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What risk managers can learn from Alibaba

Risk, Performance, and Reporting

By Matthew Van Der Weide  |  September 17, 2014

After the initial filing of Alibaba, we posted what to consider when adding a recently IPOed security to a risk model. With that in mind, I looked to see what kind of information is available about a company pre-IPO and stumbled upon Alibaba’s prospectus. Interestingly enough, the prospectus has an actual section entitled Risk Factors. In turn, the descriptions that followed highlighted how we sometimes get caught in the trap of falling back to the same metrics and concepts when confronted with a specific topic. When thinking about risk, the things that readily come to mind are specific metrics such as VaR, tracking error, and the like. While valid and useful, risk is a much broader concept, especially at a company — rather than portfolio level and needs to be both recognized and approached as such.

Let’s take a different angle: what is Alibaba’s own view on risk? Here are some of the items it lists as risk factors in its prospectus:

  • “Maintaining the trusted status of our ecosystem is critical to our success, and any failure to do so could severely damage our reputation and brand, which would have a material adverse effect on our business, financial condition and results of operations.”

Reputation, and with that governance, is clearly on the radar at Alibaba. In a world where information is shared so easily via social media, it seems a fair point that brand and reputation are critical risk factors for a company.

  • “We may not be able to maintain and improve the network effects of our ecosystem, which could negatively affect our business and prospects.”
  • “We may not be able to successfully monetize traffic on our mobile platform, which could have a material adverse effect on our business.”

Alibaba is aware of the context, or by its term "ecosystem," it operates in. We cannot look at a company as an isolated entity without connections to the rest of the world. We have to view it as a node in a network of suppliers, customers, and competitorsc. Once we capture these relations we can get a full understanding of the company and its risks.

From a quant perspective, these concepts are historically rather qualitative and therefore hard to measure — something quants generally don’t like (they are called quants and not qualts after all). One can argue about the validity of tracking error as a measure or the preference for a normal vs. fat-tail distribution used in a value-at-risk estimate, but at least in broad terms there is agreement on how to compute these. Does the recognition of these "other" qualitative factors and their exclusion from standard models lead perhaps to a slight sense of paranoia that we are missing something?

Even though we cannot deal with the unknown unknowns, does this mean we have found some new known unknowns? The good news is that a lot of these qualitative concepts have become much more readily available, and that, in turn, allows us to take to a more quantitative approach. While you may not have the capacity to analyze a universe of thousands of companies in such detail, companies such as GMI and MSCI do, consuming the data and building comparative models to calculate ESG scores and ratings. We can then look at these both at a security but also at a portfolio level, as we did here.

Furthermore, companies such as FactSet Revere enable us to structurally capture the network of a company, by identifying its partners, competitor, suppliers and customers.


The nature of these networks underline the ecosystem concept, where, for example, we see Weibo and Cheetah Mobile attributing 26% and 25%, respectively, of their revenue as being related to Alibaba. Overweighting Weibo or Cheetah and thinking of subscribing to the Alibaba IPO: is that a double exposure you’re comfortable with?

Not only can we capture the global footprint of a single company, but through combining this consistent dataset we can also extend this to a portfolio level. Is our China fund representing purely domestic risk, or do we indirectly also get exposure to export markets such as Europe and the United States?

So what can we learn from Alibaba? A company might have a very different perspective on risk than what we’re used to at the portfolio level. Rather than this being alarming, it is actually something we can and should use to our advantage. Let’s not forget we still have the benefit of diversification at the portfolio level, reducing the impact of individual companies to some extent, so do not trash that tracking error and value-at-risk just yet. Furthermore, we now have a new set of tools at our disposal that provides a qualitative overlay that compliments rather than challenges the traditional risk measurements. It is crucial to take ESG, and specifically governance, into account and monitor on a consistent basis. Furthermore, we must look at our risk exposures both via links up and down the supply chain, as well as via geographical revenues. This is  necessary to gain a better understanding of our regional exposures, rather than relying just on place of domicile or incorporation.

In short, rather than introducing new known unknowns, we incorporate these new concepts and use them to our advantage. This leaves with one known unknown though: Will Alibaba’s IPO be a success? Will it become the next Google or Amazon, or will it struggle like Twitter more recently? Not knowing, perhaps, is actually a good thing.


The information contained in this article is not investment advice. FactSet does not endorse or recommend any investments and assumes no liability for any consequence relating directly or indirectly to any action or inaction taken based on the information contained in this article.