Tutorial 1 - Navigating Market Tops and Bottoms
This guide introduces a series of simple yet effective top and bottom indicators that have been developed by Bitcoin market analysts over time.
Last updated
This guide introduces a series of simple yet effective top and bottom indicators that have been developed by Bitcoin market analysts over time.
Last updated
Bitcoin markets are infamously volatile, and often experience large boom and bust cycles. Over time, models and tools have been developed by a variety of methods in an attempt to identify periods of over, and undervaluation. These models vary in complexity and inputs, ranging from simple moving averages, to momentum oscillators, to on-chain spending behaviours.
The Investor Tool was created by Philip Swift as a tool for long term investors, indicating periods where prices are likely approaching cyclical tops or bottoms. The tool uses two simple moving averages of price as the basis for under/overvalued conditions: the 2-year MA (green) and a 5x multiple of the 2-year MA (red).
Price trading below the 2-year MA has historically generated outsized returns, and signalled bear cycle lows.
Price trading above the 2-year MA x5 has been historically signalled bull cycle tops and a zone where investors de-risk.
The Bitcoin Top Cap model was developed by Willy Woo to identify market cycle tops. It is calculated by multiplying the Average Cap by a factor of 35. The Average Cap (blue) is calculated as the cumulative sum of daily Market Cap values divided by the age of the market in days. An additional Top Cap model considering a 15x multiplier is included to show sensitivity, and to gauge the effect of diminishing returns.
The Pi Cycle Top was also created by Philip Swift, and works by comparing the momentum of two moving average indicators. It compares the 111 SMA (blue) and 2 * 350 SMA (purple) of Bitcoin’s Price. These two moving averages were selected as 350 / 111 = 3.153; An approximation of the Pi number.
When the 111 SMA (blue) meets the 2 * 350 SMA (purple), it is an indication of an overheated market. The mid timeframe momentum reference crosses above the long timeframe momentum reference.
When the 111 SMA (blue) falls beneath the 2 * 350 SMA (purple), it is an indication of a deflating market that is cooling of after a period of overheating.
The Mayer Multiple is an oscillator calculated as the ratio between price, and the 200-day moving average. The 200-day MA is a widely recognised indicator for establish macro bull or bear bias. The Mayer Multiple therefore represents a measure of distance away from this long-term average price as a tool to gauge overbought and oversold conditions.
Following the original analysis by Trace Mayer, overbought, and oversold conditions, have historically coincided with Mayer Multiple values of 2.4, and 0.8 respectively. These multiples are then applied to the 200DMA to establish cycle top and bottom pricing models.
Values Below 0.8 (green) represent prices trading at a 20% discount to the 200-day MA. Bitcoin has traded at Mayer Multiple values below 0.8 for approximately 20% of trading history.
Values Above 2.4 (red) represent prices trading at a premium of 240% times the 200-day MA. Bitcoin has traded at Mayer Multiple values above 2.4 for approximately 10% of trading history.
Hash Ribbons track phases of the mining market boom and bust cycles. During expansion, the 30DMA of hash-rate will rise faster than the 60D, whilst during miner capitulation it will fall below, signifying a loss of hash-rate online.
During Bull Markets, Hash-rate will expand as miners invest in more mining hardware. This causes the 30DMA of hash-rate to rise faster than the 60D.
During bear markets, when miner incomes are stressed, some miners must turn off non-profitable rigs. This can lead to miner capitulation, creating a Hash Ribbon inversion, where the 30D falls below the 60D.
Bitcoin market cycles are infamously volatile, and often over-extend beyond ‘fair value’ both on the upside and downside. Analysts have thus developed models to help navigate market tops and bottoms
##Topics for Discussion:
Assessing over and under extended market pricing.
Simple models built from price moving averages.
Oscillators to monitor mean reversion potential.
On-chain models considering miner performance.
The Bitcoin market cycle is the result of many factors, with dynamics of accumulation, distribution and everything in between. With a Glassnode Advanced plan, we can expand our analysis to encompass investor sentiment and coin spending/HODLing cycles, estimated investor profitability, the balance of wealth held between new and more experienced holders, and much more. Some example Advanced metrics include:
MVRV Z-Score shows us distance that price is away from the estimated cost basis of the market. Thus we can identify extremes, such as when the market is in a large profit, or loss.
Entity-Adjusted Dormancy Flow captures the balance between market valuation, and whether it is supported by the volume of coins with long holding periods that are being spent over the last year.
Reserve Risk combines market price, with the degree of HODLing or liquidation taking place on-chain. It constructs a reflexive oscillator showing long periods of accumulation, and sharp peaks of exuberance near tops.
Realized HODL Ratio is a cyclical oscillator that measures the relative balance between young coins (1wk) and old coins (1y-2y) as a measure of market strength and weakness.
