How Technical Traders Apply Their Expertise To Crypto Markets

Technical analysis has become a go-to strategy for many traders to build strategies and gauge market strategy. It is a broad subject, but at its core technical analysis relies on the use of charting tools and indicators to gauge market momentum and trends. This information can then be used to identify buy and sell signals, as well as getting an early sense of when market sentiment is starting to shift.

However, technical analysis is not without is criticisms, especially when it comes to crypto. Indicators can be wrong, or send off conflicting signals. Additionally, crypto’s relatively short lifespan, especially beyond Bitcoin and Ethereum, provide little historical data to test strategies and assumptions. Additionally, concerns surrounding wash trading and market manipulation, although know unique to crypto, can be problematic.

One of the industry leaders in providing crypto-specific technical analysis is Katie Stockton, founder and managing partner of Fairlead Strategies, LLC, an independent research firm and investment advisor. I spoke with her to learn how she approaches these challenges and what she has learned in her coverage of crypto.

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Forbes: What does technical analysis actually mean?

Stockton: I hate to say it but I wish it wasn’t called technical analysis because I think it’s mistaken for things that are technical as it pertains to technology. Charting is more accurate as a description of what we do. We see technical analysis as one discipline of several that can be used to understand markets, and its goal is primarily to understand price trends and where there may be inflection points as well as potential areas of buying and selling pressure.

And we’re doing that through an understanding of supply and demand. The way you understand supply and demand is by simply analyzing price. The only other data point that the market lends itself to in technicals is volume, but our focus is on price. We use a number of technical indicators to take out some of the gray area of the markets, and because they give you a binary buy or sell signal. We welcome that since the takeaway is usually black and white.

Forbes: What are some of those indicators?

Stockton: I’ll give you sort of the big picture and how I think about technical indicators. I classify them in three ways: trend following, overbought/oversold conditions and relative strength. We have probably two or three for each category. I always tell people, you don’t want to have too many indicators that are trying to get the same answer, because then you’ll find some confirmation bias and or duplication in what you’re doing. And remember, this is all based on price. So you also don’t want to get too many derivatives away from price. One of the indicators I use for trend following is the MACD, which stands for moving average convergence divergence.

Here is what it means: We want to buy things that are going up and to the right. Very simply, we want to buy things that are going to go higher, and a trend has this inherent momentum to it. Suffice it to say that when something has momentum, you should make the assumption that it will continue to do so. And that’s the momentum inherent to trends. So, you really genuinely want to buy things that are working their way higher, and you want to sell things that are in downtrend or working their way lower. That is trend following. We have indicators to understand if those trends are still strong. And the indicators tend to be based on moving averages of price, including the MACD moving average convergence, divergence and the moving averages are basically look backs using historical prices. What we’ve found is that some of the indicators that are derived from them can really help isolate important shifts and trends. And not only do we want to buy securities that are going up, we want to know when to sell them. The indicators can help us know when those trends are shifting.

Here is an example using bitcoin (BTC) on the monthly chart. Bitcoin has suffered a loss of long-term upside momentum according to the monthly MACD indicator, which crossed over in a “sell” signal in January. The indicator has an inherent lag to it, but it is designed to identify major shifts in trend. The last “buy” signal occurred in July 2020 and was followed by a strong up move.

Forbes: What are some of the other buckets?

Stockton: For the overbought/oversold piece of it, we tend to gravitate towards the stochastic oscillator. Here the goal is to look at where security is closing relative to a high/low range to see where it has been over that period of time. If it continually closes near the high end of that range, it supposedly gets more overbought—talk about an overused word; same with the word oversold. I would say overbought and oversold are almost misnomers and that, overbought isn’t necessarily a bad thing. When something is overbought, it is a reflection of momentum. And there’s a reading based on the stochastic oscillator that is an actual overbought reading. And it’s an oscillator between zero and 100%. Above 80% is overbought, and we don’t mind that. In fact, we sort of like to see something overbought above 80%. What we don’t like to see in terms of following a trend or an uptrend is that reversal back down. So it’s when that overbought reading gives way to a downtick or a downturn, that’s when we feel we have some kind of sell signal.

We rely on this stochastic oscillator to help us understand when an overbought reading is finally taking its toll on price (and vice versa) and to help us identify good entry points in stocks or securities that had been trending lower. Of course, we have a lot of people watching, as an example, bitcoin or high growth stocks, for some kind of turnaround. In those cases, they want to know if this downtrend that we’ve seen is at the point where it’s oversold enough that it’s going to turn the corner. We can use this stochastic oscillator to get us to that answer in a way that is not our opinion, it’s just a reflection of what this mathematical gauge is telling us.

