发帖
雷达卡
Authors: Cheng-Few Lee, John Lee, Jow-Ran Chang, Tzu Tai
Excel 2013, MINITAB17, and SAS are integrated into the study and use of statistical analysis
Programming – includes advanced applications of Excel (VBA – Visual Basic for Application)
All Excel macros published for users to study
Pedagogy from a business perspective – implementation of statistical concepts via case-study approach
Each chapter uses data from individual stocks, stock indices, options, and futures
A practical case-study based textbook for courses in business statistics, investment analysis, options, and futures
An in-depth reference for statistical analysis using multiple software packages for financial industry professionals
This introductory textbook for business statistics teaches statistical analysis and research methods via business case studies and financial data using Excel, MINITAB, and SAS. Every chapter in this textbook engages the reader with data of individual stock, stock indices, options, and futures.
One studies and uses statistics to learn how to study, analyze, and understand a data set of particular interest. Some of the more popular statistical programs that have been developed to use statistical and computational methods to analyze data sets are SAS, SPSS, and MINITAB.
Of those, we look at MINITAB and SAS in this textbook. One of the main reasons to use MINITAB is that it is the easiest to use among the popular statistical programs. We look at SAS because it is the leading statistical package used in industry. We also utilize the much less costly and ubiquitous Microsoft Excel to do statistical analysis, as the benefits of Excel have become widely recognized in the academic world and its analytical capabilities extend to about 90 percent of statistical analysis done in the business world. We demonstrate much of our statistical analysis using Excel and double check the analysis and outcomes using MINITAB and SAS – also helpful in some analytical methods not possible or practical to do in Excel.
Table of contents (32 chapters)
Front Matter
Statistical Analysis
• Front Matter
• Introduction
• Data Collection, Presentation, and Yahoo Finance
• Histograms and the Rate of Returns of JPM and JNJ
• Numerical Summary Measures on Rate of Returns of Amazon, Walmart, and the S&P 500
• Probability Concepts and Their Analysis
• Discrete Random Variables and Probability Distributions
• The Normal and Lognormal Distributions
• Sampling Distributions and Central Limit Theorem
• Other Continuous Distributions
• Estimation
• Hypothesis Testing
• Analysis of Variance and Chi-Square Tests
• Simple Linear Regression and the Correlation Coefficient
• Simple Linear Regression and Correlation: Analyses and Applications
• Multiple Linear Regression
• Residual and Regression Assumption Analysis
• Nonparametric Statistics
• Time Series: Analysis, Model, and Forecasting
• Index Numbers and Stock Market Indexes
• Sampling Surveys: Methods and Applications
• Statistical Decision Theory
Advanced Applications of Microsoft Excel Programs in Financial Analysis
• Front Matter
• Introduction to Excel Programming
• Introduction to VBA Programming
• Professional Techniques Used in Excel and Excel VBA Techniques
• Binomial Option Pricing Model Decision Tree Approach
• Microsoft Excel Approach to Estimating Alternative Option Pricing Models
• Alternative Methods to Estimate Implied Variance
• Greek Letters and Portfolio Insurance
• Portfolio Analysis and Option Strategies
• Simulation and Its Application
Applications of SAS Programs to Financial Analysis
• Front Matter
• Application of Simultaneous Equation in Finance Research: Methods and Empirical Results
• Hedge Ratios: Theory and Applications
Back Matter
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