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Alexander C. — Market Models: A Guide to Financial Data Analysis
Alexander C. — Market Models: A Guide to Financial Data Analysis



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Название: Market Models: A Guide to Financial Data Analysis

Автор: Alexander C.

Аннотация:

Market Models provides an authoritative and up-to-date treatment of the use of market data to develop models for financial analysis. Written by a leading figure in the field of financial data analysis, this book is the first of its kind to address the vital techniques required for model selection and development. Model developers are faced with many decisions, about the pricing, the data, the statistical methodology and the calibration and testing of the model prior to implementation. It is important to make the right choices and Carol Alexander's clear exposition provides valuable insights at every stage.
In each of the 13 Chapters, Market Models presents real world illustrations to motivate theoretical developments. The accompanying CD contains spreadsheets with data and programs; this enables you to implement and adapt many of the examples. The pricing of options using normal mixture density functions to model returns; the use of Monte Carlo simulation to calculate the VaR of an options portfolio; modifying the covariance VaR to allow for fat-tailed P&L distributions; the calculation of implied, EWMA and 'historic' volatilities; GARCH volatility term structure forecasting; principal components analysis; and many more are all included.
Carol Alexander brings many new insights to the pricing and hedging of options with her understanding of volatility and correlation, and the uncertainty which surrounds these key determinants of option portfolio risk. Modelling the market risk of portfolios is covered where the main focus is on a linear algebraic approach; the covariance matrix and principal component analysis are developed as key tools for the analysis of financial systems. The traditional time series econometric approach is also explained with coverage ranging from the application cointegration to long-short equity hedge funds, to high-frequency data prediction using neural networks and nearest neighbour algorithms.
Throughout this text the emphasis is on understanding concepts and implementing solutions. It has been designed to be accessible to a very wide audience: the coverage is comprehensive and complete and the technical appendix makes the book largely self-contained.
Market Models: A Guide to Financial Data Analysis is the ideal reference for all those involved in market risk measurement, quantitative trading and investment analysis.


