,000$
Upper bound adding volatility ~58,000$ ~36,500$
Lower bound subtracting volatility ~9,100$ ~14,500$

*23000 is obtained with 1st January as a starting price (around 16500$) times (1.0090^365)=~1.39   |  16500*1.39=22900, just change 365 with the number of days you prefer for a different forecast.

What happened in 2022? 

A year ago, I predicted an upper boundary of $199,000 using full volatility and about $123,000 using half of historical volatility, these two targets were calculated based on the opening price on January 1, 2022, which was around $48,000. The calculated support levels were $48,000 and $29,800. 
It has been a negative year as we have never gone beyond the first calculated support level of $48,000, indicating a general weakness, while some support at $29,800 was seen during the year until May, after which even that level was abandoned and broken to the downside.
It should be noted that the first support at $48,000 acted as resistance during the spring when Bitcoin was unable to break through this support from below. When yearly supports act as resistance, it is evident that the market is weak.

Conclusions

I do not have any clear long-term trading recommendations for you this year as the Federal Reserve’s change in monetary policy to combat inflation has reduced the liquidity necessary to support strong Bitcoin prices. It may be wise to wait for a potential change in policy, but I expect Bitcoin prices to gradually decline towards calculated support levels for next year ($9,100 and $14,500). Based on my analysis using monthly bands based on Kaufman’s average, the most probable support area is around $12,000 (as shown in the chart section below), inside the 9,000$-14,000$ support price range for 2023.

If market volatility increases significantly above historical average, it may be a good opportunity to engage in a short-term trade by buying Bitcoin within the price range of $6,500 to $9,000. The value of $6,500 has been calculated using twice the historical volatility of Bitcoin as a reference and I consider it a rock solid support level in the event of a catastrophic market downturn.

If there is an improvement without making new lows, it is evident to me that resistances should be sought around $36,000, where we have the first resistance level computed with entropic methods and where there is also the monthly Kama average.
It is very unlikely to break $58,000 during 2023.

Unfortunately, this year I do not have a clear idea, I remain pessimistic however looking for a target at $12,000 where eventually buy something should I notice an improvement in market liquidity.

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

Charts

Bitcoin’s cumulative volatility as expected is dropping every year and is stabilizing towards a value that is still a bit high compared to other traditional assets (stocks, gold, bonds range from 0.01 to 0.03) but the very high average returns of btc compensate the high volatility. The values represent the root mean square of logarithmic returns of bitcoin daily data.
The second lower monthly kama average price band will probably slowly reach the $12,000 level during the 2023.
I expect to find similarities between the levels calculated in the Kama indicator i use and those used with this approach, the formulas for calculating the bands in my indicator are the same as those used in this update.

Long Term Update: 2022 Outlook with entropic methods

On By CryptoAdvisorIn Long Term Trading15 Comments

Every year i post an outlook using entropic methods explained in the technical section of this blog. Here you can find the 2015, 2016, 2017,  2018, 2019, 2020 and 2021 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 data of 4 main exchanges when possible).

   BTC/USD
Growth Factor G 1.00130 (1.00104)
Shannon Probability P (see this as entropy) 0.5254 (0.5232)
Root mean square RMS (see this as volatility) 0.049 (0.055)

Bitcoin’s entropic values versus the Usd improved during 2021,  the Growth Factor (G) grow to 1.00130% compounded daily or 160% yearly, higher then 1y ago. The optimal fraction of your total wealth to invest in bitcoin rised to 5.1%  (~0.5254*2=1.051 – 1 = 0.051 or 5.1% roundable to 5%).
Volatility continues to drop year after year and that’s normal as bitcoin gets bigger and bigger so less prone to volatility.
The BTCUSD growth factor is much better then conventional markets except the Shannon Probability that still match the US Stock Markets (around 0.522); it means that out of 100 days an asset goes up 52 days and down for 48 days, on average. I am not surprised of this because the same agents trading in conventional markets are more or less the same as those trading in the crypto market, so they have the same entropy or mental disorder.

