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A large literature over several decades reveals both extensive concern with the question of time-varying betas and an emerging consensus that betas are in fact time-varying, leading to the prominence of the conditional CAPM. Set against that background, we assess the dynamics in realized betas, vis-à-vis the dynamics in the underlying realized market variance and individual equity covariances with the market. Working in the recently popularized framework of realized volatility, we are led to a framework of nonlinear fractional cointegration: although realized variances and covariances are very highly persistent and well approximated as fractionally integrated, realized betas, which are simple nonlinear functions of those realized variances and covariances, are less persistent and arguably best modeled as stationary I(0) processes. We conclude by drawing implications for asset pricing and portfolio management.

The world in which companies operate today is volatile, uncertain, complex, and ambiguous, thus subjecting contemporary forms to an array of risks that challenge their viability in an increasingly competitive landscape. Organizations that cling to their traditional ways of operating impede their ability to survive while those able to embrace evolving changes and lever their strategic response capabilities (SRCs) will thrive against the odds. The possession of such capabilities has become a prominent explanation for effective adaptation to the impending changes but is rarely analyzed and tested empirically. Strategic adaptation typically assumes innovation as an important component, but we know little about how the innovative processes interact with the firm’s SRCs. Hence, this study investigates these implied relationships to discern their effects on organizational performance and risk outcomes. It explores the effects of SRCs and the role of innovation as intertwined adaptive mechanisms supporting strategic renewal that can attain superior performance and risk effects. The relationships are analyzed based on a large sample of US manufacturing firms over the decade 2010–2019. The study reveals that firms possessing effective SRCs have the ability to exploit opportunities and deflect risky situations to gain favorable performance and risk outcomes. While innovation indeed plays a role, the precise nature and dynamic effect thereof remain inconclusive.

The author introduces a strategic responsiveness model that reflects an organization’s ability to sense environmental changes and learn from emergent adaptive responses that attempt to realign organizational activities and gain a better fit with the changing conditions. The author shows in computational simulations how superior strategic adaptation is associated with higher average returns and lower performance risk among firms that compete in the same industry contexts and generate negatively skewed outcome distributions consistent with empirical observations. The model is refined to incorporate an interactive strategy-making process, where experiential insights from decentralized initiatives update forward-looking projections in central planning. The ensuing analysis demonstrates how this adaptive strategy-making approach further enhances the favorable risk-return outcomes. The author discusses these findings and the implications for the study of dynamic adaptive strategy-making processes.

The global business context is turbulent and becoming a dynamic complex system where small events can trigger large outcomes that are difficult to predict. This gives urgency to the search for responsive global organizations that are able to adapt the multinational corporate strategy so it provides a better fit with the changing demands of the environment. An important key to this challenge is to activate the responsive potential of the many individuals in the multinational corporation and use them to inform strategic decisions and gain updated insights from the field and instill an organizational culture with supportive structures that will release the entrepreneurial human potential throughout the global organization. The eight chapters presented in this book provide useful insights to fuel these considerations.

This chapter outlines the major analytical efforts performed as part of the overarching research project with the aim to investigate the organizational and environmental circumstances around the extreme negatively skewed performance outcomes regularly observed across firms. It presents the collection and treatment of comprehensive European and North American datasets where subsequent analyses reproduce the contours of performance distributions observed in prior empirical studies. Key theoretical perspectives engaged in prior studies of performance data and the implied risk-return relationships are presented and these point to emerging commonalities between empirical findings in the management and finance fields. The results from extended analyses of more fine-grained data from North American manufacturing firms uncover the subtle effects of leadership and structural features, and computational simulations demonstrate how the implied adaptive processes can lead to the empirically observed performance distributions. Finally, the findings from the analytical project activities are set in context and the implications of the observed results are discussed to reach at a final conclusion.

The global environments that surround contemporary business activities are uncertain, fast-changing, and frequently exposed to abrupt unexpected events with the potential to inflict extreme impacts where the ability to respond and adapt the organization effectively becomes a primary strategic concern. However, various firms that operate across diverse industry contexts approach this adaptive challenge in distinct ways that lead to quite diverse outcomes with many negative performers and some high performers with positive risk features. The heterogeneous approaches appear to consistently form extreme left-tailed performance distributions with inverse risk-return features but we are not really able to explain why and how these regularly observed phenomena come about. Hence, we want to study these organizational artifacts by collecting an extensive updated dataset to test the proposed relationships, explore alternative explanations, and learn from the extreme exemplars often referred to as outliers. There are extensive literatures in (strategic) management and finance that have dealt with the distribution of firm returns from slightly different angles but with some emerging commonalities that can inspire further analyses of the performance data. As a precursor for this, we discuss the odds of effective strategic adaptation in complex dynamic environments and introduce resilience as a proper outcome when simple solutions are scarce, and consider conditions that may facilitate these aims. The premises for the ensuing analyses are laid out and the main contents of the following chapters are presented.

This chapter explores other theoretical explanations to the commonly observed phenomenon of negatively skewed performance outcomes and inverse risk-return relationships in empirical firm data. The analysis conducted in many prior studies have implicated direct causal dependencies between performance and risk, or vice versa, with the possibility of simultaneous two-way relationships that are harder to discern. It is also shown how spurious artifacts deriving from the arithmetic links between mean and variance associate left-skewed distributions with negative mean variance correlations. However, the heterogeneous display of response capabilities among firms that compete in the same industry contexts may provide an alternative explanation for the observed performance characteristics. This is expressed as strategic responsiveness where performance outcomes with high negative skewness and excess kurtosis derive from heterogeneous adaptive processes among firms as they respond to a dynamic environment with different degrees of success. We test these results in different simulated competitive contexts disrupted by major unexpected events and find robust results across different environmental scenarios. The analysis looks at two different response processes, one modeled as conventional adaptive planning following an annual budget cycle, and another modeled as interactive updating where executives have frequent informative budget discussions with operating managers in the firm. The computational simulations show that interactive updating generates outcomes with higher returns and lower performance risk for moderate learning levels and restructuring costs. However, the resulting performance distributions are not as left-skewed as those observed in the empirical data that show higher resemblance to the adaptive planning outcomes.

This first chapter argues that turbulent environments require adaptive strategy for survival and continued prosperity and thereby introduces the attempts to determine effective response capabilities in contemporary firms, which are presented in the ensuing chapters. The background in prior strategy research is outlined to position the various contributions within a proper backdrop as potential extensions to prior insights generated in the strategic management field. It suggests a need for multiple methodological approaches to gain new diverse and relevant knowledge from rich qualitative field studies as well as quantitative data probes and computational analyses. Finally, the ensuing chapters are briefly presented to provide a coherent view of the contributions made by this specific collection of chapters that the authors hope will inspire and fuel ongoing work in this important area.