By Ronnie Barnes, Kristin M. Feitzinger, Greg Leonard, and Shaama Pandya 

This article is the first part of a two-part series. You may read the second part here.

While shareholder actions (or “securities class actions”) have been litigated in a number of jurisdictions (most actively in the US and Canada, but also in Australia) for many years, these matters are a more recent addition to the legal landscape in the UK. The passing of the Financial Services and Markets Act 2000 (“FSMA” or the “Act”) made it easier (at least in principle) to bring collective actions on behalf of a large group of investors.  

Two sections of FSMA, 90 and 90A, provide for remedies to shareholders for losses caused by untrue or misleading statements. Focusing on prospectuses and listing particulars, Section 90 of FSMA “provides a statutory remedy for shareholders who acquire securities and who suffer loss as a result of untrue or misleading statements or omissions in prospectuses or listing particulars relating to those securities.”¹ Section 90A of the Act deals with a broader set of information sources and “provides a remedy for untrue or misleading statements made knowingly (or recklessly) or dishonest omissions contained in published information, or dishonest delays in publishing the relevant information, for securities traded on a regulated market.”²

While there have been only a small number of shareholder actions brought in the UK in the more than two decades since the passing of FSMA,³ to the extent that such cases do materialise in the future,⁴ experience from the US would suggest that economic analysis will play an important role. This article first provides a summary of certain key concepts in financial economics that may be important in the context of shareholder actions in the UK. The article then discusses how a financial economist would address issues of causation and damages,⁵ as well as the legal question of reliance that arises in such litigation.⁶

Key Economic Concepts For Shareholder Actions

Stock Prices and Market Efficiency 

A basic principle of financial economics states that the value of a security reflects the present value of the future cash flows that an investor expects to receive from owning that security.⁷ These expected future cash flows are typically not known in advance with certainty, i.e., they are “risky” cash flows. To value the security therefore requires the investor to formulate expectations with respect to the amount and timing of these future cash flows, as well as the likelihood of the cash flows being realised. 

Consider an investor who is assessing the value of the shares of ABC plc (“ABC”), a UK pharmaceutical company. The investor’s expectations of the future cash flows of ABC will depend on the set of information that is available to the investor at that time. Based on this information, the investor will come up with a particular price that they are willing to pay for ABC shares. To the extent that the information available to the investor changes in a manner that alters their expectations regarding ABC’s future cash flows, their assessment of ABC’s share price would also change.⁸

The concept of market efficiency, first addressed in an academic article by Eugene Fama in 1965,⁹ provides a link between the price of a company’s shares and the information available to investors under certain conditions. An “efficient market” is one in which there is sufficient liquidity and competition among sophisticated investors for security prices to “always ‘fully reflect’ available information.”¹⁰ As is the case with courts in the US, this article focuses on the semi-strong form of the efficient markets hypothesis, which states that “the market uses all publicly available information in setting prices.”¹¹ 

The concept of market efficiency has implications for the relationship between ABC’s share price and the information available to investors about the company.  

The concept of market efficiency has implications for the relationship between ABC’s share price and the information available to investors about the company.  

• First, if ABC’s share price “fully reflects” all publicly available information, then the share price should react quickly to new, value-relevant information that becomes publicly available. If it does not, then the share price would not reflect “all publicly available information.” 
• Second, the share price should only change in response to new, value-relevant information. If information is “old,” then it should already have been incorporated into the share price when it was first released. If information is not value-relevant, then it does not change investors’ expectations about ABC’s future cash flows, and therefore would not lead to a change in the share price. 
• Third, the share price will react to the total mix of new, value-relevant information that is released. In other words, if multiple pieces of new, value-relevant information become publicly available, the share price will respond to reflect the totality of the information content that is released. If different pieces of information have opposite implications for investors’ expectations about ABC’s future cash flows (say, positive news and negative news are released in the same announcement), their impacts could offset each other. 

