Index

  • 60/40 equity/bond mix, 59
  •  
  • Absolute momentum, 71
  • Alternative risk premium (ARP), 68–72
    • canonical forms, 68–70
      • concave/convex ARP, payoffs, 69f
    • distributions, 72
    • moment contributions, 75f
    • common types, 70f
    • ubiquity, 70–71
  • Approximation error
  • Arbitrage pricing theory (APT), 81
  • Asset allocation
    • error bars, decrease, 97
    • modern definition, 30–31
    • sensitivity, 105–109
  • Asset classes
    • benchmarks, 73
    • characteristics, 57
    • defined 73–77
    • KS test results, 89–90
    • creation methodology, 73f
    • paradigm, 66–77
    • taxonomy, 74f
  • Asset portfolio
    • EU concept, extension, 4
    • expected utility, 6–7
  • Assets
    • allocation, definition, 30–31
    • higher moments, existence, 10
    • comovement, 56, 63
    • diversification, 48–49
    • selection, 55–57
    • skew/kurtosis, 11f
  •  
  • Balance sheet model, 48f
  • Basis risk, absence, 57
  • Behavioral biases, moderation, 45–46
    • accommodation, contrast, 46f
    • embodied in utility function, 18–20
  • Behavioral parameters, 18–20, 45
  • Bernoulli, Daniel, 2
  • Black-Litterman model (shrinkage estimator), 26, 30
  • Bond prices
    • interest rate sensitivity, 6
    • Taylor expansion, 6
  • Bootstrap
    • definition, 83
    • forecasting standard errors, 83–89
    • asset allocation sensitivity, 106–109
  • Break-even effect, 38
  • Bretton Woods, cessation, 86
  • Brownian motion assumptions, 68
  •  
  • Capital Asset Pricing Model (CAPM), 10, 71, 81
    • higher moment CAPM, empirical work, 12
  • Capital gains taxes, 93
    • forecasting adjustments, 94
  • Capital market assumptions, 79
  • Carry strategies, rate spread capture, 71
  • Center for Research in Security Prices (CRSP), 60–61, 83, 99, 109
  • Central Limit Theorem, 8
  • Client
    • benefit, 57
    • irrational preference, 41
    • portfolios, building, 13
    • risk parameters, three-dimensional space, 99–100
    • risk preferences, 30
    • utility function
      • shape, 5
      • definition, 20
      • uniqueness/complexity, 15
    • validation process, 105
  • Client risk profile, 33
    • goals, incorporation, 43–54
    • preferences, measurement, 34–43
  • Cokurtosis, 29, 58
  • Co-moments
    • forecasting, 80
    • standard errors, 83
  • Comovements, 29, 56. See also Asset
  • Concave/convex ARP, payoffs, 69f
  • Concave/convex strategy, visual representation, 68–69
  • Consumption assumptions, flexibility, 52
  • Coskewness, 29, 58
  • Covariance, 29, 58, 63
  • Credit-dominated high-yield bonds, 66
  • Cross-asset portfolio moment contributions, impact, 55
  • Cross-sectional momentum, 72
  •  
  • Decision variable, 22
  • Decision weights, 19
  • Discretionary wealth, 33, 47–51
    • negative value, 49
  • Dispersion, avoidance, 12
  • Distinct assets, investment, 1
  • Diversifying assets, 58–59
    • concept, 59
  • Drawdowns, avoidance, 12
  • Due diligence tools, 93
  • Duration-dominated Treasuries, 66
  •  
  • Earnings assumptions, flexibility, 52
  • Emotional biases, 46
    • importance, 47
  • Equity premium puzzle, explanation, 38
  • Equity risk premium, 28
  • Equity value strategies, 61
  • Error bars, 86, 97
    • forecasting
      • confidence levels, 89
      • improvement, 88
      • post-winsorization, 88
      • symmetry, 84–85
  • Error sensitivity problem, addressing, 29–30
  • Estimation error, 1, 23–30, 83–89
    • effects, minimization, 30
    • handling, 86–87
    • impact, 14
    • minimization, 24–28, 86–87
    • sample size, contrast, 27f
    • sensitivity, reduction, 28–30
  • Estimators, distribution assumption, 25–26
  • Excess kurtosis, 12
  • Expected kurtosis. See Portfolio
  • Expected returns, expected utility (contrast), 3f
  • Expected utility (EU), 1, 2
    • concept, extension, 4
    • next period wealth function, 5
    • problem, distribution, 26
    • returns-based EU maximization, 21–23
