This book is an exploration of statistical methodologies and their applications in finance. Readers are taken on a journey in each chapter through practical explanations and examples, enabling them to develop a solid foundation of these methods in R and their applications in finance.
This book is an exploration of statistical methodologies and their applications in finance. Readers are taken on a journey in each chapter through practical explanations and examples, enabling them to develop a solid foundation of these methods in R and their applications in finance.
Jenny K. Chen graduated with a Master's and Bachelor's degree in the Department of Statistics and Data Science at Cornell University. With expertise honed through academic pursuits and her current role as a quantitative product manager at Morgan Stanley, she is particularly interested in the applications of statistical modelling in finance and portfolio management. She was the youngest published author at the Joint Statistical Meetings in 2016 and has published several research papers in statistical modelling and data analytics.
Inhaltsangabe
1. Introduction to R 2. Linear Regression 3. Transition from Linear to Nonlinear Regression 4. Nonlinear Regression Modeling 5. The Logistic Regression 6. The Poisson Regression: Models for Count Data 7. Autoregressive Integrated Moving-Average Models 8. Generalized AutoRegressive Conditional Heteroskedasticity Model 9. Cointegration 10. Financial Statistical Modeling in Risk and Wealth Management Bibliography
1. Introduction to R 2. Linear Regression 3. Transition from Linear to Nonlinear Regression 4. Nonlinear Regression Modeling 5. The Logistic Regression 6. The Poisson Regression: Models for Count Data 7. Autoregressive Integrated Moving-Average Models 8. Generalized AutoRegressive Conditional Heteroskedasticity Model 9. Cointegration 10. Financial Statistical Modeling in Risk and Wealth Management Bibliography
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