 2022 Price forecast  Full Historical Volatility  Half Historical Volatility
Forecast using only G* ~77,000$ ~77,000$
Upper bound adding volatility ~199,000$ ~123,000$
Lower bound subtracting volatility ~29,800$ ~48,000$

*77000 is obtained with 1st January as a starting price (around 48000$) times (1.00130^365)=~1.6   |  48000*1.6=~77000, just change 365 with the number of days you prefer for a different forecast.

What happened in 2021? 

A year ago, I predicted a top of $121,000 using full volatility and about $72,000 using half of historical volatility, the latter being more likely to be hit and this is exactly what happened considering some room of error.
This market has made a low in June at $28,750, 10% above the $25,000 forecasted support level, again using half historical volatility.
During 2022 I recommend to hold your position till the upper boundary of the next cycle defined by monthly kama upper resistance bands ($80,000-$130,000) in accordance with the forecasted value of $123,000 using entropy methods and half historial volatility. 

Conclusions

As I said in the previous October update, I continue to believe that conditions in this market have changed since the other halving cycles which usually saw a Top around 19 months after the halving date. I expect a consolidation in 2022 with a slightly bullish sideways phase.
A very strong support zone remains the $30k to $48k price range that might be fine tuned during the year using Kama monthly price bands.
Should there be an excess of volatility I would advise you to take advantage of the event with some profit-taking between 120 and 200 thousand dollars; if volatility push the price down to the support area of $30,000-$48,000 do the opposite, buy:)

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

Charts

Bitcoin’s cumulative volatility as expected is dropping every year and is stabilizing towards a value that is still a bit high compared to other traditional assets (stocks, gold, bonds range from 0.01 to 0.03) but the very high average returns of btc compensate the high volatility. The values represent the root mean square of logarithmic returns of bitcoin daily data.
Monthly Chart BTCUSD with 2022 Price Forecast using entropic method.
The first lower monthly kama average will probably slowly reach the $30,000 level during the 2022.
I expect to find similarities between the levels calculated in the Kama indicator i use and those used with this approach, the formulas for calculating the bands in my indicator are the same as those used in this update.

Long Term Update: Critical Point

On By CryptoAdvisorIn Long Term Trading24 Comments

It is always better to look, as I always say, at larger time frames to understand how to build a winning operating strategy. I invite you first to look at this monthly chart of the BTCUSD, before commenting it.

BTCUSD Monthly Chart with Kama Roof/Floor price zones

We are clearly compressed in a price range well defined by the monthly average that defines the equilibrium point of this halving cycle (2020-2024) and an intermediate level with reduced volatility (around $28,000).

A Failure to move and to stay above the monthly Kama average would be bearish in my opinion and it would clearly be followed by a decline to the support zone of this halving cycle, between $11 and $18K.

With a confirmed break of the monthly average above $40,000 then the view would change and bitcoin would return to a position of strength that should bring it towards the resistance zone located between $80 and $130,000, in accordance with what I wrote in January in my “2021 outlook with entropic methods” where upper bound level was 121,000$

Bitcoin and the top of the previous cycle rule

Because of this rule i’m very skeptic to see bitcoin at 18,000$ or even lower inside the support price zone. Bitcoin in its history never tested the price level of the top of the previous halving cycle and if 29,000$ bottom is confirmed this rule will not be broken (29,000$ is above 2017 Top at around 20,000$).

What would a bottom in this cycle below 20,000$ imply? Well, it would mean that bitcoin’s long-term trend is slowing down and we would probably have to wait for the next halving cycle, after 2024, to see a Top above the current one at $64,000. Thus, as i wrote in this post title, we are at a critical point in time to understand what scenario bitcoin will go into.

The Big Picture

BTCUSD Monthly Chart since first halving

Here you can see what I said before, the Top of a halving cycle is always lower than the bottom of the next cycle, I interpret this as a strong bullish signal of the fundamental trend of bitcoin.

To conclude many of you are probably asking why the hell i sold below 29,000$ if there was an intermediate support slightly lower, well once i define a strategy with a trailing profit order i prefer to avoid to continously change it to accomodate what the market does, i had already moved the trailing profit order from 35,000$ down to 29,000$ to contain the volatility of bitcoin and it worked for several weeks then some bad luck damaged me, however this is all part of trading and i’m not upset at all.

