420 Index
Matrix operations, 393–396
addition, 394
inverse and adjoint, 395–396
multiplication, 394–395
transpose, 393–394
Maximum likelihood estimation (MLE)
application to factor models, 282–283
application to regression models, 279–282
Maximum likelihood estimation (MLE)
method, 243, 278–283
about, 278–279
MLE application to factor models,
282–283
MLE application to regression models,
279–282
Mean, defined, 329
Mean absolute deviation (MAD), 330
Mean absolute deviation (MeanAD), 410
Mean squared errors (MSEs), 48, 188,
364–365
Mean squares of regression, 48
Measures of location and spread, 328–332
absolute deviation, 330
center and location, 329–330
parameters vs. statistics, 328–329
skewness, 331–332
variance and standard deviation, 330–331
variation, 330
Measures of variation, 330
Median, defined, 329
Median absolute deviation, 410
Medium, 410
M-estimation method and M-estimators, 289
M-estimators, 408
Method of moments, 284–289
about, 284–285
generalized method of moments, 285–289
Method of moments (MOM) estimation,
284
Minimum-variance linear unbiased estimate
(MVLUE), 369
Minimum-variance unbiased estimator, 365
Minor, 389
Mode, defined, 329
Model, 42–43
Model building techniques, 84–88
standard stepwise regression method, 87
stepwise exclusion regression method,
86–87
stepwise regression method, 85–86
Model complexity and sample size,
293–295
Model design, 45–46
Model estimation, 3–5, 11
estimation methods, 267–268
instrumental variables, 283–284
least-squares (LS) estimation method,
268–278
M-estimation method and M-estimators,
289
method of moments, 284–289
statistical estimation and testing,
265–267
summary/key points, 289–290
Model estimation methodology, 309–310
Model parameters estimates, 43–45,
245–249
Model risk, 300–301
Model selection, 2–3
condensation of, 301–303
data snooping, 296–297
model complexity and sample size,
293–295
model risk, 300–301
physics and economics, 291–293
sample defects, 297–300
survivorship biases, 297–300
summary/key points, 303
Model selection criteria
about, 399
AKAIKE information criterion (AIC),
400–402
Bayesian information criterion (BIC),
402–403
Model testing, 4–5, 11
Modeling, 215–223
Modeling in presence of autocorrelation, 99
Moment of P, 284
Mortgage-backed security (MBS), 72
Moving average, 176. See also
Autoregression moving average
(ARMA) models
Moving average (MA) models, 176–177, 189
Moving average models, 176–178
Moving training windows, 298–300
Multicollinearity problem, 81
about, 81–83
procedures for mitigating, 83–84
Multifactor models evidence, 78–79
Multiple coefficient of determination, 47