Àâòîðèçàöèÿ
Ïîèñê ïî óêàçàòåëÿì
Richard A. DeFusco CFA, McLeavey D.W., Runkle D.E. — Quantitative Methods For Investment Analysis
Îáñóäèòå êíèãó íà íàó÷íîì ôîðóìå Íàøëè îïå÷àòêó?
Íàçâàíèå: Quantitative Methods For Investment AnalysisÀâòîðû: Richard A. DeFusco CFA, McLeavey D.W., Runkle D.E.Àííîòàöèÿ: As part of the CFA Institute Investment Series, the Second Edition of Quantitative Investment Analysis has been designed for a wide range of individuals, from graduate-level students focused on finance to practicing investment professionals. This globally relevant guide will help you understand quantitative methods and apply them to today's investment process.
ßçûê: Ðóáðèêà: Ýêîíîìèêà è ôèíàíñû /Ñòàòóñ ïðåäìåòíîãî óêàçàòåëÿ: Ãîòîâ óêàçàòåëü ñ íîìåðàìè ñòðàíèö ed2k: ed2k stats Èçäàíèå: 2Ãîä èçäàíèÿ: 2007Êîëè÷åñòâî ñòðàíèö: 721Äîáàâëåíà â êàòàëîã: 11.03.2010Îïåðàöèè: Ïîëîæèòü íà ïîëêó |
Ñêîïèðîâàòü ññûëêó äëÿ ôîðóìà | Ñêîïèðîâàòü ID
Ïðåäìåòíûé óêàçàòåëü
Multifactor models in portfolio management, passive management 633 Multifactor models in portfolio management, risk premium 638 Multifactor models in portfolio management, sensitivity 635 Multifactor models in portfolio management, summary 671—672 Multifactor models in portfolio management, types 633—634 Multinomial formula for labeling problems 216—217 Multiperiod forecasts and chain rule of forecasting 533—536 Multiple linear regression 442—476 Multiple linear regression, adjusted 457 Multiple linear regression, analysis of variance 445 454—456 Multiple linear regression, application example 443—447 Multiple linear regression, assumptions 448—453 Multiple linear regression, coefficient of variance, adjusted 457 Multiple linear regression, definition 442 Multiple linear regression, dummy variables usage in 458—462 Multiple linear regression, examples 443—447 449—453 453—454 458—462 464 465—467 474—475 Multiple linear regression, heteroskedasticity see "Heteroskedasticity" Multiple linear regression, introduction 442—448 Multiple linear regression, multicollinearity see "Multicollinearity" Multiple linear regression, partial regression coefficients 447 448 Multiple linear regression, partial slope coefficients 447 Multiple linear regression, predicting dependent variable in 453—454 Multiple linear regression, serial correlation see "Serial correlation and regression" Multiple linear regression, significance of 454—456 Multiple linear regression, slope coefficients 447 448 454—455 Multiple linear regression, uncertainty in 454 Multiple linear regression, violations of assumptions 462—476 Multiplication rule for independent events 189 Multiplication rule of counting 215—216 Multivariate distribution 251 Multivariate normal distribution 251 Mutually exclusive 181 Net present value (NPV), computing 58 Net present value (NPV), definition 58 Net present value (NPV), internal rate of return and 58—65 Net present value (NPV), internal rate of return versus rule of 63—65 Net present value (NPV), rule and 58—60 Newey — West method 472 Node 245 Nominal risk-free interest rate 3 Nominal scales 89 Noncovariance-stationary time series 528 Nonlinear relation 381 382 Nonparametric inference 356—360 Nonstationarity 489 490 529 Normal distribution 250—257 Normal distribution, applications 257—260 Normal distribution, asset prices and 252 Normal distribution, bivariate 251 Normal distribution, characteristics 250—251 Normal distribution, diagram of 250 Normal distribution, equity portfolio, diversified, and 252 Normal distribution, Introduction 250 Normal distribution, joint 251 Normal distribution, multivariate 251 Normal distribution, portfolio return and 251 Normal distribution, range of possible outcomes 250 Normal distribution, roles of 250 Normal distribution, standard 251 Normal distribution, unit 251 Number of periods, solving for 29 One-tailed probabilities table 688 Opportunity cost 2 optimizer 601 Option pricing model example, volatility as used in 264—265 Ordinal scales 90 Ordinary annuity, definition 13 Ordinary annuity, equal cash flows 13—14 Ordinary least squares (OLS), definitions 448 519 Ordinary least squares (OLS), Durbin — Watson statistic for regression 471 Ordinary least squares (OLS), regression coefficients estimates 473 Ordinary least squares (OLS), serial correlation and 469 472 Out-of-sample forecast errors 536 537—538 Out-of-sample