Learning Quantitative Finance with R

Dr. Param Jeet, Prashant Vats

買這商品的人也買了...

商品描述

Key Features

  • Understand the basics of R and how they can be applied in various Quantitative Finance scenarios
  • Learn various algorithmic trading techniques and ways to optimize them using the tools available in R.
  • Contain different methods to manage risk and explore trading using Machine Learning.

Book Description

The role of a quantitative analyst is very challenging, yet lucrative, so there is a lot of competition for the role in top-tier organizations and investment banks. This book is your go-to resource if you want to equip yourself with the skills required to tackle any real-world problem in quantitative finance using the popular R programming language.

You'll start by getting an understanding of the basics of R and its relevance in the field of quantitative finance. Once you've built this foundation, we'll dive into the practicalities of building financial models in R. This will help you have a fair understanding of the topics as well as their implementation, as the authors have presented some use cases along with examples that are easy to understand and correlate.

We'll also look at risk management and optimization techniques for algorithmic trading. Finally, the book will explain some advanced concepts, such as trading using machine learning, optimizations, exotic options, and hedging.

By the end of this book, you will have a firm grasp of the techniques required to implement basic quantitative finance models in R.

What you will learn

  • Get to know the basics of R and how to use it in the field of Quantitative Finance
  • Understand data processing and model building using R
  • Explore different types of analytical techniques such as statistical analysis, time-series analysis, predictive modeling, and econometric analysis
  • Build and analyze quantitative finance models using real-world examples
  • How real-life examples should be used to develop strategies
  • Performance metrics to look into before deciding upon any model
  • Deep dive into the vast world of machine-learning based trading
  • Get to grips with algorithmic trading and different ways of optimizing it
  • Learn about controlling risk parameters of financial instruments

About the Author

Dr. Param Jeet is a Ph.D. in mathematics from one of India's leading technological institute in Madras (IITM), India. Dr. Param Jeet has a couple of mathematical research papers published in various international journals. Dr. Param Jeet has been into the analytics industry for the last few years and has worked with various leading multinational companies as well as consulted few of companies as a data scientist.

Prashant Vats is a masters in mathematics from one of India’s leading technological institute, IIT Mumbai. Prashant has been into analytics industry for more than 10 years and has worked with various leading multinational companies as well as consulted few of companies as data scientist across several domain.

Table of Contents

  1. Introduction to R
  2. Statistical Modeling
  3. Econometric and Wavelet Analysis
  4. Time Series Modeling
  5. Algorithmic Trading
  6. Trading Using Machine Learning
  7. Risk Management
  8. Optimization
  9. Derivative Pricing

商品描述(中文翻譯)

主要特點


  • 了解R的基礎知識以及如何應用於各種量化金融場景

  • 學習各種算法交易技術以及如何使用R中的工具進行優化

  • 介紹不同的風險管理方法,並探索使用機器學習進行交易

書籍描述

量化分析師的角色非常具有挑戰性和利潤性,因此在頂尖機構和投資銀行中競爭非常激烈。如果您想要掌握使用流行的R編程語言解決量化金融領域中的任何實際問題所需的技能,本書是您的首選資源。

您將首先了解R的基礎知識以及它在量化金融領域的相關性。建立了這個基礎後,我們將深入探討在R中建立金融模型的實際操作。這將幫助您對這些主題及其實施有一個公平的理解,因為作者提供了一些易於理解和相關的用例和示例。

我們還將研究算法交易的風險管理和優化技術。最後,本書將解釋一些高級概念,例如使用機器學習進行交易、優化、異鄉期權和對沖。

通過閱讀本書,您將熟練掌握在R中實施基本量化金融模型所需的技術。

您將學到什麼


  • 瞭解R的基礎知識以及如何在量化金融領域中使用它

  • 了解使用R進行數據處理和模型構建

  • 探索不同類型的分析技術,如統計分析、時間序列分析、預測建模和計量經濟分析

  • 使用真實案例構建和分析量化金融模型

  • 如何使用真實案例來制定策略

  • 在決定任何模型之前應該考慮的性能指標

  • 深入研究基於機器學習的交易

  • 熟悉算法交易和不同的優化方法

  • 了解金融工具的風險參數控制

關於作者

Dr. Param Jeet是印度一所領先的理工學院印度理工學院馬德拉斯分校(IITM)的數學博士。Dr. Param Jeet在各種國際期刊上發表了幾篇數學研究論文。Dr. Param Jeet在過去幾年一直從事分析行業工作,曾與多家領先的跨國公司合作,並擔任數據科學家的顧問。

Prashant Vats是印度一所領先的理工學院孟買印度理工學院的數學碩士。Prashant在分析行業工作超過10年,曾與多家領先的跨國公司合作,並在多個領域擔任數據科學家的顧問。

目錄


  1. R介紹

  2. 統計建模

  3. 計量和小波分析

  4. 時間序列建模

  5. 算法交易

  6. 使用機器學習進行交易

  7. 風險管理

  8. 優化

  9. 衍生品定價