The Nature of Cryptocurrency Markets
An analysis of three trend-based strategies
You can also read this blog post on the Adaptive Analysis website.
Emerging markets are more speculative and trend-driven in nature given the absence of robust frameworks to value them
As markets mature, prices become increasingly driven by fundamentals-based models
A number of trend-based strategies based on past data have managed to outperform bitcoin long and hold positions
In light of recent price increases and “when moon?” midnight messages, it is worthwhile doing a little exploration into the nature of the cryptocurrency market. What do we mean by nature? Don’t worry, we are not going to provide you with any spiritual or philosophical outlooks on the “nature of the market”. We are simply going to do a little exploration into what the data suggests about how the cryptocurrency market moves.
We have previously stated that the cryptocurrency market is largely trend-driven. Here, we will see whether the data backs this up. The reason we have stated this previously without backing it up is emerging markets tend to be driven by trend or the speculation of investors instead of utility based fundamentals.
More mature markets such as equities (which has been in existence since the early 1600’s) are more so driven by fundamental valuation models. Analysts largely agree upon these models but will argue over the input. This is why when an earnings announcement varies from what analysts have estimated, we will see the price quickly move to adjust and match the valuation models.
Emerging markets, especially emerging technologies, don’t have such valuation models. The very reason these technologies even exist is because they are disruptive and this means breaking the norm. They capture value in ways which have never been quantified before and this can lead to huge overvaluations or undervaluations. Many were uncertain of how to value technology stocks in the late 1990s and this led to manic price increases.
In the absence of generally accepted valuation models, more and more of the price movements we observe are due to speculation and trend as opposed to actual utility. We have utility metrics such as the amount of value transferred across these decentralized networks but changes in these metrics are often not factored into the price. As the market matures, we will likely see a gradual shift towards valuations based on these metrics until we arrive at a point where we have models that quantify exactly how they play into price.
We are seeing the very first valuation frameworks for cryptocurrency networks being created over the past two to three years. Analyst Chris Burniske is pioneering some of the earliest work in this field. Burniske himself acknowledges that valuation frameworks for cryptocurrency networks are still at a rudimentary phase. While it took hundreds of years for the equities markets to converge on generally accepted fundamental models, Burniske foresees this phenomenon happening orders of magnitude faster in the cryptocurrency markets.
“In time, I expect similar convergence on standard valuation models to happen around popular cryptoassets until we get to that point where we have consensus mathematical models and merely bicker over the inputs to the models, as currently happens with the rest of the capital markets. We will get there an order of magnitude faster than equities did.”
Until that point arrives, the market remains largely trend driven and the data presented here backs it up. We present three trend-based strategies that would have outperformed bitcoin long and hold based on past data. While strategies based on past data are never guaranteed to repeat themselves, these trend-based strategies do provide evidence that the cryptocurrency has mostly been very trend-driven to date. The idea of all of these strategies is to outperform a bitcoin buy and hold portfolio. If bitcoin buy and hold is beta, the idea of these strategies is to add in a little bit of active management in search of alpha. If the nature of the cryptocurrency market starts to change, these strategies could do the opposite and actually eat into the returns an investor would have with bitcoin buy and hold. With that disclaimer, let's move on to the strategies...
Yearly Average Price Momentum Strategy
The first strategy is based on research completed by Elm Funds. It’s very simple. Every month-end, if the price of bitcoin is above its average price over the past year, you maintain or enter a long position. If it happens to be below the average price over the past year, convert to fiat.
Pretty simple, right? In the past, this strategy has captured the meat of the upward moves while also converting into fiat long before market capitulation. The graph compares the strategy with a long and hold strategy from the start of 2013 to the 15th of December 2018.
Using this strategy, traders would have exited the market at approximately $6190 at the end of June 2018 allowing them to the capitulation crashes of November 2018. This would have been the exit after entering for around $313 at the end of October 2015. On this strategy, traders would have recently reentered their long positions at the end of May at approximately $8277.
This strategy works well now because of the trending nature of the cryptocurrency market. A more mature market which trades more regularly around its year average would not perform as well with such a strategy. The more regularly the price crosses the 365 daily moving average, the less effective this strategy is.
