书评: 量化领域书越来越多。这本书用R来描述量化投资中分析的一些数学手段,一些基础工具,如果你使用R 这本书作为起点是不错的,如果你以前使用其他工具,没有必要改变,就用你以前的工具吧。但如果你想以后和开源社区交流,R 是你躲不过去的工具和技能
这本书不是建模的书。作者没有说他在建模。试想,如果一个人忽悠他的模型,何必来写书讨生活?
模型和策略是 一个公司最机密的东西,不可能公开,本书就是R在量化交易中的一些应用。不是模型。 这个领域骗子和忽悠的越来越多(辨别很简单,如果他推销模型,他就是骗子,此断言有极高的置信度)。除了不是现成的模型,本书是以 R做量化比较重要比较好的参考书,所以定价15. 和金融产品一样,让市场决定是否值得。
目录如下,拷贝出来就是这个烂样子,不好意思
本帖隐藏的内容
Contents
List of Figures List of Tables Acknowledgments
1 An Overview The mission statement Financial markets and instruments Trading strategies High-frequency trading About the orderbook Trading automation Where to get data from Summary
2 Tools of the Trade The R language Getting started with R The c() object The matrix() object The data.frame() object The list() object The new.env() object Using the plot() function Functional programming Writing functions in R Branching and looping A recommended style guide A pairwise correlation example Summary
3 Working with Data Getting data into R Installing packages in R Storing and transmitting data Extracting data from a spreadsheet
10Accessing a database The dplyr package Using the xts package Using the quantmod package Charting with quantmod Graphing with ggplot2 Summary
4 Basic Statistics and Probability What is a statistic? Population versus sample Central Limit Theorem in R Unbiasedness and efficiency Probability basics Random variables Probabilities Probability distributions Bayes versus frequentist approach Simulations of coins On the use of RStan Summary
5 Intermediate Statistics and Probability Random process Stock price distributions Stationarity Determining stationarity with urca Assumptions of normality Correlation Filtering data R formulas The linear in linear regression Volatility Summary
6 Spreads, Betas and Risk Defining the stock spread Ordinary Least Squares versus Total Least Squares Constructing the spread Signal generation and validation Trading the spread Considering the risk More on the equity curve Strategy attributes
11Summary
7 Backtesting with Quantstrat Backtesting methodology About blotter and PerformanceAnalytics Initial setup The first strategy: A simple trend follower Backtesting the first strategy Evaluating the performance The second strategy: Cumulative Connors RSI Evaluating the mean-reverting strategy Summary
8 High-Frequency Data High-frequency quotes Inter-quote arrival times Identifying liquidity regimes The micro-price Distributions and autocorrelations The highfrequency package Summary
9 Options Option theoretical value A history of options Valuation of options Exploring options trade data Implied volatility Summary
10 Optimization The motivating parabola Newton’s method The brute-force approach R optimization routines A curve-fitting exercise Portfolio optimization Summary
11 Speed, Testing, and Reporting Runtime execution improvements Benchmarking R code The Rcpp solution Calling R from C++ with RInside Writing unit tests with testthat
12
Using knitr for documentation Summary
Notes References Index