Optimal Economic Capital Allocation in Banking on the Basis of Decision Rights
BOOK
Cite BOOK
Style
Müller, J. (2015). Optimal Economic Capital Allocation in Banking on the Basis of Decision Rights. Verlag Wissenschaft & Praxis. https://doi.org/10.3790/978-3-89644-707-4
Müller, Jan. Optimal Economic Capital Allocation in Banking on the Basis of Decision Rights. Verlag Wissenschaft & Praxis, 2015. Book. https://doi.org/10.3790/978-3-89644-707-4
Müller, J (2015): Optimal Economic Capital Allocation in Banking on the Basis of Decision Rights, Verlag Wissenschaft & Praxis, [online] https://doi.org/10.3790/978-3-89644-707-4
Format
Optimal Economic Capital Allocation in Banking on the Basis of Decision Rights
Studienreihe der Stiftung Kreditwirtschaft an der Universität Hohenheim, Vol. 52
(2015)
Additional Information
Book Details
Pricing
Abstract
As a regulatory consequence banks today have to provide more equity for the same risk exposure than before the financial crisis. This significantly increases the banks’ need for a strict risk-return driven management. However, the mere neoclassical risk management view appears inadequate in the case of overall bank management.Consistently applying portfolio optimization on an overall bank level requires the consideration of the decision makers’ behavior where portfolios cannot be assumed fix any longer. The current model shows this using a value at risk limit system strictly understanding limits as addressees’ decision rights.Despite the resulting unstable correlations the model shows the overall bank management in the form of a global optimization being the superior approach. The model clearly demonstrates the costliness for banks dispensing with sophisticated limit setting.
Table of Contents
| Section Title | Page | Action | Price |
|---|---|---|---|
| FOREWORD | 5 | ||
| CONTENTS | 7 | ||
| FIGURES | 11 | ||
| TABLES | 15 | ||
| ALGORITHMS | 17 | ||
| 1 INTRODUCTION | 19 | ||
| 1.1 Problem and research question | 19 | ||
| 1.2 Organization of the research | 21 | ||
| 2 CORPORATE MANAGEMENT BYECONOMIC CAPITALALLOCATION | 25 | ||
| 2.1 Properties of economic capital | 25 | ||
| 2.2 Required economic capital by downside riskmeasurement | 26 | ||
| 2.3 Corporate management by bank-wide VARlimit systems | 28 | ||
| 2.4 Economic capital allocation on the basis of riskadjusted performance measurement | 31 | ||
| 2.4.1 Introduction to risk adjusted Performance measures | 31 | ||
| 2.4.2 Controversial benchmarking on the basis of hurdle rates | 32 | ||
| 2.4.3 Implications of limit addressees in the form of decision makers | 33 | ||
| 2.5 Economic capital allocation as a situation ofdelegation by decision rights | 34 | ||
| 2.5.1 Implications for the risk management process | 34 | ||
| 2.5.2 Costs of delegation by decision rights | 36 | ||
| 3 IMPLICATIONS OF RELATEDFIELDS OF RESEARCH | 41 | ||
| 3.1 Different situations of economic capitalallocation | 41 | ||
| 3.2 Risk contribution – a form of economic capitalallocation | 42 | ||
| 3.2.1 Risk contribution schemes | 42 | ||
| 3.2.2 Particular approaches from the field of risk contribution | 44 | ||
| 3.3 Axiomatization of economic capital allocation | 46 | ||
| 3.3.1 Axiomatization of risk measures | 46 | ||
| 3.3.2 Transfer of the axiomatization framework to economic capitalallocation | 48 | ||
| 3.4 Risk assessment over time by dynamic riskmeasures | 50 | ||
| 3.5 Economic capital allocation as a means ofcorporate management | 53 | ||
| 3.6 Portfolio optimization under a downside riskconstraint | 60 | ||
| 3.6.1 Approaches on the basis of traditional methods of optimization | 60 | ||
| 3.6.2 Heuristic methods of optimization | 62 | ||
| 3.6.2.1 Categorization of the field of heuristic optimization | 62 | ||
| 3.6.2.2 Approaches on the basis of heuristic optimization methods | 64 | ||
| 4 BASIC MODEL OF OPTIMALECONOMIC CAPITALALLOCATION | 69 | ||
