SelectedWorks @ Melbourne Business School (The University of Melbourne)
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Dynamic Asset Price Jumps and the Performance of High Frequency Tests and Measures
No full textThis paper provides an extensive evaluation of high frequency jump tests and measures, in the context of dynamic models for asset price jumps. Specifically, we investigate: i) the power of alternative tests to detect individual price jumps, including in the presence of volatility jumps; ii) the frequency with which sequences of dynamic jumps are identified; iii) the accuracy with which the magnitude and sign of sequential jumps are estimated; and iv) the robustness of inference about dynamic jumps to test and measure design. Substantial differences are discerned in the performance of alternative methods in certain dimensions, with inference being sensitive to these differences in some cases. Accounting for measurement error when using measures constructed from high frequency data to conduct inference on dynamic jump models would appear to be advisable
Time Series Copulas for Heteroskedastic Data
No full textWe propose parametric copulas that capture serial dependence in stationary heteroskedastic time series. We develop our copula for rst order Markov series, and extend it to higher orders and multivariate series. We derive the copula of a volatility proxy, based on which we propose new measures of volatility dependence, including co-movement and spillover in multivariate series. In general, these depend upon the marginal distributions of the series. Using exchange rate returns, we show that the resulting copula models can capture their marginal distributions more accurately than univariate and multivariate GARCH models, and produce more accurate value at risk forecasts
Don’t know, don’t care: An exploration of evidence based knowledge and practice in human resource management
No full textOver the past two decades the integrity (alignment of words and deeds) of the Human Resource Management (HRM) profession has been questioned by scholars who have identified a gap between the rhetoric of ‘people are our most important asset’ and the reality of ‘impersonal economic rationalism’. In a more recent, and as yet unconnected, stream of research there has been concern about a research-practice gap in HRM. This article draws on both streams of research to explain why HRM Does not implement evidence based practice. It focuses on research indicating that HRM practitioners are not incentivized to learn about evidence based practice and develops theory proposing that their satisfaction with the status quo reflects a value proposition based on utilitarian instrumentalism. Further to this, it is proposed that management’s focus on the short-term drives and obfuscates current approaches. It concludes that neither academia nor HRM practitioners are incentivized to change current practice with negative consequences for employees, organizations, and HRM practitioners. Arguments are supported and illustrated with High Performance Work Practices and solutions are proposed to implement evidence based practice
THE TWO SIDES OF CEO PAY INJUSTICE: A POWER LAW CONCEPTUALIZATION OF CEO OVER AND UNDERPAYMENT
No full textPurpose - The goal of our study was to examine the extent to which CEOs deserve the pay they receive both in terms of over as well as underpayment.Design/methodology/approach – Rather than using the traditional normal distribution view in which CEO performance clusters around the mean with relatively little variance, we adopt a novel power law approach. We studied 22 industries and N = 4,158 CEO-firm combinations for analyses based on Tobin’s Q and N = 5,091 for analyses based on return on assets. Regarding compensation, we measured the CEO distribution based on total compensation and three components of CEO total pay: salary, bonus, and value of options exercised.Findings - 86% of CEO performance and 91% of CEO pay distributions fit a power law better than a normal distribution, indicating that a minority of CEOs are producing top value for their firms (i.e., CEO performance) and a minority of CEOs are appropriating top value for themselves (i.e., CEO pay). But, we also found little overlap between CEOs who are the top performers and CEOs who are the top earners.Implications - Our findings shed new light on CEO pay deservingness by using a novel conceptual and methodological lens that highlights systematic over and underpayment. Results suggest a violation of distributive justice and offer little support for agency theory’s efficient contracting hypothesis, which have important implications for agency theory, equity theory, justice theory, and agent risk sharing and agent risk bearing theories
Market Mediators and the Tradeoffs of Legitimacy-Seeking Behaviors in a Nascent Category
