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date: 18 November 2019

(p. xv) List of Tables

(p. xv) List of Tables

  1. 5.1 Partner search. 69

  2. 5.2 Return distribution. 69

  3. 5.3 Probable asset mixes over two periods. 70

  4. 5.4 Expected utility for 60/40 portfolio. 70

  5. 5.5 Rebalancing versus sub-optimality costs (basis points) and optimal rebalancing roadmap. 72

  6. 5.6 The curse of dimensionality. 73

  7. 5.7 Standard deviation and transaction cost assumptions. 76

  8. 5.8 Correlations. 76

  9. 5.9 Optimal portfolios. 77

  10. 5.10 Performance comparison — Total costs (bps). 78

  11. 5.11 Dynamic programming discretization scheme. 79

  12. 5.A.1 Securities used for stock portfolios. 81

  13. 5.A.2 Performance comparison — Two assets (5,000 Monte Carlo simulations). 82

  14. 5.A.3 Performance comparison — Three assets (5,000 Monte Carlo simulations). 82

  15. 5.A.4 Performance comparison — Four assets (5,000 Monte Carlo simulations). 83

  16. 5.A.5 Performance comparison — Five assets (5,000 Monte Carlo simulations). 83

  17. 5.A.6 Performance comparison — Ten assets (5,000 Monte Carlo simulations). 84

  18. 5.A.7 Performance comparison — Twenty-five assets (5,000 Monte Carlo simulations). 84

  19. 5.A.8 Performance comparison — Fifty assets (5,000 Monte Carlo simulations). 85

  20. 5.A.9 Performance comparison — Hundred assets (5,000 Monte Carlo simulations). 85

  21. 6.1 The Ellsberg paradox. 97

  22. (p. xvi) 7.1 Performance of portfolios: Idealistic setup. 127

  23. 7.2 Statistical significance of outperformance: Idealistic setup. 128

  24. 7.3 Performance of portfolios: Realistic setup. 128

  25. 7.4 Statistical significance of outperformance: Realistic setup. 129

  26. 8.1 List of replication products, their methods, and inception date. 143

  27. 8.2 Performance statistics of replication products and some market indicesover the period March 2008 to September 2009. 146

  28. 8.3 Linear correlation of replication products and some market indices overthe period March 2008 to September 2009. 148

  29. 8.4 Performance statistics of replication products over the two followingsample periods: March 2008 to March 2009 and April 2009 toSeptember 2009. 151

  30. 9.1 Constant investment opportunities. 166

  31. 11.1 Market capitalization percentiles in millions of dollars. 214

  32. 11.2 Fraction of firms during 1986—2009 with IDIFFI greater than ρ. 220

  33. 11.3 Comparison with IDIFFI values in Martin and Simin (2003) for 1992—1997. 221

  34. 11.4 Number of firms with tail percentages of outlier rejections. 226

  35. 13.1 Investor’s choice of portfolio. 274

  36. 13.2 EU calculated using one-step ahead draws from predictive distributions. 277

  37. 13.3 Summary of average portfolio mean and variance, by experiment andapproach. 280

  38. 15.1 World markets, 2009. 309

  39. 15.2 Global over-the-counter derivatives markets, 2009. 310

  40. 15.3 Comparison of U.S. Treasury 10-year rate first differences 1962—2009 —Original and normalized. 322

  41. 16.1 Sample parameter set. 341

  42. 17.1 Decision table to choose the appropriate benchmark and executionstrategy. 381

  43. 17.2 Decision table to choose appropriate refinements once the benchmarkand strategy have been set. 382

  44. 18.1 Parameter values used in the optimization problem. 406

  45. 19.1 Present value of duration 14 liability — Impact of discount rate. 427

  46. 19.2 Leveraging effect of the asset liability relationship on the pension. 427

  47. 19.3 Liability measurement — Key differentiating features. 428

  48. 19.4 Example: Active employee total compensation and accounting. 430

  49. (p. xvii) 19.5 Corporate asymmetry example. 439

  50. 19.6 Debt-to-equity ratio: Impact of hedging strategies. 442

  51. 20.1 Summary statistics and VAR estimation results. 457

  52. 20.2 Calendar rebalancing and dynamic mix. 463

  53. 20.3 Influence of initial funding ratio on option values and risk exposure. 466

  54. 21.1 The growth of SWFs (assets under management $bn). 473

  55. 21.2 Simplified balance sheet. 475