Trading strategy
Automatic trading strategy Statistical arbitrage is based on a paired market-neutral trading strategy.
Statistical arbitrage (Stat Arb) is a trading strategy that uses statistical techniques and quantitative analysis to identify trading opportunities. This refers to the mid-frequency strategy and can last from several hours to several days. Stat Arb uses mean reversion analysis to invest in a variety of stock portfolios over a short period of time. One of the most popular examples of Stat Arb in pairs trading is the shares of Pepsi and Coca-Cola. Both stocks belong to the same sector and move in sync depending on market events.
For example, if Pepsi stock rises significantly relative to Coca-Cola stock, you could sell Pepsi stock and buy Coca-Cola stock in anticipation of a favorable return.
Statistical arbitrage uses quantitative methods and software to track patterns or trends in the rising and falling cycles of securities. These trends are based on the volume, frequency and price of the securities traded. For example, statistical arbitrage can be used between two cryptocurrencies such as BTC and ETH.
In the image below, you can see that both cryptocurrencies stay pretty close to each other for the entire span of time with a few splits. During these separation periods, arbitrage opportunity arises based on the assumption of price convergence.
Identifying such opportunities consists of two factors: identifying pairs for advanced analysis and specifying entry-exit points for the strategy. Some platforms have built-in pair trading indicators to identify and trade pairs. However, transaction costs can be a critical factor in profiting from a strategy and are often not taken into account when calculating projected returns.
After the automatic strategy has found a sufficient divergence in the rates of trading pairs, it enters the market in such a way that the expensive pair is sold and the cheap pair is bought in anticipation of a subsequent convergence of rates. If rates continue to diverge, the strategy enters the market again, thereby averaging the total entry price and increasing the total position volume.
Now, for better clarity, we will look at the strategy step by step.
- The spread between the value of BTC and the weighted value of ETH reaches 2%, with the CrossComparator indicator crossing the first level, which is a trigger for the purchase of our custom BTC/ETH index. To buy this index, we buy the pair that is cheaper and sell the one that is more expensive, while the volume of both positions must be equal in modulus to the quoting currency of the pair.
- The spread between the value of BTC and the weighted value of ETH reaches 4%, with the CrossComparator indicator crossing the second level, which is the trigger for buying and averaging our custom BTC/ETH index.
- The spread between the cost of BTC and the weighted cost of ETH returns to 2%, while the value of the CrossComparator indicator crosses the first level, which is a trigger for closing part of our position based on the volume accumulated by the second trigger.
- The spread between the cost of BTC and the weighted cost of ETH disappears and is equal to 0%, while the value of the CrossComparator indicator crosses the zero level, which is a trigger for closing our entire position based on the volume accumulated by the first trigger.