Long Term Update: Estimating a TOP using Kama Efficiency Ratio

On By CryptoAdvisorIn Long Term Trading

The Efficiency Ratio (from now on ER) was presented by Perry Kaufman in his 1995 book “Smarter Trading” and it is calculated by dividing the price change over a fixed number of bars by the sum of the price movements that occurred to achieve that change.  The resulting ratio ranges between 0 and 1 with higher values representing a more trending market.
The idea here is to measure the value of the ER during an important Bitcoin Top to see if there is a strong coherence between different timeframes.

DateDaily ERWeekly ERMonthly ERAverage of 3
November 30, 20130.700.790.640.71
December 18, 20170.660.740.880.76
January 8 , 20210.620.770.440.61
Multi TimeFrame Kama Efficiency Ratio at Bitcoin Historical Tops

The high of last January 8 does not seem to have a situation on the various timeframes similar to that one of two important Bitcoin top (2013 and 2017), in particular the situation on the monthly timeframe is inconsistent.
On the weekly timeframe instead ER is quite high but I think that in the end the monthly timeframe will prevail. It is always difficult to understand which timeframe dominates over the others but personally I prefer to give precedence to the highest timeframe, in this case the monthly where there is room to rise.
I attach below the weekly chart so you can better visualize the ER situation

Weekly Chart BTCUSD with Kama Efficieny Ratio

And here the monthly chart where you can clearly see there is room for a prolonged trend.

BTCUSD Monthly Chart with 18 periods Kama Efficiency Ratio

Long Term Update: 2021 Outlook with entropic methods

On By CryptoAdvisorIn Long Term Trading14 Comments

Every year i post an outlook using entropic methods explained in the technical section of this blog. Here you can find the 2015, 2016, 2017,  2018 , 2019 and 2020, 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 data of 4 important exchanges when possible).

   BTC/USD
Growth Factor G 1.00104 (1.00087)
Shannon Probability P 0.5232 (0.5219)
Root mean square RMS (see this as volatility) 0.055 (0.056 )

Bitcoin’s entropic values versus the Usd improved during 2020,  the Growth Factor (G) grow to 1.00104% compounded daily or 146% yearly, higher then 1y ago. The optimal fraction of your total wealth to invest in bitcoin rised to 4.6%  (~0.5232*2=1.046 – 1 = 0.046 or 4.6% roundable to 5%).
Volatility continues to drop year after year and that’s normal as bitcoin gets bigger and bigger so less prone to volatility.
These values are still much better then conventional markets except the Shannon Probability that still match the US Stock Markets (around 0.522); it means that out of 100 days an asset goes up 52 days and down for 48 days, on average.

 2021 Price forecast  Full Historical Volatility  Half Historical Volatility
Forecast using only G* ~42,400$ ~42,400$
Upper bound adding volatility ~121,000$ ~71,850$
Lower bound subtracting volatility ~14,750$ ~25,000$

*42400 is obtained with 1st January as a starting price (around 28985$) times (1.00104^365)=~1.463   |  28985*1.463=~42400, just change 365 with the number of days you prefer for a different forecast.

What happened in 2020? 

A year ago, I forecasted a maximum top of $29380 almost reached the last day of the year.
This market has made a low in March that I like to call a “selling climax bottom” when the bearish momentum is exhausted during a major event, this low (3850$) was a bit above the 3370$ support level forecasted 1 year ago using full historical volatility.
During 2021 I recommend to hold your position till the upper boundary of the next cycle and, personally, i’ll continue to hold  my position opened at ~9100$ and I will not buy more bitcoins during 2021.

Conclusions

For this year i think that there is a good probability to reach an incredible new all time high above 100,000$!
Like one year ago,  i think that it will be wise to reduce your bitcoin investment if the price goes above ~200k USD (price calculated using the equivalent of 1.5 times the historical volatility of bitcoin).

