Learning Quantitative Finance With R

DOWNLOAD

Download Learning Quantitative Finance With R PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Learning Quantitative Finance With R book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page

Learning Quantitative Finance With R

DOWNLOAD
Author : Dr. Param Jeet
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-03-23

Learning Quantitative Finance With R written by Dr. Param Jeet and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-03-23 with Computers categories.

Implement machine learning, time-series analysis, algorithmic trading and more About This Book 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. Who This Book Is For If you want to learn how to use R to build quantitative finance models with ease, this book is for you. Analysts who want to learn R to solve their quantitative finance problems will also find this book useful. Some understanding of the basic financial concepts will be useful, though prior knowledge of R is not required. 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 In Detail 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. Style and approach This book introduces you to the essentials of quantitative finance with the help of easy-to-understand, practical examples and use cases in R. Each chapter presents a specific financial concept in detail, backed with relevant theory and the implementation of a real-life example.

Learning Quantitative Finance With R

DOWNLOAD
Author : Dr Param Jeet
language : en
Publisher: Packt Publishing
Release Date : 2017-03-23

Learning Quantitative Finance With R written by Dr Param Jeet and has been published by Packt Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-03-23 with Computers categories.

Implement machine learning, time-series analysis, algorithmic trading and moreAbout This Book- 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.Who This Book Is ForIf you want to learn how to use R to build quantitative finance models with ease, this book is for you. Analysts who want to learn R to solve their quantitative finance problems will also find this book useful. Some understanding of the basic financial concepts will be useful, though prior knowledge of R is not required.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 instrumentsIn DetailThe 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.Style and approachThis book introduces you to the essentials of quantitative finance with the help of easy-to-understand, practical examples and use cases in R. Each chapter presents a specific financial concept in detail, backed with relevant theory and the implementation of a real-life example.

Hands On Intermediate Econometrics Using R Templates For Learning Quantitative Methods And R Software Second Edition

DOWNLOAD
Author : Hrishikesh D Vinod
language : en
Publisher: World Scientific
Release Date : 2022-04-08

Hands On Intermediate Econometrics Using R Templates For Learning Quantitative Methods And R Software Second Edition written by Hrishikesh D Vinod and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-04-08 with Business & Economics categories.

How to learn both applied statistics (econometrics) and free, open-source software R? This book allows students to have a sense of accomplishment by copying and pasting many hands-on templates provided here.The textbook is essential for anyone wishing to have a practical understanding of an extensive range of topics in Econometrics. No other text provides software snippets to learn so many new statistical tools with hands-on examples. The explicit knowledge of inputs and outputs of each new method allows the student to know which algorithm is worth studying. The book offers sufficient theoretical and algorithmic details about a vast range of statistical techniques.The second edition's preface lists the following topics generally absent in other textbooks. (i) Iteratively reweighted least squares, (ii) Pillar charts to represent 3D data. (iii) Stochastic frontier analysis (SFA) (iv) model selection with Mallows' Cp criterion. (v) Hodrick-Prescott (HP) filter. (vi) Automatic ARIMA models. (vi) Nonlinear Granger-causality using kernel regressions and bootstrap confidence intervals. (vii) new Keynesian Phillips curve (NKPC). (viii) Market-neutral pairs trading using two cointegrated stocks. (ix) Artificial neural network (ANN) for product-specific forecasting. (x) Vector AR and VARMA models. (xi) New tools for diagnosing the endogeneity problem. (xii) The elegant set-up of k-class estimators and identification. (xiii) Probit-logit models and Heckman selection bias correction. (xiv) Receiver operating characteristic (ROC) curves and areas under them. (xv) Confusion matrix. (xvi) Quantile regression (xvii) Elastic net estimator. (xviii) generalized Correlations (xix) maximum entropy bootstrap for time series. (xx) Convergence concepts quantified. (xxi) Generalized partial correlation coefficients (xxii) Panel data and duration (survival) models.

Mastering R For Quantitative Finance

DOWNLOAD
Author : Edina Berlinger
language : en
Publisher: Packt Publishing Ltd
Release Date : 2015-03-10

Mastering R For Quantitative Finance written by Edina Berlinger and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-03-10 with Computers categories.

This 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.

Machine Learning For Factor Investing R Version

DOWNLOAD
Author : Guillaume Coqueret
language : en
Publisher: CRC Press
Release Date : 2020-08-31

Machine Learning For Factor Investing R Version written by Guillaume Coqueret and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-31 with Business & Economics categories.

Machine learning (ML) is progressively reshaping the fields of quantitative finance and algorithmic trading. ML tools are increasingly adopted by hedge funds and asset managers, notably for alpha signal generation and stocks selection. The technicality of the subject can make it hard for non-specialists to join the bandwagon, as the jargon and coding requirements may seem out of reach. Machine Learning for Factor Investing: R Version bridges this gap. It provides a comprehensive tour of modern ML-based investment strategies that rely on firm characteristics. The book covers a wide array of subjects which range from economic rationales to rigorous portfolio back-testing and encompass both data processing and model interpretability. Common supervised learning algorithms such as tree models and neural networks are explained in the context of style investing and the reader can also dig into more complex techniques like autoencoder asset returns, Bayesian additive trees, and causal models. All topics are illustrated with self-contained R code samples and snippets that are applied to a large public dataset that contains over 90 predictors. The material, along with the content of the book, is available online so that readers can reproduce and enhance the examples at their convenience. If you have even a basic knowledge of quantitative finance, this combination of theoretical concepts and practical illustrations will help you learn quickly and deepen your financial and technical expertise.

R For Basic Biostatistics In Medical Research

DOWNLOAD
Author : Anand Srinivasan
language : en
Publisher: Springer Nature
Release Date : 2024-12-02

R For Basic Biostatistics In Medical Research written by Anand Srinivasan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-02 with Medical categories.