No full textAlthough existing research has demonstrated the importance of attaining legitimacy for new market categories, few scholars have considered the tradeoffs associated with such actions. Using the U.S. organic food product category as a context, we explore how one standards-based certification organization—the California Certified Organic Farmers (CCOF)—sought to balance efforts to legitimate a nascent market category with retaining a shared, distinctive identity among its members. Our findings suggest that legitimacy-seeking behaviors undertaken by the standards organization diluted the initial collective identity and founding ethos of its membership. However, by shifting the meaning of organic from the producer to the product, CCOF was able to strengthen the categorical boundary, thereby enhancing its legitimacy. By showing how the organization managed the associated tradeoffs, this study highlights the double-edged nature of legitimacy and offers important implications for the literatures on legitimacy and new market category formation
A weight-relaxed model averaging approach for high-dimensional generalized linear models
No full textCharacter Cues and Contracting Costs: The Relationship Between Philanthropy and the Cost of Capital
No full textPrior studies in business ethics highlight the role of philanthropy in shaping stakeholders’ perceptions of a firm’s underlying moral tendencies and values (“character”). Scholars argue that philanthropy-based character inferences influence whether and how stakeholders engage with firms. We extend this line of reasoning to examine the impact of philanthropy on firms’ contracting costs in the capital market. We posit that philanthropy-based character inferences reduce investors’ agency concerns, thereby reducing firms’ cost of capital. We also posit that the strength of the philanthropy–cost of capital relationship is contingent on uncertainty regarding a firm’s character, visibility of a firm, and prevailing philanthropic norms. We test and find support for our arguments in a longitudinal study of philanthropy and the cost of capital. Our findings have implications for business ethics research on corporate philanthropy and corporate social performance and for organizational research on social judgment
The Effects of Within-Country Linguistic and Religious Diversity on Foreign Acquisitions
No full textThis paper explores how within-country diversity of both language and religion influences the ownership structure of foreign acquisitions. Commentators have acknowledged the potential importance of “within-country diversity”, but to date this issue has received minimal empirical attention. We propose that diversity plays two distinct roles. Namely, diversity within the host country may be an additional source of behavioral uncertainty and information asymmetry, over and above the effects arising from cross-national differences. Moreover, diversity within the home country may increase the cognitive complexity of the decision-makers, moderating the firm’s response to the distance and diversity of the host country. Results based on foreign acquisitions across 67 acquirer and 69 target countries confirm both of these roles. While the main focus of this paper is on the role that within-country diversity plays in international business decisions, it also makes contributions in terms of expanding the range of dimensions of distance investigated in the cross-border acquisition literature, in highlighting a potentially positive role that diversity might play in such acquisitions, and in providing a potential explanation for asymmetries in distance – i.e. differences in cognitive complexity
Auxiliary Likelihood-Based Approximate Bayesian Computation in State Space Models
No full textA new approach to inference in state space models is proposed, using approximate Bayesian computation (ABC). ABC avoids evaluation of an intractable likelihood by matching summary statistics computed from observed data with statistics computed from data simulated from the true process, based on parameter draws from the prior. Draws that produce a \u27match\u27 between observed and simulated summaries are retained, and used to estimate the inaccessible posterior; exact inference being feasible only if the statistics are sufficient. With no reduction to sufficiency being possible in the state space setting, we pursue summaries via the maximization ofan auxiliary likelihood function. We derive conditions under which this auxiliary likelihood-based approach achieves Bayesian consistency and show that - in a precise limiting sense - results yielded by the auxiliary maximum likelihood estimator are replicated by the auxiliary score. Particular attention is given to a structure inwhich the state variable is driven by a continuous time process, with exact inference typically infeasible in this case due to intractable transitions. Two models for continuous time stochastic volatility are used for illustration, with auxiliary likelihoods constructed by applying computationally efficient filtering methods to discrete timeapproximations. The extent to which the conditions for consistency are satisfied is demonstrated in both cases, and the accuracy of the proposed technique when applied to a square root volatility model also demonstrated numerically. In multiple parameter settings a separate treatment of each parameter, based on integrated likelihood techniques, is advocated as a way of avoiding the curse of dimensionality associated with ABC methods
Are Nonfinancial Metrics Good Leading Indicators of Future Financial Performance?
No full textIt’s become increasingly popular to use nonfinancial measures such as customer satisfaction in performance management frameworks and executive compensation schemes. But how well does that work