Event Studies: Approach and Potential Inferences 

Financial economists routinely use a technique known as an event study to analyse the effect on share prices¹² of new information that is released publicly.¹³ Event studies have been widely used in academic research to measure the effects of company-specific events (such as earnings announcements or announcements of mergers and acquisitions) and regulatory changes (such as merger-related regulations).¹⁴ The event study approach used in the academic literature has also been applied in the context of securities litigation in the US.¹⁵  

Event study analysis requires the researcher to specify the event (i.e., release of information) to be analysed and to identify, with as much precision as possible, the earliest public release of that information. The researcher then measures the share price movement over the “event window,” i.e., the period when the researcher expects to observe the price response to the identified event. Often, regression analysis is used to isolate the company-specific price movement over the event window, removing the estimated effects of broader market and industry factors on the share price movement. Regression analysis also allows the researcher to assess whether the company-specific movement is “statistically significant,” i.e., whether it can be distinguished from the typical level of daily volatility or variation in the share price. 

While event study analysis is a valuable statistical tool that allows a researcher to analyse the share price effect of new information released to the market, it is important to keep in mind that the event study approach also has certain limitations which affect the inferences that may be drawn from the analysis, particularly in the litigation context.  

For example, an event study can only provide insight into how the share price reacted to the specific information released at the time the information was actually released. This means that the event study cannot measure the price response to an omission (i.e., information that is not publicly released) at the time that it allegedly should have been disclosed. Further, if the omitted information is eventually released at a later date, an event study alone cannot establish how the price would have reacted on the date that the omission occurred. Using any price reaction measured by an event study on one date to estimate a hypothetical price reaction on another requires assumptions or analysis in addition to the event study itself.  

Moreover, the typical event study cannot distinguish between or separate the price effects of multiple pieces of information released during the same event window. As noted earlier, the share price would react to the total mix of information released. Accordingly, in order to draw an inference about the share price movement associated with the specific event being studied, it is necessary to properly evaluate the totality of the information released during the event window.  

Consider the following illustrative example: 

ABC announces disappointing sales at 10:00 AM on February 1, 2022, reporting 2021 revenues of £9 million, when the market expected revenues of £10 million. The company attributes the revenue shortfall to (1) the sudden termination of a contract by an important customer, and (2) slower sales caused by now-resolved supply chain issues.  

At 2:00 PM on the same day, ABC announces a major fire at one of its plants, which is expected to lead to reduced production for an extended period of time.  

Regression analysis shows that there is a statistically significant company-specific share price decline of 12.4% on February 1, 2022—i.e., after adjusting for market and industry factors, the company-specific share price movement is -12.4%, which is statistically distinguishable from the typical daily volatility in ABC’s share price. 

Now consider a researcher who is utilising an event study analysis to evaluate ABC’s share price response to the termination of the customer contract.  

Given that the -12.4% price response reflects the total mix of information released on February 1, 2022, the researcher cannot, without further analysis, conclude that the entire amount of this decline was caused by the announcement of the contract termination. In other words, simply observing that the contract termination was announced on February 1, 2022, and that there was a statistically significant company-specific share price decline of 12.4% that day, is insufficient for the researcher to draw a causal inference from the event study analysis because multiple pieces of information were disclosed.  

The researcher has to identify and assess other new, value-relevant information (unrelated to the event of interest) that may have been released during the same event window. A range of techniques and tools used in financial economics may help address this issue. For example: 

• An analysis of the intra-day movements in ABC’s share price can help disentangle the portion of the overall price decline on February 1, 2022, that occurred following the 10:00 AM revenue shortfall announcement (which included the contract termination) from the portion of the price decline that occurred after the 2:00 PM announcement of the plant fire.¹⁶ 
• Fundamental financial analysis can be useful to disaggregate the share price effects of different pieces of information that are released contemporaneously. This analysis may allow the researcher to disaggregate the estimated effects of the contract termination on ABC’s expected future cash flows from the estimated effects of the supply chain issues,¹⁷ and therefore estimate the price response attributable to each item. 

A review of securities analyst reports¹⁸ following the announcements may provide additional insight into whether market participants viewed the information released as new and value-relevant, as well as provide insight into the relative importance to market participants of different pieces of information about the company.

