Nonparametric Finance
eBook - ePub

Nonparametric Finance

  1. English
  2. ePUB (mobile friendly)
  3. Available on iOS & Android
eBook - ePub

Nonparametric Finance

About this book

An Introduction to Machine Learning in Finance, With Mathematical Background, Data Visualization, and R

Nonparametric function estimation is an important part of machine learning, which is becoming increasingly important in quantitative finance. Nonparametric Finance provides graduate students and finance professionals with a foundation in nonparametric function

estimation and the underlying mathematics. Combining practical applications, mathematically rigorous presentation, and statistical data analysis into a single volume, this book presents detailed instruction in discrete chapters that allow readers to dip in as needed without reading from beginning to end.

Coverage includes statistical finance, risk management, portfolio management, and securities pricing to provide a practical knowledge base, and the introductory chapter introduces basic finance concepts for readers with a strictly mathematical background. Economic significance

is emphasized over statistical significance throughout, and R code is provided to help readers reproduce the research, computations, and figures being discussed. Strong graphical content clarifies the methods and demonstrates essential visualization techniques, while deep mathematical and statistical insight backs up practical applications.

Written for the leading edge of finance, Nonparametric Finance:

• Introduces basic statistical finance concepts, including univariate and multivariate data analysis, time series analysis, and prediction

• Provides risk management guidance through volatility prediction, quantiles, and value-at-risk

• Examines portfolio theory, performance measurement, Markowitz portfolios, dynamic portfolio selection, and more

• Discusses fundamental theorems of asset pricing, Black-Scholes pricing and hedging, quadratic pricing and hedging, option portfolios, interest rate derivatives, and other asset pricing principles

• Provides supplementary R code and numerous graphics to reinforce complex content

Nonparametric function estimation has received little attention in the context of risk management and option pricing, despite its useful applications and benefits. This book provides the essential background and practical knowledge needed to take full advantage of these little-used methods, and turn them into real-world advantage.

Jussi Klemelä, PhD, is Adjunct Professor at the University of Oulu. His research interests include nonparametric function estimation, density estimation, and data visualization. He is the author of Smoothing of Multivariate Data: Density Estimation and Visualization and Multivariate Nonparametric Regression and Visualization: With R and Applications to Finance.

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Yes, you can access Nonparametric Finance by Jussi Klemelä in PDF and/or ePUB format, as well as other popular books in Mathematics & Probability & Statistics. We have over one million books available in our catalogue for you to explore.

Information

Publisher
Wiley
Year
2018
Print ISBN
9781119409106
eBook ISBN
9781119409120

Table of contents

  1. Cover
  2. Title Page
  3. Copyright
  4. Table of Contents
  5. Preface
  6. Chapter 1: Introduction
  7. Part I: Statistical Finance
  8. Part II: Risk Management
  9. Part III: Portfolio Management
  10. Part IV: Pricing of Securities
  11. References
  12. Index
  13. End User License Agreement