  •  
  • Fallacy of large numbers, 35
  • Fama-French (F-F) factors
    • definitions, 75
    • long-only (LO) ARP, 74
    • robustness factor (F-F RMW), 11
    • value factor (F-F HML), 11, 76
      • skew contribution, 76
  • Fat tails, 10
  • Financial goals, 14, 43–54, 97
  • Financial markets, liquidity (improvement), 86
  • Forecasting horizon, 80–81
    • shortness, 24
  • Forecasts
    • adjustment, 91–96
    • allocation sensitivity, 23f
    • modification, 80
  • French, Kenneth, 83, 93, 109
  • Future assets, present value, 48
  •  
  • Gain domain, 41–42
  • Gambling phrasing, 35
  • Generalized risk aversion, 14, 105, 107–108
  • Geographic risk premium (GRP), 67–72, 89–90
  • Glidepaths, SLR (comparison), 52–54
  • Global cap-weighted benchmark, 26
  • Globalization, 86
  • Global market portfolio, reverse optimization, 81
  • Goals, incorporation into asset allocation, 43–54
  • Great Recession, 46–47
    • principal/agent responses, 17
  •  
  • Heuristic models, consideration (absence), 30
  • Higher moment
    • impact on asset allocation, 101
    • motivation, 8–13
    • preferences, 12–13
  • High kurtosis distributions, fat tails, 10
  • High minus low (HML) factor, 74
  • High-yield bonds, 65
    • grouping, 63
  • Historical data, usage, 25, 27–28
    • Historical return distributions, 79
      • history-based forecast, usage, 92
      • modification, 92f
      • winsorization, 87f
    • usage, forecast (example), 81–91
  • Home bias, avoidance, 68
  • House money effect, 38
  • Human capital, inclusion/correlation, 53
  •  
  • Incentive effects, 36
  • Interest rates
    • bond price sensitivity, 6
    • regime shifts, 90f, 91–82
  • Intermediate-term investment grade (IG) bonds, 65
  • Intermediate-term Treasuries, 65
  • Internal homogeneity, 63
  • Investment, risk-free rate, 49
  • Irrational risk preferences, 14–15
  •  
  • Jarque-Bera test, 10
  • Joint distribution forecasts, 87
  • Joint return distribution, 22
    • estimate, creation, 28–29
  •  
  • Kinked utility, 58–59
    • function, 17–18
  • Kolmogorov-Smirnov (KS) test, 89–90
  • Kurtosis
    • contribution, 75–76
    • decrease, 101
    • distribution, 10
    • effects, 9f
    • excess, 12
    • expected kurtosis, 7
    • negative kurtosis, 21
    • symmetrical effect, 9–10
  •  
  • Large numbers, fallacy, 35
  • Least squares, optimization, 64
  • Liabilities, minimization, 49
  • Linear comovements, 29
  • Liquidity, improvement, 86
  • Living risk, standard, 33
  • Long-only (LO) ARP investment, 75
  • Long-term (LT) Treasuries
    • addition, 63
    • impact, calculation, 59–62
  • Long-term (LT) wealth optimization, 45
  • Loss-averse portfolios, sub-optimal nature, 52
  • Loss aversion, 39–41, 99
    • absence, 34
    • diagnosis, 38
    • gambles, 43
    • mapping, 41
    • PT feature, 18, 20
    • questionnaire, 40f
    • score measurement, 39–40
  • Loss domain, 41–42
  • Loss, potential, 2
  • Lottery-style questionnaires, usage, 33–34
    • loss aversion, 39–41
    • question sizing, 43
    • reflection, 41–43
    • risk aversion, 34–39
  • Low-volatility bets, 71
  •  
  • Management fees, deduction, 92–93
  • Manager alpha, 93
  • Market anomaly, template, 69–70
  • Market portfolio, implied returns, 26
  • Mean estimates, distribution, 84
  • Mean return, secular shifts (effect), 91
  • Mean-semivariance framework
    • comparison, 102f
    • mean-variance framework, comparison, 104f
  • Mean-semivariance portfolio, deviation, 102
  • Mean standard error, 88
    • focus on, 85
  • Mean-variance (M-V)
    • asset allocation, 80
    • dominance, 17
    • efficient frontier, 14
    • framework, 5
      • comparison, 102f
      • mean-semivariance framework, comparison, 104f
    • optimization, 1, 23
      • solution, 7
    • optimizer, 101
  • Meucci, Attilio, 27
  • Mimicking portfolio tracking error (MPTE), 76
    • decision, 101–102
    • definition/equation, 65
