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INVESTIGATION ON TECHNICAL TRADING IN CRYPTO MARKETS

Two days ago, there was an investigation on technical trading rules in the cryptocurrency market and profitability of technical trading rules among cryptocurrencies with a privacy function by a group of people.

In their first study, they collected daily price data on eleven cryptocurrencies for the period Jan. 1, 2016 to Dec. 31, 2018. their sample consisted of cryptocurrencies exhibiting the highest market capitalization as at Jan. 3, 2016. their 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, their sample of cryptocurrencies produced an average return of 36.87% per year over their 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.

They 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. They only focused on the payoffs from buy positions simply because it is not possible to take short positions on cryptocurrencies apart from Bitcoin.

The first  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, they keep the money in cash. In a similar manner, they implemented (1, 20), (1, 50), (1, 100), (1, 150) and (1, 200) strategies.

When implementing the (1, 20) strategy, theyv 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. Their results also suggest that a longer time horizon used for implementing the VMA strategies results in less profitable technical trading.

In their second study,they followed the same research design of their 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, their 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 their 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 they averaged the average returns across the entire set of 10 privacy coins, they did not find any positive average portfolio returns in excess of the equally-weighted buy-and-hold portfolio.

In summary, the results of their two studies provide mixed evidence. 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.

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