These 20+ charts that can help you gauge late bull markets and top formations.

Long thread 🧵👇

1/ MVRV, a classic. Measures unrealized profitability and has previously signaled overheated above 7.

Currently hovering around 3 – room to grow.

2/ MVRV Pricing Bands are derived from the amount of days that MVRV has traded at extreme levels.

The top band denotes the 3.2 level, which has been exceeded for around 6% of trading days.

Its current value is $127,000.

3/ I often prefer to look at the long-term holder profitability to assess exuberation and the risk of profit taking.

Relative Unrealized Profit and LTH-NUPL just hit 0.75, entering the euphoria zone. In 2021, #BTC made another ~3x from here (not saying I expect this again).

Previous top formation levels: 0.9+

Room to grow.

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5/ The other side of the coin is looking at coin spending and profit taking.

The Yearly Realized Profit/Loss Ratio, has previously peaked at values above 700%—currently we sit at around 580%.

Room to grow.

6/ Market Cap to Thermocap Ratio. Another metric from the early on-chain days that serves as a reference for a monetary premium by comparing the market cap to the aggregated amount of coins paid to miners (cost of production).

I’d be careful with specific ranges here, but leave it to show that we’re not close to previous extremes.

7/ Historically speaking, #Bitcoin has topped at a 32-64 multiple of the Thermocap. We’re at the bottom of this range, the top band would put BTC at a market cap of just above $4T.

8/ Investor Tool is a simple price-only model that uses the 2-year SMA of price and its 5x multiple to determine potential topping zones–which currently denotes $230,000.

9/ Similarly, Bitcoin Price Temperature builds on price only and determines bands based on deviations from a 4-year moving average that seeks to capture the cyclicality of #Bitcoin halvings.

The BPT6 band that was reached within previous bull markets sits currently at $151,000.

10/ The True Market Mean is an alternative cost basis model based on Investor Cap and Active Supply. Its MVRV equivalent, AVIV, represents the deviation from the market mean and typically reached more than 3 standard deviations during previous tops – today amounting to values above ~2.3.

Currently sitting at 1.7 – room to grow.

The popular Mayer Multiple is the ratio between price and its 200d SMA.

Typical overbought conditions previously coincided with MM values of above 2.4 – which currently means a price of $167,000.

15/ The Cycle Extremes Oscillator Chart incorporates multiple metrics (MVRV, aSOPR, Puell Multiple, Reserve Risk) as binary indicators to gauge market extremes.

Currently 2/4 are on, hence not yet signalling a full bull market overheat.

16/ Pi Cycle Top Indicator. Based solely on price, shows when #BTC becomes significantly overheated, i.e. when the shorter SMA reaches the levels of the larger SMA.

Has worked for previous tops. Currently the short moving average sits well below the larger ($74k vs. $129k), ergo no signs of topping yet according to this datapoint.

22/ Important remarks:

* Never rely on single datapoints – confluence is your friend.

* This is a non-comprehensive list of (on-chain) charts and datapoints that help gauge market cycles – but there’s much more that’s not covered here. I will add as I (re-)discover.

* Charts are not presented in any particular order (I was lazy).

* Listing charts here does not mean endorsement, nor do they all have equal importance to me. My views on them have changed over time and will continue to do so.

* Bitcoin and crypto evolves and the current environment is surely vastly different than during previous cycles. Today we have ETFs, increased regulatory clarity, companies and governments acquiring BTC – a lot of tailwinds. At the same time, Bitcoin is more than ever embedded into the global economy which has a completely different effect on crypto markets than it used to. This needs to be taken into account more than ever when analyzing crypto markets.

* When we talk about Bitcoin cycles, the amount of data points is very limited. Keep that in mind, overfitting is a sneaky foe. Do not make the mistake of naively generalizing. This cycle can look vastly different, yet (historical) data is all we have.

* Not financial advice, do your own research.

We put a lot of research and work into this thread before reading it.🙏 🚨

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