{"product_id":"nonparametric-finance","title":"Nonparametric Finance","description":"\u003cp\u003e\u003cb\u003eAn Introduction to Machine Learning in Finance, With Mathematical Background, Data Visualization, and R\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eNonparametric function estimation is an important part of machine learning, which is becoming increasingly important in quantitative finance. \u003ci\u003eNonparametric Finance \u003c\/i\u003eprovides graduate students and finance professionals with a foundation in nonparametric function\u003c\/p\u003e \u003cp\u003eestimation 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.\u003c\/p\u003e \u003cp\u003eCoverage 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\u003c\/p\u003e \u003cp\u003eis 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.\u003c\/p\u003e \u003cp\u003eWritten for the leading edge of finance, \u003ci\u003eNonparametric Finance:\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e• Introduces basic statistical finance concepts, including univariate and multivariate data analysis, time series analysis, and prediction\u003c\/p\u003e \u003cp\u003e• Provides risk management guidance through volatility prediction, quantiles, and value-at-risk\u003c\/p\u003e \u003cp\u003e• Examines portfolio theory, performance measurement, Markowitz portfolios, dynamic portfolio selection, and more\u003c\/p\u003e \u003cp\u003e• 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\u003c\/p\u003e \u003cp\u003e• Provides supplementary R code and numerous graphics to reinforce complex content\u003c\/p\u003e \u003cp\u003eNonparametric 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.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eJussi Klemelä, PhD, \u003c\/b\u003eis Adjunct Professor at the University of Oulu. His research interests include nonparametric function estimation, density estimation, and data visualization. He is the author of \u003ci\u003eSmoothing of Multivariate Data: Density Estimation and Visualization\u003c\/i\u003e and \u003ci\u003eMultivariate Nonparametric Regression and Visualization: With R and Applications\u003c\/i\u003e \u003ci\u003eto Finance.\u003c\/i\u003e\u003c\/p\u003e","brand":"John Wiley \u0026 Sons Inc","offers":[{"title":"Default Title","offer_id":54069097038168,"sku":null,"price":122.99,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0278\/1295\/4195\/files\/9781119409106_6b7259e2-a178-4a8c-8d4e-1cb84c3d8150.jpg?v=1780392654","url":"https:\/\/agendabookshop.com\/products\/nonparametric-finance","provider":"Agenda Bookshop","version":"1.0","type":"link"}