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Statistical analysis of financial data : with examples in R / James Gentle.

By: Gentle, James E, 1943- [author.].

Material type: Text

TextSeries: Chapman & Hall/CRC texts in statistical science series.Publisher: Boca Raton : CRC Press, 2020Edition: 1st.Description: xix, 645 pages; PDS 89.99 ill.; 24 cms.Content type: text Media type: computer Carrier type: online resourceISBN: 9780429939228 (ePub ebook) :; 9780429939235 (PDF ebook) :; 9780429939211 (Mobipocket ebook) :; 9780429485602 (ebook) :.Subject(s): Finance -- Mathematical models | Finance -- Econometric models | R (Computer program language) | Management and Business StudiesAdditional physical formats: Print version :: No titleDDC classification: 332.0151955

Contents:

1.      The Nature of Financial Data <OL>Financial Time Series Autocorrelations Stationarity Time Scales and Data Aggregation Financial Assets and Markets Markets and Regulatory Agencies Interest Returns on Assets Stock Prices; Fair Market Value Splits, Dividends, and Return of Capital Indexes and "the Market" Derivative Assets Short Positions Portfolios of Assets: Diversification and Hedging Frequency Distributions of Returns Location and Scale Skewness Kurtosis Multivariate Data The Normal Distribution Q-Q Plots Outliers Other Statistical Measures Volatility The Time Series of Returns Measuring Volatility: Historical and Implied Volatility Indexes: The VIX The Curve of Implied Volatility Risk Assessment and Management Market Dynamics Stylized Facts about Financial Data Notes and Further Reading Exercises and Questions for Review Appendix A: Accessing and Analyzing Financial Data in R A R Basics A Data Repositories and Inputting Data into R A Time Series and Financial Data in R A Data Cleansing Notes, Comments, and Further Reading on R Exercises in R </OL>2.       Exploratory Financial Data Analysis <OL>Data Reduction Simple Summary Statistics Centering and Standardizing Data Simple Summary Statistics for Multivariate Data Transformations Identifying Outlying Observations The Empirical Cumulative Distribution Function Nonparametric Probability Density Estimation Binned Data Kernel Density Estimator Multivariate Kernel Density Estimator Graphical Methods in Exploratory Analysis Time Series Plots Histograms Boxplots Density Plots Bivariate Data Q-Q Plots Graphics in R Notes and Further Reading Exercises </OL>3.       Probability Distributions in Models of Observable Events <OL>Random Variables and Probability Distributions Discrete Random Variables Continuous Random Variables Multivariate Distributions Measures of Association in Multivariate Distributions Copulas Transformations of Multivariate Random Variables Distributions of Order Statistics Asymptotic Distributions; The Central Limit Theorem The Tails of Probability Distributions Sequences of Random Variables; Stochastic Processes Diffusion of Stock Prices and Pricing of Options Some Useful Probability Distributions Discrete Distributions Continuous Distributions Multivariate Distributions General Families of Distributions Useful in Modeling Constructing Multivariate Distributions Modeling of Data-Generating Processes R Functions for Probability Distributions Simulating Observations of a Random Variable Uniform Random Numbers Generating Nonuniform Random Numbers Simulating Data in R Notes and Further Reading Exercises </OL>4.       Statistical Models and Methods of Inference <OL>Models Fitting Statistical Models Measuring and Partitioning Observed Variation Linear Models Nonlinear Variance-Stabilizing Transformations Parametric and Nonparametric Models Bayesian Models Models for Time Series Criteria and Methods for Statistical Modeling Estimators and Their Properties Methods of Statistical Modeling Optimization in Statistical Modeling; Least Squares and Other ApplicationsThe General Optimization Problem Least Squares Maximum Likelihood R Functions for Optimization Statistical Inference Confidence Intervals Testing Statistical Hypotheses Prediction Inference in Bayesian Models Resampling Methods; The Bootstrap Robust Statistical Methods Estimation of the Tail Index Estimation of VaR and Expected Shortfall Models of Relationships among Variables Principal Components Regression Models Linear Regression Models Linear Regression Models: The Regressors Linear Regression Models: Individual Observations and ResidualsLinear Regression Models: An Example Nonlinear Models Specifying Models in R Assessing the Adequacy of Models Goodness-of-Fit Tests; Tests for Normality Cross Validation Model Selection and Model Complexity Notes and Further Reading Exercises </OL>5.       Discrete Time Series Models and Analysis <OL></OL>          Basic Linear Operations           The Backshift Operator           The Difference Operator           The Integration Operator           Summation of an Infinite Geometric Series           Linear Difference Equations           Trends and Detrending           Cycles and Seasonal Adjustment           Analysis of Discrete Time Series Models           Stationarity           Sample Autocovariance and Autocorrelation Functions; Estimators          Statistical Inference in Stationary Time Series           Autoregressive and Moving Average Models           Moving Average Models; MA(q)           Autoregressive Models; AR(p)           The Partial Autocorrelation Function (PACF)           ARMA and ARIMA Models           Simulation of ARMA and ARIMA Models           Statistical Inference in ARMA and ARIMA Models           Selection of Orders in ARIMA Models  &nbsp

List(s) this item appears in: 2023-06-10

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Item type	Current location	Call number	Status	Date due	Barcode	Item holds
Book	Chennai Mathematical Institute General Stacks	519.535 GEN (Browse shelf)	Available		11063

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Statistical analysis of financial data : with examples in R / James Gentle.

By: Gentle, James E, 1943- [author.].