Achievement, information ratio as measure of, 112
Active management, 1–2
as dynamic problem, 574
as forecasting, 261
and information, 316–318
information ratio as key to, 125
objective of, 119–121
as process, 578–579
Active risk, 50
After-tax investing, 575–576
Allocation (see Asset allocation)
Alpha(s), 91–92
benchmark-neutral, 384–385
characteristic portfolio of, 134
definition of, 111–112
and event studies, 331 -332
extreme values, trimming, 382–383
and information horizon, 357–359
and information ratio, 127–129
and portfolio construction, 379–385, 411–413
risk-factor-neutral, 385
Arbitrage pricing theory (APT), 13, 26, 173–192
applications of, 187–190
assumptions of, 177–178
examples using, 178–181
and factor forecasting, 185–190, 194–197, 304
and Portfolio Q, 182–185
rationale of, 181–182
and returns-based analysis, 249
and valuation, 203–205, 207, 208, 218–220
and weaknesses of CAPM, 174–177
ARCH, 279–280
Asset allocation, 517–532
asset selection vs., 518
and construction of optimal portfolios, 525–532
and forecasting of returns, 520–525
and international consensus expected returns, 526–532
and liability, 575
out-of-sample portfolio performance, 532–533
technical aspects of, 536–539
as three-step process, 519–520
types of, 517
Asset valuation, 6–7
AT&T, 67
Attributed returns, cumulation of, 510–512
Attribution, performance, 498–503
Attribution of risk, 78, 81–83
Autocorrelation, 491
Aversion to total risk, 96
BARRA, 4, 51, 60, 63, 73, 184–186, 188, 252, 284, 435, 438, 449, 454, 500
Behavioral finance, 576
Benchmark risk, 100–101
Benchmark timing, 101–102, 491–493, 541–554
defining, 541–542
and forecasting frequency, 549–552
with futures, 543–544
and performance analysis, 552–554
technical aspects of, 555–558
and value added, 544–549
Beta, 13–16
forecasts of, 24
and information ratio, 125–127, 140
a priori estimates of, 493
Biased data, 450
Book-to-price ratios, 322, 323
Capital asset pricing model (CAPM), 11–40, 487–489, 494, 496, 503, 560
characteristic portfolios in, 28–35
and efficient frontier, 35–37
and efficient markets theory, 17–18
example of analysis using, 20–21
and expected returns, 11, 18–19
and forecasting, 24
logic of, 16–17
mathematical notation in, 27
security market line in, 19–20
statement of, 16
as tool for active managers, 22–23
usefulness of, 22
and valuation, 203–205, 207, 208, 218–220
weaknesses of, 174–177
Cash flows:
certain, 200
uncertain, 200–201
Casinos, 150–151
Censored data, 450
Chaos theory, 280–281
Characteristic portfolios, 28–35
Commissions (see Transactions costs)
Comparative valuation, 244–248
Consensus expected returns, 11, 526–532
Constant-growth dividend discount model, 231–232
Corporate finance, 226–228
Covariance, 206–207
Cross-sectional comparisons, 58, 296–302, 332–333, 484–487
Currency, 527–532
Data mining, 335–336
Descriptors, 63
Diaconis, Percy, 335
characterizing, 404
definition of, 402
example of, 403–404
managing, 404–408
Dividend discount model(s), 7, 229–233, 242–244
beneficial side effects of, 244
certainty in, 229–230
constant-growth, 231–232
and returns, 242–244
three-stage, 239–242
uncertainty in, 230
Downside risk, 44–45
Duality theory of linear programming, 215
Efficient frontier, 35–37
Efficient markets theory, 17–18
Elementary risk models, 52–54
Event studies, 329–333, 343–345
Exceptional benchmark return, 91
Expectations, risk-adjusted, 203–206
Expected cash flows, 201
Expected return:
components of, 90–93
and value, 207–210
Expected utility, 96
Factor forecasts, 303–305
Factor models, 194–197
Factor portfolios, 74
Factor-mimicking portfolios, 74
Fama-MacBeth procedure, 72–73
Financial economics, 1
Financial value, 227
Forecast horizon, 274–275
Forecasts/forecasting, 7, 261–285, 295–313
active management as, 261, 579
advanced techniques for, 278–285
alpha scaling, testing, 311–312
with ARCH/GARCH, 279–280
and asset allocation, 520–525
basic formula for, 287–290
and chaos theory, 280–281
and cross-sectional scores, 296–302
examples of, 290–292
factor forecasts, 303–305
with genetic algorithms, 284–285
and intuition, 267–268
with Kalman filters, 280
with multiple assets/multiple forecasts, 271–275, 296
multiple forecasts for each of n assets, 302–303, 311
naïve, 262
with neural nets, 281–283
with one asset/one forecast, 264–268
with one asset/two forecasts, 268–271
one forecast for each of n assets, 309–310
