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Richard A. DeFusco CFA, McLeavey D.W., Runkle D.E. — Quantitative Methods For Investment Analysis
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Íàçâàíèå: Quantitative Methods For Investment Analysis
Àâòîðû: 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.
In this latest edition, the distinguished team of Richard DeFusco, Dennis McLeavey, Jerald Pinto, and David Runkle update information associated with this discipline; improve the presentation and coverage of several major areas, including regression, time series, and multifactor models; and introduce an even greater variety of investment-oriented examples—which reflect the changes currently taking place in the investment community. Throughout the text, special attention is paid to ensuring the even treatment of subject matter, consistency of mathematical notation, and continuity of topic coverage that is so critical to the learning process.
Valuable for self-study and general reference, this book provides clear, example-driven coverage of a wide range of quantitative methods. Topics discussed include:
* The time value of money
* Discounted cash flow applications
* Common probability distributions
* Sampling and estimation
* Hypothesis testing
* Correlation and regression
* Multiple regression and issues in regression analysis
* Time-series analysis
* Portfolio concepts
And to further enhance your understanding of the tools and techniques presented here,don't forget to pick up the Quantitative Investment Analysis Workbook, Second Edition—an essential guide containing learning outcomes and summary overview sections along with challenging problems and solutions.
With each author bringing his own unique experiences and perspectives to the table, the Second Edition of Quantitative Investment Analysis distills the knowledge, skills, and abilities you need to succeed in today's fast-paced financial environment. Filled with in-depth insights and practical advice, Quantitative Investment Analysis, Second Edition offers a comprehensive treatment of quantitative methods that combines best practices with solid theory.
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Ãîä èçäàíèÿ: 2007
Êîëè÷åñòâî ñòðàíèö: 721
Äîáàâëåíà â êàòàëîã: 11.03.2010
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Ñêîïèðîâàòü ññûëêó äëÿ ôîðóìà | Ñêîïèðîâàòü ID
Ïðåäìåòíûé óêàçàòåëü
Absolute dispersion 126
Absolute frequency 93 103
Accrued interest 74
Active factor risk, analysis example 660—663
Active factor risk, definition 657
Active management 633
Active return definition 652
Active risk, comparison example 658—659
Active risk, definition 655
Active risk, squared 657 658
Active specific risk definition 657
Adjusted beta definition 628
Analyzing sources of returns 652—655
Analyzing sources of risk 655—663
Annual percentage rate (APR) 12
Annuity see also "Ordinary annuity"
Annuity payments size, solving for 29—33
Annuity, definition 13
Annuity, due 13
Annuity, perpetual 23
Arbitrage Pricing Theory (APT) 633 637—643
Arbitrage pricing theory (APT), assumptions of 637
Arbitrage pricing theory (APT), capital asset pricing model versus 637 638
Arbitrage pricing theory (APT), examples 639—642
Arbitrage pricing theory (APT), factor risk premium 638
Arithmetic mean 103—107 243
Arithmetic mean, definition 103
Arithmetic mean, disadvantage of 107
Arithmetic mean, Foolish Four and 307
Arithmetic mean, population mean and 103—104
Arithmetic mean, properties of 106—107
Arithmetic mean, returns examples 117—118 119
Arithmetic mean, sample mean and 103 104—105
Arithmetic mean, usage example 109—110
Arithmetic mean, using geometric and 153—155
Arithmetic mean, variations of 107
Arithmetic mean, weighted mean formula versus formula of 113
Asian call option 267
Asset selection risk definition 657
Asset's risk measurement 135
Autocorrelations of time series 52—530 545 551
Autoregressive (AR) time-series models 527—540
Autoregressive (AR) time-series models, comparing forecast model performance 536—538
Autoregressive (AR) time-series models, covariance-stationary series 528—529
Autoregressive (AR) time-series models, detecting serially correlated errors in 529—532
Autoregressive (AR) time-series models, determining which model to use 567—568
Autoregressive (AR) time-series models, instability of regression coefficients 538—540
Autoregressive (AR) time-series models, mean reversion 532—533
Autoregressive (AR) time-series models, moving-average versus 551—553
Autoregressive (AR) time-series models, multiperiod forecasts and chain rule of forecasting 533—536
Autoregressive (AR) time-series models, seasonality and 553
Autoregressive conditional heteroskedasticity (ARCH) models 559—562 568
Autoregressive model 517—518
Autoregressive moving-average models 558—559
Average versus mean usage 104
Back simulation 271
Bank discount basis 73—74
Bank discount basis, definition 73
Bank discount basis, example 73—74
Bank discount basis, yield 74
Bayes' formula 180 211—215
