For years, trading was a manual affair. A single trader would painstakingly track markets and trends, identify the right opportunities to buy or sell, then place a call to the floor. In the 90s, it entered an electronic era with the convenience of buying and selling from the comfort of the computer. But in the 2000s, automated trading platforms started to become the norm— giving an edge to traders everywhere.
Quantitative trading is done via the implementation of several sophisticated systems and algorithms. Successful trading requires a multi-step approach:
- Finding a reliable strategy
- Backtesting against historical data
- Building the proper system
- Risk management
Over the next few posts, I’ll be diving into each of these components. Today, we’re leading off with the first: strategy identification.
Why Is Strategy Important?
Let’s say you manage your securities on a mobile app. In all likelihood, you’re closely following financial news from a major publication or trusted blog. The app also has also charted past performance for each security, further informing your decision. Board votes, executive leadership, and new products or innovations are all factors that go into your decision to buy or sell.
With quant trading, you’re essentially blind to that. You’re more concerned with finding an algorithm that can make those decisions for you, and trade on the fly. The quantitative trader is concerned with the underlying data, and can use that to create an algorithm that can make automated determinations as to the likelihood of the price going up and down. But a few good trades does not a reliable algorithm make. You need it to be consistent. The best program is able to read and process all of that data and provide insight on when to buy or sell a particular security.
Why Bother With an Algorithm?
Let’s go back to the mobile app scenario. If you’re settled into a routine work day, you’re only maybe checking your portfolio every few hours, or when some breaking news comes in. And at that, you’re only looking at a select few stocks at any given point in time. But while you’re looking at two or three, a good algorithm can track thousands. That’s the fascinating thing about quantitative trading— by not focusing on the minutiae, your time and resources are freed up to refine and perfect a platform that can consistently make good decisions.