raw, 262
and risk, 275–277
rule of thumb for, 265–268
with time series analysis, 278–279
two forecasts for each of n assets, 310–311
and uncertain information coefficients, 305–308, 312–313
Fractiles, 273–274
Fundamental law of active management, 147–168, 225, 550
additivity of, 154–157
assumptions of, 157–160
attributes of, 148
derivation of, 163–168
examples using, 150–154
and investment style, 161
statement of, 148
and statistical law of large numbers, 160
tests of, 160–161
usefulness of, 149–150
Futures, 543–544
GARCH, 279–280
General Electric, 47–50, 60, 63
Generalized least squares (GLS)
Genetic algorithms, 284–285
Gini coefficient, 428
GLS regressions (see Generalized least squares regressions)
Golden Rule of the Dividend Discount Model, 235, 236
Growth, 231–239
and constant-growth dividend discount model, 231–232
implied rates of, 235–236
with multiple stocks, 233–235
unrealistic rates of, 236–239
Heterokedasticity, 491
Historical alpha, 111
Historical beta, 111
Humility principle, 225
ICs (see Information coefficients)
Implementation (see Portfolio construction)
Implied growth rates, 235–236
Implied transactions costs, 459–460
Industry factors, 60–62
Information analysis, 7, 315–338
and active management, 316–318
and event studies, 329–333, 343–345
flexibility of, 318
pitfalls of, 333–338
and portfolio creation, 319–321
and portfolio evaluation, 321–329
technical aspects of, 341–345
as two-step process, 318
Information coefficients (ICs), 148
and information horizon, 354–362
Information horizon, 347–363
and gradual decline in value of
information, 359–363
macroanalysis of, 348–353
microanalysis of, 353–357
and realization of alpha, 357–359
return/signal correlations as function of, 371–372
technical aspects of, 364–373
Information ratio (IR), 5–6, 109, 132, 135–139
calculation/approximation of, 166–168
empirical results, 129–132
as key to active management, 125
and level of risk, 116
as measure of achievement, 112
as measure of opportunity, 113–117
negative, 112
and objective of active management, 119–121
and preferences vs. opportunities, 121–122
and residual frontier, 117–119
and residual risk aversion, 122–124
and time horizon, 116–117
and value-added, 124–125
See also Fundamental law of active management
Information-efficient portfolios, 341–342
Inherent risk, 107
Intuition, 267–268
Inventory risk model, 450–451
Investment research, 336–338
Investment style, 161
IR (see Information ratio)
Kalman filters, 280
Liabilities, 575
Linear programming (LP), 395–396
Linear regression, 589–590
Long/short investing, 419–441
appeal of, 438–439
and benchmark distribution, 426–428
benefits of, 431–438
capitalization model for, 427–431
controversy surrounding, 421
empirical results, 439–440
long-only constraint, impact of, 421–426
LP (see Linear programming)
Luck, skill vs., 479–483
Major Market Index (MMI), 65–67, 235–236, 268, 488
Managers, 564–567
Marginal contribution for total risk, 78–81
factor marginal contributions, 79–80
sector marginal contributions, 80–81
Market microstructure studies, 447–448
Market volatility, 83–84
Market-dependent valuation, 207
Markowitz, Harry, 44
MIDCAP, 275–277
Mixture strategies, 365–369
MMI (see Major Market Index)
Modern portfolio theory, 3–4, 93
Modern theory of corporate finance, 226–228
Mosteller, Frederick, 335
Multiple-factor risk models, 57–60
cross-sectional comparisons in, 58
and current portfolio risk analysis, 64–67
external influences, responses to, 57–58
statistical factors in, 58–60
Naïve forecasts, 262
Neural nets, 281–283
Neutralization, 383
Nixon, Richard, 357
Nonlinearities, 575
OLS (ordinary least squares) regressions, 246
Operational value, 227
Opportunity(-ies):
arbitrage, 214
information ratio as measure of, 113–117
preferences vs., 121–122
Options pricing, 217–218
Ordinary least squares (OLS) regressions, 246
Out-of-sample portfolio performance, 532–533
Performance, 559–569
and manager population, 564–567
persistence of, 562–564
predictors of, 567–568
studies of, 560–562
Performance analysis, 477–507
and benchmark timing, 552–554
with cross-sectional comparisons, 484–487
and cumulation of attributed returns, 510–512
and definition of returns, 483–484
goal of, 477
portfolio-based, 497–506
returns-based, 487–497
risk estimates for, 512–513
and skill vs. luck, 479–483
usefulness of, 478
valuation-based approach to, 513–515
