The rules and strategies for the technical trading in the cryptocurrency market: What did we learn from the past?
In two recent studies, I investigated the technical trading rules in the cryptocurrency market and profitability of technical trading rules among cryptocurrencies with a privacy function.
In our first study, we collected daily price data on eleven cryptocurrencies for the period Jan. 1, 2016 to Dec. 31, 2018. Our sample consisted of cryptocurrencies exhibiting the highest market capitalization as at Jan. 3, 2016. Our main sample comprised Ripple (XRP), Litecoin (LTC), Ether (ETH), Dogecoin (DOGE), Peercoin, BitShares, Stellar Lumen (XLM), Nxt, MaidSafeCoin and Namecoin.
Using a simple buy-and-hold strategy of an equally weighted portfolio, our sample of cryptocurrencies produced an average return of 36.87% per year over our sample period. It is important to note that technical trading in cryptocurrency markets is different from equity markets for many reasons, two being that cryptocurrencies are traded 24/7, and short positions cannot be taken on cryptocurrencies unless trading Bitcoin (BTC) only.
We implemented the simplest and most widely used technical trading rule referred to as Variable Moving Average oscillator, which generates trading signals employing a short period and a long period, both moving in accordance with the average level of a price index. We only focused on the payoffs from buy positions simply because it is not possible to take short positions on cryptocurrencies apart from Bitcoin.
In the study, running a (1, 20) strategy meant taking a long position on a cryptocurrency whenever its current price exceeds the 20-day moving average, and holding the position until a sell signal is generated. A sell signal, in turn, was generated when the current price of a cryptocurrency was below the 20-day moving average. In this case, we keep the money in cash. In a similar manner, we implemented (1, 20), (1, 50), (1, 100), (1, 150) and (1, 200) strategies.
When implementing the (1, 20) strategy, we found that five of the 10 cryptocurrencies generated payoffs that were statistically significant on at least a 5% level. On average, the (1, 20) VMA strategy produced a 45.63% average return per year for the 10 cryptocurrencies compared to their buy and hold average return of 36.87% per year. More precisely, this technical trading rule generated around 8.76% per year in excess return over the sample period. Our results also suggest that a longer time horizon used for implementing the VMA strategies results in less profitable technical trading.
In our second study, we followed the same research design of our earlier paper, but used data on the 10 most-traded cryptocurrencies that provide a so-called “privacy function.” The privacy function allows users to maintain some anonymity on either the user level, the transaction level, the account balance level, or having full privacy on all levels. As an example, Dash allows users to have the “anonymous send” option if they wish to anonymize their user level information.
Hence, our study employed the following cryptocurrencies: Dash (DASH), Bytecoin (BCN), DigitalNote (XDN), Monero (XMR), CloakCoin (CLOAK), AeonCoin (AEON), Stealth (XST), Prime-XI (PXI), NavCoin (NAV), Verge (XVG). The sample covers the same period as in our earlier study.
The results of this study shows that VMA strategies are successful only for Dash (on the single cryptocurrency level) and yielded returns of 14.6% to 18.25% per year in excess of the simple buy-and-hold trading strategy for this coin. Surprisingly, when we averaged the average returns across the entire set of 10 privacy coins, we did not find any positive average portfolio returns in excess of the equally-weighted buy-and-hold portfolio.
In summary, the results of our two studies provide mixed evidence. On the one hand, technical trading seems to generate profits when implementing strategies among non-privacy cryptocurrencies. The profitability is, however, limited as only shorter time horizons of the VMA’s long-period moving average appear to provide useful information. On the other hand, privacy cryptocurrencies seem to form a more efficient market, as technical trading does not appear to provide significant payoffs in excess of the simple buy-and-hold strategy from a market-wide perspective.
The views, thoughts and opinions expressed here are the author’s alone and do not necessarily reflect or represent the views and opinions of Cointelegraph.
This article does not contain investment advice or recommendations. Every investment and trading move involves risk, you should conduct your own research when making a decision.
The mentioned studies were conducted together with my colleagues Shaker Ahmed and Niranjan Sapkota, who both work as doctoral students in finance at the University of Vaasa (Finland).
Klaus Grobys is a docent in financial economics at the University of Jyväskyla and an assistant professor of finance at the University of Vaasa. Grobys is also affiliated with the research platform InnoLab at the University of Vaasa. His recent studies investigate the opportunities and risks associated with new innovative digital financial markets. His recent research was, among others, covered by U.S. business magazine Forbes.
