Machine Learning for Imbalanced Data: Tackle imbalanced datasets using machine learning and deep learning techniques Kumar Abhishek
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Learning Quantitative Finance with R: Implement machine learning, time-series analysis, algorithmic trading and more
- Sprog
- Engelsk
- Format
- Kategori
Fakta
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.
© 2017 Packt Publishing (E-bog): 9781786465252
Release date
E-bog: 23. marts 2017
Learning Quantitative Finance with R: Implement machine learning, time-series analysis, algorithmic trading and more
- Sprog
- Engelsk
- Format
- Kategori
Fakta
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.
© 2017 Packt Publishing (E-bog): 9781786465252
Release date
E-bog: 23. marts 2017
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