The KS Model analyzes Bitcoin price action. It assesses past halving cycles to determine where halving events occurred, market peaks, market bottoms, and the differences between cycles.
The KS Model was originally designed for my own use as a full time crypto trader. As a former lecturer in 1st and 2nd year statistics, I started sharing the KS Model because many in the media were misrepresenting graphs and placing people under enormous stress. I started a YouTube channel to present statistical and mathematical analysis based on years of practical trading experience. The KS Model was pivotal in comparing different parts of the cycle without violating the law of mathematical consistency (comparing apples to apples). The KS Model also helps to de-FUD (contextualize Fear Uncertainty and Doubt) and de-FOMO (contextualize the Fear of Missing Out). I also share my trading tips, trading rules to assist the YouTube community to be more of a financial blessing to themselves and those they love.
Disclaimer: Any information found on this page is not to be considered as financial advice. You should do your own research before making any decisions.
The KS Model
The KSModel is a Bitcoin technical trading model based on institutional price psychology. The KSModel is being refined, enhanced, and added to twice per day 7 days per week and is discussed on the Crypto Trading YouTube channel.
Institutional vs Retail Psychology
Institutions are very different from retail investors.
1. Time frames: Institutions (fund managers, pension funds, banks, and whales) have long time horizons from which they view price action (years, and decades). Retail investors, view price action on a low time frame (minutes, hours, or days).
2. Objectivity: Retail investors experience rapid shifts between optimism and pessimism due to current price action and stories reflected through media outlets. It can be a bull market one day and a bear market another day to a retail investor. Institutional investors are not emotional, they assess market industry growth rates, total addressable market size, adoption, network growth, revenue analysis — to forecast profitability over years and decades. Once a conclusion is drawn from an institutional investor, it is held until underlying financial situations change.
3. Economic Power: Retail investors typically have limited funds to pursue investments, and therefore often leverage investments that typically results in total liquidation. Leveraged investments have limited upside and unlimited potential losses. Because of this retail investors (who do not buy at spot), get easily shaken out of trades as leveraged losses are unlimited.
There is a reason why 90%+ of retail traders lose money.
Low economic power plus a focus on fear is used by institutions. Institutional investors have access to billions of dollars worth of funds, and have teams of quantitative/statistical experts who guide automated trading algorithms.
4. Influence: Institutional investors have deep pockets and can influence industry wide sentiment through the press (news, social media, and interviews). Institutions influence the news that retail investors to consume. Institutions are well known in their ability to advertise higher prices for retail traders to “buy at the top” in an effort to avoid FOMO (Fear of Missing Out). They are also well known for causing immense market fear (FUD — Fear Uncertainty and Doubt) to incentivize retail traders to “sell at the bottom.”
5. Behavior: Institutions actively participate in futures, options, and derivatives markets. They both actively benefit from short-term cycles in price behavior as well as longer term accumulation strategies. Retail investors tend to have short time horizons. Institutions are sophisticated, financially strong, and expertly resourced. Institutions make money from attracting retail investors into the market (via FOMO) and then liquidating their positions (via FUD) to gain. In a market one person’s loss is another's gain.
Institutional Psychological Price Action
There are three institutional psychological phases after very halving cycle in the crypto market.
- Bull market phase (psychological sunshine),
- Bear market phase (psychological darkness), and
- Consolidation phase (psychological dawn — the emergence of tentative optimism after capitulation).
Psychological sunshine: The Bull Market Phase
Psychological sunshine occurs when institutional investors advertise the price of Bitcoin and other cryptos up through news and media outlets towards a peak that is inconceivable to retail investors. This “out of reach’ target is critical because it causes “inverse capitulation,” or a “blow-off top” that brings the bull market phase to an end and commences the bear market.
A blow-off top hammers in the bull market top.
Retail investors are attracted to the market, where institutions seek to liquidate those positions through a series of rallies and retracements. Such retracements can be brutal to retail investors, but highly lucrative to short positions.
A blow-off top is an exponential rise in prices that is followed by very sharp drop in prices that occurs within 5% of the end time period of the bull market. Exponential price blow-offs before the end of the period are corrections.
