Buch, Englisch, 672 Seiten, Format (B × H): 157 mm x 235 mm, Gewicht: 1113 g
ISBN: 978-0-470-40093-7
Verlag: Wiley
A comprehensive look at how probability and statistics is applied to the investment process
Finance has become increasingly more quantitative, drawing on techniques in probability and statistics that many finance practitioners have not had exposure to before. In order to keep up, you need a firm understanding of this discipline.
Probability and Statistics for Finance addresses this issue by showing you how to apply quantitative methods to portfolios, and in all matter of your practices, in a clear, concise manner. Informative and accessible, this guide starts off with the basics and builds to an intermediate level of mastery.
• Outlines an array of topics in probability and statistics and how to apply them in the world of finance
• Includes detailed discussions of descriptive statistics, basic probability theory, inductive statistics, and multivariate analysis
• Offers real-world illustrations of the issues addressed throughout the text
The authors cover a wide range of topics in this book, which can be used by all finance professionals as well as students aspiring to enter the field of finance.
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
Preface xv
About the Authors xvii
Chapter 1 Introduction 1
Probability vs. Statistics 4
Overview of the Book 5
Part One Descriptive Statistics 15
Chapter 2 Basic Data Analysis 17
Data Types 17
Frequency Distributions 22
Empirical Cumulative Frequency Distribution 27
Data Classes 32
Cumulative Frequency Distributions 41
Concepts Explained in this Chapter 43
Chapter 3 Measures of Location and Spread 45
Parameters vs. Statistics 45
Center and Location 46
Variation 59
Measures of the Linear Transformation 69
Summary of Measures 71
Concepts Explained in this Chapter 73
Chapter 4 Graphical Representation of Data 75
Pie Charts 75
Bar Chart 78
Stem and Leaf Diagram 81
Frequency Histogram 82
Ogive Diagrams 89
Box Plot 91
QQ Plot 96
Concepts Explained in this Chapter 99
Chapter 5 Multivariate Variables and Distributions 101
Data Tables and Frequencies 101
Class Data and Histograms 106
Marginal Distributions 107
Graphical Representation 110
Conditional Distribution 113
Conditional Parameters and Statistics 114
Independence 117
Covariance 120
Correlation 123
Contingency Coefficient 124
Concepts Explained in this Chapter 126
Chapter 6 Introduction to Regression Analysis 129
The Role of Correlation 129
Regression Model: Linear Functional Relationship Between Two Variables 131
Distributional Assumptions of the Regression Model 133
Estimating the Regression Model 134
Goodness of Fit of the Model 138
Linear Regression of Some Nonlinear Relationship 140
Two Applications in Finance 142
Concepts Explained in this Chapter 149
Chapter 7 Introduction to Time Series Analysis 153
What Is Time Series? 153
Decomposition of Time Series 154
Representation of Time Series with Difference Equations 159
Application: The Price Process 159
Concepts Explained in this Chapter 163
Part Two Basic Probability Theory 165
Chapter 8 Concepts of Probability Theory 167
Historical Development of Alternative Approaches to Probability 167
Set Operations and Preliminaries 170
Probability Measure 177
Random Variable 179
Concepts Explained in this Chapter 185
Chapter 9 Discrete Probability Distributions 187
Discrete Law 187
Bernoulli Distribution 192
Binomial Distribution 195
Hypergeometric Distribution 204
Multinomial Distribution 211
Poisson Distribution 216
Discrete Uniform Distribution 219
Concepts Explained in this Chapter 221
Chapter 10 Continuous Probability Distributions 229
Continuous Probability Distribution Described 229
Distribution Function 230
Density Function 232
Continuous Random Variable 237
Computing Probabilities from the Density Function 238
Location Parameters 239
Dispersion Parameters 239
Concepts Explained in this Chapter 245
Chapter 11 Continuous Probability Distributions with Appealing Statistical Properties 247
Normal Distribution 247
Chi-Square Distribution 254
Student’s t-Distribution 256
F-Distribution 260
Exponential Distribution 262
Rectangular Distribution 266
Gamma Distribution 268
Beta Distribution 269
Log-Normal Distribution 271
Concepts Explained in this Chapter 275
Chapter 12 Continuous Probability Distributions Dealing with Extreme Events 277
Generalized Extreme Value Distribution 277
Generalized Pareto Distribution 281
Normal Inverse Gaussian Distribution 283
a-Stable Distribution 285
Concepts Explained in this Chapter 292
Chapter 13 Parameters of Location