    • example (fixed income), 65f
    • geographies, 68, 73
    • low level, 98
  • Modernized preference motivation, 13–15
  • Modern portfolio theory (MPT)
    • approximation, 5–7
    • formulation, 103
    • issues, 13–14
    • solution, 17
    • transition, 5
    • usage, decision, 103–105
  • Moment contributions, 57–63
    • calculation, 59–62
    • consideration, 73–74
    • definition/equation, 60
  • Moments
    • deployment, 64
    • estimates, standard error, 87f
    • estimation, 88
      • error bars, confidence levels, 89
    • forecasting, 80
    • standard errors, 87–88
  • Momentum
    • absolute momentum, 71
    • cross-sectional momentum, 72
    • time-series momentum, 71
  • Monte Carlo simulations, deployment, 51–52
  • Multi-dimensional questionnaires, value, 37
  • Multi-period problem, 33
  •  
  • National Institute of Standards and Technology (NIST) atomic clock, validity test, 37–38
  • Negative outcome avoidance, 5
  • Negative skew, effect, 8–9
  • Non-normal assets, 101–102
  • Non-normal distribution, estimate, 88
  • Non-normality
    • confidence, 88
    • Jarque-Bera test, 10
  • Non-parametric estimation, 25
    • deployment, 98
  • Normal distribution, skew/kurtosis effects, 9f
  • Null estimate, 86
  •  
  • Objective risk, 45, 50
  • Opportunistic forecasting horizon, 80–81
  • Optimization, 69. See also Portfolio
    • framework, 22–23
    • results, 98–103
    • sensitivity, 56
  • Optimizers
    • asset allocation, 23–24
    • input, 29
    • optimizer-recommended portfolios, accuracy, 83
    • running, 80
  • Out-of-sample forecast accuracy, 86
  •  
  • Payoffs
  • Performance assets, 58–59
    • concept, 59
  • Personality discovery process, 105
  • Pompian, Michael, 45
  • Portfolio
    • building, hyper-fiduciary mission, 44–45
    • cross-asset portfolio moment contributions, impact, 55
    • diversification, 59
    • expected kurtosis, 7
    • expected monthly return, 62–63
    • expected skew, 6–7
    • expected utility, 6–7
    • expected volatility, 6
    • goals, 45
    • loss-averse portfolios, sub-optimal nature, 52
    • mimicking, 55, 63–66
    • optimization, 97
    • portfolio-level higher moments, 10
    • return distributions, 8
    • variations, 100
    • volatility, 58–59
  • Positive convexity, 72
  • Positively skewed distributions, shaping, 10–11
  • Positive payoff outcome, 3–4
  • Positive premia, 72
  • Positive skew, 21, 72
    • distributions, 9
  • Post-dividend tax shifts, 94
  • Post-tax adjustments, 93–96
  • Power utility, 58–59
    • function, curvature (determination), 34–35
    • plotting, 16
  • Preference moderation, SLR (usage), 43–48, 50f
  • Present value (PV), 48
  • Pre-tax adjustments, 91–93
  • Pre-tax shifts, 94
  • Prospect theory (PT), 18, 47
    • effects, 18–19
  •  
  • Qualitative questionnaires, value, 37
  • Questionnaire
    • reliability, 42
    • validity, 37–38, 42
  •  
  • Rate spread capture, 71
  • Real estate, example, 2–4
  • Reflection (PT feature), 18, 41–43
    • questionnaire, 42f
  • Regression, coefficients, 64
  • Relative momentum, 71
  • Reliability, questionnaire, 42
  • Retirement, income level reduction, 49
  • Return distribution, 29
    • characterization, 7
    • forecast, 92
    • non-parametric estimation, viewpoint, 27
    • scaling process, 94
    • shifting/scaling, calculation steps, 95, 95f
  • Returns-based asset allocation framework, 79
  • Returns-based EU maximization, 21–23
  • Returns-based framework, 1, 88–89
  • Returns-based optimization, 22
    • requirement for full utility function, 31
  • Reverse optimization, global market portfolio, 81
  • Risk
    • capacity, 45
    • factor model, 62
    • parity, error bars, 107–108
    • sharing, 94
    • tolerance, self-assessment, 37
  • Risk aversion, 14, 16, 20, 99
    • deployment, avoidance, 104
    • generalized, 14, 105, 107–108
    • mapping, 36f, 40
    • non-linear representation, 35–36