test 306 307 Outcomes 180 p-value see "Probability value" Paired comparisons test 347 Paired observations 347 Pairs arbitrage trade 184 Panel data 291 396 PARAMETER 89 286 Parameter instability 418 Parametric test 356 357 Passive management 633 Pearson coefficient of skewness 146 Percentiles 120 121 122—124 Perfect collinearity 449 Performance appraisal 65 Performance measurement 65 Permutation 217—218 Perpetual annuity 23—25 Perpetuity definition 13 Platykurtic 149 150 Point estimators 295—297 Pooled estimate 342 Population mean 103—104 253 Population mean, confidence intervals for 297—303 Population mean, point estimators of 295—297 Population, definitions 89 253 Population, error variance 469 Population, samples see "Sample" "Sampling" Population, standard deviation 130—132 Population, variance 129—130 Portfolio as stand-alone investments 619—620 Portfolio return, determining 202 Portfolio return, management 65—72 Portfolio return, money-weighted rule of return 66—67 Portfolio return, normal distribution and 251 Portfolio return, random variables and 202 Portfolio return, time-weighted rate of return 67—72 Portfolio, adding investment decision 620—622 Portfolio, analysis and weighted mean 112—113 Portfolio, arbitrage pricing theory see "Arbitrage pricing theory" Portfolio, capital allocation line 610—617 Portfolio, capital asset pricing model see "Capital asset pricing model (CAPM)" Portfolio, capital market line 617 618 Portfolio, choice from mean-variance perspective 619—623 Portfolio, choice with risk-free asset 609—617 Portfolio, concepts 587—683 Portfolio, determining asset allocation 622—623 Portfolio, diversification and size 602 605—609 Portfolio, efficient 590 Portfolio, efficient frontier 594 599 602 Portfolio, examples 595—597 603—605 608—609 610—614 616—617 621—622 627 630—632 636 639—642 644—645 653—655 658—659 660—663 663—664 665—666 Portfolio, expected return and variance of return 202—211 Portfolio, factor 663—664 Portfolio, inefficient 594 Portfolio, introduction 589 Portfolio, mean-variance analysis see "Mean-variance analysis" Portfolio, minimum-variance 590—599 629—632 Portfolio, multifactor models see "Multifactor models in portfolio management" Portfolio, performance attribution 649 Portfolio, possibilities curve 592 Portfolio, pure factor 638 Portfolio, risk versus return 597 599 613 Portfolio, selection 590 Portfolio, tangency 610 617 618 622 Portfolio, three-asset 599—602 Portfolio, tracking 664—666 Portfolio, two-asset 590—591 592 595—597 Portfolio, variance 202 205 Prediction intervals 416—418 Present value (PV) see also "Net present value (NPV)" Present value (PV) of series of cash flows 18—26 Present value (PV) of single cash flow 15—18 Present value (PV), definition 4 Price relative 262 Priced risk 633 635 Principal definition 4 Probabilities for common stock portfolio example 256—257 probability 179—230 Probability distributions, common 231—283 Probability distributions, common, binomial distribution 236—246 Probability distributions, common, continuous random variables 246—266 Probability distributions, common, definition 232 Probability distributions, common, discrete random variables 232—246 Probability distributions, common, discrete uniform distribution 234—236 Probability distributions, common, introduction 232 Probability distributions, common, Monte Carlo simulation 266—272 Probability distributions, common, summary 272—274 Probability, a priori 182 215 Probability, additional rule for 187—189 Probability, approaches to estimating 182 Probability, binomial 240 Probability, conditional 184 185 186—187 191—192 Probability, definition 181 Probability, density function (pdf) 234 246 247 248 Probability, distributions see "Probability distributions common" Probability, down transition 245 Probability, empirical 182 Probability, function 234 Probability, inconsistent 184 Probability, introduction 180 Probability, inverse see "Bayes' formula" Probability, joint 185 209 Probability, marginal 184 Probability, mass function (pmf) 234 Probability, multiple rule for 185 Probability, objective 182 Probability, portfolio expected return and variance of return 202—211 Probability, posterior 213 Probability, principles of counting and 215—218 Probability, prior 212 213 Probability, profiting from inconsistent 183—184 Probability, properties of 181 