Risk measures and the risk-return paradox: an analysis in the context of the economic crisis.
| Autor | Munoz, Rosa Maria |
1 Introduction
The first indications of the global crisis appeared in August 2007, when there were problems in the interbank lending market and the subprime mortgage market began to implode. It continued with a slowdown in the U.S. economy and the sale of Bear Stearns in March 2008, after which several economic disasters occurred, such as the bankruptcy of Lehman Brothers, the sale of Merrill Lynch, and the collapse of AIG, Fannie Mae, and Freddie Mac in September 2008 (Heracleous & Werres, 2016). Governments and businesses have subsequently been struggling to return to normal. Europe had similar banking problems. The "great financial rescue" of banks by governments in 2008 stopped further collapse, but the age of austerity still continues, with significant effects for nations, companies, families, and individuals (Starkey, 2015). One of the questions researchers and economists attempt to answer when crises occur is whether it is possible to predict them (Lukason, Laitinen, & Suvas, 2016) and risk is an important variable in this respect. In this research, we present various risk measures and analyze their prediction capacity by considering the global crisis of 2008. After reviewing the main theories, we adopt an integrative risk perspective and formulate the following hypothesis:
[H.sub.1]--Variability measures of risk have a greater predictive power than that of downside risk measures.
As a complement, we also develop another line of research in relation to the well-known riskreturn paradox, i.e., we analyze the relationship between risk and return. This issue has already been studied from different points of view and with different results. We employ the perspective that considers that the risk-return paradox appears to be dependent upon the time period to formulate the following hypothesis:
[H.sub.2]--The risk-return paradox was more likely to exist in the more uncertain environment of the period of time just before the beginning of the 2008 economic crisis.
In order to test the first hypothesis, we created two groups of companies, the first of which was formed of those companies that were able to survive the crisis in question, while the second was composed of those that did not. We then generated the selected risk measures using data from the period just before the crisis and subsequently verified whether their predictions eventually proved to be correct. This objective was attained through the development of a logistic regression, while the second hypothesis was tested by examining Bowman's paradox using multiple linear regression.
The research results support the two hypotheses formulated:
1) variability measures of risk have a greater predictive power than that of downside risk measures;
2) the risk-return paradox is more likely to exist in the more uncertain environment of a pre-crisis period of time.
The results obtained from our research therefore support the integrative risk perspective, which suggests that managers should consider all important aspects to which a company is exposed, and not only the downside risk or below-target performance. Moreover, the riskreturn paradox appears to be dependent upon the time period: it would appear to be more likely in more uncertain environments, such as at the beginning of a global crisis.
The study is organized as follows. First, we present the risk variable and the different ways in which it can be measured, after which we analyze the relationship between risk and return, highlighting previous management research and its different contributions regarding the issue. We go on to explain the sample and the methodology, and then present the main results. The final section provides our conclusions.
2 Risk
Risk has become an important variable in many areas of strategy research. It has been included in research on business strategy and the characteristics of industry (Andersen, Denrell, & Bettis, 2007; e.g., Cool, Dierickx, & Jemison, 1989; Oviatt & Bauerschmidt, 1991; Woo, 1987), corporate diversification (Amit & Livnat, 1988; Belderbos, Tong, & Wu, 2014; Bettis & Mahajan, 1985; Kim, Hwang, & Burgers, 1993), and organizational processes and structures (Hoskisson, 1987; Jemison, 1987). In some cases, risk is used to describe managerial choices associated with uncertain outcomes (managerial risk taking). In others, risk is a characteristic of organizations experiencing volatile income streams (organizational risk) (Palmer & Wiseman, 1999).
Historically, firms have managed different kinds of risk separately. Bannister and Bawcutt (1981) proposed that risk management requires multiple disciplines working together to manage future uncertainty, which requires the alignment of risk management with corporate governance and strategy. In this respect, Andersen (2008) considers three risk perspectives: 1) conventional risk management practices, which have typically focused on the containment of economic risks and environmental hazards, where exposures can be covered in derivative and insurance markets; 2) the enterprise risk management approaches, which also consider operational risks within an integrative framework often implemented in conjunction with internal auditing and control systems; 3) the total risk management perspective, which considers all risk categories from a more holistic perspective, including strategic risks in which the pursuit of upside potential is as important as counteracting downside losses. Bromiley, McShane, Nair, and Rustambekov (2015) claim that enterprise risk management incorporates not only traditional risks, such as product liability and accidents, but also strategic risks, such as product obsolescence or competitor actions. That is, a systematic and integrated approach to managing the total number of risks that a company confronts is taking on importance in the research community. An integrative risk management perspective suggests that all a firm's important exposures should be considered. This is difficult to achieve in practice, and the reality is that conventional risk management is usually associated with corporate finance departments and often fails to incorporate marketing, strategy, product development, etc. into its risk assessments. In this respect, many regulators, executives, and academics have advocated Enterprise Risk Management, which can be defined as "the idea that emerged in the late 1990s that a firm should identify and (when possible) measure all of its risk exposures, including operational and competitive risks, and manage them within a single unified framework in contrast to the silo approach to risk management" (Harrington, Niehaus, & Risko, 2002).
Recent history raises doubts about the effectiveness of risk management as previously practiced. In the economic downturn caused by the crisis in 2008, the most sophisticated practitioners of risk management (e.g., the Wall Street banks) suffered most heavily, causing tremendous damage to international economies (Bromiley et al., 2015). However, recent studies show that Enterprise Risk Management has a positive effect on a firm's value in the context of an emerging economy (Anton, 2018).
In this paper we deal with this claim by considering the 2008 crisis as the reference point in order to verify the prediction capacity of some of the most common risk measures.
2.1 Risk measures
Previous studies have employed a variety of risk measures derived from stock return data and accounting in an attempt to capture the variability of firms' performances. The most common measures are the variance of return on assets (ROA) and return on equity (ROE), and systematic (i.e., beta) and unsystematic risk derived from historical stock returns. Three considerations have led many researchers to evaluate total risk rather than systematic risk (Cool & Schendel, 1988): (1) the empirical difficulty involved in estimating the beta at the business level in the absence of financial market data; (2) the fact that the beta is, both empirically and theoretically, related to total risk; and (3) management is responsible for a wider group of stakeholders than just shareholders, thus making total risk a prominent concern. The measurement of risk in terms of standard deviation has, therefore, been employed rather than the beta in many studies.
Despite the widespread use of variability measures, behavioral decision theory suggests that this approach may not reflect managers' and investors' conceptualizations of risk. Criticisms can also be found in the strategic management and finance literature. Authors in these fields propose that investors and managers are averse to downside risk, i.e., below-target performance. Miller and Reuer (1996) introduce three categories for downside risk measures that include measures based on historical performance, a downside version of the capital asset pricing model (CAPM), and stock analysts' earnings forecasts. After considering the sample characteristics, that is, firms that do not operate in the stock market, we judged the first to be the most appropriate and therefore chose and modeled it using lower partial moments (LPM), as suggested by Fishburn (1977). LPM refers to the inclusion of only the left-hand (downside) tail of the returns distribution in the calculation.
Using...
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