This article was originally published in Cornerstone Research on 12 September 2022. It can be accessed here: https://www.cornerstone.com/wp-content/uploads/2022/09/The-Role-of-Economic-Analysis-in-UK-Shareholder-Actions-2022.pdf

References

1. Damien Byrne Hill et al., Class Actions in England and Wales (London,
   England: Sweet & Maxwell, 2018) (“Class Actions in England and Wales”),
   p. 386.
2.  Class Actions in England and Wales, p. 402.
3.  By contrast, 2020 alone saw plaintiffs file 333 new securities class actions across federal and state courts in the US. See Securities Class Action Filings—2021 Year in Review, Cornerstone Research, February 2021, p. 1, https://www.cornerstone.com/wp-content/uploads/2022/02/SecuritiesClass-Action-Filings-2021-Year-in-Review.pdf.
4.  Among other things, the increase in third-party litigation funding and availability of “after the event” insurance suggest the potential for an increase in shareholder actions in the UK. See, e.g., “Securities Litigation Gathers Momentum in the UK,” In-House Lawyer, Autumn 2019, https://www.inhouselawyer.co.uk/legal-briefing/securities-litigationgathers-momentum-in-the-uk/. See also “New Class Action Platform Launches to Boost UK Market,” Law360, 14 July 2022, https://www.law360.com/articles/1511500/new-class-action-platformlaunches-to-boost-uk-market, which discusses the recent launch of “[a] new platform designed to connect lawyers with individuals to pursue group litigation . . . in a bid to inject new life into the group litigation sector in the U.K.”; “Guest Post: An Investor Roadmap: The Jurisdictional Differences and Impact of ESG in European Shareholder Class Actions,” D&O Diary, 18 July 2022, https://www.dandodiary.com/2022/07/articles/securitieslitigation/guest-post-an-investor-roadmap-the-jurisdictional-differencesand-impact-of-esg-in-european-shareholder-class-actions/, which, while focused on ESG issues, suggests implications for shareholder actions more generally: “While class actions in Europe may appear to in be in their infancy, especially in comparison to the United States, there have been many interesting developments in case law and legislation across Europe that will hopefully make it easier for investors to hold companies to account for failures to meet ESG-related standards. Investors are increasingly finding innovative ways to bring such claims and the courts and legislatures across Europe appear willing to find solutions to ease the burden and costs traditionally associated with these actions, making them more accessible to investors.”
5.  Unless otherwise specified, any discussion of damages in the context of US securities litigation in this article refers to damages under Section 10(b) of the Securities Exchange Act of 1934 and SEC Rule 10b-5 promulgated thereunder.
6.  This article will concentrate on the economic issues that are likely to arise in Section 90A cases, although in practice, many of these issues are also likely to be relevant to Section 90 matters.
7. Aswath Damodaran, “Approaches to Valuation,” in Investment Valuation: Tools and Techniques for Determining the Value of Any Asset, 3rd ed. (Hoboken, NJ: John Wiley & Sons, 2012), pp. 11–26.
8. It is important to note that not all information about a company is necessarily value-relevant. For example, while news that a customer cancelled an important long-term contract with a company may cause investors to revise downward their expectations regarding the company’s future cash flows, and is therefore value-relevant, an announcement that the company was changing its name might not cause investors to change their expectations regarding these future cash flows.
9.  Eugene F. Fama, “Random Walks in Stock Market Prices,” Financial Analysts Journal 21, no. 5 (1965): 55–59.
10. Eugene F. Fama, “Efficient Capital Markets: A Review of Theory and Empirical Work,” Journal of Finance 25, no. 2, (1970): 383–417 at 383.
11. Stephen A. Ross et al., Corporate Finance, 11th ed. (New York, NY: McGraw-Hill/Irwin, 2015), p. 462 (emphasis added). Depending on the set of information considered, there are two other forms of the efficient markets hypothesis: weak form (“the market uses the history of share prices and is therefore efficient with respect to these past prices”) and strong form (“the market uses all of the information that anybody knows about the company, even inside information.”).
12. The discussion of event study analysis in this article refers to price movements for common shares, but the concepts apply more broadly to other securities as well, such as bonds or preferred shares.
13. See, e.g., Eugene F. Fama et al., “The Adjustment of Stock Prices to New Information,” International Economic Review 10, no. 1 (1969): 1–21; Stephen J. Brown and Jerold B. Warner, “Measuring Security Price Performance,” Journal of Financial Economics 8 (1980): 205–258; Stephen J. Brown and Jerold B. Warner, “Using Daily Stock Returns: The Case of Event Studies,” Journal of Financial Economics 14 (1985): 3–31; Eugene F. Fama and Kenneth R. French, “Common Risk Factors in the Returns on Stocks and Bonds,” Journal of Financial Economics 33, no. 1 (1993): 3–56.
14. See, e.g., A. Craig MacKinlay, “Event Studies in Economics and Finance,” Journal of Economic Literature 35, no. 1 (1997): 13–39, which provides numerous examples of event studies and their use in academic research. See also John J. Binder, “The Event Study Methodology Since 1969,” Review of Quantitative Finance and Accounting 11 (1998): 111–137; Katherine Schipper and Rex Thompson, “The Impact of Merger-Related Regulations on the Shareholders of Acquiring Firms,” Journal of Accounting Research 21 (1983): 184–221.
15. See, e.g., Mark L. Mitchell and Jeffry M. Netter, “The Role of Financial Economics in Securities Fraud Cases: Applications at the Securities and Exchange Commission,” Business Lawyer 49, no. 2 (1994): 545–590.
16. A starting point for intra-day analysis may be to chart the share price movements and associated trading volume on an intra-day basis. This data visualisation exercise can be supplemented with other techniques, such as intra-day regression analysis, as needed. Details of such analysis are beyond the scope of this article.
17. Even if the supply chain issues had been resolved, to the extent that the announcement led market participants to adjust their expectations of ABC’s future cash flows, that adjustment would be reflected in the company’s share price.
18. Securities analysts typically provide share recommendations, earnings forecasts, and reports on companies in a particular industry or market sector, and they are viewed as “important information intermediaries between firms and investors.” See Kee H. Chung and Hoje Jo, “The Impact of Security Analysts’ Monitoring and Marketing Functions on the Market Value of Firms,” Journal of Financial and Quantitative Analysis 31, no. 4 (1996): 493–512. See also Boris Groysberg and Linda-Eling Lee, “The Effect of Colleague Quality on Top Performance: The Case of Security Analysts,” Journal of Organizational Behavior 29, no. 8 (2008): 1123–1144.

