Features

Technology links and predictable returns

By Dr Stephen Sun

Dr Stephen Sun, Assistant Professor in the Department of Accountancy, shows how technology links among firms can help investors predict stock returns. This article is based on "Technological links and predictable returns," by Charles Lee, Stephen Sun, Rongfei Wang, Ran Zhang published in the Journal of Financial Economics, June 2019.

In today's knowledge-based economy, technological prowess is becoming an increasingly important determinant of firms' short-term profitability as well as long-term survival. Many of the largest firms in the world such as Amazon, Google, Intel, and Samsung, may have minimal overlap in product space, yet are closely-aligned in terms of technological expertise. These technological affinities transcend traditional industry boundaries and are typically not readily discernible from firms' financial reports. Nevertheless, they can be key drivers of the economic fortune of today's businesses. Our paper entitled "Technological Links and Predictable Returns" exploits this special type of inter-firm linkage and applies this insight to predict stock returns in the US equity market.



The "Steve Jobs' patent"

The inter-linkage of firms' technologies has been around for some time. Let's consider the so-called "Steve Jobs' patent." This patent basically opened the door for the creative production of smartphones as we know them today. It is entitled "Touch Screen Device, Method and Graphical User Interface for Determining Commands by Applying Heuristics." We can see a screenshot of the patent information from the Google Patents website above. It is indeed the core patent of Apple's multi-touch technology and has been cited and used in countless devices that have a multi-touch screen. This patent is nicknamed "The Steve Jobs' patent" as he is listed as the first co-inventor on the patent filing form and has been cited over 1000 times since its approval in 2009. The patent is so valuable that it has even received litigation to contest and invalidate it. It was initially invalidated in December 2012 and finally revalidated in October 2013.



Patent citations reveal knowledge flows among firms

We can see a screenshot of follow-on patents by other companies that cited this patent on the next page. Patent citation can give us a concrete way to see knowledge flows or technology linkages among firms. We observe a broad range of companies around the globe citing this patent, from well-known companies such as Google, Microsoft and Tencent, as well as companies in related electronics sectors in China, South Korea and the US. All these companies can be regarded as technologically linked to Apple in this respect.



The value of investigating firms' technology linkages

There are two major reasons why firms' technology linkages can actually be useful in transmitting values and helpful in predicting stock returns. First, firms working on areas of innovation that substantially overlap with each other could be subject to similar input or output linkages, which become important transmission channels for common price shocks. For example, breakthroughs in production technology have led to dramatic cost reductions in silicon chips, which in turn greatly impacted on the vitality of the electronics industry relying on these chips as a raw material. Similarly, technological progress in touch screen technology today bodes well for the firms making products that use these touch-screens.

The second reason is that, firms with similar technologies can also benefit from the spillover effect of each other's innovation activity along technological lines. More specifically, firms working on similar technologies may use similar inputs of production, with inputs being broadly understood as anything required in the production process, for example human resources, key raw materials, production equipment, information and communication technology, or intangible knowledge.



Scientific critique of new technology can directly impact share price

Here is a concrete real-world example to illustrate the point. CRISPR is a new bio-technology that can enable scientists to edit genes and has wide applicability. It is believed by some to be the most important biological breakthrough in the past decade. However, the technology itself is still in an early stage and rapidly developing. A letter in the renowned journal Nature Methods on 30 May, 2017 pointing out potentially dangerous flaws in the CRISPR-Cas9 gene editing system, gave biotech investors a sinking feeling that day and stocks in genome-editing companies using that technology had the same experience. By the close of trading Editas Medicine had fallen nearly 12 percent, Crispr Therapeutics was down just over 5 percent, and Intellia Therapeutics had plunged just over 14 percent. All these bio companies relied upon technology very similar to the CRSPR technology.

A similar event happened again on 8 January 2018. The world of science awoke to news that suddenly cast uncomfortable doubt on many of the past five years' major breakthroughs: A new paper had identified a possible barrier to using the revolutionary gene-editing tool CRISPR-Cas9 in humans. The news incited a temporary hysteria that sent the stocks of all three major CRISPR biotech firms tumbling in premarket trading, declining by as much as 11.9 percent.



How to exploit inter-firm technological linkages to make profits

In our paper, we find that investors can exploit the inter-firm technological linkages to make profits in the equity market. The idea is very simple. For each firm, we can identify a set of companies to which it is technologically related in terms of their patenting similarities. We call such closely related companies "technology peers." We then calculate the average stock return in the past month of these technology peers. We then sort firms at the beginning of each month according to the average stock return of their tech peers. We will buy those firms above 90% most profitable average tech peer returns and short sell those firms below 10% most profitable average tech peer returns, in equal weighting. This turns out to be a very profitable investment strategy, generating a mean annual return over 14% and is quite robust, with T-statistics over 5. We also explore the underlying mechanisms for this strong asset pricing anomaly result. We find the results are driven by investors' limited attention bias, consistent with a growing behavioral finance literature that documents similar patterns. That is, investors do not seem to pay enough attention to the timely change in technologically related firms' stock price changes. As the technologically related firms convey value-relevant information to the focal firm, ultimately the focal firm's stock price will move in similar directions to their technology peers.



Greater attention to technology-linkages leads to better investment decisions

Our study matters as it points to researchers needing to better understand the mechanism through which such technological attributes impact information processing costs, and thus market prices. In our own words: "It is difficult to argue that this publicly available mapping should not be taken into account when forming expectations about technology-intensive firms' future cash flows. Certainly, from an investor's perspective, greater attention to technology-linkages could lead to better investment decisions. From a firm's perspective, educating investors on its technological capabilities, perhaps through greater media coverage, may likewise yield improvements in pricing efficiency."



A note from the author

The paper, "Technological Links and Predictable Returns" was coauthored with my former colleague Professor Rania Zhang and PhD student Rongfei Wang at Peking University, Guanghua School of Management, as well as Professor Charles Lee at Stanford University, where I obtained my PhD in economics in 2015. The paper was published in the 2019 June issue of the Journal of Financial Economics and has won the 2018 Roger F. Murray Prize by The Institute for Quantitative Research in Finance, also known as the Q-group. The work is not only published in a world-class academic journal, but has also been well received in the investment community. While our study only uses data from the US stock market, some Chinese hedge funds have replicated our results and applied it in the China equity market.

Dr Stephen Sun
Assistant Professor
Department of Accountancy