The world of quantitative trading is littered with terms and strategies that may seem complex at first glance. Among them, Spread Trading is a strategy that deserves particular attention due to its profit potential and intrinsically diversified nature. In this article, we'll demystify Spread Trading, explore its nuances and detail its advantages and disadvantages, while focusing on its integration into the algo trading universe.
What is spread trading?
Spread trading is a form of trading in which you buy one financial instrument while selling another, usually linked or correlated. The difference between the buying and selling prices of these instruments is known as the spread. This strategy is commonly used in the futures and options markets, although it can also be applied to other financial instruments.
Spread Trading variations
Spread trading can be classified according to several criteria:
- Temporal Spread: This involves taking positions on the same financial instrument with different maturities.
- Inter-commodity spread: This concerns related but different financial instruments, such as WTI and Brent in the oil market.
- Inter-market spread: This involves trading the same or related instruments on different exchanges.
Take your algo trading strategies to the next level
Use our strategy database to develop quantitative strategies faster.
✔️ Research papers
✔️ Trading rules
✔️ Performance metrics
✔️ Python code
👉 Try our Database of Trading Strategies Now →
Spread trading benefits
Spread trading offers several advantages:
- Risk reduction: Since positions are taken simultaneously on correlated instruments, the risk is often lower than when trading a single instrument.
- Cost efficiency: Trading costs are often reduced, and real-time data is not always required for success.
- Flexibility: This strategy can be applied to a variety of asset classes, although commodities are the most commonly used.
Examples of Spread Trading
A classic example is the spread between WTI and Brent. Although these two types of oil are similar, their spread has a certain predictability. As a result, traders can profit from temporary price differences between these two products.
Another example is the "Frac Spread" between natural gas and propane. This spread exploits the long-term relationship between these two energy products and the supply and demand dynamics that influence them.
Spread Trading and Algo Trading
With the evolution of technology, Spread Trading can be easily integrated into algo trading strategies. Algorithms can be designed to continuously monitor price spreads and execute orders when certain conditions are met, making the strategy more efficient and reactive.
Conclusion
Spread trading is a powerful strategy in the quantitative trader's arsenal. By understanding the underlying dynamics of this strategy and integrating it into algo trading systems, traders can maximize their chances of success while minimizing risk. As always, thorough research and a good understanding of the market are essential for success with Spread Trading.
💡 Read more:
- Trading strategies papers with code on Equities, Cryptocurrencies, Commodities, Currencies, Bonds, Options
- A curated list of awesome libraries, packages, strategies, books, blogs, and tutorials for systematic trading
- A bunch of datasets for quantitative trading
- A website to help you become a quant trader and achieve financial independence