I developed the term “short fueling,” to describe a time period when shorts have excessive psychological safety that “they cannot lose.” This mindset is manufactured by institutional investors that use the covering of shorts as a cover to drive prices up.
In the KS Model below, points 1, 2, and 3 signify Bull markets in crypto:
Psychological darkness: The Bear Market Phase
Psychological darkness occurs when institutional investors now sell-off their crypto after the “blow-off top” that brings the bull market phase to an end. It takes a while for retail investors to know that the top has already been hammered in and the decent has begun.
Capitulation hammers in the bear market low.
During capitulation hope dissolves and disbelief evolves into painful losses for retail investors. Traders become investors until they finally surrender at the “capitulation,” or the “blow-off bottom.” Whilst this is happening small rallies making higher lows follow. Bear markets can be excellent to trade and have good upside potential.
Psychological dawn: The Consolidation Phase
Psychological dawn starts immediately after “capitulation,” that brings the bear market to end.
Immediately after capitulation prices begin to rise due to absence of sellers. Capitulation is therefore an exceptionally profitable trading strategy for an entry either from a trading or investing stand-point.
Points 1 and 2 define the previous consolidation phases.
Free training video: KS Model Foundations
The following video is the essential introduction to the KS Model, why it is important, how it is used and the application to your ALT coins.
I also suggest you look at the video on BTCALT Gearing, this will give you a powerful insight into how the engine of the crypto market;
The KS Model is used in twice daily updates, released 7 days a week, on Bitcoin & ALT coin movements within the market.
Understanding the KS Model
As a trader coming from a finance, statistical and actuarial background, I focus on price action and mathematical concepts. In 2005, I wrote the book Intangible Finance Standards: Advances in Fundamental Analysis and Technical Analysis, for Academic Press when I was Chairman of the Intangible Management Standards Institute. Some additional back ground is here.
The KS Model analyzes Bitcoin price action via institutional psychological impact on price. Each YouTube update I share one or more trading rules that I have acquired over many decades to help the YouTube community to better understand the crypto market to save them time, reduce losses, and increase their financial blessings (thereby helping them to bless others).
Each rule created has taken years to create and is evidenced by the “tuition fee of the market” — losses. I hope sharing these rules is of benefit to you.
It assesses past halving cycles to determine where halving events occurred, market peaks, market bottoms, and the differences between cycles. I put updates out on this and other crypto analysis each day through my Twitter account at https://twitter.com/StandfieldKen.
Halving Events in the KS Model
The Halving cycle occurs when the block height reaches 210,000 blocks (it is not a date of 4 years as commonly understood). At this block height, the miners reward for mining/processing reward is reduced by 50%. As mining operations are expensive capital intensive operations, this results in a 100% increase in mining costs and consequential requirements to replace hardware with faster processors to lower cost. This sends the market into a supply shock where prices increase to offset the real cost of running the network.
Bitcoin halving's create a supply shock forcing prices to increase rapidly.
In the KS Model the halving's are represented as follows. All dates and times are given in the details section associated with the halving:
For the KS Model market cycle tops are represented by horizontal dotted green lines. You can see the 2012 market peak occurred at Point 1, 2017 market peak at line 2, and the estimated market peak at Point 3.
Bull market peaks
Bull market peaks are represented by horizontal dotted green lines.
Bear market lows
Bull market lows are represented by horizontal dotted red lines. Bear market lows are hammered in via the capitulation (surrender) event. The exact date of capitulation marks the beginning of the consolidation phase psychological dawn).
Bull Market Cycle Lengths
Cycle lengths are measured from the halving date to the Bull Market peak. As measured directly:
Point 1: The 1st bull market lasted 367 days,
Point 2: The 2nd bull market lasted 526 days (43.32% more),
Point 3: An increase of 43.32% is reasonable to assume for the current bull market. This would last 754 days from the halving. I am conservatively estimating a peak 744 days from the halving around the 25th of May 2022.
