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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
Sharpe ratio, negative 142
Sharpe ratio, portfolio choice and 620 621 622
Sharpe ratio, positive 142
Sharpe ratio, safety-first ratio versus 258
Sharpe ratio, Spearman rank correlation and 358—359
Shortfall risk 257 259
Shorting stock 184
Shrinkage estimators 625
Simulation trial 267
Skewed/skewness in return distribution 144 146—149
Spearman rank correlation 357—360
Standard deviation, definitions 129 195
Standard deviation, equity market returns 135
Standard deviation, interpreting 139 195
Standard deviation, using 135
Standard error of estimate (SEE) 401—403 407
Standard error of sample mean 292
Standardized beta definition 643
standardizing 255
Stationarity tests 489—490
Statistical concepts and market returns 87—177
Statistical concepts and market returns, fundamental concepts, some 88—91
Statistical concepts and market returns, geometric and arithmetic means, using 153—155
Statistical concepts and market returns, graphic presentation of data 99—103
Statistical concepts and market returns, introduction 88
Statistical concepts and market returns, kurtosis in return distribution 149—153
Statistical concepts and market returns, measurement scales 89—91
Statistical concepts and market returns, measures of central tendency 103—120
Statistical concepts and market returns, measures of dispersion 126—144
Statistical concepts and market returns, populations and samples 89
Statistical concepts and market returns, quantiles as measure of locations 120—126
Statistical concepts and market returns, summarizing data using frequency distributions 91—99
Statistical concepts and market returns, summary 155—157
Statistical concepts and market returns, symmetry and skewness in return distributions 144—149
Statistical factor models 634 652
Statistical inference 88 89 295 325 see
Statistics, definitions 88 89 286
Statistics, descriptive 88—89
Statistics, inferential 88
Statistics, nature of 88—89
Statistics, sampling distribution of 287 292
Statistics, test 327
Stratified random sampling 288—289
Stress testing/scenario analysis 260
Student's t-distribution table 688
Summarizing data using frequency distributions 91—99
Surprise definition 634
Survey of Professional Forecasters (SPP) 384
Survivorship bias in sample selection 308—309 310—311 333
Symmetry and skewness in return distributions 144—149
Systematic factors 633
T-bill see "U.S. Treasury bill"
t-test 335—336 339 342 347 357 406
Target semideviation 136 137
Target semivariance 136 137
Time value of money (TVM) 1—55
Time value of money (TVM), examples 6—8 9—10 11 14 16—17 18 19—20 20—22 23 24 25 27—28 29—30 30—33
Time value of money (TVM), future value of series of cash flows 13—15
Time value of money (TVM), future value of single cash flow 4—13
Time value of money (TVM), interest rates interpretation 2—3
Time value of money (TVM), introduction 1—2
Time value of money (TVM), present value of series of cash flows 18—26
Time value of money (TVM), present value of single cash flow 15—18
Time value of money (TVM), solving for rates, number of periods, or size of annuity payments 26—35
Time value of money (TVM), stationary 529
Time value of money (TVM), summary 36
Time-period bias in sample selection 310 311 333
Time-series analysis 515—585
Time-series analysis, autocorrelations 529—530
Time-series analysis, autoregressive conditional heteroskedasticity models 559—562 568
Time-series analysis, autoregressive models see "Autoregressive (AR) time-series models"
Time-series analysis, autoregressive moving-average models 558—559
Time-series analysis, chain rule of forecasting 533
Time-series analysis, challenges of working with 517—518
Time-series analysis, cointegrated 563 564
Time-series analysis, comparing forecast model performance 536—538
Time-series analysis, data 105 396 418 449
Time-series analysis, definition 516
Time-series analysis, examples 516—517 519—521 522—526 531—532 533—536 537—538 539—540 542—544 546—548 549 552—553 553—558 560—561 562 563 564—565
Time-series analysis, first-differencing 543
Time-series analysis, forecasting steps, suggested 566—568
Time-series analysis, instability of regression coefficients 538—540
Time-series analysis, introduction 516—517
Time-series analysis, logical ordering of 526
Time-series analysis, mean reversion 532—533
Time-series analysis, misspecifications 486—490
Time-series analysis, moving-average model 548—553 567
Time-series analysis, multiperiod forecasts 533
Time-series analysis, random walks 490 541—545
Time-series analysis, regressions with multiple 562—566
Time-series analysis, seasonality in models 553—558 567 568
Time-series analysis, stationary 545
Time-series analysis, summary 568—570
Time-series analysis, trend models see "Trend models in time series"
Time-series analysis, uncertainty of forecasts 566
Time-series analysis, unit root tests see "Unit root tests"
Time-series and cross-sectional data 289—291
Time-weighted rate of return 66 67—72
Time-weighted rate of return, computation steps 67
Time-weighted rate of return, definition 67
Time-weighted rate of return, examples 69—72
Total probability for expected value 197
Total probability rule 192 193—194
Tracking error (TE) 242 243 655
Tracking risk 242 243 655
Tree diagram 197—198
Trend models in time series 518—527
Trend models in time series for correlated errors 526—527
Trend models in time series, Durbin — Watson test and 526—527
Trend models in time series, examples 519—521 522—526
Trend models in time series, linear 518—521
Trend models in time series, log-linear 521—526 527
Trimmed mean 107
U.S. Treasury bill(s) 3
U.S. Treasury bill(s) as pure discount instrument 72—73 75
U.S. Treasury bill(s) as risk-free asset 609
U.S. Treasury bill(s), equivalents, other countries 3
U.S. Treasury bill(s), face value of 72
U.S. Treasury bill(s), quoting conventions for 73
Unbiased estimator 296
Uniform distribution, continuous 246—249
Unit root test see also "Dickey — Fuller test for unit root"
Unit root test of nonstationarity 545—548
Unit root test, examples 562 563 565
Unit root test, Fisher effect and 562
Unit root test, time series regressions and 562—564
Univariate distribution 251
Value at Risk (VaR) 260
Variable(s), dummy 458—462
Variable(s), models with qualitative dependent variables 490—492
Variable(s), random 180
Variance 195—196
Variance of binomial random variables 243
Variance of return 205
Variance, analysis of (ANOVA) 335 413—415 445 454—456
Variance, conditional 198—199
Variance, conditional versus unconditional 198—199
Variance, definitions 129 195
Variance, hypothesis tests concerning 351—356
Variance, portfolio expected return and variance of return 202—211
Variation, coefficient of 139—140
Volatility 264—265
Weighted mean 112—115
Weighted mean formula 113
Weighted-average cost of capital (WACC) 58
White-corrected standard errors 468
Winsorized mean 107
Working capital management 58
Yield definition 74
Yield to maturity (YTM) see "Internal rate of return"
z-test alternative 339—340 341—342
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