Introduction to R for Quantitative Finance

Gergely Daróczi, Michael Puhle, Edina Berlinger, Péter Csóka, Daniel Havran, Márton Michaletzky, Zsolt Tulassay, Kata Váradi, Agnes Vidovics-Dancs

商品描述

R is a statistical computing language that's ideal for answering quantitative finance questions. This book gives you both theory and practice, all in clear language with stacks of real-world examples. Ideal for R beginners or expert alike.

Overview

  • Use time series analysis to model and forecast house prices
  • Estimate the term structure of interest rates using prices of government bonds
  • Detect systemically important financial institutions by employing financial network analysis

In Detail

Introduction to R for Quantitative Finance will show you how to solve real-world quantitative finance problems using the statistical computing language R. The book covers diverse topics ranging from time series analysis to financial networks. Each chapter briefly presents the theory behind specific concepts and deals with solving a diverse range of problems using R with the help of practical examples.

This book will be your guide on how to use and master R in order to solve real-world quantitative finance problems. This book covers the essentials of quantitative finance, taking you through a number of clear and practical examples in R that will not only help you to understand the theory, but how to effectively deal with your own real-life problems.

Starting with time series analysis, you will also learn how to optimize portfolios and how asset pricing models work. The book then covers fixed income securities and derivatives like credit risk management. The last chapters of this book will also provide you with an overview of exciting topics like extreme values and network analysis in quantitative finance.

What you will learn from this book

  • How to model and forecast house prices and improve hedge ratios using cointegration and model volatility
  • How to understand the theory behind portfolio selection and how it can be applied to real-world data
  • How to utilize the Capital Asset Pricing Model and the Arbitrage Pricing Theory
  • How to understand the basics of fixed income instruments
  • You will discover how to use discrete- and continuous-time models for pricing derivative securities
  • How to successfully work with credit default models and how to model correlated defaults using copulas
  • How to understand the uses of the Extreme Value Theory in insurance and fi nance, model fitting, and risk measure calculation

Approach

This book is a tutorial guide for new users that aims to help you understand the basics of and become accomplished with the use of R for quantitative finance.

Who this book is written for

If you are looking to use R to solve problems in quantitative finance, then this book is for you. A basic knowledge of financial theory is assumed, but familiarity with R is not required. With a focus on using R to solve a wide range of issues, this book provides useful content for both the R beginner and more experience users.

商品描述(中文翻譯)

R是一種統計計算語言,非常適合解答量化金融問題。這本書以清晰的語言和大量實際例子,結合理論和實踐,為您提供理想的學習資源。無論您是R的初學者還是專家,都能從中受益。

概述:
- 使用時間序列分析來建模和預測房價
- 利用政府債券價格估計利率期限結構
- 通過金融網絡分析來檢測系統重要金融機構

詳細內容:
《量化金融的R入門》將向您展示如何使用統計計算語言R解決現實世界的量化金融問題。本書涵蓋了從時間序列分析到金融網絡等多樣主題。每一章節都簡要介紹了特定概念背後的理論,並通過實際例子展示如何使用R解決各種問題。

本書將指導您如何使用和精通R,以解決現實世界的量化金融問題。本書涵蓋了量化金融的基本知識,通過一系列清晰實用的R示例,不僅幫助您理解理論,還能有效應對自己的實際問題。

從時間序列分析開始,您還將學習如何優化投資組合以及資產定價模型的工作原理。本書還涵蓋了固定收益證券和衍生品,如信用風險管理。本書的最後幾章還將為您提供有關量化金融中的極值和網絡分析等令人興奮的主題的概述。

本書將教您:
- 如何使用協整和模型波動性來建模和預測房價,並改善對沖比率
- 如何理解投資組合選擇理論的基礎以及如何應用於現實數據
- 如何利用資本資產定價模型和套利定價理論
- 如何理解固定收益工具的基礎知識
- 如何使用離散和連續時間模型定價衍生證券
- 如何成功使用信用違約模型,以及如何使用copulas模型相關違約
- 如何理解極值理論在保險和金融中的應用,模型擬合和風險度量計算

本書的方法:
本書是新用戶的教程指南,旨在幫助您了解R在量化金融中的基礎知識,並成為熟練的使用者。

本書的讀者:
如果您希望使用R解決量化金融問題,那麼本書適合您。我們假設您具備基本的金融理論知識,但不需要熟悉R。本書專注於使用R解決各種問題,為R初學者和有經驗的用戶提供有用的內容。