Think Quant Trading Doesn’t Work in Crypto? Think Again
The recent CoinDesk opinion article “10 Reasons Quant Strategies for Crypto Fail” by Jesus Rodriguez makes for a great headline, but it overlooks relevant developments and key data in the sector.
While Rodriguez makes reasonable points about the weakness of quant technology for crypto, a growing number of professional crypto quant fund managers address these through their strategies, demonstrating clear success. Going forward, crypto assets are set to become the perfect asset class for quant strategies.
The 2020 PwC–Elwood Crypto Hedge Fund Report says the most common crypto hedge fund strategy (48% of those surveyed) is quantitative (or taking a systematic approach to the market in either a directional or a market neutral manner), followed by discretionary long only (19% of funds; meaning funds that are long only and whose investors have a longer investment horizon), discretionary long/short (17% of funds; meaning funds that cover a broad range of strategies including: long/short, relative value, event driven, technical analysis and some strategies that are crypto specific, such as mining), and multi-strategy (17% of funds; meaning funds adopting a combination of the above strategies).
To understand why almost half of all crypto hedge funds worldwide are focused on quant strategies requires a look at the broader (crypto) hedge fund sector.
It is important to note that the models used by quantitative funds usually extend beyond digital asset datasets. Many quantitative crypto fund managers come from the traditional finance world, their strategies are defined based on decades of data from traditional asset classes, and these strategies are tested thoroughly before being applied to the crypto market.
Additionally systematic strategies are superior to human decision-making procedures in an environment of irrational and volatile markets, which is definitely the case with most cryptocurrencies.
The crypto market is still dominated by traders making decisions by monitoring the price action on the charts. This increases the strength of trends and favors a quantitative approach based on time series analysis.
Traders can retrieve a vast amount of information by analysing digital asset datasets – particularly when taking on-chain metrics into account (e.g. transaction values, miner fees, etc.). That can be used by quantitative funds to garner some element of predictability instead of relying on technical price data alone.
Read the full article, Think Quant Trading Doesn’t Work in Crypto? Think Again