Nonparametric Finance (Wiley Series in Probability and Statistics) - Image 1

Price loading...

Wiley Nonparametric Finance (Wiley Series in Probability and Statistics)

Name: Nonparametric Finance (Wiley Series in Probability and Statistics)
Brand: Wiley

Accounting

Price History & Forecast

No Price Data Available

Price history will appear here once data is collected from Amazon.

Price Distribution

No price data available for histogram

Description

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.

Product Specifications

Brand: Wiley
Format: hardcover
ASIN: 1119409101
Category: Books > Subjects > Business, Finance & Law > Accounting
Domain: Amazon UK
Release Date: 29 June 2018
Listed Since: 08 August 2017

Barcode

No barcode data available

Wiley Nonparametric Finance (Wiley Series in Probability and Statistics)

Price History & Forecast

No Price Data Available

Price Distribution

Description

Product Specifications

Barcode

Similar Products You Might Like

Multivariate Nonparametric Regression and Visualization: With R and Applications to Finance (Wiley Series in Computational Statistics)

Introduction to Nonparametric Regression (Wiley Series in Probability and Statistics)

Financial Data Analytics with Machine Learning, Optimization and Statistics (Wiley Finance)

Financial Risk Forecasting: The Theory and Practice of Forecasting Market Risk with Implementation in R and Matlab (The Wiley Finance Series)

Nonparametric Statistics with Applications to Science and Engineering with R (Wiley Series in Probability and Statistics)

Financial Signal Processing and Machine Learning (IEEE Press)

Tidy Finance with R (Chapman & Hall/CRC The R Series)

Statistical Analysis of Financial Data in R (Springer Texts in Statistics)

Statistical Analysis of Financial Data in R (Springer Texts in Statistics)

Machine Learning and AI in Finance

Quantitative Finance (Statistics in Practice)

Market Risk Analysis, Quantitative Methods in Finance (The Wiley Finance Series)

Stochastic Simulation and Applications in Finance with MATLAB Programs (The Wiley Finance Series)

Mathematical Finance: Theory, Modeling, Implementation

Tidy Finance with Python - Chapman and Hall/CRC Textbook

Machine Learning in Finance: From Theory to Practice

Machine Learning in Finance: From Theory to Practice

Bayesian Nonparametric Data Analysis (Springer Series in Statistics)

Mathematical Finance

Tidy Finance with Python (Chapman & Hall/CRC The Python Series)

Novel Financial Applications of Machine Learning and Deep Learning: Algorithms, Product Modeling, and Applications: 336 (International Series in Operations Research & Management Science, 336)

Actuarial Finance: Derivatives, Quantitative Models and Risk Management

Market Risk Analysis: Quantitative Methods in Finance, Practical Financial Econometrics, Pricing, Hedging and Trading Financial Instruments, Value-at-Risk Models

Risk and Financial Management: Mathematical and Computational Methods