Ж

kernel regression, 500 average derivative estimators, Г>1)Г> convergence property, fit)I curse ol riiincnsiimaliiv, fit) I optimal bandwidth seleetioit, 502 universal approximation properiv. Г.1Г.

weight linn lion, 501) Kroneeker pruritic l, 5.32 kurtosis. Hi, 19, HI, 480, 1,4,4. .SVv/;Л leltu us

labor income, 318

I .agrangian Iiiik lion, 1.4 1

latent-variable models, I Hi

Law ol Iterated Lxpeci.ttitms, 21, 255

lead-lag relations. .Sir eniss-auioi tit relation

le.tilting nciivoiks. 512, 518

Black-Sc holes l<>i iиiil:i and. 519 limitations, 518 multilayer pcrrcplmiis, .512 projection pursuit regression, 518 radial basis hint lions, 5 Hi

legal liability. Il), 17!)

leisure in the utility Iiiik iкni. 320

leverage hypothesis, 497

likelihood function, 302, 537. .SVr Ли niaxiinum likelihood estimation

likelihood ratio test. 193

liquidity elTects, 405

local averaging. fiOO, 502

local volaiiliiv, 375

log < I is i с 11 1111 j > i it с ratio, 20 I

log forward rate, 100. IOH. \,r и!ш forward rate j log bolding-pcifori return, 398 1 log pure expeclalions hypothesis,

: hi

j log yield, 307, 399, IOH. .SVr alw vield [ lo maturity

j log-likelihootl Itttu lion, 140, 35H.

I 487. Sir also tn.txiiiitiiii likelibootl

i estimation

j logisiir litnt lion. 51.3

j logistic map. 525

loglinear approximation, 200, 320. -100 accuracy, 202 coupon bonds, 100 inlerlemporal budget constrain). 320

lognormal distribution, 15 lognormal model olasset pricing, 300

Cobly-Oouglas utility, 320 l-.pslein-/.in-VVeil recursive utility, 319

external-habit model, 32H power utility, 300 long-horizon regressions, 207 /г .statistics, 271 orthogonality tests, 279 variance ratio, 272 bias, 273

dividend-price ratio, 208 dynamic asset-allocation models, 287

liiule-sainplc inference, 273 investment strategies, 287

long-horizon returns, 55, 7H. .SVr also variance ratio

long-range dependence, 59

I .ongstaff-Schwai tz model, -138

lookback options, 391

loss aversion, 333

Macaidays duration, 103

marked to maikel, 159

market efliciency, 20, .30. Sit also

EHicieiU Markets I lypothesis market frictions, 311

aggregate consumplion data, 310 I lanseibjagannalhan bounds, 315 maikel mirtostitit tutc, 83. .SVr also

barrier models, bid-ask spread.

bid-ask bounce, nonsyiu luonotis

trading, price discreteness,

rounding models market model, 155 conditional, 193 market portfolio. 155. 181.323, 195 M.ukov chain, 38, 81, 115

Markov process, 357 Markov-switching models, 172 martingale, 28, 256 martingale convergence theorem, 184

martingale pricing technique, 354 maturity, 3%

maximum correlation portfolio, 298. .SVc (iiso Hansen-Jagannath.m volatility bound maximum likelihood, 7 maximum likelihood estimation, .358, 536 asymptotic distribution, 538 continuous-record asymptotics, 364

factor analysis, 234 GARCH models, 487 information matrix, 538 information-matrix equality, 539 irregularly sampled data, 363 option price, 307 quasi-maximum likelihood

estimation, 539 stochastic differential equation,

White specification test, 539 mean reversion, 89 mean-variance efficient-set mathematics, 184, 243, 298 global minimum-variance

portfolio, 185, 217 1 lansen-Jagannatban volatility

bound, 298 minimum-variance frontier, 185 Sharpe ratio, 188 tangency portfolio, 188, 196, 218 zero-beta portfolio, 182, 185,218 м-histories, 112 mixed distribution, 481 mixture of normal distributions, 481 MI. estimation. .S>i maximum

