Abstract
This chapter focuses on the event study assumptions. We should carefully consider these at the start and mainly when writing up the study. While the author also addressed the assumptions in other chapters, it is helpful to identify several key assumptions early on to ensure that they are fully understood and built into the design. He discusses the primary assumption of stock market efficiency, unanticipated nature of events, independence, and how this is relevant. Examples are provided of some of the key points. Finally, he introduces several measures that can consider these assumptions and discuss how the study design can be adjusted if we violate the assumptions.
TopTheory
It is not enough to observe and describe what has happened. While the operations and supply chain management disciplines have a rich history, there has been a historical focus on practice and outcomes-driven research. Increasingly, however, there have been calls for building and developing theory. This is important as it allows us to tackle, with success, larger and more significant problems;
Nowhere is the outcome of this research-versus-practice debate more important than in the supply chain realm. Logistics research has its roots firmly planted in rubber meets-the-road practicality. Yet, today’s supply chain challenges such as collaboration, global network design, sustainability, and value creation reach strategic heights where organizational competitiveness and societal well-being are greatly influenced. (Fawcett et al., 2014, p. 1)
Roth (2007) suggests that theory is a fundamental component of effective research and developing knowledge. It helps us create hypotheses that explain or rationale for what is going on in the world around us. From these, managers and other researchers can make predictions and provide prescriptions for what ‘should’ be done in practice to achieve desired outcomes. These outcomes can be refined, modified, and verified to provide additional insight drawn from subsequent observations and descriptions of what happens as a consequence. From this, the theory-building cycle continues.
Therefore, connected to this is the assumption that theory is vital in the design and development of the event study process. While there is a historic, underlying focus on practice outcomes and empirical observation in operations management research, other areas in management have more broadly welcomed theory for years. Consequently, when conducting an event study, the theory-driven study should provide more assurance to the researchers that they will identify a result of interest and capture an estimate of the importance or magnitude of the event of interest. For example, Duan et al. (2009) draw on the theory of production economics (TPE), transaction cost economics (TCE), and the resource-based view (RBV) while Riley et al. (2017) draw on human capital theory.
Key Terms in this Chapter
Jensen’s Alpha: Also known as Jensen’s Performance Index is used to evaluate the abnormal return over the theoretical expected return and is useful when there is calendar clustering.
Efficient Market Hypothesis: The primary and long-standing assumption that the markets are efficient and instantly incorporate all new news into the stock prices.
Unanticipated Event: An event that the market participants (e.g., investors) do not anticipate. The information about the event, therefore, represents a new release of information that the participants respond to instantaneously.
Risk Aversion: The likelihood that investors and market participants will elect to preserve their capital rather than invest in a stock with a volatile or uncertain future outcome, such as driven by large legal challenges that extend over many years.
Short-Horizon Event Study: A study that uses changes in abnormal returns over a horizon of days rather than months or years. The change reflects an unbiased market participant estimation of the event and the consequences for the company over time, reflected in the current prices.
Long-Horizon Event Study: A study over a longer horizon that will be months, quarters, or years. It follows the changes and, with a long-horizon study of stock returns, can capture actual returns from a buy-and-hold investment strategy and provide more confirmation.