The scientific community at the global level is fast becoming aware of the rising use of open-source tools such as R and Python for data analysis. Unfortunately, in spite of the awareness, the conversion of the intrigue to the practical knowledge in utilization of the open-source tools for routine day-to-day data analysis is seriously lacking both among physicians and medical scientists. This book enables physician-scientists to understand the complexity of explaining a programming/ data-analytic language to a healthcare professional and medical scientist. It simplifies and explains how R can be used in medical projects and routine office works. It also talks about the methodologies to convert the knowledge to practice. The book starts with the introduction to the structure of R programming language in the initial chapters, followed with explanations of utilizing R in the basics of data analysis like data importing and exporting, operations on a data frame, parametric and non-parametric tests, regression, sample size calculation, survival analysis, receiver operator characteristic analysis (ROC) and techniques of randomization. Each chapter provides a brief introduction to the involved statistics, for example, dataset, working codes, and a section explaining the codes. In addition to it, a chapter has been dedicated to describing the ways to generate plots using R. This book primarily targets health care professionals and medical/life-science researchers in general.

The Rise Of Machines

DOWNLOAD
Author : Adrian David Cheok
language : en
Publisher: CRC Press
Release Date : 2024-11-21

The Rise Of Machines written by Adrian David Cheok and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-21 with Computers categories.

This book provides an in-depth look at the impact of artificial intelligence (AI) on the future of work. The rise of AI and automation is transforming the world of work, and the book explores the implications of this transformation on jobs and skills. It begins by introducing readers to the basics of AI technology and its various applications in the workplace. It then moves on to examine the impact of AI on jobs and skills, including the changing nature of work and the potential for job loss due to automation. It also delves into the ethical implications of AI in the workplace, including the moral and ethical questions that arise when AI is used to make decisions that affect people's lives. Besides exploring the impact of AI on the workforce, the book provides practical advice for preparing for the future of work in the age of AI. This includes the importance of reskilling and upskilling, as well as strategies for adapting to the changing world of work in the age of AI. It concludes with a future outlook, exploring the likely direction of the workforce in the years to come and the importance of preparing for the future with a proactive approach to AI and the workforce. This book provides a comprehensive and accessible look at the impact of AI on the future of work. It is ideal for anyone interested in understanding the implications of AI on the workforce and preparing for the future of work in the age of AI.

R Data Analysis And Visualization

DOWNLOAD
Author : Tony Fischetti
language : en
Publisher: Packt Publishing Ltd
Release Date : 2016-06-24

R Data Analysis And Visualization written by Tony Fischetti and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-06-24 with Computers categories.

Master the art of building analytical models using R About This Book Load, wrangle, and analyze your data using the world's most powerful statistical programming language Build and customize publication-quality visualizations of powerful and stunning R graphs Develop key skills and techniques with R to create and customize data mining algorithms Use R to optimize your trading strategy and build up your own risk management system Discover how to build machine learning algorithms, prepare data, and dig deep into data prediction techniques with R Who This Book Is For This course is for data scientist or quantitative analyst who are looking at learning R and take advantage of its powerful analytical design framework. It's a seamless journey in becoming a full-stack R developer. What You Will Learn Describe and visualize the behavior of data and relationships between data Gain a thorough understanding of statistical reasoning and sampling Handle missing data gracefully using multiple imputation Create diverse types of bar charts using the default R functions Familiarize yourself with algorithms written in R for spatial data mining, text mining, and so on Understand relationships between market factors and their impact on your portfolio Harness the power of R to build machine learning algorithms with real-world data science applications Learn specialized machine learning techniques for text mining, big data, and more In Detail The R learning path created for you has five connected modules, which are a mini-course in their own right. As you complete each one, you'll have gained key skills and be ready for the material in the next module! This course begins by looking at the Data Analysis with R module. This will help you navigate the R environment. You'll gain a thorough understanding of statistical reasoning and sampling. Finally, you'll be able to put best practices into effect to make your job easier and facilitate reproducibility. The second place to explore is R Graphs, which will help you leverage powerful default R graphics and utilize advanced graphics systems such as lattice and ggplot2, the grammar of graphics. You'll learn how to produce, customize, and publish advanced visualizations using this popular and powerful framework. With the third module, Learning Data Mining with R, you will learn how to manipulate data with R using code snippets and be introduced to mining frequent patterns, association, and correlations while working with R programs. The Mastering R for Quantitative Finance module 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 module, you will be well-versed with various financial techniques using R and will be able to place good bets while making financial decisions. Finally, we'll look at the Machine Learning with R module. With this module, you'll discover all the analytical tools you need to gain insights from complex data and learn how to choose the correct algorithm for your specific needs. You'll also learn to apply machine learning methods to deal with common tasks, including classification, prediction, forecasting, and so on. Style and approach Learn data analysis, data visualization techniques, data mining, and machine learning all using R and also learn to build models in quantitative finance using this powerful language.

Contemporary Studies Of Risks In Emerging Technology

DOWNLOAD
Author : Simon Grima
language : en
Publisher: Emerald Group Publishing
Release Date : 2023-05-10

Contemporary Studies Of Risks In Emerging Technology written by Simon Grima and has been published by Emerald Group Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-05-10 with Business & Economics categories.

With the rapid development of technologies, it becomes increasingly important for us to remain up-to-date on new and emerging technologies. This series, therefore, aims to deliver content on current and future technologies and how the young generation benefits from this.

Financial Modeling

DOWNLOAD
Author : Hercules Vladimirou
language : en
Publisher:
Release Date : 2007

Financial Modeling written by Hercules Vladimirou and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Finance categories.