About the Authors

Ronnie Barnes is a vice president in the London office of Cornerstone Research. He has testified in a number of cases involving corporate valuation, cost of capital, and financial derivatives. In addition to his work as an expert, Dr Barnes has led teams in a range of high-profile matters involving major financial institutions, including a European Union investigation into the market for complex financial instruments, a number of cases involving structured finance products, and US securities class actions. Dr Barnes has a Ph.D. and an M.Sc., both from London Business School, where he served on the faculty for over ten years. 

Kristin M. Feitzinger is a senior vice president in the Silicon Valley office of Cornerstone Research. She has more than two decades of experience addressing securities, valuation and governance issues arising in class, corporate and regulatory actions, and is a frequent speaker on these topics. Ms Feitzinger particularly focuses on Rule 10b-5 and Section 11 disclosure cases involving equity and debt trades, and has consulted on more than a hundred such cases, including some of the largest class actions in recent history. Her experience spans all stages of the litigation process, including pre-litigation investigations; exposure analysis and settlement estimation; class and expert discovery; and mediation, arbitration, trials and regulatory agency proceedings. 

Greg Leonard is a senior vice president in the London office of Cornerstone Research and heads the firm’s finance practice and its European finance practice. Dr Leonard has nearly two decades of experience consulting for clients in complex litigation and regulatory proceedings. On behalf of clients, he has led regulatory investigations on both sides of the Atlantic, managing teams and simultaneously supporting experts across multiple related matters. Dr Leonard has substantial experience directing analyses of large and complex high-frequency financial data sets, from both private entities and trading exchanges. 

Shaama Pandya is a vice president in the Washington D.C. office of Cornerstone Research. She leads teams in complex litigation and regulatory investigations related to securities, consumer finance, and valuation. In matters involving equity, debt and derivative securities issued by public companies, Ms Pandya has analysed issues of market efficiency and price impact, materiality, loss causation, inflation and damages across a range of industries. Ms Pandya has worked on matters in a variety of venues, including US federal and state courts, the Delaware Court of Chancery, and international jurisdictions, notably in Latin America and Europe.  

The views expressed herein are solely those of the authors, who are responsible for the content, and do not necessarily represent the views of Cornerstone Research.