Top 10 Whale bubble rules and more

If you haven’t had a chance to read the previous 3 chapters, I highly recommend giving them ago, especially part 3.

1. What the *** are UTXOs
2. How can UTXOs be analysed
3. Tracking Bitcoin Whales using blockchain data (deep dive)

This last part will be some additional notes on the previous chapters but nevertheless quite useful to understand too. Let’s begin!

Top 10 bubble rules (in no particular order)

1. Best wallet cohorts that form best bubbles are whales and 1k-10k. Other cohorts were not noticed to hold a lot of value for trading.
2. The larger the bubble — the better the support/resistance
3. Whale bubbles are not the ultimate key to the market. Sometimes they don’t work
4. The most recent whale bubbles (ones at the end of the price line) are usually due to exchanges reshuffling their funds.
5. Whale bubble’s strength increases the longer it stays in the same place. Some bubbles stay in place for years and hence provide the best S/R. In the figure below, the 2018 bubble was the support during the Corona crash.

Bubbles at the location of the cursor are almost 4 years old as of now. At the time of the “corona drop” they were 1.5 years old and served as the “almost to the dollar” price where Bitcoin bounced ($3901). (could have made a fortune by buying BTC there)

6. In order to use bubbles you have be comfortable with trading supports and resistances already. Bubbles are just an actionable way of identifying S/R

7. A whale bubble can consist of multiple whale wallets.

8. A bubble forms if a whale wallet received even 1BTC given its balance was >10,000. The bubble will be tiny in this case.

9. As mentioned before, if the wallet moves its funds, the bubble associated with this whale may disappear. In this case, the whale outflows chart will show which whales moved bitcoin.

10. The difference between hourly and daily resolutions for bubbles is that the user is able to identify date, time and price of whale activity more precisely, making his trades more precise and profitable in return

Who are >10,000BTC wallets?

At the time of writing, 10,000BTC = ~$350,000,000. Who are the people who hold that much money in a single wallet. Well, a lot of these wallets are actually exchange wallets, i.e. wallets that exchanges such as Coinbase, Binance or Bitfinex use for storing their own funds (cold wallets. Others could be hedge funds, banks, OTC trading desks, pension funds, VCs, etc.

Other categories of bubbles

We can track where other wallets accumulate bitcoin too.

The categories that Whalemap currently tracks are:

• 1–10
• 10–100
• 100–1,000
• 1,000–10,000
• 10,000 (beloved whales category)

This is the standard that is used by the on-chain analytics industry.

N.B. Some of our charts categorise >1,000BTC wallets as whales (volume profile, mpl, on-chain volumes). That is because for some charts >1,000 classification is more useful for trading.

“Whale bubbles are the most useful for trading”

“Whale bubbles” are bubbles on the large wallet inflows chart that track wallets with balance >10,000 BTC only, i.e. bubble show where such big wallets accumulate Bitcoin. Whale bubbles are the most useful for trading. There are multiple examples on our Twitter/X where they sometimes show supports and resistance price levels accurate almost to the dollar.

Example from Whalemap’s twitter

Step 1: Levels identified by our bubbles (notice the $29,314 level):https://twitter.com/whale_map/status/1350754019699003393?s=20&t=oOQGjP7Ri9ezCyC9ddEiSw

Step 2: Later price action obeys bubble levels perfect to the dollar:https://twitter.com/whale_map/status/1355095770035351552?s=20&t=oOQGjP7Ri9ezCyC9ddEiSw

Why do whale bubbles work?

Intrinsic value and liqudity

One of the more frequent questions that we receive about our whale bubbles is “why would you care about exchange bubbles”. Exchanges are not whales, they don’t trade, they don’t accumulate, they don’t care about Bitcoin’s price, so how could Whale bubbles of exchanges indicate important prices for Bitcoin?

The answer to why our bubbles work is not simple, and is my personal hypothesis. Though, the thing that helps with questions like this is that Whalemap’s twitter exists for 3 years and is a great historical reference that empirically shows actionability of this data.

If you go there you will find that despite the fact a lot of >10,000 wallets are exchanges, all large whale bubbles indicate important S/R levels for the entire Bitcoin market, no matter the bubble’s nature (whether it was an exchange or not) quite consistently.