Benchmark 633
Bernoulli random variable 236—239 244
Bernoulli trial 236 238 239
Beta definitions 618
Beta definitions, adjusted 628
Beta definitions, fundamental 629
Beta definitions, standardized 643
Bid-ask spread, explaining 443—447
Bid-ask spread, nonlinearity and 480—483
Bid-ask spread, variable bias and, omitted 478—479
Binomial distribution 236—246
Binomial formula 217
Binomial model of stock price movement 245
Binomial option pricing model 232 236
Binomial tree 245 246
Black — Litterman asset allocation model 623
Black — Scholes — Merton option pricing model 260 262
Black — Scholes — Merton option pricing model, Monte Carlo simulation versus 272
Black — Scholes — Merton option pricing model, probability distribution and 232
Black — Scholes — Merton option pricing model, volatility and 264
Block brokers 237—238 240—242
Bond portfolio example, expected number of defaults in 244
Bond-equivalent basis 77
Bond-equivalent yield 77
Box — Pierce Q-statistic 530
Breusch — Pagan test 465—467
Capital allocation line (CAL) 610—617 636
Capital Asset Pricing Model (CAPM) 618—619
Capital asset pricing model (CAPM), arbitrage pricing theory versus 637 638 666—667
Capital asset pricing model (CAPM), asset allocation and 623 625
Capital asset pricing model (CAPM), assumptions of 618
Capital asset pricing model (CAPM), definition 618
Capital asset pricing model (CAPM), heteroskedasticity and 464
Capital asset pricing model (CAPM), probability distribution and 232
Capital asset pricing model (CAPM), risk adjustment and 414
Capital budgeting 58
Capital market line (CML) 617 618
Capital structure 58
Cash flow additivity principle 30 35
Cash flow(s) see also "Discounted cash flow applications"
Cash flow(s), future value of series of 13—15
Cash flow(s), future value of single 4—13
Cash flow(s), incremental 58
Cash flow(s), ordinary annuity and 13—14
Cash flow(s), present value of series of 18—26
Cash flow(s), present value of single 15—18
Cash flow(s), unequal 15
CD equivalent yield see "Money market yield"
Central limit theorem 292—295 328
Central limit theorem, definition 292
Central limit theorem, example 293—294
Central limit theorem, Monte Carlo simulation and 293—294
Central limit theorem, normal distribution and 263
Central limit theorem, population distribution and 339
Central limit theorem, sampling and 286
Central tendency, measure of 103—120
Central tendency, measure of, arithmetic mean 103—107
Central tendency, measure of, comparison of values of means 120
Central tendency, measure of, geometric mean 115—119
Central tendency, measure of, harmonic mean 119—120
Central tendency, measure of, median 108—110
Central tendency, measure of, mode 110—112
Central tendency, measure of, weighted mean 112—115
Chain rule of forecasting and multiperiod forecasts 533—536
Chebyshev's inequality 137—138 249
Coefficient of variation (cv) 139—140
Combination 217
Common size statements 483
Company fundamental factors 651
Company share-related factors 652
Complement 192
Compounding see also "Interest rate(s)"
Compounding, continuous 10—12
Compounding, definition 4
Compounding, examples 9—10 11
Compounding, frequency of 9—10
Compounding, future value effect from 11
Compounding, importance of 5
Conditional expected values 196
Conditional variances 198—199
Confidence interval 253—254 325
Confidence interval for population mean 297—303
Confidence interval, chi-square test and 352
Confidence interval, construction of 297—298
Confidence interval, definition 297
Confidence interval, degree of confidence 207
Confidence interval, hypothesis tests and 332 405 406
Confidence interval, one-sided 297
Confidence interval, regression forecasts and 416—418
Confidence interval, reliability factors for 299
Confidence interval, sample size selection 303 304—305
Confidence interval, Sharpe ratio and 300 302—303
Confidence interval, two-sided 297
Consistent estimator 296—297
Constants-proportions strategy 114
Continuous compounded return 262 264
Continuous random variables 232 246—266
Continuous random variables, applications of normal distribution 257—260
Continuous random variables, definition 233
Continuous random variables, integration and 195
Continuous random variables, lognormal distribution 260—266
Continuous random variables, normal distribution 250—257
Continuous random variables, rate of return as 233
Continuous random variables, uniform distribution 246—249
Correlation, analysis 376—395
Correlation, analysis examples 384—391
Correlation, analysis limitations 381—384
Correlation, analysis uses 384—391
Correlation, coefficient 377
Correlation, coefficient, calculating and interpreting 379—381
Correlation, coefficient, testing significance of 392—395
Correlation, definitions 207 591
Correlation, examples 384—391 392—394
Correlation, exchange rate return 386—387
Correlation, linear association and 377
Correlation, matrix 207
correlation, positive 395
Correlation, properties of 207—208
Correlation, scatter plots and 376—377 378 379 383
