Selected Works William T Ziemba Memorihb: Selected Works of William T Ziemba: a Memorial Volume

This book is a selection of the journal publications of William T Ziemba. Over a span of 50 years, Professor Ziemba contributed to a wide variety of disciplines including Stochastic Programming, Portfolio Theory, Sports Betting, and Risk Management. In his work he collaborated with academics and practitioners worldwide. Bill wrote for a variety of audiences. He was widely known as a leading practitioner of operations research methods applied to problems in financial planning and sports betting. Prior to his death, Bill Ziemba was working on a multivolume series on his collected papers. The Selected Works of William T Ziemba: A Memorial Volume captures some of the sentiment of Professor Ziemba's plans. Contents Preface Reflections on a Life of a Renaissance Academic Testimonials About the Editors Acknowledgments Introduction Chapter 1 An Overview of the Research of William T. Ziemba 1 Academic Profile — William T. Ziemba, PhD 2 Stochastic Programming SP Publications (Selected Papers in Bold) 3 Finance and Economics F&E Publications (Selected Papers in Bold) 4 Asset and Liability Management ALM Publications (Selected Papers in Bold) 5 Kelly Optimal Growth Kelly Publications (Selected Papers in Bold) 6 Sports Betting and Analytics Sports Publications (Selected Papers in Bold) 7 Market Anomalies and Crashes Anomalies and Crashes Publications (Selected Papers in Bold) 8 Conclusion Section I Stochastic Programming Chapter 2 Solving Nonlinear Programming Problems with Stochastic Objective Functions I. Introduction II. Basic Algorithmic Modifications III. Related Simple Recourse Problems IV. Solution Method via SUMT V. Example: Portfolio Selection VI. Solution Method of the Portfolio Problem via Generalized Programming VII. Some Remarks REFERENCES Chapter 3 Bounds on the Expectation of a Convex Function of a Random Variable: With Applications to Stochastic Programming 1. JENSEN'S LOWER BOUND AND ITS GENERALIZATION 2. THE EDMUNDSON-MADANSKY UPPER BOUND AND ITS GENERALIZATION 3. GENERALIZATIONS AND DISCUSSION 4. APPLICATIONS ACKNOWLEDGMENTS REFERENCES Chapter 4 Bounds for Two-Stage Stochastic Programs with Fixed Recourse 1. Introduction 1.1. Bounds using moment problems 2. Bounds for the expectation of the recourse function 2.1. Tight bounds using first and cross moments 2.2. Convexity of the bounds 2.3. Relation to generalized moment problems 3. First moment bounds—dependent case 4. Application to stochastic programming 5. Concluding remarks Acknowledgements References Section II Finance and Economics Chapter 5 Portfolio Selection in a Lognormal Market When the Investor has a Power Utility Function I. Introduction and Summary II. The Portfolio and Surrogate Problems III. Comparing S with Quadratic Approximations IV. Solving the Surrogate Problem REFERENCES Chapter 6 Comparison of Alternative Utility Functions in Portfolio Selection Problems 1. Introduction 2. The Portfolio Problem 3. Rubinstein's Risk Aversion Measure and Characterization of Optimal Portfolios 4. Empirical Results Appendix: Optimality of Rubinstein's Risk Aversion Measure References Chapter 7 The Effect of Errors in Means, Variances, and Covariances on Optimal Portfolio Choice THEORY DATA AND METHODOLOGY RESULTS IMPLICATIONS AND CONCLUSIONS ENDNOTES REFERENCES Chapter 8 A Dynamic Investment Model with Control on the Portfolio’s Worst Case Outcome 1. INTRODUCTION 2. ASSET PRICE MODEL AND WEALTH PROCESS 3. MODEL FORMULATION AND SOLUTION 3.1. Model Formulation 3.2. Model Solution 4. OPTION STRATEGY INTERPRETATION 5. HARA UTILITY AND GBM PRICES 6. CONCLUDING REMARKS APPENDIX REFERENCES Section III Asset and Liability Management Chapter 9 A Bank Asset and Liability Management Model 2. Stochastic Linear Programs with Simple Recourse 3. Formulation of the ALM Model 3.1. Notation for the ALM Model 3.2. The ALM Model 3.3. Data Required to Implement the ALM Model 4. Application of ALM to the Vancouver City Savings Credit Union 4.1. Model Details 4.1.1. Legal Constraints 4.1.2. Budget Constraints 4.1.3. Liquidity Constraints 4.1.4. Policy Constraints 4.1.5. Deposit Flows 4.1.6. Objective Function 4.2. Results of the VCS Application 5. Comparison of the ALM and SOT