| 4.1 Qualitative description of the model | 69 | ||
| 4.2 Determination of the underlying stochasticprogram | 71 | ||
| 4.3 Valuation of the objective function on the basisof a trading simulation | 74 | ||
| 4.3.1 Simulation of the stocks’ returns | 74 | ||
| 4.3.2 Simulation of the business units’ profits and losses | 76 | ||
| 4.3.3 Simulation of the heterogeneous prospects of success of the businessunits | 78 | ||
| 4.4 Out-of-sample backtesting and the role ofimportance sampling | 80 | ||
| 5 HEURISTIC OPTIMIZATION OFRISK LIMIT SYSTEMS BYTHRESHOLD ACCEPTING | 83 | ||
| 5.1 Visual proof of non-convexity by an exemplarymodel case | 83 | ||
| 5.2 Basic algorithm of threshold accepting | 87 | ||
| 5.3 Determination of start solutions | 89 | ||
| 5.4 Neighborhood function | 94 | ||
| 5.4.1 Basic design of the neighborhood function | 94 | ||
| 5.4.2 Generation of the transfer value | 96 | ||
| 5.4.3 Monitoring of the constraints’ satisfaction | 99 | ||
| 5.5 Generation of the threshold sequence | 101 | ||
| 5.6 Parallelization of threshold accepting | 104 | ||
| 6 PARAMETERIZATION OFTHRESHOLD ACCEPTING | 107 | ||
| 6.1 Concept of successive parameterization incontext with the present model | 107 | ||
| 6.2 Effective combinations of thresholds andtransfer values | 108 | ||
| 6.2.1 Simple parameterization by visual analysis | 108 | ||
| 6.2.2 Comprehensive analysis on the basis of detailed grid structures | 112 | ||
| 6.2.3 Excursus on the impact of the transfer value generation on theparameterization | 115 | ||
| 6.3 Effective combinations of restarts and steps | 119 | ||
| 6.3.1 Appropriate coverage of the solution space | 119 | ||
| 6.3.2 Particular aspects of parallel computing | 121 | ||
| 6.4 Concluding remarks on the parameterizationfor different model cases | 123 | ||
| 7 SUPERIORITY OF OPTIMALECONOMIC CAPITALALLOCATION – THE INFORMEDCENTRAL PLANNER | 125 | ||
| 7.1 Introduction to the benchmarking of allocationmethods in case of an informed central planner | 125 | ||
| 7.2 Benchmarking of allocation methods in case ofan informed central planner | 127 | ||
| 7.2.1 Allocation methods’ performances before the background of anarbitrary model bank | 127 | ||
| 7.2.2 Precise benchmarking on the basis of particular model settings | 132 | ||
| 7.2.2.1 Implementation of a level playing field | 132 | ||
| 7.2.2.2 Impact of restrictions through minimum limits | 135 | ||
| 7.2.2.3 Relevance of optimal allocation in case ofless privately informed traders | 138 | ||
| 7.2.2.4 Influence of higher degrees of diversification in the form of highernumbers of business units | 141 | ||
| 7.3 Discussion of the superiority of optimaleconomic capital allocation | 143 | ||
| 8 UNINFORMED CENTRALPLANNER – INFORMATION ONTHE BASIS OF BAYESIANLEARNING | 147 | ||
| 8.1 Introduction to the case of an uninformedcentral planner | 147 | ||
| 8.2 Description of the Bayesian learning algorithm | 148 | ||
| 8.3 Bayesian learning central planner in case ofindependently acting decision makers | 153 | ||
| 8.3.1 Benchmarking of allocation methods using perfect priorprobabilities | 153 | ||
| 8.3.2 Benchmarking under adjusted prior probabilities for the anticipationof risk underestimation | 160 | ||
| 8.4 Influence of herding decision makers on optimaleconomic capital allocation | 168 | ||
| 8.4.1 Herding and informational cascades in case of economic capitalallocation | 168 | ||
| 8.4.2 Modeling of herding tendencies among the decision makers | 170 | ||
| 8.4.3 Benchmarking of allocation methods under herding decision makers | 176 | ||
| 8.5 Conclusions on optimal allocation before thebackground of an uninformed central planner | 187 | ||
| 9 CONCLUSIONS | 191 | ||
| 9.1 Summary of results | 191 | ||
| 9.2 Closing remarks on the model assumptions andsuggested future research | 194 | ||
| APPENDIX | 197 | ||
| REFERENCES | 207 | ||
| Studienreihe der Stiftung Kreditwirtschaftan der Universität Hohenheim | 214 |