    • parameter, 48
    • preferences, measurement, 34–39
    • questionnaire, 35f
    • questions, dollar amount, 39
    • SLR-based objective risk aversion, 50
    • time-varying risk aversion, usage, 38
  • Risk preferences
    • mathematicaly defined, 15–21
    • measured, 34–43
  • Risk premia, 57
    • alternative risk premium (ARP), 68–69
    • definition, 66–67
    • geographic risk premium (GRP), 67–68
    • justification, 71–72
    • review, 11–12, 67–72
    • traditional risk premium (TRP), 67–72
  • Robust minus weak (RMW), 74, 76
  •  
  • Sample size, 83–89
    • estimation error, contrast, 27f
    • function, 108f
  • Samuelson, Paul, 35
  • Savings, increase, 49
  • Second derivative, measure, 14
  • Second order approximation, 7
  • Self-control bias, assumption, 47
  • Sharpe ratio, 68, 70
  • Shrinkage, 81
    • estimator, 26
  • Single-period expected utility problem, focus, 44
  • Single-period lifecycle framework, selection, 54
  • Single-period problem, 33
  • Skew
    • contributions, 62
    • effects, 9f
    • increase, 101
  • Skewness risk premium, proxy, 74
  • S-shaped function, curvature (setting), 41–42
  • S-shaped utility, construction, 19–20
  • Stable, term (usage), 82
  • Standard error, concept, 80
  • Standard of living risk (SLR)
    • basis, 105
    • definition, purpose, 51
    • equation, 49
    • glidepaths, comparison, 52–54
    • level, selection, 51
    • measurement, 47–48
    • portfolio goal, 45
    • SLR-based objective risk aversion, 50
    • SLR-mapped loss aversion, 51
    • usage, 43–48, 50
  • Standard & Poor's 500 (S&P 500) return, 25
  • Stationarity, 89–91
    • test results, 90f
  • Stationary returns (estimates deployment), out-of-sample accuracy (goal), 86
  • Stochastic processes, 82
  • St. Petersburg paradox, 2
  • Structured models, avoidance, 81
  • Subjective risk, 36, 45
  • Survey of Consumer Finance (SCF) risk assessment, 37
  •  
  • Tactical forecasting horizon, 80–81
  • Test-retest reliability procedure, 42–43
  • Three-dimensional risk preference utility function, 20–21
    • deployed, 98–103
    • importance, 97
    • moderation, 103–05
    • moment sensitivity, increase, 102
    • second order approximation, equation, 103
  • Timeframe, question, 80–81
  • Time-series momentum, 71
  • Time-varying risk aversion, usage, 38
  • Tracking error, 65–66
  • Traditional risk premium (TRP), 67–72
    • asset class, inclusion, 77
  • Treasuries
    • constant maturity indices, 11
    • grouping, 63
  • Trend-following momentum, 72
  • Trend-following strategy, 69–70
  • True distribution, 24
    • non-parametric estimation, 25
  •  
  • Uncertainty, choice under, 3f
  • Unconstrained regression model, replication (shift), 64
  • US equities
    • average monthly return, bootstrap estimates, 84f
    • mean estimate, error, 86
    • moment estimates, standard error, 85f, 87f
    • monthly returns, 83–84
  • US large cap equities, 23–24
  • US small cap equities, 23–24
  • Utility
    • benefit, 56–57
    • contribution, 62–63
    • higher order expansion, equation, 5–6
    • maximization, 4
    • optimization, 69
    • outcomes, probabilities, 4–5
    • preferences, moderation, 50
    • utility-maximized portfolio, 107–108
  • Utility function, 15–21
    • graphical representation, 16f
    • maximization, 1
      • returns-based optimization, requirement, 31
    • ordinality, 3
    • parameters, 33
    • preference, 8
    • results, 97
    • series approximation, expected value solution, 7
  •  
  • Validity, questionnaire, 37–38, 42
  • Volatility, 86
    • aversion, 14
    • error bars, 107–108
    • estimate, accuracy, 88
    • shorting, 71
  •  
  • Willingness-to-accept (WTA) test, 47
  • Willingness-to-purchase (WTP) test, 47
  • Winsorized changes, 90–91
  • Winsorized commodities data, usage, 91
  • Winsorizing, 87–88
  •  
  • Yield curves, 71
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