My personal hypothesis on why it is the case is that each Bitcoin’s intrinsic value changes based on when it was received by a wallet. The same Bitcoin that was received by wallet A at $1000, will be a different Bitcoin if it was received by wallet B at $4000.

The intrinsic value changes because whenever a wallet receives BTC, it’s either exercising its right to sell (meaning he believes $4000 is too much) or decides to hold (meaning he believes $1000 is too little). The fact of the transfer just indicates that this “exercise” has taken place.

Same applies for big whale bubbles.

If a whale, an exchange for instance, received 100,000 Bitcoins at $1000, the intrinsic value of those Bitcoins was exercised and now, a lot of Bitcoins cost $1000 (they were either purchased or are intended to sell at that price)

Then the market decides whether these Bitcoins will be sold or bought at that price. If price goes higher, to $2000 and then back to $1000, if the whale bubble is still there, it means that the entity that’s holding bitcoins at that price (or as we will later see, a large number of market participants) is not willing to sell, in turn meaning that “smart” entity is comfortable with those Bitcoins costing $1000.

💡 Hence, you can sum this up up as smart money being comfortable with Bitcoins costing $1000. This in turn means that $1000 is a good buying opportunity.

Supply & Demand

Another reason why whale bubble may work is that the supply/demand dynamics change at levels with a lot of Bitcoin residing there. Especially, whale bitcoins.

This is the more intuitive hypothesis on why whale bubbles work…

Since any market is just an auction (more on this here “auction theory”), the volume of sellers and buyers at every price level is what causes price to change at every level. Rarely there could be an equilibrium where the number of sellers and buyers at particular price level is the same.

If there are more buyers than sellers at say $1000, price will push higher as the sellers can afford to sell their Bitcoin at a higher price. If price goes to $1100 and still demand is high, price will go even higher up. Say it reaches $1500 and demand is starting to run out, i.e. few people want to purchase Bitcoin at such a high price. Also, assume that demand for selling is now higher than demand for buying. This will push price down, naturally.

💡 At whale levels, supply/demand dynamics change, and price is likely to take a turn.

This is similar to iPhone prices. Imagine, historically, a lot of people were comfortable with buying iPhones at $1000. If iPhone prices go up some will be willing to sell their iPhones and some will hold them (not sell). If price is say $2000 and people are still holding (not selling) their iPhones, it means that they are expecting price to go even higher, or they are enjoying their iPhone and the $2000 reward for selling it is not a good enough price to say bye bye to it.

If price goes back to $1000 after it was at $2000, we can expect less selling pressure at $1000. That is because, you can assume the same number of people that were holding at $2000 will be holding at $1000 and also all the extra sell pressure that was present at $2000 (or at any price above $1000) is now non existent because you can’t turn a profit now. There will also be people willing to buy iPhones back at $1000.

This means that suddenly, demand at $1000 is higher than usual, and sell pressure is lower than usual.

This creates a support for iPhones price at $1000 where price bounces.

However, no-one including ourselves knows why Whale bubbles work for certain. They just do 😃

How do we get data for Large Wallet Inflows?

Remember the UTXO set? And how it looks like?

Here is a reminder.

What happens if we select all wallets with “wallet balance” ≥ 10,000BTC from the above table?

We will get all UTXOs that belong to whales.

Each UTXO will have a

• date
• value
• and price

Then, if we round date to either an hour or a day and sum all the UTXO values where the date repeats, we will get an amount of UTXOs that belong to whale wallets for a particular day or hour in the past, i.e. some random whale wallets that had received Bitcoins on that day or hour.

So, we get data that looks something like this

We can plot this as a bubble chart now.

But also,

• We can plot bubble charts for different resolutions: day, hour, minute, block, week, month, etc depending on how we group our date and time in the UTXO table.
• We can also be selecting different wallet categories for our analysis (i.e. we selected ≥ 10,000BTC wallet balance category but can also choose <1BTC wallet balance category for example).
• Bear in mind — “price” would be the price of Bitcoin for that day or hour , not the price of the actual UTXO. This is just that we are consistent with the price line of Bitcoin since that’s where we plot our bubbles.