《精通R語言：用於量化金融》是2016年東南大學出版社出版的圖書。
基本介紹
- 中文名：精通R語言：用於量化金融
- 作者：Edina Berlinger、Ferenc Illes、Milan Badics
- 類別：程式設計
- 出版社：東南大學出版社
- 出版時間：2016年
- 開本：16 開
- 裝幀：平裝
- ISBN：9787564160654
內容簡介,圖書目錄,
內容簡介
Edina Berlinger、Ferenc lllés、Milán Badics等*的《精通R語言--用於量化金融(影印版)( 英文版)》是關於如何運用R語言的實踐指南，按循序漸進的步驟編寫而成。從時間序列分析開始逐步介紹，你還將從中學到如何預測VWAP交易規模。本書涵蓋了FX衍生品、利率衍生品及*優對沖等其他相關主題。*後幾章將講述流動性風險管理、風險評估等*多內容。
本書立足實際，介紹了量化金融概念和R語言建模方法，讓你可以自行建立定製化的交易系統。讀完本書後，你將可以熟練運用R語言實現各種金融技術並且能夠做出正確的金融決策。
該書旨在為那些需要學習使用R語言進行高級建模的量化金融領域人士而準備。如果你希望完美地跟上每個章節的節奏，需要在量化金融方面具備中級水平，並且需要準備R語言相關基礎知識。
圖書目錄
Preface
Chapter 1: Time Series Analysis
Multivariate time series analysis
Cointegration
Vector autoregressive models
VAR implementation example
Cointegrated VAR and VECM
Volatility modeling
GARCH modeling with the rugarch package
The standard GARCH model
The Exponential GARCH model (EGARCH)
The Threshold GARCH model (TGARCH)
Simulation and forecasting
Summary
References and reading list
Chapter 2: Factor Models
Arbitrage pricing theory
Implementation of APT
Fama-French three-factor model
Modeling in R
Data selection
Estimation of APT with principal component analysis
Estimation of the Fama-French model
Summary
References
Chapter 3: Forecasting Volume
Motivation
The intensity of trading
The volume forecasting model
Implementation in R
The data
Loading the data
The seasonal component
AR(1) estimation and forecasting
SETAR estimation and forecasting
Interpreting the results
Summary
References
Chapter 4: Big Data - Advanced Analytics
Getting data from open sources
Introduction to big data analysis in R
K-means clustering on big data
Loading big matrices
Big data K-means clustering analysis
Big data linear regression analysis
Loading big data
Fitting a linear regression model on large datasets
Summary
References
Chapter 5: FX Derivatives
Terminology and notations
Currency options
Exchange options
Two-dimensional Wiener processes
The Margrabe formula
Application in R
Quanto options
Pricing formula for a call quanto
Pricing a call quanto in R
Summary
References
Chapter 6: Interest Rate Derivatives and Models
The Black model
Pricing a cap with Black's model
The Vasicek model
The Cox-Ingersoll-Ross model
Parameter estimation of interest rate models
Using the SMFI5 package
Summary
References
Chapter 7: Exotic Options
A general pricing approach
The role of dynamic hedging
How R can help a lot
A glance beyond vanillas
Greeks - the link back to the vanilla world
Pricing the Double-no-touch option
Another way to price the Double-no-touch option
The life of a Double-no-touch option - a simulation
Exotic options embedded in structurecl products
Summary
References
Chapter 8: Optimal Hedging
Hedging of derivatives
Market risk of derivatives
Static delta hedge
Dynamic delta hedge
Comparing the performance of delta hedging
Hedging in the presence of transaction costs
Optimization of the hedge
Optimal hedging in the case of absolute transaction costs
Optimal hedging in the case of relative transaction costs
Further extensions
Summary
References
Chapter 9: Fundamental Analysis
The basics of fundamental analysis
Collecting data
Revealing connections
Including multiple variables
Separating investment targets
Setting classification rules
Backtesting
Industry-specific investment
Summary
References
Chapter 10: Technical Analysis, Neural Networks, and Logoptimal Portfolios
Market efficiency
Technical analysis
The TA toolkit
Markets
Plotting charts - bitcoin
Built-in indicators
SMA and EMA
RSI
MACD
Candle patterns: key reversal
Evaluating the signals and managing the position
A word on money management
Wraping up
Neural networks,
Forecasting bitcoin prices
Evaluation of the strategy
Logoptimal portfolios
A universally consistent, non-parametric investment strategy
Evaluation of the strategy
Summary
References
Chapter 11: Asset and Liability Management
Data preparation
Data source at first glance
Cash-flow generator functions
Preparing the cash-flow
Interest rate risk measurement
Liquidity risk measurement
Modeling non-maturity deposits
A Model of deposit interest rate development
Static replication of non-maturity deposits
Summary
References
Chapter 12: Capital Adequacy
Principles of the Basel Accords
Basel I
Basel II
Minimum capital requirements
Supervisory review
Transparency
Basel III
Risk measures
Analytical VaR
Historical VaR
Monte-Carlo simulation
Risk categories
Market risk
Credit risk
Operational risk
Summary
References
Chapter 13: Systemic Risks
Systemic risk in a nutshell
The dataset used in our examples
Core-periphery decomposition
Implementation in R
Results
The Simulation method
The simulation
Implementation in R
Results
Possible interpretations and suggestions
Summary
References
Index