Here is an example of the stochastic oscillator using ether (ETH). Ether has made a lower high associated with a downturn in the weekly stochastic oscillator from overbought territory above 80%. This tends to be a setback with a duration of several weeks as it pertains to the weekly bar chart. Ether was oversold as recently as March, when risk assets bottomed, but the rally was fleeting. We see upturns and downturns in the stochastics as catalysts.

Forbes: What happens if you get mixed signals?

Stockton: There’s a degree of subjectivity depending on the state of the market, such as whether it’s a trending market or a sideways market. In a trending market, you should give more weight to momentum gauges, trend following gauges and moving average based gauges. A range bound environment, which is where an oscillating measure like the market breadth measure or the stochastic oscillator, will be a little bit more valuable.

Forbes: The crypto market can be fragmented. How do you make sure that you are looking at accurate prices?

Stockton: That’s a good question. I always like to review what most people are looking at, such as a mainstream exchange. And honestly, usually, the first thing that you pull up, if you were to type in a ticker, is usually the primary exchange on which this instrument is traded. We primarily use Coinbase for bitcoin and ether.

Forbes: The transparency of blockchains has led to an explosion of technical indicators that are available to traders. Do you use any or do you just focus on price?

Stockton: We just focus on price. And that’s across the board for all asset classes, not just cryptocurrencies. We’re interested in reading about things like these emerging trends because they also help you make an informed decision. So it’s not to say we don’t agree with using that as an input. It’s just not really what our expertise is. One reason that the equity market is great for us is because there’s so much data around it. You get not just price data, but you also get what we call market internals. Market participation/sentiment can be measured either as an investor poll, like how you feel or it can be like a transactional gauge of how people are positioned like using the volatility index or put call ratios. So we have this abundance of data for these market internals for the equity market, just because of how long it’s been around, in part. We don’t yet have the same level of price history for cryptocurrencies, but we also don’t have all these data points that we would consider to be market internals. And it would be really helpful if we did.

Forbes: I’m sure you’ve seen some of the criticisms of technical analysis when it comes to crypto, such as the challenges presented by such a shallow pool of data. How do you adapt to this?

Stockton: The good news about the short history of bitcoin and others is that we’ve actually had some cyclicality already within that context. I call it time compression, the moves that used to take six months now take two months, and then those that take two months run their course in two weeks. I think the more price history, the better. But as long as you’re capturing different types of environments you can still build models around it. And you can still trust your indicators, as long as you have enough signals to analyze. The technical indicators, at least the ones we use, should theoretically carry over to anything that has a price and liquidity. So there’s definitely going to be nuances or maybe a certain timeframe just matters a bit more for one security than the next, but overall, you should see that transference of the methodology be pretty seamless, especially bitcoin and ether, obviously, like deep liquid markets. Others should still carry over pretty equally unless liquidity is so thin that you see a chart that has a lot of gaps on it, not just a gap up in response to news, because that’s kind of normal at times, but gaps throughout a trend as well.

Forbes: I’m sure you’re aware of wash trading and other ways that people try to manipulate the markets. How do you try to account for that, especially for assets that might be a little less known and less trustworthy that trade primarily on exchanges that aren’t necessarily based in the U.S. or have strong regulatory credentials?

Stockton: That would be concerning if we’re looking at something that we don’t trust. So we would probably avoid that at all costs, if we can. The price is the price. If the volumes are strong enough to move the price, we care about that. And as mentioned, we’re not really looking at volumes as much anyway.

Forbes: It is impossible for someone to be right 100% of the time. But I’m curious if you have any sense of what your success rate is or if you find your predictions in crypto being more or less accurate than in traditional markets.

Stockton: I don’t have a way to measure my accuracy ratio, per se, because I’ve always been a publishing research analyst, money manager until very recently. So now, as you know, as a money manager, we have a way to track records. The company recently launched the Fairlead Tactical Sector ETF (TACK) that tracks technical trends across asset classes. But what you hope is that people will subscribe to your research and follow your calls if you’re right, more often than not.

We will be wrong at times, but we’d like to think that we don’t stay wrong for very long because the indicators don’t let us. The indicators will keep you honest. We don’t try to be ultra predictive, but rather just keep people on the right side of trends, give them some risk metrics to watch and some objectives, perhaps based on the current action, talk about catalysts, etc. So we’re not saying we think bitcoin will be at price X by year end—we don’t add value that way or have that crystal ball. But when people can follow the views in a consistent manner, that’s where the real benefit can be.

Disclosure: I own several cryptocurrencies, including bitcoin and ether, which are mentioned in this article