likelihood estimation Ml.l. .SVr multilayer perception modified duration, 405. .SVc also

duration moment conditions, 359

Monte Carlo simulation methods, 340, 382,386 antithetic variates method, 388 comparisons with closed-form

solutions, 384 computational cost, 386 control variate method, 387 crude Monte Carlo, 386 discretization, 383, 385 efficiency, 386 importance sampling, 388 limitations, 390 number-theoretic method, 388 path-dependent option pricing, 382

stratified sampling, 388 variance-reduction techniques, 387

mortgage-backed securities, 406 multifactor models, 219, 324. Seealso Arbitrage Pricing Theory, exact factor pricing. Intertemporal Capital Asset Pricing Model, selection of factors Black version of the CAPM, 224, 229

cross-sectional regression

approach, 222, 233 empirical studies, 240 ) Epstein-Zin-Weil recursive utility

model, 324 \

estimation of expected retuijns,

231 j

estimation of risk premia, 231 factor portfolios spanning the

mean-variance frontier, 228 Generalized Method of MoriVents,

I lotelling Tl statistic, 232 macroeconomic variables as

factors, 226 portfolios as factors, 223 term-structure models, 440 multilayer perceplron (MLP), 512 multiplicative linear congruential

generators (MLCG), 525 multipoint moment conditions, 361

multiqiiatliics, 517 multivariate GARCH models, 490 multivariate stochastic-volatility models, 493

Nadaraya-Watson kernel estimator, 5()0

network topology, 514

iielwi irks, 512. See also learning

n .(works netirjil networks, 512. See also

lclarning networks Newtfy-VVest estimator, 535 news;impact curve, 485 n-hisiorics, 470 по-anbitrage condition, 339 noise- traders, 317 nominal bonds, 442 nominal stochastic discount factor,

443. See also stochastic discount

factor

nonlinear ЛКМЛ models, 471 nonlinear autoregressive models, 471

nonlinear dynamical systems, 473.

Лее alsa deterministic nonlinear

dynamical systems nonlineai in-mean time-series

models, 409 noiiliiiear-iii-variance linie-series

models, 409 nonlinear least squares estimation,

515,518

nonlineai moving-average models, 409

nonlinear time-series analysis, 408 uniiliucHriiy testing. See testing lor

nonlinear structure iionparainetric estimation, 498, 515 universal approximation property, 515

iioiipaiametiir option pricing

methods, 340, 392, 510 nonparametric tests, 172 nonperiodic cycles, 03 noiisepaiahility in utility, 320 iiotisyiiclironous trading, 84, 177

empirical Findings, 128

nontrading process, 145 noiilrading. See tionsytuiironous

trading normal distribution, 15 niunbei-lheoielic method, 388

offer. See ask price optimal orthogonal porllolio. 243, 245, 248. See also exact fill lot pricing option pricing, 349

adjusting the Black-Scholes

formula for predictability, 375 Black-Scholes and Merlon option

pricing model, 350 Black-Scholes formula, 371, 373 discrete-time models, 381 estimator for a1, 374 incomplete markets, 392 martingale approach, 354 maximum likelihood estimation, 307

nonparamelric methods, 392 / path-dependent options, 382 risk-neutral pricing method, 382 slate-price densities, 509 option sensitivities, 353 ordered probit model, 122, 130 maximum likelihood estimation, 127,141