Correlation, serial see "Serial correlation and regression errors"
Correlation, spurious 384
Correlation, style analysis 386
Cost averaging 120
Counting, principles of 215—218
Counting, principles of, applying 218
Counting, principles of, labeling problems 216—217
Counting, principles of, multiplication rule of 215
Covariance 204—205
Covariance, computing between random variables 210
Covariance, definitions 204 379
Covariance, effect on portfolio variance 205
Covariance, finite 542
Covariance, historical 209
Covariance, matrix 205—206 625
Covariance, observations about 205
Covariance, return estimating 209
Covariance, sample 379—381
Covariance, stationaiy 562 563 564 565 567
Covariance-stationary series 528—529 541
Credit ratings for bonds 90
Cross-sectional data 105—106 291 395—396 418 449
Cross-sectional data and time-series 289—291
Cumulative distribution function (cdf) 234 236 247—248
Cumulative frequency 94
Cumulative frequency distribution 100 101 102—103
Cumulative probabilities for standard normal distribution 686—687
Cumulative relative frequency 94 103
Data snooping see "Data mining"
Data, graphics presentation of 99—103
Data, graphics presentation of, cumulative frequency distribution 100 101 102—103
Data, graphics presentation of, frequency polygon 100
Data, graphics presentation of, histogram 99—100 101
Data-mining, bias 306—308
Data-mining, definition 306
Data-mining, intergenerational 306—307
Data-mining, signs of use of 307—308
Deciles 120
Default risk premium 3
Degrees of freedom (df) 300—301 335
Degrees of freedom, level of significance table 689
Dependent variable(s) 395 442 490—492
Descriptive statistics 88—89
Dickey — Fuller test for unit root 545—546 562 564 565
Diffuse priors 215
Discount definition 2 73
Discount yield see "Bank discount basis"
Discounted cash flow applications 57—86
Discounted cash flow applications, introduction 57
Discounted cash flow applications, money market yields 72—77
Discounted cash flow applications, net present value and internal rate of return 58—65
Discounted cash flow applications, portfolio return measurement 65—72
Discounted cash flow applications, summary 77—78
Discrete random variables 195 232—246
Discrete random variables, binomial distribution 236—246
Discrete random variables, definition 232—233
Discrete random variables, uniform distribution, discrete 234—236
Discriminant analysis 490
Dispersion, measures of 126—144
Dispersion, measures of, Chebyshev's inequality 137—138
Dispersion, measures of, coefficient of variation 139—140
Dispersion, measures of, definition 126
Dispersion, measures of, interquartile range 127
Dispersion, measures of, mean absolute deviation 127—129
Dispersion, measures of, population variance and population standard deviation 129—132
Dispersion, measures of, range 126—127
Dispersion, measures of, relative 139
Dispersion, measures of, sample variance and sample standard deviation 132—135
Dispersion, measures of, semivariance, semideviation, and related concepts 135—137
Dispersion, measures of, Sharpe ratio 141—144
Distribution-free tests see "Non-parametric tests"
Diversification, portfolio 602 605—609
Dollar-weighted return see "Money-weighted rate of return"
Dummy variables in regressions, using 458—462
Durbin — Watson (DW) statistic, critical values for 694
Durbin — Watson (DW) statistic, testing for correlated errors and 526—527
Durbin — Watson (DW) statistic, testing for serial correlation and 470—472 529
Durbin — Watson (DW) statistic, time-series forecasting and 567
Dutch Book Theorem 184
Earnings per share (EPS), forecasting 194
Earnings per share (EPS), nature of statistics and 88
Economic forecasts, evaluating 384—385
Effective annual rate (EAR) 12
Effective annual yield (EAY) 75 76
Efficiency definition 296
Efficient frontier 594 599 602
Error autocorrelations 530
Error term 395
Estimators see also "Sampling"
Estimators, consistent 296—297
Estimators, point 295—297
Estimators, precision of 298
Estimators, properties of 296
Estimators, questions answered by 295
Estimators, unbiased 296 300
European option 267
European-style option 267
Event(s), definition 180—181
Event(s), dependent 189
Event(s), independent 189
Event(s), multiplication rule for independent 189
Excess kurtosis 150
Exhaustive definition 181
Expected value(s) 115
Expected value(s) of product of uncorrelated random variables, multiplication rule 211
Expected value(s) of random variable 194—195
Expected value(s), calculation of portfolio 203
Expected value(s), conditional 196—197
Expected value(s), definition 194
Expected value(s), properties of 203
Expected value(s), total probability rule for 197
Expected value(s), weight and 203
F-distribution table 690—693
Face value of T-bill 72
Fat tails 252
Financial risk definition 260
Finite population correction (fpc) factor 336
First-differencing 542
Fisher effect regression with lagged dependent variable 486—487
Fisher effect regression with measurement error 488—489
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