Язык: en

Рубрика: Экономика и финансы/

Статус предметного указателя: Готов указатель с номерами страниц

ed2k: ed2k stats

Год издания: 2001

Количество страниц: 494

Добавлена в каталог: 19.09.2006

Операции: Положить на полку | Скопировать ссылку для форума | Скопировать ID
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Предметный указатель
VaR (value-at-risk) models, normality assumption      185
VaR (value-at-risk) models, not sub-additive      259
VaR (value-at-risk) models, P&L      180 253 254 262—263
VaR (value-at-risk) models, portfolio volatility      185
VaR (value-at-risk) models, process volatility      139
VaR (value-at-risk) models, risk evaluation      249—283
VaR (value-at-risk) models, risk management      236 259
VaR (value-at-risk) models, RiskMetrics data      102 203—204
VaR (value-at-risk) models, scenario analysis      278—281
VaR (value-at-risk) models, sensitivity analysis      277—278
VaR (value-at-risk) models, short risk horizons      186
VaR (value-at-risk) models, simulation      267—274
VaR (value-at-risk) models, stress testing      278 281—283
VaR (value-at-risk) models, tails prediction      125
VaR (value-at-risk) models, trading limits      257
VaR (value-at-risk) models, traditional measures compared      256—257
Variance estimation and forecasting, exponentially weighted moving average (EWMA)      127 163
Variance estimation and forecasting, h-period      100
Variance estimation and forecasting, one-step ahead      99
Variance estimation and forecasting, parameters      50
Variance estimation and forecasting, regression      123 124
Variance estimation and forecasting, squared returns      123 124
Variance estimation and forecasting, standard error      127
Variance estimation and forecasting, weighted average      126
Variance, analysis of variance (ANOVA)      427—428
Variance, conditional heteroscedasticity      14
Variance, confidence intervals      126
Variance, linear portfolios      180—182 183
Variance, minimum      see "Minimum variance portfolios"
Variance, P&L      181—182
Variance, quadratic      181
Vech models, bivariate GARCH      16 108 109 110
Vech models, diagonal      108 109 110 114 217 218 219
Vech models, parameter estimates      219
Vech models, parameterization      114
Vega, ATM options      44
Vega, Black — Scholes model      32 44
Vega, volatility sensitivity      24
Volatility      see also "Implied volatility" "Process "Statistical "Realized
Volatility clustering, asymmetry      68 79
Volatility clustering, autoregressive conditional heteroscedasticity (ARCH)      63 65—67 97 386
Volatility clustering, commodity markets      65
Volatility clustering, currency markets      65 97
Volatility clustering, equity markets      65
Volatility clustering, excess kurtosis      66 67
Volatility clustering, mean-reversion      31
Volatility clustering, news announcements      65—66
Volatility clustering, skews      66 67
Volatility clustering, square root of time rule      97
Volatility cones      29
Volatility estimates and forecasts, A-GARCH      80—81 99
Volatility estimates and forecasts, academic research      120
Volatility estimates and forecasts, benchmark forecast      118
Volatility estimates and forecasts, central values      119
Volatility estimates and forecasts, combined forecasts      118 129—134
Volatility estimates and forecasts, confidence intervals      118 119 126—134
Volatility estimates and forecasts, different horizons      29 98
Volatility estimates and forecasts, evaluation      117
Volatility estimates and forecasts, exponential GARCH (E-GARCH)      80
Volatility estimates and forecasts, exponentially weighted moving average (EWMA)      57—58 60 119
Volatility estimates and forecasts, extreme values      119
Volatility estimates and forecasts, GARCH      73—75 81 93 98 99—100
Volatility estimates and forecasts, historic volatility      50—52 57 128
Volatility estimates and forecasts, I-GARCH      76 77
Volatility estimates and forecasts, implied volatility      117—118 124—125
Volatility estimates and forecasts, long-term      85—91 92 98 99
Volatility estimates and forecasts, look-back periods      57
Volatility estimates and forecasts, mark-to-model values      135
Volatility estimates and forecasts, mean-reversion      75 79
Volatility estimates and forecasts, moving averages      126—128
Volatility estimates and forecasts, out-of-sample likelihood      121
Volatility estimates and forecasts, point forecasts      118 126
Volatility estimates and forecasts, process volatility      117 118 129
Volatility estimates and forecasts, risk horizons      11 43 57 60 117
Volatility estimates and forecasts, root mean square error (RMSE)      122—123
Volatility estimates and forecasts, standard deviation      121
Volatility estimates and forecasts, standard error      118—119 126 127
Volatility estimates and forecasts, straddles      124
Volatility estimates and forecasts, uncertainty      119
Volatility estimates and forecasts, underlying volatility      117
Volatility estimates and forecasts, variance      50
Volatility sensitivity, ATM volatility      167 168 169
Volatility sensitivity, option vega      24
Volatility sensitivity, prices      34 43 44
Volatility smile surface, implied volatility      106 154
Volatility smile surface, N-GARCH      81 106 107
Volatility smile surface, volatility surface distinguished      33
Volatility surfaces, implied volatility      32—34
Volatility surfaces, parameterization      167—170
Volatility surfaces, quadratic      38 45 144 168
Volatility surfaces, Taylor approximations      169
Volatility surfaces, volatility process      11
Volatility surfaces, volatility smile surface distinguished      33
Volatility term structures, call options      31 32
Volatility term structures, constant volatility      61 99
Volatility term structures, convergence      12 75 76 97—98 102—103
Volatility term structures, currency markets      102
Volatility term structures, equity markets      101—103
Volatility term structures, GARCH models      32 50 61 64 80 85 98—103 212
Volatility term structures, implied volatility      31—32 78
Volatility term structures, mean-reversion      61 98 109 111
Volatility term structures, put options      31 32
Volatility term structures, returns of different frequencies      5
Volatility term structures, scenario analysis      92
Volatility, basic concept      3—4
Volatility, basket options      56—57
Volatility, bursts, clusters      see "Volatility clustering"
Volatility, common volatility      386—387
Volatility, conditional      12 14
Volatility, dispersion, measure      4 119
Volatility, financial markets      9—12 119 250 297
Volatility, hedging      139—140
Volatility, irreducible risk      9
Volatility, long-term      57 85
Volatility, parallel shifts      38
Volatility, persistence      see "Persistence"
Volatility, reaction      59 73 86 90
Volatility, smile      see "Smile effect" "Volatility
Volatility, spiky      73 78 85 86 91
Volatility, surfaces      see "Volatility smile surface" "Volatility
Volatility, time horizon      18
Volatility, time-varying volatility models      12—14
Volatility, uncertainty      18
Weibull distribution      293 294
Weighted average      see also "Historic correlation" "Historic
Weighted average, beta      109
Weighted average, EWMA      see "Exponentially weighted moving average"
Weighted average, ghost features      53 60 125
Weighted average, historic volatility      49 50 52—53
Weighted average, RiskMetrics data      179 201
Weighted average, sampling error      49
Weighted average, short-term      53
Weighted average, unconditional correlation      49
Weighted average, unconditional variance      50
Weighted average, unconditional volatility      49
Weighted average, variance forecasts      126
White's test      432
Wiener process      21 104
WTI (West Texas Intermediate)      55 78 111
Yield curves, modelling multiple yield curves      149—153
Yield curves, principal component analysis (PCA)      147—153
Yield curves, scenario analysis      143
Yield curves, trend/tilt/convexity      147—149
Zero-coupon bonds      147—148 182 216
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