Oriislein-Uhleuhcck process, 300,

371, 434 orthogonality condition, 528 orthogonality tests, 270 O-U process. Лек

Ot iisiein-Uhletibeck process output layer, 513 ovei titling, 498, 523

par, 401

parallel processing, 515 parametric option-pricing model,

340, 350 path-dependent derivatives, 310 patli-dependeni options, 340, .382 I * К11. See pure expectations

hypothesis

pet lecl-loiesiglu slock price, 275

observability in linile samples, 278 perfectly hedged portfolio, 352. See

idso delta-hedging strategy performance evaluation, 183 pet inatieiil shock, 05. .SVr i .wMtnil

rooi process persistence in expected stock

reuuiis, 205 persistence in volatility, 483, 492 peso prohlein, lilt) piei ewise-liueai models, 472 plain vanilla options, 349 Ininearc section. 475 pulviioiiii.il models, 471 porllolio pet lortnance evaluation,

power utility, 305. 434 ills. .Sir projection pursuit

regression precautionary savings, 310, 331 ptedictability ol stock returns, 27,

Black-Scholes lorintila. 371, 375

(.anipbcll-(.ochianc model, 332

dividend-price ratio, 208

rational bubbles, 200

time-varying risk-aversion, 3.32 preferred habitats, 418 price

clustering, 109, 145

discovery, 107

iliscteleness, 109, 143

ex-dividend, 12

imparl. 107. 143

ticks. 108 price ol risk. 432, 405 pricc-cai nings-ratio cllcct, 21 I pricing kernel, 294 principal components, 230 principle ol ittvaiiance, 307 piojeciinn pursuit regression, 518 prospect theory, 333 psychological models ol preferences, 332

pure expectations hypothesis (1*1-111). 113. .Sir idso expectations

hypothesis, lei m structure of

interest tales alternatives. 118 implications, 117 log put с expectations hypothesis, III

preleried liabilals, I 18 pit! option. 3 19

(XiARCI I model. 197 (-statistic. 17 quadratic form, 528 quadratic Г.АКС11 model. 497 qii.tsi-maxiinuin likelihood estimation. 489, 539

/;- statistic. 271

radial basis linn lions (RBKs), 510

rainbow options, 391

random number generators, 525

random walk, 27. See also

long-horizon returns, long-range dependence. Random Walk 1 model, Random Walk 2 model. Random Walk 3 model, technical analysis, unit root processes, variance difference, variance ratio

(oniiiuniiis-limc limit, 344 discrete-lime random walk, 341 empirical evidence, 05 Random Walk 1 model. 28, 31, 33 K-slalislics, 34 canonical cot relation, 34 (!owles-ones ralio, 35 eigenvalues ol the covariance

matrices, 34 Kendall r cot relation lest, 34 likelihood ralio statistic, 34 , nonparanulric tests, 34 tuns test, 38

seniip.it allien ic tests, 31 sequences and reversals, 35 Spearman rank correlation test, 34 Spearmans fool rule lest, .34 Random Walk 2 model, 28, 32, II Oiler i tiles, 42

Iciiniic al analysis, 43 Random Walk 3 model, >S. зз. II. Situ/mi Bnx-lic-rc с (V-sfalisiic. vai ian< e clif (cit-ncc, variant с i.UN)

portmanteau statistics, 17 lank lest, 17. rational bubbles, 258 RBEs. .SVr railial basis functions regiil.irizalion, Г)Г>, Г>22 rcplic aling portfolio, 353. 3H0, .391 repliealion in Monte ( i.u lo

siinulalion. знз representative .tgcnl models, il-.

(scaled range statistic . 02 relurns, 25 I

aimnali/ed. 10

Bernoulli distribution. IS

< iaiirhy disliibulion. IS

compound, 10

(imdiiion.il disliibulion. I I

continuously conipounded, I I, 255

discount bond, 107 discreteness, I 10 discreteness bias. I I (i excess, 12

excess kurtosis 17, IKS, 512 luii-casting returns. 20S gross, 0

lioldiiig-pei ioil return, IS iinlependetttlv and identic ally

distributed (III)), 15 joint distribution, 13 kurtosis, l(i, 10, SI, ISO, ISS log, 11. 255

logncii tital disii i I и 11 i> >i i, 15 net, (I

normal disnibiiiiiiu. 15 simple, 11

skewness, 17, HI. 172. IOH slable disli ilitilion. I 7 unconditional distribution, 15 unexpected stock teuiiiis. 204, 281

virtual, 85. See also

noiisync hrniions trading riding die yield curve, -lib risk aversion

riillerence habit-formation

models, .32!) Equity Premium Puzzle. 308. 32.!. 329

lirsi-orricr, 33 I loss aversion, 33.3 separating risk aversion from

intertemporal substitution, 319 time-varying, 330, 335 risk prices, 325

iisk-iiculral option pricing method.