Approaches 5.1. The Bradley–Crane Stochastic Decision Tree Model (SOT) 5.2. The Economic Scenarios 5.3. Formulations of the Stochastic Dynamic Programming Model 5.4. Formulations of the ALM Model 5.5. Results of the Simulation 6. Final Remarks Acknowledgment References Chapter 10 Formulation of the Russell–Yasuda Kasai Financial Planning Model 1. OVERVIEW OF YASUDA KASAl'S PROBLEM 2. BACKGROUND ON MULTISTAGE STOCHASTIC LINEAR PROGRAMMING AND FINANCIAL PLANNING MODELS 3. FORMULATING THE RUSSELL-YASUDA KASAl MODEL AS A MULTISTAGE STOCHASTIC LINEAR PROGRAM 4. ALLOCATION CONSTRAINTS 5. THE LOAN MODEL 6. THE LIABILITY MODEL 7. THE FLOW OF FUNDS MODEL 8. FINAL REMARKS ACKNOWLEDGMENTS REFERENCES Chapter 11 Concepts, Technical Issues, and Uses of the Russell–Yasuda Kasai Financial Planning Model 1. SCENARIO GENERATION 2. END EFFECTS 3. COMPUTATIONS 4. COMPARISON TO MEAN VARIANCE 5. EXPERIENCE AND BENEFITS OF THE MODEL 6. SUMMARY OF BENEFITS OF THE RY MODEL ACKNOWLEDGMENT REFERENCES Chapter 12 The Innovest Austrian Pension Fund Financial Planning Model InnoALM Introduction 1. The Pension Fund Situation in Austria and Europe 2. Formulating the lnnoALM as a Multistage Stochastic Linear Programming Model 3. Scenario Generation and Statistical Inputs 4. Implementation and Sample Results 4.1. Sample Application—Assumptions 4.2. Sample Application—Results 4.3. Model Tests 5. Conclusions and Final Remarks Appendix. Pseudo-Code for Scenario Generation Acknowledgments References Section IV Kelly Optimal Growth Chapter 13 Growth versus Security in Dynamic Investment Analysis 1. The Basic Investment Problem 1.1. Measures of Growth 1.2. Measures of Security 2. Computation of Measures 3. Effective Growth-security Tradeoff 4. Applications 4.1. Blackjack : (φ, β) 4.2. Horseracing: (μt, γt) 4.3. Louo Games: (η, β) 4.4. Playing the Turn of the Year Effect with Index Futures: (φ, β) References Chapter 14 Time to Wealth Goals in Capital Accumulation 1. Introduction 2. Dynamic estimation of asset price distributions 2.1. Price model 2.2. Bayes estimation 3. Portfolio planning models 3.1. Expected utility strategy with fixed rebalance times 3.2. Wealth goals strategy and random rebalance times 3.3. Wealth goals 4. Comparisons 5. Conclusion Acknowledgements Appendix A References Chapter 15 Long-Term Capital Growth: The Good and Bad Properties of the Kelly and Fractional Kelly Capital Growth Criteria The good properties Some bad properties Some observations Acknowledgements References Appendix A Section V Sports Betting and Analytics Chapter 16 Efficiency of the Market for Racetrack Betting 1. The Racetrack Market 2. Previous Work on Racetrack Efficiency 3. Proposed Test 4. A Betting Model 5. Making the System Operational 6. Implementation and Reliability of the System References Chapter 17 Arbitrage Strategies for Cross-Track Betting on Major Horse Races I. Introduction II. Efficiency of the Various Betting Markets III. Inefficiency of the Win Market and the Risk-free Hedging Model IV. The Optimal Capital Growth Model V. Testing the One-Track Capital Growth Model VI. Final Discussion References Section VI Market Crashes Chapter 18 Stock Market Crashes in 2007–2009: Were We Able to Predict Them? 1. Background 2. Moving average and signal chart 3. The Chinese Shanghai stock market crash 4. The Icelandic stock market crash 5. The US 2007–2009 crash 6. Logarithmic model 7. Final remarks Acknowledgements References Chapter 19 Land and Stock Bubbles, Crashes and Exit Strategies in Japan Circa 1990 and in 2013 1. Introduction 2. Was the 1990 Japanese stock market crash predictable? 3. The changepoint detection model for exit bubble-type markets 3.1. The description of the model 3.2. Application of the model to market data 4. The Japanese stock market bubble 4.1. Background 4.2. Nikkei stock average in the 1980–1990s 5. The Japanese golf course membership market 5.1. Background 5.2. Application of the changepoint detection method 6. The overall Japanese land market, 1955–2013 7. Applying the model to the Nikkei in 2013 8. Short selling the Nikkei portfolio 9. Conclusion Acknowledgements References Appendix B — Selected Books, Published and in Progress J — Selected Published Journal Articles K — Selected Articles in Books P — Working Papers Index