精通R语言--用于量化金融(影印版)(英文版)

Edina Berlinger、Ferenc lllés、Milán Badics等著的《精通R语言--用于量化金融(影印版)( 英文版)》是关于如何运用R语言的实践指南，按循序 渐进的步骤编写而成。从时间序列分析开始逐步介绍 ，你还将从中学到如何预测VWAP交易规模。本书涵盖 了FX衍生品、利率衍生品及最优对冲等其他相关主题 。最后几章将讲述流动性风险管理、风险评估等更多 内容。 本书立足实际，介绍了量化金融概念和R语言建 模方法，让你可以自行建立定制化的交易系统。读完 本书后，你将可以熟练运用R语言实现各种金融技术 并且能够做出正确的金融决策。 该书旨在为那些需要学习使用R语言进行高级建 模的量化金融领域人士而准备。如果你希望完美地跟 上每个章节的节奏，需要在量化金融方面具备中级水 平，并且需要准备R语言相关基础知识。

Milan Badics拥有布达佩斯Corvinus大学金融学硕士学位，现在是博士研究生及PADS博士学者项目成员。 Ferenc Illes拥有Eotvos Lorand大学数学科学硕士学位。毕业多年后。他开始研究保险精算和金鼬数学，并即将从布达佩斯Corvinus大学获得其博士学位。 Edina Berlinger拥有布达佩斯Corvinus大学经济学博士学位。她是一位副教授，从事公司财务、投资和金融风险管理等学科的教学工作。她是该校的金融系主任，同时也是匈牙利科学院的金融委员会主席。

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