Persistence, performance, 562–564
Plan Sponsor Network (PSN), 484
Portfolio construction, 377–409
and alternative risk measures, 400–402
and dispersion, 402–408, 414–416
inputs required for, 377–378
with linear programming, 395–396
practical details of, 387–389
with quadratic programming, 396–398
revisions, portfolio, 389–392
with screens, 393–394
with stratification, 394–395
technical aspects of, 410–118
techniques for, 392–398
testing methods of, 398–400
and transaction costs, 385–387
Portfolio-based performance analysis, 497–506
Predictors, 317
Proust, Marcel, 336
PSN (Plan Sponsor Network), 484
Quadratic programming (QP), 396–398
Quantitative active management, 1, 3–4
Rankings, 274
Raw forecasts, 262
Realized alpha, 111
Realized beta, 111
Refining forecasts, 262–265
and intuition, 267–268
with multiple assets/multiple forecasts, 271–275
with one asset/one forecast, 264–268
with one asset/two forecasts, 268–271
Regression analysis, 589–590
Residual frontier, 117–119
Residual returns, active vs., 102–103
Residual risk, 16–17, 50, 100–101, 122–124
Return forecasting, 7
Returns regression, 487–491
Returns-based analysis, 248–252
Returns-based performance analysis, 487–497
Revisions, portfolio, 389–392
Risk, 41–84
active, 50
and active vs. residual returns, 102–103
annualizing of, 49
aversion to residual, 122–124
aversion to total, 96
benchmark, 100–101
definitions of, 41–46
downside, 44–45
elementary models of, 52–54
and forecasting, 275–277
and industry factors, 60–62
information ratio and level of, 116
inherent, 107
marginal impact on, 78–81
and market volatility, 83–84
and model estimation, 72–73
multiple-factor models of, 57–60, 73–75
over time, 575
residual, 16–17, 50, 100–101, 122–124
and semivariance, 44–45
as shortfall probability, 45–46
specific, 75–76
and standard deviation of return, 43–44, 47–52
structural models of, 55–56
total, 51
total risk and return, 93–99
and usefulness of risk models, 64–70
value at, 46
Risk analysis, 76–78
Risk estimates (for performance analysis), 512–513
Risk premium, 91
Risk-adjusted expectations, 203–206
Scheduling trades, 457–458
Science of investing, 1
Screens, 393–394
Security market line (in CAPM), 19–20
Semivariance, 44–45
Sharpe ratio (SR), 27, 32–33, 135–137, 487, 489–490
Shelf life (see Information horizon)
Shortfall probability, 45–46
Shrinkage factor, 433
Skill, luck vs., 479–483
S&P 500, 100, 275–277, 439, 445, 488, 505
Specific asset selection, 499
Specific risk, 75–76
Standard deviation, 43–44, 47–52
Standard errors, 589
Statistical law of large numbers, 160
Statistical risk factors, 58–60
Statistics, 588–589
Strategic asset allocation, 517
Strategy mixtures, 365–369
Stratification, 394–395
Structural risk models, 55–56
Style, investment, 161
t statistics, 325–327, 336–337
Tactical asset allocation, 517
Target portfolio, 464
Target semivariance, 45
Theory of Investment Value (John Burr Williams), 229
Tick-by-tick data, 450
Time premium, 91
Time series analysis, 278–279
Timing, benchmark (see Benchmark timing)
Tracking error, 49
Trading, 447
implementation, strategy, 467–468
optimization of, 473–475
as portfolio optimization problem, 463–467
Transactions costs, 385–387, 445–454, 458–459, 462–463, 574–575
analyzing/estimating, 448–454
implied, 459–460
and market microstructure, 447–448
See also Turnover
definition of, 456
and implied transactions costs, 459–460
and scheduling of trades, 457–458
and value added, 455–457, 471–472
Unrealistic growth rates, 236–239
Valuation, 109, 199–210, 225–257
and CAPM/APT, 218–220
comparative, 244–248
and dividend discount model, 229–233, 242–244
and expected return, 207–210
formula for, 202–203
market-dependent, 207
and modeling of growth, 232–239
modern theory of, 199–201, 212–217
and modern theory of corporate finance, 226–228
with nonlinear models/fractiles, 255–257
and options pricing, 217–218
of Portfolio S, 220–223
and returns-based analysis, 248–252
and risk-adjusted expectations, 203–206
and three-stage dividend discount model, 239–242
and benchmark timing, 544–549
and information ratio, 124–125
objective for management of, 106–108
optimal, 139–140
and performance analysis, 493, 513–515
and turnover, 455–457
Value at risk, 46
Volatility:
cross-sectional, 302
market, 83–84
See also Risk
Volume-weighted average price (VWAP), 450
Wall Street Journal, 245
Williams, John Burr, 229