How to trade crypto: Leading & Lagging Indicators

What you'll learn

  • What are leading & lagging indicators?
  • Common examples of each
  • Indicators within crypto transactional data
  • Data Indicators from the wider crypto economy

As you start to decipher the world of cryptocurrency trading it might seem that you are overloaded with information and acronyms.

At the basic level Learn Crypto’s section on how to trade cryptocurrency has made a distinction between Trading and Investing, based on short or long term focus, the different types of analysis generally used for each - Technical or Fundamental - and the level of commitment required.

Technical Analysis is far more labour intensive simply because your focus is on short term patterns, and the constant flux of prices. As yet we haven’t even scratched the surface of the indicators and tools that you might employ.

Rather than provide an overwhelming A-Z of every possible technical indicator, it is more helpful to understand how indicators can be grouped which can then help you find an affinity with a specific aspect of Technical or Fundamental Analysis.

Technical indicators within trading of traditional financial assets - like shares or foreign exchange - are generally grouped as being Leading, Lagging or Macro.

  • A Leading Indicator points at where the price might be going.
  • A Lagging Indicator confirms patterns in prices once they have formed

You might think that given a choice you’d rather spend your time looking at where price is going rather than where it's been, but both Leading and Lagging are equally useful.

Common Leading & Lagging Indicators

We’ve already provided one example of each type of indicator. Relative Strength Index (RSI) is a leading indicator as it hints at whether the market is becoming overbought or oversold.

Moving Averages, in contrast, rely on historic data and provide a continually updating retrospective view of average price behaviour.

On Balance Volume

We introduced On Balance Volume in a previous article looking at volume in general. By indexing volume changes OBV can provide a potential indication of price direction, given price and volume are so closely linked.

Bollinger Bands 

Taking their name from their creator, John Bollinger, Bollinger Bands are a measure of volatility and can be useful as both a leading and lagging indicator.

Bollinger Bands are plotted as three lines. The middle line is just a Simple Moving Average (we discussed Moving Averages previously) usually at 20 days/weeks. The top and bottom lines are two standard deviations above and below the Moving Average.

So Bollinger Bands essentially plot the extremes of potential volatility. When the bands are close together, markets are stable, the trick is to know the signs that volatility is coming, and obviously in which direction.

As volatility increases,  the bands will expand as the potential range of change increases. Conversely, when Bollinger Bands are far apart, it's important to try and pre-empt them squeezing back closer together as volatility declines.

Because of their use of a Moving Average and standard deviation, Bollinger Bands are often described as mean reversion indicators.

Crypto Specific Data Indicators

One of the difficulties of getting into Trading is the sheer amount of time required to understand the techniques used and find a successful strategy that might work. It is not particularly intuitive and there are some who doubt that Technical Analysis even works.

Fortunately, there are different sources of information that can act as indicators to both short and long term price movement, which are less abstract, more intuitive and specific to cryptocurrency.. 

Transactional Data

If you were considering investing in your local coffee shop, one of the first things you’re going to want to look at is revenue. Total revenue is crucial but so would the daily patterns in revenue, relative growth rates week-on-week, and what types of coffee are being sold so you can create basic customer profiles.

You can take a similar approach to analysing cryptocurrencies by pulling transactional data yourself - by running a node - or relying on existing services or analysts. Just taking Bitcoin as an example, there is a wealth of data that can act as leading indicators:

Mining Data

Miners are the backbone of the Bitcoin network, their work - in running the hashing algorithm - literally secures the integrity of transactions. Mining is measured in Hashrate, so the logic goes that the higher the hashrate, the stronger Bitcoin is and the better it functions as a store of value.

Hash Rate plotted over time supports this idea, but of course isn’t very granular. By looking at things like 

  • Mining Distribution you can assess whether this crucial function is becoming concentrated.
  • Mining Revenue and its movement will tell you whether it is being retained, or sold to finance operations.
  • Transaction Fees can help you understand the types of users and how this might relation to further adoption.