Probability, stated as odds 182—183 Probability, subjective 182 Probability, summary 219—221 Probability, topics in 211—218 Probability, total probability rule 192 193—194 Probability, total probability rule for expected value 197 Probability, unconditional 184 185 Probability, up transition 245 Probability, value 334—335 407 447 Probit models 490 491—492 Pseudorandom numbers 268 Pure discount instruments 72 Qualitative dependent variables, models with 490—492 Quantiles 120—126 Quantiles in investment practice 124—126 Quantiles, analysis of variance and 455 Quantiles, commonly used, most 120—124 Quartiles 120 121 122—124 Quintiles 120 122—124 Random number generator 268 269 Random variable(s) 180 Random variable(s), Bernoulli 236—238 Random variable(s), binomial 236—246 Random variable(s), definition 232 Random variable(s), independence for 210 Random variable(s), standardizing 255 Random variable(s), uncorrelated 211 Random variable(s), upper and lowercase letters and 233 Random walks 490 541—545 RANGE 126—127 Ratio scales 90 Real risk-free interest rate 3 Regression analysis see "Linear regression" "Model "Multiple Regression coefficients 395 443 538—540 Rejection point (critical value) for test statistic 330—331 333 Relative dispersion 139 Relative frequency 103 Relative frequency, cumulative 94 Relative frequency, definition 94 Reliability factors, basis of computing 303 Residual autocorrelations 530 Return distributions, kurtosis in 149—153 Return distributions, properties of 88 Return distributions, semivariance and 136 Return distributions, symmetry and skewness in 144—149 Risk premium test 327 332 333—334 Risk-adjusted net value added (RANVA) 449—451 453—454 Robust standard errors 467 468 472 Root mean squared error (RMSE) 537 566 Roy's safety-first criterion 257 258 260 Rule of 72 29 Safety-first rules 257—259 Sample statistics definition 89 Sample, covariance 379—381 Sample, definition 89 Sample, distribution of mean 291—295 Sample, excess kurtosis 150—153 Sample, mean 103 104—105 194 253 287 Sample, mean formula 104 Sample, populations and 89 Sample, random, simple 286—287 Sample, relative skewness 147 Sample, selection bias 308—309 Sample, size selection 303—305 Sample, skewness 147 Sample, standard deviation 133—135 253 Sample, variance 132 133—134 Sampling 285—322 Sampling, biases in investment research 310—311 Sampling, central limit theorem 286 292—295 Sampling, data-mining bias 306—308 Sampling, definition 286 Sampling, delistings selection bias 309 Sampling, distribution of sample mean 291—295 Sampling, distribution of statistics 287 Sampling, error and 286 287 291 303 Sampling, introduction 285—286 Sampling, look-ahead bias 309 311 Sampling, out-of-sample test 306 Sampling, plan 287 Sampling, point and interval estimates of population mean 295—305 Sampling, random sampling, simple 286—287 Sampling, reasons for 286 Sampling, selection bias 308—309 333 Sampling, stratified random sampling 288—289 Sampling, summary 311—313 Sampling, survivorship bias 308—309 310—311 333 Sampling, systematic 287 Sampling, time-period bias 310 311 333 Sampling, time-series and cross-sectional data 289—291 Scatter plots 376—377 378 379 383 Seasonality in models 555—558 567 568 Security Market Line (SML) 618 Selling short 184 Semideviation 135—136 137 Semilogarithmic scales 154 Semivariance 135 136 137 Serial correlation and regression errors 468—473 476 Serial correlation and regression errors, autoregressive model and detecting 529—532 Serial correlation and regression errors, consequences of 469 Serial correlation and regression errors, consistent standard errors 472 Serial correlation and regression errors, correcting for 472—473 Serial correlation and regression errors, Dubin — Watson statistic and 470—472 527 Serial correlation and regression errors, first-order 469 Serial correlation and regression errors, negative 469 Serial correlation and regression errors, positive 469 Serial correlation and regression errors, summary 476 Serial correlation and regression errors, testing for 470—472 Sharpe ratio 137 141—144 Sharpe ratio as risk-adjusted performance measure 72 126 Sharpe ratio, calculating 143—144 290 Sharpe ratio, confidence interval for population mean of, examples 300 302—303 Sharpe ratio, definition 289 Sharpe ratio, formula 141 Sharpe ratio, limitation 142
Ðåêëàìà
|
|
Î ïðîåêòå