For your curiosity, if there will be an explosion of volatility for whatever reason (massive migration of institutional investors from gold to bitcoin), using twice the value of historical volatility our target is ~350,000$ instead of 121,000$

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

Charts

 

Bitcoin’s cumulative volatility as expected is dropping every year and is stabilizing towards a value that is still a bit high compared to other traditional assets (stocks, gold, bonds range from 0.01 to 0.03) but the very high average returns of btc compensate the high volatility. The values represent the root mean square of logarithmic returns of bitcoin daily data.
Last 3 years of annual forecasts

My Bitcoin Price Model Part II

On By CryptoAdvisorIn Long Term Trading2 Comments

For those who follow me on twitter know that my bitcoin price model v1.1 that I presented on this blog last September 2019 has been invalidated by the recent low of March 13 at $3850.  I use 95% confidence level bands around my model forecast and that day the lower confidence level has been violated thus invalidating my model.
Since that day I have at various times pondered how to improve my old model and I recycled an idea that came to my mind last year when I presented the first model.
This idea is not to use the time factor to calculate the price of bitcoin but instead use the number of existing bitcoins that as you know grows over time and halves about every 4 years (until now it happened in 2012,2016 and 2020).
In doing so I discovered that there is a fairly strong linear relationship between the logarithm of the bitcoin price and the number of existing bitcoins at that particular moment.

All the important bitcoin bottoms are inside the 95% confidence bands (dotted lines)

With the software i use isn’t complicated to find a formula that approximate all the selected bitcoin bottoms.
This is the dataset used to compute the model:

Date Low Bitcoin Supply
2010/07/17 $0.05 3436900
2010/10/08 $0.06 4205200
2010/12/07 $0.17 4812650
2011/04/04 $0.56 5835300
2011/11/23 $1.99 7686200
2012/06/02 $5.21 9135150
2013/01/08 $13.20 10643750
2015/08/26 $198.19 14536950
2015/09/22 $224.08 14637300
2016/04/17 $414.61 15439525
2016/05/25 $444.63 15582350
2016/10/23 $650.32 15943563
2017/03/25 $889.08 16235100
2019/02/08 $3,350.49 17525700
2018/12/15 $3,124.00 17423175
2019/03/25 $3,855.21 17608213
2020/03/13 $3,850.00 18270000

The Formula is a very simple one, a first order price regression  between log(Low) and Bitcoin supply:

Where:
FPL = expected line where bitcoin is fairly priced
intercept = a costant
c1 = another coefficient that defines the slope of the Bitcoin supply input.

Here’s the resulting model after computing the parameters of the above formula.

This is the new bitcoin price model “FPL Line” v1.3 applied to a monthly bitcoin/usd chart:

Next Step: Computing the formula for the TopLine

The formula for computing the Top is:


Where:
TopLine= is the forecasted price where the next long term top might be.
intercept = a costant
c1 = another coefficient that defines at which pow the bitcoin supply is elevated

This formula is different from the one used to compute the FPL or bottom line. I’ve seen that there is not a strong linear relationship betweel the logarithm of important Bitcoin Tops and the Bitcoin supply, so i decided to switch to the formula used for the old model and it works better.

This is the dataset used to compute the model:

Date Price Bitcoin Supply
2010/07/17  $      0.05 3436900
2011/06/08  $      31.91 6471200
2013/11/30  $      1,163.00 12058375
2013/12/04  $      1,153.27 12076500
2017/12/19  $    19,245.59 16750613

Here’s the resulting model after computing the parameters of the above formula.

This is the new bitcoin price model “Top Line” v1.3 applied to a monthly bitcoin/usd chart:

95% Confidence Error Bands

With the indicator that i give you for TradingView i included also the error bands.
This are the error bands for the TopLine:

And for the bottom line or FPL (FairPriceLine)

It is quite obvious that with fewer points available the error bands for the TopLine are wider and less accurate compared to the FPL error bands where I have more points (17 instead of 5).

TradingView Indicator

I have also included an indicator for TradingView to give you the opportunity to experience the concepts and model illustrated in this update. You can also check the code and/or modify it as you like.