In exactly the same way, you can look at the following data groups and find useful potential indicators:

Network Activity

This is a proxy for customer data, as you can see things like number of Addresses, Number of Transactions, Transaction Processed per Second, UTXOs (balances) & Average Transaction Value

Wallets/Exchange Accounts

Wallet providers like Blockchain.com provider data on the number of wallet downloads. This is quite a crude indicator as it doesn’t mean the user has funds. In a similar way, big exchanges like Coinbase release data on customer growth, and as it will soon be a publicly listed company will have to share this kind of data. Its recent filing provided a trove of information.

Scarcity

Bitcoin’s most important characteristic is its scarcity. It is programmed into the rules that govern its function and works like clockwork, creating 6.25 BTC roughly every 10 minutes (a rate that halves every four years). A model has emerged that charts a relationship between this predictable scarcity and price, called Stock-to-Flow.

Stock-to-flow was created in 2019 by an anonymous analyst called PlanB, and uses a traditional measure of the scarcity of precious metals like Gold. It uses the relationship between existing stocks and new stocks in a simple formula:

Stock-to-flow = 1/Supply growth rate

Gold’s supply is predictable, because it is indestructible and extraction is inflexible. SF is about 62. Bitcoin’s SF is constantly increasing, because supply growth rate is constantly declining and trending to zero, as in 2140 the last Bitcoin is expected to be mined.

Broader Ecosystem Data

Cryptocurrencies don’t have standard measures PE Ratios but there are a growing set of bespoke metrics that can provide indicators of network health, growth and hodling. Sites like Blockchain.com, Glass Node and Woo Bull Charts provide them for free.

A good example is Market Value vs Realised Value (MVRV) - which measures the Market Value of bitcoin in relation to the price it last moved. This is one of a number of proxies for understanding how much users are hoarding. 

In the same way, statistics measuring the proportion of balances that haven’t moved over the last 12 months helps quantify hodling behaviour, and potential selling pressure.

In a similar way, measures in the growth of Whale Accounts and Institutional Investment are both valuable indicators, as are patterns in the movement of coins into or off exchanges, which act as pro or contra-indicators of hodling.

Macroeconomic Indicators

Crypto is generally portrayed as being a challenge to traditional finance. Bitcoin’s use case as an effective store of value means that it should have an inverse relationship to key indicators of the health of the system it is intended to replace. You’ll often hear the phrase ‘safe haven’ asset, for example.

The reality is that it is yet to conclusively demonstrate that relationship, but there are some things that are worth keeping a close eye on:

The Dollar Index (DXY)

The DXY is a measure of the US Dollar against a basket of other world currencies. A fall in the DXY suggests dollar weakness and a rise the opposite. The DXY and Bitcoin broadly correlate inversely, as a weakening dollar suggest flight from the world’s reserve currency into better stores of value.

Stock Markets

Though BTC may move inversely to dollar strength, it is yet to de-couple from stock markets which have benefited from ongoing stimulus since the 2008 financial crisis.

This seems counter-intuitive to Bitcoin’s value proposition, but suggests that both are benefiting from the same kind of investment behaviour - the search for yield in a low yield environment. In other words, anything that gives a better return on savings than the record low base interest rates. 

This means that crypto investors will cheer both the dollar’s demise AND the ‘number goes up’ mentality of major stock markets. 

Signs that Bitcoin’s relationship to the stock markets is changing are significant, because as things stand, a very simplistic analysis suggests that the levers that the US Treasury and Federal Reserve pull are also connected to Bitcoin price

Bond Yields

Another important macro indicator that is watched by crypto traders are Bond Yields. Bonds are forms of tradable debt, most commonly the way governments raise money. A bond always has a coupon or return and a maturity date.

The coupon should reward the investor in excess of expected inflation, otherwise the Bond would provide a negative real return. Coupons therefore go up as maturity increases because there is greater uncertainty about inflation going forward.

Increasing Bond Yields are therefore a leading indicator of inflation, and Bitcoin should fair well in an inflationary environment because of its store of value characteristics. The relationship isn't however that straight forward. If inflation is anticipated this might reduce the necessity of the kind of stimulus that has also been strongly correlated to price increases within crypto markets.

Though the leading and lagging indicators we have discussed play out in the short term, as the lens starts to zoom out away from the specifics of price and volume, the line starts to blur between Technical Analysis and strays into what we'll focus on in the next article, analysing broader measures of adoption and influence on price, known as Fundamental Analysis.

Next step: What is Fundamental Analysis?

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