Interest rate models

Paris-princeton lectures on mathematical finance 2004

<p>Although there are many books on mathematical finance, few deal with the statistical aspects of modern data analysis as applied to financial problems. This textbook fills this gap by addressing some of the most challenging issues facing financial engineers. It shows how sophisticated mathematics and modern statistical techniques can be used in the solutions of concrete financial problems. Conce...

Univariate Data Distributions.- Heavy Tail Distributions.- Dependence and Multivariate Data Exploration.- Parametric Regression.- Local and Nonparametric Regression.- Time Series Models.- Multivariate Time Series, Linear Systems and Kalman Filtering.- Nonlinear Time Series: Models and Simulation.- Appendices.- Indices.

Univariate Data Distributions.- Heavy Tail Distributions.- Dependence and Multivariate Data Exploration.- Parametric Regression.- Local and Nonparametric Regression.- Time Series Models.- Multivariate Time Series, Linear Systems and Kalman Filtering.- Nonlinear Time Series: Models and Simulation.- Appendices.- Indices.

Although there are many books on mathematical finance, few deal with the statistical aspects of modern data analysis as applied to financial problems. This textbook fills this gap by addressing some of the most challenging issues facing financial engineers. It shows how sophisticated mathematics and modern statistical techniques can be used in the solutions of concrete financial problems. Concerns...

Univariate Data Distributions.- Heavy Tail Distributions.- Dependence and Multivariate Data Exploration.- Parametric Regression.- Local and Nonparametric Regression.- Time Series Models.- Multivariate Time Series, Linear Systems and Kalman Filtering.- Nonlinear Time Series: Models and Simulation.- Appendices.- Indices.

Univariate Data Distributions.- Heavy Tail Distributions.- Dependence and Multivariate Data Exploration.- Parametric Regression.- Local and Nonparametric Regression.- Time Series Models.- Multivariate Time Series, Linear Systems and Kalman Filtering.- Nonlinear Time Series: Models and Simulation.- Appendices.- Indices.

Although there are many books on mathematical finance, few deal with the statistical aspects of modern data analysis as applied to financial problems. This textbook fills this gap by addressing some of the most challenging issues facing financial engineers. It shows how sophisticated mathematics and modern statistical techniques can be used in the solutions of concrete financial problems. Concerns...

Univariate Data Distributions.- Heavy Tail Distributions.- Dependence and Multivariate Data Exploration.- Parametric Regression.- Local and Nonparametric Regression.- Time Series Models.- Multivariate Time Series, Linear Systems and Kalman Filtering.- Nonlinear Time Series: Models and Simulation.- Appendices.- Indices.