On April 10th, 2020 tradingview staff decided to censor my indicator and threatened to close my account, because of this i publish here the code so you can create your own indicator by yourself.

Bitcoin Model v1.3 Sourcecode:

Code is also available at pastebin

Remember to add a “TAB” key once before stock (line 10 and 13), in the process of copying and pasting data back and forth from tradingview the tab key is gone probably because there is not a tab code in HTML.

//@version=2

study(“Bitcoin Price Model v1.3”, overlay=true)

//stock = security(stock, period, close)
stock = security(“QUANDL:BCHAIN/TOTBC”,’M’, close)

if(isweekly)
//insert “TAB” key before stock
stock = security(“QUANDL:BCHAIN/TOTBC”,’W’, close)
if(isdaily)
//insert “TAB” key before stock
stock = security(“QUANDL:BCHAIN/TOTBC”,’D’, close)

FairPriceLine = exp(-5.48389898381523+stock*0.000000759937156985051)

FairPriceLineLoConfLimit = exp(-5.86270418884089+stock*0.000000759937156985051)
FairPriceLineUpConfLimit = exp(-5.10509377878956+stock*0.000000759937156985051)

FairPriceLineLoConfLimit1 = exp(-5.66669176679684+stock*0.000000759937156985051)
FairPriceLineUpConfLimit1 = exp(-5.30110620083361+stock*0.000000759937156985051)

plot(FairPriceLine, color=gray, title=”FairPriceLine”, linewidth=4)

show_FPLErrorBands = input(true, type=bool, title = “Show Fair Price Line Error Bands 95% Confidence 2St.Dev.”)
plot(show_FPLErrorBands ? FairPriceLineLoConfLimit : na, color=gray, title=”FairPriceLine Lower Limit”, linewidth=2)
plot(show_FPLErrorBands ? FairPriceLineUpConfLimit : na, color=gray, title=”FairPriceLine Upper Limit”, linewidth=2)

show_FPLErrorBands1 = input(false, type=bool, title = “Show Fair Price Line Error Bands 68% Confidence 1St.Dev.”)
plot(show_FPLErrorBands1 ? FairPriceLineLoConfLimit1 : na, color=gray, title=”FairPriceLine Lower Limit”, linewidth=1)
plot(show_FPLErrorBands1 ? FairPriceLineUpConfLimit1 : na, color=gray, title=”FairPriceLine Upper Limit”, linewidth=1)

TopPriceLine = exp(-30.1874869318185+pow(stock,0.221847047326554))
TopPriceLineLoConfLimit = exp(-30.780909776998+pow(stock,0.220955789986605))
TopPriceLineUpConfLimit = exp(-29.5940640866389+pow(stock,0.222738304666504))

TopPriceLineLoConfLimit1 = exp(-30.3683801339907+pow(stock,0.221575365176983))
TopPriceLineUpConfLimit1 = exp(-30.0065937296462+pow(stock,0.222118729476125))

plot(TopPriceLine, color=white, title=”TopPriceLine”, linewidth=2)

show_TOPErrorBands = input(false, type=bool, title = “Show Top Price Line Error Bands 95% Confidence 1St.Dev.”)
plot(show_TOPErrorBands ? TopPriceLineLoConfLimit : na, color=white, title=”TopPriceLine Lower Limit”, linewidth=1)
plot(show_TOPErrorBands ? TopPriceLineUpConfLimit : na, color=white, title=”TopPriceLine Upper Limit”, linewidth=1)

show_TOPErrorBands1 = input(false, type=bool, title = “Show Top Price Line Error Bands 68% Confidence 1St.Dev.”)
plot(show_TOPErrorBands1 ? TopPriceLineLoConfLimit1 : na, color=white, title=”TopPriceLine Lower Limit”, linewidth=1)
plot(show_TOPErrorBands1 ? TopPriceLineUpConfLimit1 : na, color=white, title=”TopPriceLine Upper Limit”, linewidth=1)

Forecast up to 2032

Bitcoin Model 1.3

This is a forecast up to 2032 halving, price will saturate between 27,000$ and 130,000$ with a maximum possible peak at 450,000$ in case of a strong bubble.

