Considerations for Using Market Breadth in Cryptocurrencies

Louis Sykes
August 4, 2022

From the Desk of Louis Sykes @haumicharts

In yesterday's letter, we discussed in great detail the considerations when applying AVWAP analysis to cryptocurrencies.

You can click here to read that post.

Today, we're addressing yet another popular tool among technical analysts: market breadth. Put simply, this type of analysis lets us gauge the strength of underlying securities that compose an index or other broad group of assets.

The most common is the advance-decline line, which is used by investors to measure the number of individual stocks participating in a market trend. Using this data, analysts can get a heads-up on potential turning points in market rallies, as well as gain conviction through confirmation.

But breadth indicators can (and should) get a lot funkier.

We do a lot of market breadth analysis here at All Star Charts, primarily in the equities markets but also in foreign exchange and commodities. In crypto markets, our breadth coverage has been rather light.

So we're happy to announce we'll be conducting more of this research moving forward to supplement our traditional price analysis.

But in saying this, there have been three primary reasons we've avoided quantifying this data in the past:

  • the smaller scale of crypto markets;
  • the extreme survivorship bias; and
  • the efficacy of breadth analysis in crypto markets.

Let's walk through each of these individually.

Scale

When it comes to market size, crypto is naturally significantly smaller than its counterparts in legacy markets.

We're not dealing with 3,000 stocks, like in the Russell 3000, nor do we have 11 GICS sectors or 69 GICS industry groups. Instead, we can reduce much of the crypto asset class into a few dozen names.

Unlike equities, we can get away with just looking at the top five coins by market cap to get a read on where the asset class is going forward. Of course, for trading opportunities, we do like to get dirty in the smaller names.

But the reality is that the smaller names are just correlated to but higher-beta plays than Bitcoin and Ethereum. The same can't be said in equity markets, where each publicly listed company has far more idiosyncratic drivers than any given crypto project (more on this later).

To address this, we're using only the top 100 cryptocurrencies by market cap for all breadth numbers.

This number was kind of arbitrary in the initial stages of deciding to apply breadth to crypto, but it makes sense after we've done the math. Running a comparison between market capitalization by market-capitalization rank (e.g., the rank of Bitcoin is 1 because it's the largest by market cap), 100 was an appropriate threshold.

Coins within this 100 threshold represent an overwhelming 98.13% of the total market cap of the asset class.

Further additions beyond this point make marginal differences, and our universe of the top 100 coins captures a significant majority of the asset class.

For our tactical trade setups, we never venture beyond coins smaller than the top 100, so why would we include them in our breadth work?

Survivorship

Once we organize our static universe, yet another problem arises: survivorship. This simply refers to how index components change over time.

For instance, if you were to run breadth on a list of the current components of the S&P 500 to find the percentage making new 90-days, the further you go back in time, the less accurate your chart will become. This is because the S&P 500 components today are very much different compared to a decade ago.

This is put on extreme display in crypto, where the top 100 thresholds we've established will be changing quite literally on a weekly basis; coins going to zero and new daily ICOs make this a troubling conundrum.

Our solution is rather crude, but it limits survivorship within our breadth charts. That is, we're simply not going to go back in time beyond one year.

While in an ideal world, we'd love breadth charts originating many years, this survivorship makes it a rather impossible task.

Idiosyncrasy

One of my primary arguments for not using breadth charts is their efficacy in supplementing our market research.

Commonly, breadth in legacy markets is used to ascertain and assist in a directional bias, whereby traders can easily visualize how well a market trend is being supported by its components.

In legacy markets, breadth is an amazing tool.

But, in the case of crypto, 95% of the time altcoins are merely an extension of Bitcoin and Ethereum. The only difference is that alts are merely higher-beta.

When it comes to the stock market, however, there's less co-movement between individual securities given their unique, idiosyncratic drivers. For equities, it truly is a market of stocks.

For crypto, there's a stronger argument to be made that it's Bitcoin and Ethereum that drive everything, not the smaller alts.

It poses the following question: Why use breadth to ascertain a directional bias in Bitcoin and Ethereum when all breadth measures are securities that follow Bitcoin and Ethereum?

It's the age-old "does the tail wag the dog" discussion.

I don't have a great answer here, and there really isn't enough long-term historical data to support either argument (once again, enter the survivorship issue).

The one certain element in this whole discussion is that there is more than likely some edge in quantifying market breadth, considering I've seen no one in this space formally run these numbers.

Much of this letter is me thinking aloud.

We're still in the process of developing accurate breadth charts and reconciling the potential issues we've discussed today. It'll take us a few weeks to fully hash everything out, so be on the lookout for that.

Why does crypto always have to make things so complicated, amiright?

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Thanks for reading, and please let us know if you have any questions!

Allstarcharts Team

 

 

 

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