Introduction to R for Quantitative Finance
暫譯: 量化金融的 R 課程導論

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

相關主題

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,非常適合用來解答量化金融問題。本書提供理論與實踐,語言清晰,並附有大量真實案例。無論是R的初學者或專家都能從中受益。

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算利率的期限結構
- 通過金融網絡分析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來解決現實世界中的量化金融問題。本書涵蓋多樣的主題,從時間序列分析到金融網絡。每一章簡要介紹特定概念背後的理論,並通過實際範例來解決各種問題。

本書將成為您使用和掌握R以解決現實世界量化金融問題的指南。本書涵蓋量化金融的基本要素,通過一系列清晰且實用的R範例,幫助您理解理論,並有效處理自己的現實問題。

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運作。接著,本書將介紹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提供有關極端值和量化金融中的網絡分析等令人興奮主題的概述。

您將從本書學到的內容
- 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背後的理論,以及如何將其應用於現實數據
- 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本知識
- 您將發現如何使用離散時間和連續時間模型來定價衍生證券
- 如何成功處理信用違約模型,以及如何使用copulas建模相關違約
- 如何理解極端值理論在保險和金融中的應用、模型擬合和風險度量計算

方法
本書是針對新用戶的教程指南,旨在幫助您理解R在量化金融中的基本知識並熟練使用。

本書的讀者對象
如果您希望使用R來解決量化金融中的問題,那麼本書適合您。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的初學者和更有經驗的用戶提供有用的內容。