Introduction to R for Quantitative Finance
Introduction to R for Quantitative Finance will show you how to solve real-world quantitative fi nance problems using the statistical computing language R. The book covers diverse topics ranging from time series analysis to fi nancial networks. Each chapter briefl y presents the theory behind specific concepts and deals with solving a diverse range of problems using R with the help of practical examples. This book will be your guide on how to use and master R in order to solve quantitative finance problems. This book covers the essentials of quantitative finance, taking you through a number of clear and practical examples in R that will not only help you to understand the theory, but how to effectively deal with your own real-life problems. ...
Introduction to R for Quantitative Finance will show you how to solve real-world quantitative fi nance problems using the statistical computing language R. The book covers diverse topics ranging from time series analysis to fi nancial networks. Each chapter briefl y presents the theory behind specific concepts and deals with solving a diverse range of problems using R with the help of practical examples. This book will be your guide on how to use and master R in order to solve quantitative finance problems. This book covers the essentials of quantitative finance, taking you through a number of clear and practical examples in R that will not only help you to understand the theory, but how to effectively deal with your own real-life problems. ...
Mastering Python for Finance
Built initially for scientific computing, Python quickly found its place in finance. Its flexibility and robustness can be easily incorporated into applications for mathematical studies, research, and software development. With this book, you will learn about all the tools you need to successfully perform research studies and modeling, improve your trading strategies, and effectively manage risks. You will explore the various tools and techniques used in solving complex problems commonly faced in finance. You will learn how to price financial instruments such as stocks, options, interest rate derivatives, and futures using computational methods. Also, you will learn how you can perform data analytics on market indexes and use NoSQL to store tick data. ...
Built initially for scientific computing, Python quickly found its place in finance. Its flexibility and robustness can be easily incorporated into applications for mathematical studies, research, and software development. With this book, you will learn about all the tools you need to successfully perform research studies and modeling, improve your trading strategies, and effectively manage risks. You will explore the various tools and techniques used in solving complex problems commonly faced in finance. You will learn how to price financial instruments such as stocks, options, interest rate derivatives, and futures using computational methods. Also, you will learn how you can perform data analytics on market indexes and use NoSQL to store tick data. ...
Clojure for Finance
Clojure is a dynamic programming language with an emphasis on functional programming. Clojure is well suited to financial modeling as it is a functional programming language. Such languages help developers work with high-level mathematical abstractions without having to implement low-level code that handles the arithmetic operations. Starting with the importance of representing data and calculations effectively, this book will take you all the way to being competent in financial analytics and building financial applications. First, we introduce the notions of computation and finance, which will help you understand Clojure's utility to solve real-world problems in many domains, especially finance. Next, we will show you how to develop the simple-moving-average function by using the more advanced partition Clojure data transformation function. This function, along with others, will be used to calculate and manipulate data. ...
Clojure is a dynamic programming language with an emphasis on functional programming. Clojure is well suited to financial modeling as it is a functional programming language. Such languages help developers work with high-level mathematical abstractions without having to implement low-level code that handles the arithmetic operations. Starting with the importance of representing data and calculations effectively, this book will take you all the way to being competent in financial analytics and building financial applications. First, we introduce the notions of computation and finance, which will help you understand Clojure's utility to solve real-world problems in many domains, especially finance. Next, we will show you how to develop the simple-moving-average function by using the more advanced partition Clojure data transformation function. This function, along with others, will be used to calculate and manipulate data. ...
Advanced Quantitative Finance with C++
This book will introduce you to the key mathematical models used to price financial derivatives, as well as the implementation of main numerical models used to solve them. In particular, equity, currency, interest rates, and credit derivatives are discussed. In the first part of the book, the main mathematical models used in the world of financial derivatives are discussed. Next, the numerical methods used to solve the mathematical models are presented. Finally, both the mathematical models and the numerical methods are used to solve some concrete problems in equity, forex, interest rate, and credit derivatives. The models used include the Black-Scholes and Garman-Kohlhagen models, the LIBOR market model, structural and intensity credit models. The numerical methods described are Monte Carlo simulation (for single and multiple assets), Binomial Trees, and Finite Difference Methods. You will find implementation of concrete problems including European Call, Equity Basket, Currency Eur ...
This book will introduce you to the key mathematical models used to price financial derivatives, as well as the implementation of main numerical models used to solve them. In particular, equity, currency, interest rates, and credit derivatives are discussed. In the first part of the book, the main mathematical models used in the world of financial derivatives are discussed. Next, the numerical methods used to solve the mathematical models are presented. Finally, both the mathematical models and the numerical methods are used to solve some concrete problems in equity, forex, interest rate, and credit derivatives. The models used include the Black-Scholes and Garman-Kohlhagen models, the LIBOR market model, structural and intensity credit models. The numerical methods described are Monte Carlo simulation (for single and multiple assets), Binomial Trees, and Finite Difference Methods. You will find implementation of concrete problems including European Call, Equity Basket, Currency Eur ...
Python for Finance
The financial industry has adopted Python at a tremendous rate recently, with some of the largest investment banks and hedge funds using it to build core trading and risk management systems. This hands-on guide helps both developers and quantitative analysts get started with Python, and guides you through the most important aspects of using Python for quantitative finance. Using practical examples through the book, author Yves Hilpisch also shows you how to develop a full-fledged framework for Monte Carlo simulation-based derivatives and risk analytics, based on a large, realistic case study. ...