Conclusions

This model is clearly experimental, we will see in the future how it will behave. It is probably questionable my choice to use the existing bitcoin supply instead of using time as a main input for the model, I’m curious to know your opinion about it. Thank you.

Long Term Update: Volume Analisys at Kraken/Bitstamp Part II

On By CryptoAdvisorIn Long Term Trading

Old post is here

The trading platform used here is unchanged: Sierrachart 64 bit.
The big amount of tick data processed to compute this interesting volume oscillator wouldn’t be possible to do at TradingView or similar online platforms.
The “up/down Volume Ratio” oscillator is computed and smoothed using a 18 periods (18 months or 1 year and a half) linear regression moving average.
Volume made on an uptick is considered positive while if made on a downtick is negative, then the aforementioned oscillator is applied.
I added also in the chart the widely know ALMA moving average (9 periods, standard settings).

I added for comparison the same template applied to BTCUSD at Bitstamp exchange.

Volume Ratio Oscillator Kraken/Bitstamp Comparison (click to enlarge)

Very curious to see a perfectly balanced volume activity at Kraken exchange for 3 months in a row while at the Bitstamp the volume activity is unbalanced upwards.
As a positive note i can say that i don’t see any negative volume activity in either of the two exchanges considered. Said this my best guess is that the price retracement from about $13800 to $6400 was a normal correction of a bullish market and that the bear market ended on March ’19.

 

Long Term Update: 2020 Outlook with entropic methods

On By CryptoAdvisorIn Long Term Trading1 Comment

Every year i post an outlook using entropic methods explained in the technical section of this blog. Here you can find the 2015, 2016, 2017  2018 and 2019, 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 data of 4 important exchanges when possible).

 BTC/USD
Growth Factor G 1.00087 (1.00088)
Shannon Probability P 0.5219 (0.5222)
Root mean square RMS (see this as volatility) 0.056 (0.058 )

Bitcoin’s entropic values versus the Usd stayed stable during 2019 although volatility has fallen a bit like in 2018,  the Growth Factor (G) decreased a bit to 1.00087% compounded daily or 137.7% yearly, close to the value of 1y ago. The optimal fraction of your total wealth to invest in bitcoin is unchanged to 4.4%  (~0.522*2=1.044 – 1 = 0.044 or 4.4% roundable to 5%)
These values are still much better then conventional markets except the Shannon Probability that still match the US Stock Markets (around 0.522); it means that out of 100 days an asset goes up 52 days and down for 48 days, on average.

 2020 Price forecast  Full Historical Volatility  Half Historical Volatility
Forecast using only G* ~9951$ ~9951$
Upper bound adding volatility ~29380$ ~17097$
Lower bound subtracting volatility ~3370$ ~5790$

*9949 is obtained with 1st January as a starting price (around 7227$) times (1.00087^365)=~1.377   |   7227*1.377=~9951, just change 365 with the number of days you prefer for a different forecast.

What went wrong in 2019? Nothing:)

A year ago, I forecasted a maximum top of $16150 never reached during the year.
This market stayed above the 3000$ support forecasted 1 year ago but it didn’t go to the 1700$ support level using full historical volatility. On the other side it tried to reach the 16150$ resistance level with a top at 13880$ on June ’19.
During 2020 I recommend to buy inside the half volatility support area between 5790$ and 9950$ (target price using only the growth factor G) having already an open position from ~9000$ I will not buy more bitcoins during 2020.

Conclusions

For this year i think that there is a good probability to stay inside the 5790$-17100$ price zone with an equilibrium point at 9950$.
Like one year ago,  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 50k USD (price calculated using the equivalent of 1.5 times the historical volatility of bitcoin while the other 17k usd target is calculated using 0.5 times historical volatility)

For all of you that are probably asking why i haven’t mentioned my fresh new bitcoin price model in this update i answer saying that i prefer to don’t mix different approaches. Aniway actual value of the Bitcoin FairPriceLine is roughly 5800$ and it’ll be at 10600$ at the end of 2020, same support price area of my quantitative approach (5790$-9950$)

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