Did you hear about Goblin Town?

Apparently, the crypto market’s in it.

What’s Goblin Town?

“A dark, depressing place where dreams die and anguish reigns.”

MAJIN.SILK @majinsayan

a dark depressing place where dreams die and anguish reigns

Mark Helfman @mkhelfman

@majinsayan What does goblin town mean? Asking for a reader (not kidding)

March 16th 2022

2 Retweets22 Likes

Where I come from, we call that a “day job.”

I get it. Since the market reached its zenith on November 8, 2021, overall trading volume has dropped every month, along with prices.

Actually, prices have gone up for three months.

Also, on a monthly basis, volume peaked in December 2020, not November 2021. It’s gone down for 15 months, even though bitcoin made multiple new all-time highs over that time.

See for yourself:

• Bitcoinity

• TradingView

Mark, that can’t be. 2021 was crazy! Laser eyes, supercycle, etc.

Yea. Kinda like when you get to a party at 2 am. Everybody’s happy but you already missed most of the fun. You only get the tail end and the hangover that comes the next day.

To be fair, volume is not a meaningful statistic and it will continue to mean less as more money flows to derivatives and investment funds instead of the spot market.

Those products let people speculate on crypto prices without actually buying or selling crypto. The spot market still sets prices, but a lot of the volume flows elsewhere. Maybe not the best metric to look at.

Can you ever really find clarity in a single metric?

Be careful with conclusions

For example, entity data, a type of analysis that came into vogue last year. This data uses inference and heuristics to figure out how transactions are linked to one another. From that, analysts can identify unique entities and the bitcoins they control.

Its best producer, Glassnode, warns people that the data includes a lot of guesswork.

On top of that, entity data obscures what the actual bitcoins are doing, which is for me the most important information you get from on-chain data. An entity can buy, sell, and move 10 bitcoins and leave no trace in the entity data. To find those bitcoins, you need to look at other metrics.

At the end of the day, I don’t need to know what the entities are doing, I need to know what the bitcoins are doing.

Some prefer whale watching. A few of the biggest wallets have an uncanny ability to send bitcoin out of their wallets near the local tops and bring bitcoin into their wallets near the local bottoms.

Often, they’re off by weeks, during which time the price can move 25-50%. Sometimes, they send at bottoms and receive at tops. How reliable are they?

Many people apply some form of technical analysis. Traders use that type of analysis to plan entries, exits, stop-losses, and hedges. Essentially, it’s a risk-management tool for people who want to make money from changes in the prices of cryptos.

Is that your goal? If not, are you sure you want to make decisions based on technical analysis?

What about fractals? Can you take one outcome from one event on one dimension at one point in time, then use it to form your expectations of this moment?

At best, you can stack a few fractals over each other across several dimensions with perfect alignment. Like, 5 or 6 independent points of data, not two coincidences across different timeframes. Unfortunately, you’re not going to find those very often.

That one perfect metric

Every chart, metric, model, and indicator has its limits. Accept it for what it can tell you, not more than that.

With custodial accounts, multi-sig wallets, investment products, private deals, Lightning Network, and mixers, on-chain data gets less useful.

With smaller floats, low balances on exchanges, more leverage, and more people with access to quality market intelligence, technical analysis gets less useful.

Does that mean you should throw your hands up and dollar-cost average forever? Give up trying to use observation and reflection to understand how people act in various market conditions?

No.

Just don’t think every data has holds the key to success. Thinking only goes so far and you can never see the full picture no matter what data you have.

Choose your conclusions wisely.

Mark Helfman publishes the Crypto is Easy newsletter. He is also the author of three books and a top bitcoin writer on Medium and Hacker Noon. Learn more about him in his bio.

Follow Me on Twitter.

• @mkhelfman

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