The average price over the past year for bitcoin, on the 6th of July 2019, is $5,833. Let’s say price violently swings back down to this point and stays below until month end. Then the strategy converts back to fiat at a loss. This would call into question whether cryptocurrency markets are still largely trend-driven. But if they are, the idea of this strategy is the next time price crosses beneath its average price over the last year, it will be significantly greater than the entry at $8,277.
200 SMA Momentum Strategy
The next strategy is designed based on the same principle of bitcoin being trend-driven. I heard about this strategy when I went to a presentation by crypto analyst Willy Woo which I talked about here.
The strategy involves buying when the price of bitcoin crosses its 200 daily moving average to the upside and selling when it crosses to the downside. Willy didn’t run through the numbers but he stated there needs to be a buffer of about 6-8 weeks when the price has crossed the line before buying or selling.
I went through the numbers on this one with a buffer of six weeks, seven, and eight weeks. Similar to the last strategy, the performance can be compared in terms of what $1 dollar would have turned into from February 1st 2018 to December 15th 2018.
With an ending value of $760, this strategy would have outperformed the yearly price strategy from the Elm Fund research. If the strategy was continued, traders would have reentered on the 14th of May 2019 at $7986. At the end of June, that would have brought the value of the initial $1 invested to $1,023.
Giving a buffer of seven weeks would have outperformed both the Elm Funds research strategy and the 200 SMA strategy giving a buffer of six weeks. If continued, traders would have reentered on the 21st of May 2019 at $7955. This would have brought the value of the initial $1 to $1,662 at the end of June.
The eight-week buffer would have shown approximately the same result as the seven-week buffer come mid-December. If continued, traders would have reentered on the 28th of May 2019 at $8,717. At the end of June, this would have brought the value of the initial dollar invested to $1,516 with this strategy.
Past results show all three of these strategies to be effective and to outperform the Elm Funds research strategy. Of the three, a buffer of seven to eight weeks performed best and may be optimal to base future strategies on.
Altcoins BTC Momentum Strategy
The trending nature of cryptocurrency markets is not only limited to bitcoin. We tested a momentum-based strategy on two of the leading altcoins, litecoin and ether, against bitcoin. The strategy is based on the idea that in a trending market, if an altcoin outperforms in a given month, it is more likely to outperform in the following month. If the altcoin outperformed bitcoin in a given month, the bitcoin position was converted to the altcoin for the following month.
This strategy was tested on the litecoin BTC market from March 2014. An initial one bitcoin at the start of the strategy would have grown into 2.48 bitcoin at the end of June 2019. The results were far more pronounced for ether. The ether BTC market was tested from August 2016. An initial one bitcoin would have grown into 31.27 bitcoin by the end of June 2019. This outperformance of ether is representative of the significant trends observed since the start of 2017. Litecoin would have actually underperformed if the testing had stopped at the end of 2016 with the 1 bitcoin being reduced to 0.82 bitcoin. However, the idea is that this strategy will allow traders to capitalize when these altcoins make significant upside movements against bitcoin.
There are a few caveats and disclaimers that need to be taken into consideration with this strategy. At Adaptive Analysis, we are very optimistic about the future prospects of bitcoin. However, given the historical tendencies of markets to converge around a few large players capturing the vast majority of the value, we are not near as optimistic about the future of altcoins. There may be a case with this strategy where a trader becomes exposed to an altcoin and it hugely underperforms bitcoin in a given month. When the market matures to become more fundamentals driven, such a scenario becomes more likely. The data also only supports an outperformance for litecoin and ether. Other altcoins were not tested.
This strategy was also tested to assess whether it outperforms bitcoin buy and hold but risk management remains paramount. Although the strategy tested converting 100% of bitcoin to altcoins at month end, in all likelihood, only converting a fraction such as 1-3% would be far more prudent from a risk management standpoint.
More Caveats and Disclaimers
Nothing in this article is financial advice. The above strategies were all tested on past data. Past data does not guarantee that the markets will continue to behave in a similar manner in the future. Markets, especially emergent ones, are a continuously evolving entity governed by the participants which ultimately play into the price. These participants are varied and complex in nature and consist of entities such as governments, institutions, regulatory bodies, retail traders, among more. This article is mainly designed to indicate that early markets that lack robust valuation frameworks are largely trend-driven and speculative in nature. The cryptocurrency market has demonstrated these characteristics to date.