Investing is an extremely difficult endeavor regardless of your goals. It takes both intelligence and strong will in order to do it successfully. With the invention of the computer and the more widespread use of data science, people eventually realized that you could take out much of the human error when it comes to investing in favor of complex investment algorithms that trade based solely on math. For some of you old school investors that need to have that “feeling” about a company, this idea may terrify you, but let me explain.
Firstly, if you have any investments in mutual funds, hedge funds, etc. your portfolio is already being exposed to the trading of quantitative investment strategies and automated investment algorithms. The days of your fund manager sitting at his desk scouring the Wall Street Journal for stock picks are long gone. Now, we simply have an idea in mind, a set of data, and a software tool in order to sift through that data.
We will use Equities Lab as an example. We currently have a large dataset that encompasses the entire market, assigning hundreds of data fields to each stock.
There is no single investment idea within Equities Lab. You build what you want to invest in based on your own personal investment philosophy. Even if you don’t have a specific idea there are quite a number of prebuilt strategies to be used at your fingertips.
Equities Lab itself is a tool that is going to allow you to sift through the data and find companies that you want to invest in.
That all said you still aren’t getting that “feeling” about a company that you want to invest in. To answer that, I must posit a question. Do you have criteria that a company must fit before you even start doing research, or do you dive into researching every company that you find? If you fall into the second half of that question, you’re wasting a lot of time trying to find investments, and I urge you to go back and look at your historical trades – I can almost promise you that you’ll find a pattern.
That pattern, no matter how much you want to deny it, is the basis of a quantitative investment formula. Virtually everything in this world can be quantified, and with that quantified data everyone has the ability to comb through and build whatever they please.
For example, say you only invest in companies that offer a dividend yield of greater than 10%. That may be your only defining parameter in your portfolio. Well, screening software (the backbone of the quantitative investment world) can dive into the market and hand you companies that match only that parameter.
That one little line of the Equihack language has dropped our potential investments from over 3000 to just 74. At this point, if you’d like to dive into these companies individually you can see if you get any sort of “feel” off of them.
In essence, quantitative investing is just the short way of saying “Making your life easier by doing what you already do, faster” in bigger words. Yes, there are more components to quantitative investing, and things can get complicated once you start building screens to match extremely certain parameters and completely eliminating the human element from your portfolio, but there is truly no need to do that when you are just managing your retirement account once every few months. There are also parts, even within the Equities Lab platform, that we didn’t go over like backtesting which can show you the historic performance of a strategy once you eliminate the human element. That being said, if you are completely new to even the idea of quantitative investing be sure to just ease into it. It’s not there to take over your portfolio and do shady things. It’s there to simply make your life easier, and expedite your investment process – leaving you more time to spend time doing what really matters.