35-1, 370, .382, 509 risk-neutral pricing density, 508 risk-neutrality, 351 i isk-iicul rali/ccI process. 355 risk-return liaricoll, II, 181 risk-sharing, 318 riskfree interest rale. .SVr riskless

interest rale riskfree rale pu lc, 310, 329 riskless interest rale. 182. 300, 3,09.

319, 328, 331 rolling standard deviation, 181 rotational iiideleiniinac v. 2.3-1 rounding models, 1II R/S statistic. .SVr rest alcri range

slalislic

RWl model. .SVr Random Walk 1 model

RW2 model. .SVr Random Walk 2 model

lsW.i model. .SVr Random Walk 3 model

sample paths. .383

sample selection biases, 212, 251

sampling interval, ЗГИ

seali-iiivariaiirc, 305

stdie vector, 537

SDM. .SVr state-dependent models security markei line, 1 I stlciiioii of lac lens, 233

cross-sectional generalized least

squares (CLS),235 data-snooping, 240, 246, 251 factor analysis, 234 principal components, 236 rotational indeterminacy, 234 strict factor structure, 234, 239 self-exciting threshold

autoregression (SETAR) models,

self-financing portfolio, 339, 351 sequences and reversals, 35 serial correlation, 44 SETAR models. .SVe self-exciting

threshold autoregression

(SETAR) models Sharpe ratio, 188, 245, 247, 300 short-term interest rate, 430, 449. See

til.si} discount bonds, riskless

interest rate (.ARCH ciicas on volatility, 452 regime-switching, 451 shortsalcs constraints, 315 sign lest, 172 size effect, 211, 496 size-sorted portfolio, 70, 75, 129 skewness, 17,81, 172,498. See also

returns slope estimators, 505 small slocks, 211,496 smoothing, 499, 517. See also kernel

regression solvency constraint, 315 spanning, 380. 391 SPD. .Sir stale-price density specification tests

I lansens test, 531

While test, 539 spline estimation, 410, 412, 517

exponential spline model, 412

tax-adjusted spline model, 412 spot rate, 414, 417 spread. .SVr bid-ask spread, yield spread

spread-lock interest rate swaps, 391 square-root single-factor

term-structure model, 435, 454

stable distribution, 17

standard Brownian motion, 344. See

alw Brownian motion state prices, 295, 507 state-dependent models (SDM), 470 state-price density (SPD), 507 stationary time-series process, 484.

See also unit root process stochastic approximation, 515 stochastic differential equation, 346,

GMM estimation, 359* Itos Lemma, 348 maximum likelihood estimation, 357

multiplication rules, 347 stochastic discount factor, 294, 427, 429. See also Euler equation equity premium puzzle, 302 habit-formation difference

models, 331 Hansen-Jagannathan volatility

bound, 296 nominal, 443 nonnegativity, 295, 301 power utility, 309 state-price density, 508 uniqueness, 296 stochastic trend, 65. See also unit

root process stochastic-volatility models, 379, 493

multivariate, 493 stratified sampling, 388 strict factor structure, 234, 239 strike price, 349 STRIPS, 396 stroboscope map, 475 structural breaks, 472 Student-i distribution, 210, 489 substitution effect, 321, 33L.S>t n elasticity of intertemporal substitution supershares, 507 support and resistance levels, 43 surplus consumption ratio, 330 survivorship bias, 311. See also

489,