All quantitative investment / trading strategies start with initial research that is often described as Strategy Identification. This process of research encompasses the development of a cryptocurrency trading strategy, developing its resources, and identifying whether that particular strategy is appropriate for a portfolio collection of strategies that might already be active.

Obtaining any data that is necessary in order to test crypto strategy and optimizing the approach for greater returns (with lower risk) is essential. Crypto enthusiasts must factor in capital requirements when operating the strategy as a retail trader. It is also important to know the number of transactions (and their associated costs) because this will affect the crypto strategy.

Most people fail to understand it is quite straightforward to identify profitable crypto strategies using various sources that are available to the public. Academic journals regularly publish works showing the results of theoretical trading models, although many of these journals fail to acknowledge gross transaction costs.

Quantitative finance studies often discuss crypto strategies in lengthy detail. Academic journals in investment often outline strategies that are employed by major funds. Some might question the reasons individuals are willing to openly discuss profitable crypto strategies, since others might crowd the trade and prevent the strategy from working over a long-term period of time.

The reason can be found in the idea that hedge funds won’t generally often discuss exact trading parameters and their tuning methods which as used in active positions. Optimizations are an important key to profiting from what might actually be a mediocre strategy which eventually becomes highly profitable. In truth, one of the best methods for creating a unique crypto strategy is to locate similar methods which are then fine-tuned to meet your individual investment needs.

Relative Value Trading vs. Directional Trading

Many quantitative hedge fund strategies are included in one or two categories: Relative Value and Directional strategies. Each of these strategies use statistical software and computer models to make their assessments. Relative Value strategies will generally look to capitalize on the specific pricing relationships and mean reversion relationships that exist between multiple assets.

As an example, there are relationships which exist between long-dated US Treasury Bond yields and short-dated US Treasury Bill yields. Another example would be the relationship that exists within implied volatility for dual option contracts. Directional strategies, on the other hand, will generally build upon trend following and other types of pattern based approaches which suggest upward/downward price momentum for an asset or group of securities.

Common Relative Value Strategies:

• Government related securities (dual countries)
• Government related securities (dual lengths to maturity)
• Mortgage bond securities vs. corporate bond securities
• Implied volatility differentials (dual derivatives)
• Bond prices (corporate bond issuer) vs. equity prices
• Credit Default Swap spreads vs. corporate bond yield spreads

Common Relative Value strategy examples include placement of relative transactions (such as buying a single asset, selling another) on closely priced assets.

Event-Driven Crypto Strategies

Event-Driven Trades are constructed using anticipated events at the corporate or macro level (such as take-over actions, mergers, and bankruptcy filings). Sometimes, this is also referred to as risk arbitrage. Focus on the world’s macroeconomic environment can help to concentrate strategies on major interest-rates moves or currencies. Emerging Market strategies invests in the debt, equity, or the currencies of emerging markets. This can also impact the value of cryptocurrencies on a relative basis.

Markets will generally be characterized by lack of liquidity and transparency, as well as the inability to locate usable derivatives contracts that can be used for hedging. These practices can also be applied to the crypto space. Market neutral factors can impact pairs of assets (buying a single asset while selling another asset).

Thus, investors are typically neutral relative to the trends in market direction (as these strategies utilize a beta levels of zero. In the market, this is also referred to as statistical arbitrage and it might involve investment in singular assets relative to an index or index ETF. At the same time, convertible arbitrage targets certain pricing anomalies which exist between convertible bonds and options on certain assets. These are all strategies which can be applied to the analysis and assessment of specific cryptocurrencies. Although these quant strategies are often directed at other market assets, there is nothing stopping their application to the world of digital currency.