Man and Machine Come Together

Big data, algorithms plus human - a necessary mix for quant investing

What is a Physics PhD from the Massachusetts Institute of Technology doing in an asset management company?

Building algorithms from data signals to facilitate better investor returns says Eastspring Investments (Singapore)’s resident quantitative analyst (quant).  In fact, he has been doing this for more than thirty years!

While consumer companies such as Alibaba and Amazon have only recently started to use customer data to understand customer behaviour, the asset management industry has been doing it for years.

The difference now is that computing power is cheaper and more powerful, allowing quants to analyse greater amounts of data in a shorter time.

The role is crucial as the cost of interpreting data wrongly is high for an asset manager. Showing you pictures of pink shoes, for example, believing that you like them when you don’t, is not exactly the end of the world. Making an investment decision based on the wrong analysis, on the other hand, can hurt returns.

Finding data that can impact investment returns and building robust investment models is hard work. While an Amazon can suggest a book title to you based on your last purchase, quant analysts need years and years of historical data. This may not be easy to get.

Quants typically spend 70% to 80% of their time assembling and “cleaning” data, putting them into a structured form that is fit for analysis. The rest of the time is spent building models to test the signals from selected data.

Good models need good data and good algorithms need good instructions to learn. The human input is a key component of the process. Here, man and machine come together to deliver better outcomes for investors.

At Eastspring Investments, our quant teams leverage technology and data to systematically identify market inefficiencies and help deliver excess returns to investors. Learn more about us here.