As the digital economy expands and omni-channel buying becomes the norm, traditional data alone is no longer adequate. Anthony Okolie talks with Xin Chen, Vice President of Asset Allocation, TD Asset Management, about the importance of alternative data to evaluate real-time impacts on the economy and company profits.
- Xin, let's start with the big picture. The coronavirus has led to a surge in the demand for alternative data. And investors are looking for real-time impacts on the economy and corporate profits. First, Xin, help us explain, what is alternative data?
- Yeah, sure, so alternative data, in some sense, they are as opposed to traditional data investors could usually find on the Bloomberg platform, or company financial balance sheets. So they're a little bit unconventional. They're created a bit more creatively.
And, for example, people usually are tracking dropping bags at the airport to proxy for flight traffics. Or they look at keywords. They scrape keywords from the website to proxy for certain sentiments about stocks. Or they actually look at geolocation data or satellite image to track shoppers' activities. So these are all examples of alternative data.
- And how has the pandemic created this unconventional data?
- Yes, so basically, there is increasing joint efforts between a broad group of people to really conduct research and actually to join the effort to help this COVID issue. So for example, Google and Apple, they started sharing the mobility data earlier this year as part of the effort. And also OpenTable, they actually publish their data on a daily basis to support the restaurant industry.
In addition to this, academia and public institutions also started to conduct and actually collect data together. And also, they share all this data publicly. So it becomes actually even more data for people to use. For us, it's actually a good way, an alternative way, to fast track the economic activities since the reopen.
- And that's a great segue to my next question. So you've got all this alternative data. How do you use it in your day-to-day investment decisions?
- Yeah, so that's a very good question. So we do have a investment store. And we actually adapted to this specific scenario and additional data. For example, we added a COVID-19 category in our framework. For example, that includes matrices like daily case curve around the world, reproduction rate, health care capacity, and things like that.
In addition, we also use the economic side of alternative data from this new wave of data set to supplement our economic and fundamental forecasting. So those are the general things we did as the investment process perspective. And we also, as an example, we also used the data for a second location, for example.
So basically, one good example would be we found that the spending data show very strong, solid spending in e-commerce, typically tech devices. Probably people work from home that time, despite the collapse in other aggregate spending as a whole during the pandemic. So that led us to gain additional confidence to overrate software and semiconductor sectors.
Another example would be the home builders. So we actually found very interesting, people spend more on home improvement. And there were stronger home builders' activities as well in the alternative data at the early stage. So that led us to overrate the Homebuilders Index, which also outperformed the S&P price significantly since the reopening.
- And those are great examples. Has anything also surprised you or changed your view about the pandemic recovery based on all this alternative data?
- Yeah, so actually the speed to return to normal was faster than we initially anticipated and many anticipated for both the US and Europe. So basically, for an example of the US, so the US started to reopen in the middle April. And by the middle of May, most of the states already reopened, at least partially.
And there was a very strong broad-based rebound showing the mobility data. And we found that not just the initial rebound. What surprised us even more was that momentum was able to maintain after the initial two-week formula had worn out. So as a result, we started to recognize the adaptability to the new normal was actually very strong. That led us to actually pull forward our expectation on the recovery.
And another example, similarly, is Europe. So people were generally not very optimistic about Europe, typically because they are being hit hard on the pandemic. So Italy, for example, their health care system completely collapsed. Deaths really skyrocketed. So people were actually a little bit pessimistic.
However, we found early high-frequency data showing their mobility, restaurant reservations, and flight traffic actually turned back to normal smoothly, and more importantly, without triggering more-- new cases. So they're able to-- also able to flatten their case curve at the same time. So this evidence actually gave us further confidence to become more optimistic about global equities compared to average institution investors.
- So there seemed to be a lot of importance put on this alternative data. Now, although much of it was borne out of the pandemic, in your view, is it here to stay?
- I would say, some of the alternative data may go away, especially those ones are COVID specific if this virus thing goes away. However, because people already adapted to faster, higher-frequency information to use in conjunction with their regular sets, this trend is hard to reverse. So I would imagine the alternative data will stay.
And actually, there will be more popularity. And there will be more people who use it to gain additional insight with this fast information. So it's like when we get used to the internet and read news faster, we don't just go back to read newspapers.
- Xin, thank you very much for your analysis.
- Thank you. Thank you for having me.