Logarithmic Regression:- Technical Analysis I
Figuring out where we are in the grand scheme of the cryptocurrency market may seem like a daunting task, particularly when faced with the Fear, Uncertainty, Doubt (FUD) associated with being in a bear market.
Yet using a little math, and by being open to the idea that there are many possible directors for price to take, we can utilize a few technical indicators to understand how the cryptocurrency market currently fairs and determine potential trajectory.
A frequently relied upon set of long-term, macro based indicators are the logarithmic regression bands which have consistently acted as support and resistance points for crypto asset prices. In this analysis going forward, we will specifically be assessing BTC’s price movements.
Shoutouts:
Before I begin, I would like to quickly give a shout out to Benjamin Cowen, whose Youtube Channel provided me with the fundamental knowledge to understand and begin looking into advanced technical analysis indicators / patterns. I highly suggest anyone interested in learning more about technical analysis to check out his channel, linked here.
I would also like to give a shout out to memotyka9009 on TradingView. I relied heavily on his script to be able to actually model the logarithmic regression bands. Despite my limited understanding of his code, I decided to run with the results as the outcomes obtained showcase regression bands consistent with the expected norm albeit with slight differences in the band positioning itself relative to a few other models.
Link to Script here.
What is a Logarithmic Regression?
Logarithmic regressions are a type of regression that model situations of rapid growth initially, then slowing over time. For those of us who had experienced the 2017 crypto pump and subsequent crash, as well as the 2021 pump understand why this indicator is utilized to model crypto price movements.
The disparity between the speed and magnitude of both pumps where apparent early on, and provide significant support for proponents of “Lengthening Cycle Theory” and “Diminishing Returns” of the crypto currency market. We will assess both concepts further.
How Do I Observe it on my Own Chart?
The way you actually include a logarithmic regression indicator to your chart on TradingView may seem complex at first yet with a little bit of direction, the task can be completed relatively quickly. To begin, you would first need to open the “BRAVENEWCOIN LIQUID INDEX” or “BLX” chart on TradingView (the model I obtain from memotyka9009 only works on this particular chart). You would then need to click on “Pine Editor” found at the bottom of the chart, and it should open up a coding script for your to enter the script you obtained from memotyka9009. Simply copy and paste the script directly into your Pine Editor, removing all existing code present. Once that is complete, save the script according whatever you would like to name it, after which you can add directly to chart by clicking the button next to the save button.
Please note, if the code executes successfully yet your regression isn’t showing on the graph, it is likely you are using a free version of TradingView and have already exceeded your 3 Indicator limit. Simply delete an indicator you have showing on your graph, add the script to the chart again, and you should be good to go.
Great, we’ve been able to set it up on the BTC chart, but how do we read the data provided? Well, like all things technical analysis, we look for consistent patterns as well as changes over time to make our own assessments on how BTC price behaves within a cycle as well as from cycle to cycle.
One key indicator to point out is the middle blue line which acts as the fair value of BTC under the VERY important assumption of monotonous growth in value. Alternatively, we can observe the middle green band coupled with the 200 Week Moving Average ( Just the average of weekly prices over the last 200 weeks — White Line) to obtain a line of support that has, in the most recently bull run, consistently held. (See Circled in White.)
What can we infer from this information? We have seen that more recently, prices tend to hold above the middle green (lower) band and have consistency held above the 200 Week Moving Average indicator (Excluding Wick Volatility). We can be relatively confident that this line of support will hold and that prices will not drop significantly below the price points specified by the two indicators. Its interest to note that in the most recent years, the 200 week MA converges with the middle green (lower) band. It is likely the conversion will continue towards the fair value support line (blue middle line) as the market progresses towards maturity, however, this is likely to take multiple years within which volatile price cycles will occur.
Looking at the upper bands, we see that historically, price has relatively consistently reached the upper band of the upper logarithmic regression prior to subsequently crashing significantly (entering a bear market). Looking at zones of resistances for forward looking prices may impose a degree of uncertainty, particularly if BTC has yet to reach that zone’s price previously. However, based on historical results, we notice a consistent pattern within every bull/bear cycle in which price spends some time below the green regression bands accumulating value. Post breaking out of the green regression bands, prices tend to remain above the 20 Week EMA (Dashed Yellow Line) acting as a strong support zone as we enter and go through a bull market. Once price breaks above the red (upper) regression lines, we face increased risk of price reversal and the beginning signs of a bear market.
It is important to note than particularly in the case of the upper regression band, different models will experience differing results in defining the upper bound with a few recent models suggesting we barely scraped the surface of the red (upper) regression bands during the 2021 bull cycle prior to crashing. That's not to say the models were incorrect but rather factored in differing computational styles and assumptions that play a key role in obtaining a conclusion from there results you obtain. Basically just because it looks like it doesn’t mean it's gonna happen again, and just because someone was right before, even if it was consistently, doesn’t mean that person can’t be wrong the next time. Keep that in mind.
The Theory of Diminishing Returns:
To put it simply, the theory states that as time progresses, the magnitude of returns obtained from investing in a particular asset (especially up and coming assets like crypto) decrease as time progresses. We can look no further for an example than BTC itself, we notice from the logarithmic graph that we move forward in time, the distance between the red and green regression bands (sometimes referred to as “No Man’s Land”) shrinks. We also notice the volatility decreasing in that prices become less likely to hit and spend time little time in major zones of regression on either side of the graph. For example, we noticed that in the 2018 bear market, price remained consistently over the middle green regression line yet in 2015, prices dropped below the middle green regression band and remained within the lowest zone outlined by the regression up until the beginning of the next cycle. Something similar could be set in regards to price volatility in the red (upper) regression bands. We notice in this case that in the most recent bull market (2021), price consolidated in the upper bands for a significantly longer period of time than in the previous cycles, transitioning us very well into “Lengthening Cycle Theory”.
Lengthening Cycle Theory:
It's a common misconception within the cryptocurrency community that cycles occur every 4 years to coincide with BTC’s halving (a process in which BTC output is reduced). However, based on historical data, this is clearly not the case. We observed cycles ranging from less than three years to 4+ years. We notice as well, that price tends to be less volatile and therefore spend a longer time consolidating in certain zones during later cycles compared to earlier ones. This reduced overall volatility in turn results in a longer timeframe being required for price to consolidate value from the lower (green) regression bands to the upper (red) regression bands representing a full cycle.
To conclude, yes this may seem like a daunting indicator overall, and yes it is a little bit complicated to set up and understand, however, I strongly believe that the knowledge obtained from understanding and reading said indicator is paramount for any consistent trader in the market and can also be extremely useful for people who plan on DCAing into the market. Check out my thread on Twitter about DCAing to understand whether it’s the right move for your portfolio.
Once again, massive shout out to Benjamin Cowen and memotyka9009, I greatly appreciate the free content you guys have posted online.
TheSocialPariah
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