Mastering R for Quantitative Finance

R is a powerful open source functional programming language that provides high level graphics and interfaces to other languages. Its strength lies in data analysis, graphics, visualization, and data manipulation. R is becoming a widely used modeling tool in science, engineering, and business. The book is organized as a step-by-step practical guide to using R. Starting with time series analysis, you will also learn how to forecast the volume for VWAP Trading. Among other topics, the book covers FX derivatives, interest rate derivatives, and optimal hedging. The last chapters provide an overview on liquidity risk management, risk measures, and more. The book pragmatically introduces both the quantitative finance concepts and their modeling in R, enabling you to build a tailor-made trading system on your own. By the end of the book, you will be well versed with various financial techniques using R and will be able to place good bets while making financial decisions.

About This Book

• A hands-on guide to web scraping with real-life problems and solutions
• Techniques to download and extract data from complex websites
• Create a number of different web scrapers to extract information

Who This Book Is For

This book is aimed at developers who want to build reliable solutions to scrape data from websites. It is assumed that the reader has prior programming experience with Python. Anyone with general knowledge of programming languages should be able to pick up the book and understand the principles involved.

What You Will Learn

• Follow links to crawl a website
• Extract data from web pages with lxml
• Build a threaded crawler to process web pages in parallel
• Cache downloads to reduce bandwidth
• Learn how to parse JavaScript-dependent websites
• Interact with forms and sessions
• Solve CAPTCHAs on protected web pages
• Reverse engineer AJAX calls
• Create high level scrapers with Scrapy

In Detail

Web scraping is becoming increasingly useful as a way to easily gather and make sense of the plethora of information available online. Using a simple language such as Python, you can scrape complex websites with little programming.

This book is the ultimate guide to using Python to scrape data from websites. It covers how to extract data from static web pages and how to use caching to manage the load on servers. Learn how to use AJAX URLs, employ the Firebug extension. Discover more scraping nitty-gritties such as using a browser renderer, managing cookies, submitting forms to extract data from complex websites protected by CAPTCHA, and so on. Finally, create high-level scrapers with Scrapy and implement what has been learned on real websites.

About This BookLearn to manipulate, visualize, and analyze a wide range of financial data with the help of built-in functions and programming in RUnderstand the concepts of financial engineering and create trading strategies for complex financial instrumentsExplore R for asset and liability management and capital adequacy modelingWho This Book Is ForThis book is intended for those who want to learn how to use R's capabilities to build models in quantitative finance at a more advanced level. If you wish to perfectly take up the rhythm of the chapters, you need to be at an intermediate level in quantitative finance and you also need to have a reasonable knowledge of R.