Active capital management: Optimising returns in a multiple stakeholder context
Abstract
Current approaches to economic capital management focus on the risk capital needed to maintain solvency and on portfolio management (eg hedging and diversification). These approaches ‘passively’ allocate capital to subportfolios subject to hurdle rates (eg risk-adjusted return on capital), implying that debt-holders provide a binding constraint on the institution's risk appetite based on the target credit rating and its assumed quantile. The emergence of ‘active’ value creation — that is, pursuing optimal asset returns while managing capital structure in relation to stakeholder risk appetite — moves from an implicit debt-holder orientation to one that combines the perspectives of all stakeholders within a multi-tiered capital structure. The analysis illustrates the potential application of scenario-based constrained optimisation techniques to jointly evaluate the risk-return preferences of multiple stakeholders. Assessing investment (asset allocation) and funding (capital structure) decisions simultaneously suggests that optimal portfolio choices change significantly when stakeholders' different risk perspectives are considered together. While optimisation techniques are used to formalise the decision-making process, the results apply to any decision rule — whether optimisation-based, analytical or heuristic. The implication is that management decisions that consider debt and equity-holder perspectives jointly are better aligned with equity-holders' preferences (while respecting debt-holder constraints) than decisions based solely on debt-holders' risk preferences.
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Author's Biography
Michael Zerbs is the President and Chief Operating Officer of Algorithmics. Since joining the firm in 1989, Michael has led both product and marketing initiatives for the company’s risk management solutions. Previously, he was Vice President of Research and Product Marketing at the firm, responsible for the strategic direction and conceptual development of Algorithmics’ solutions. He has authored several papers on pricing models and risk management and is a co-author of Mark-to-Future: A Framework for Measuring Risk and Reward. He holds several degrees, including a PhD in economics from Kepler University in Linz, Austria and an MBA with specialisation in finance from the University of Toronto.
Helmut Mausser is Mathematician–Technical Director at Algorithmics. His areas of expertise include optimisation and risk attribution. Helmut joined Algorithmics in 1997, after completing his PhD in operations research at the University of Colorado. He has also worked as a quantitative analyst in the telecommunications industry, an information systems analyst and, more recently, has lectured in the Master of Mathematical Finance programme at the University of Toronto. Helmut holds an undergraduate degree in mathematics and a master’s degree in management sciences, both from the University of Waterloo.
Martin Hansen is former Senior Manager for Risk Management Strategy at Algorithmics, with particular focus on credit risk and capital management. Previously he was a director in Fitch Ratings’ credit policy group, researching Basel II’s impact on credit markets and securitisation. Martin has also worked as a senior financial analyst at the Federal Reserve Bank of New York, where he was actively involved in the development of Basel II, serving on the Basel Committee Credit Risk Mitigation Sub-group. Martin earned an AB in politics, cum laude, from Princeton University and a master’s degree in international economics and finance from the Fletcher School, Tufts University.
Citation
Zerbs, Michael, Mausser, Helmut and Hansen, Martin (2008, June 1). Active capital management: Optimising returns in a multiple stakeholder context. In the Journal of Risk Management in Financial Institutions, Volume 1, Issue 3. https://doi.org/10.69554/FNVN9586.
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