Bear Market Durations
The 2012 Cycle bear market lasted 411 days (Point 1)
The 2016 cycle bear market lasted 361 days, 50 days less than the 2012 cycle (0r 12.165% less)
If we assume the 2020 cycle bear market will last 12.165% less as the 2016 cycle did, the bear market duration would be estimated at 317 days to capitulation.
Consolidation cycle phases
The 2012 consolidation phase lasted 541 days (Point 1).
The 2016 consolidation phase lasted 513 days (Point 2), 28 days less than the 2012 cycle (around 5.176% less).
From this we can estimate the 2020 consolidation phase lasting around 486 days (Point 3), being 94.82% of the previous consolidation phase.
The Next Halving Date
The halving occurs when the block height reaches 210,000 blocks. An excellent predictor of the Bitcoin halving is at Coin Market Cap. This calculator ignores the average block rate (1 every 10 minutes) and uses live blockchain statistics to obtain an estimation of the current average Bitcoin block time. I prefer this engine, as it accounts for hash rate variance.
Tracking to the next halving
Using the hash rate calculator above the halving date is estimated at the 28th of June 2025. This date is different from other halving time calculators.
The variance between the estimates derived from past behavior and the estimated halving date is 327 days. I have left the variances and not sought to normalize it, as other halving calculators give different dates approximately in line with estimates I have given below.
Arriving at the $486,000 price
The log (Point 1) trend line (Point 2) drawn between market peaks intersects with the 2022 market peak around the 25th of May 2022. This sets up an approximate top peak.
Previous models have estimated price targets ranging between $100k, $288k, and some estimates go as high as $500k. From my study of the data I believe $486k is reasonable.
Most of my professional career has been spent developing and implementing disruptive technologies using discontinuous innovation (not incremental improvements). After more than 30 years doing this I have gained a well-researched stance on how exponential adoption is misunderstood in terms of market forecasting.
Consider this short story … if a pond lily has just started growing across a pond and a pond scientist has calculated that the lily growth is doubling each day and will cover 100% of the pond in 30 days, what day does it cover 50% of the pond?
The answer is on the 29th day as it is doubling each time period. It moves from 50% growth of the pond to 100% as it doubles. Interesting to note that the 28th day it covers just 25% of the pond, and the 27th day it covers 12.5%. That is why exponential growth is difficult to understand.
Bitcoin & Cryptos Exponential Growth
Crypto is growing faster than the internet in terms of adoption — it is growing exponentially like the pond lilies. Crypto is like a doubling pond lily on steroids! Below is a chart showing (in log scale) the projected growth of crypto.
More information coming
I am continuously revising and simplifying the KSModel. I talk about the KSModel in the twice daily, 7-day a week crypto updates I do on YouTube.
If you would like to see the channel please use this link.
A call to the community
Just as driving too slow on a freeway is just as dangerous as driving too fast, being too conservative is just as dangerous to people’s financial health. If we can collaborate together as a community to improve the model, it would be much appreciated. Consider how the previous cycle peak ran 42% longer (156 days) than expected and Bitcoin increased from what was thought the peak an additional 668%. If we can capture such gains through mathematics, we can help so many people together.
Tops and bottoms are always based on probabilities, not certainty. The KS Model is a probabilistic model. It may happen, or may not. But it is a guide.
Trading Bitcoin is difficult, best of luck to everyone out there. I hope this article gives benefit.
About the author
Ken is a trader, for many decades, who specializes in technical analysis and seeks to keep others on the right side of the trade and the market.
He is the former Chairman of the International Intangible Management Standards Institute. He is the author of Intangible Management: Tools for Solving the Accounting and Management Crisis (Academic Press, 2002), Intangible Finance Standards: Advances in Fundamental and technical Analysis (Academic Press, 2005); Leveraging Knowledge, Time and Technology (IIMSI Press, 1998). He was a pioneer in the fields of Time Valuation, Knowledge Management, Intellectual Capital Management, and Intangible Management. He has been a keynote speaker at more than 300 events internationally. Ken commenced lecturing statistics at 18 years of age, and is an actuarial scholarship holder.