The financial industry has adopted Python at a tremendous rate recently, with some of the largest investment banks and hedge funds using it to build core trading and risk management systems. This hands-on guide helps both developers and quantitative analysts get started with Python, and guides you through the most important aspects of using Python for quantitative finance. Using practical examples through the book, author Yves Hilpisch also shows you how to develop a full-fledged framework for Monte Carlo simulation-based derivatives and risk analytics, based on a large, realistic case study. ...
Mastering pandas for Finance
This book will teach you to use Python and the Python Data Analysis Library (pandas) to solve real-world financial problems. Starting with a focus on pandas data structures, you will learn to load and manipulate time-series financial data and then calculate common financial measures, leading into more advanced derivations using fixed- and moving-windows. This leads into correlating time-series data to both index and social data to build simple trading algorithms. From there, you will learn about more complex trading algorithms and implement them using open source back-testing tools. Then, you will examine the calculation of the value of options and Value at Risk. This then leads into the modeling of portfolios and calculation of optimal portfolios based upon risk. All concepts will be demonstrated continuously through progressive examples using interactive Python and IPython Notebook. By the end of the book, you will be familiar with applying pandas to many financial problems, gi ...
This book will teach you to use Python and the Python Data Analysis Library (pandas) to solve real-world financial problems. Starting with a focus on pandas data structures, you will learn to load and manipulate time-series financial data and then calculate common financial measures, leading into more advanced derivations using fixed- and moving-windows. This leads into correlating time-series data to both index and social data to build simple trading algorithms. From there, you will learn about more complex trading algorithms and implement them using open source back-testing tools. Then, you will examine the calculation of the value of options and Value at Risk. This then leads into the modeling of portfolios and calculation of optimal portfolios based upon risk. All concepts will be demonstrated continuously through progressive examples using interactive Python and IPython Notebook. By the end of the book, you will be familiar with applying pandas to many financial problems, gi ...
Mastering R for Quantitative Finance
R is the essential skill to master for anyone looking to make an impact in quantitative finance. The reigning king of serious statistical languages, R gives you the power to turn your raw data into lucrative analyses - and this book shows you how. Chapter by chapter, the concepts of quantitative finance are interwoven with real R model programming. Its clear and practical approach gets you using R straight away for time series analysis, creating models for multiple factors, and harnessing big data for your predictive investment purposes. This book is dedicated to giving you the guidance to construct your own complete trading system, and the knowledge to tailor it to meet your needs and the needs of your clients. Get them the results that they expect as you learn how to handle foreign exchange and interest rate derivatives, using R for optimal hedging, and making sure that you have the analysis to guarantee a payoff from the most complex exotic options. ...
R is the essential skill to master for anyone looking to make an impact in quantitative finance. The reigning king of serious statistical languages, R gives you the power to turn your raw data into lucrative analyses - and this book shows you how. Chapter by chapter, the concepts of quantitative finance are interwoven with real R model programming. Its clear and practical approach gets you using R straight away for time series analysis, creating models for multiple factors, and harnessing big data for your predictive investment purposes. This book is dedicated to giving you the guidance to construct your own complete trading system, and the knowledge to tailor it to meet your needs and the needs of your clients. Get them the results that they expect as you learn how to handle foreign exchange and interest rate derivatives, using R for optimal hedging, and making sure that you have the analysis to guarantee a payoff from the most complex exotic options. ...
Personal Finance with Python
Deal with data, build up financial formulas in code from scratch, and evaluate and think about money in your day-to-day life. This book is about Python and personal finance and how you can effectively mix the two together. In Personal Finance with Python you will learn Python and finance at the same time by creating a profit calculator, a currency converter, an amortization schedule, a budget, a portfolio rebalancer, and a purchase forecaster. Many of the examples use pandas, the main data manipulation tool in Python. Each chapter is hands-on, self-contained, and motivated by fun and interesting examples. Although this book assumes a minimal familiarity with programming and the Python language, if you don't have any, don't worry. Everything is built up piece-by-piece and the first chapters are conducted at a relaxed pace. You'll need Python 3.6 (or above) and all of the setup details are included. Work with data in pandas; Calculate Net Present Value and Internal Rate Return; Qu ...
Deal with data, build up financial formulas in code from scratch, and evaluate and think about money in your day-to-day life. This book is about Python and personal finance and how you can effectively mix the two together. In Personal Finance with Python you will learn Python and finance at the same time by creating a profit calculator, a currency converter, an amortization schedule, a budget, a portfolio rebalancer, and a purchase forecaster. Many of the examples use pandas, the main data manipulation tool in Python. Each chapter is hands-on, self-contained, and motivated by fun and interesting examples. Although this book assumes a minimal familiarity with programming and the Python language, if you don't have any, don't worry. Everything is built up piece-by-piece and the first chapters are conducted at a relaxed pace. You'll need Python 3.6 (or above) and all of the setup details are included. Work with data in pandas; Calculate Net Present Value and Internal Rate Return; Qu ...
Machine Learning Applications Using Python
Gain practical skills in machine learning for finance, healthcare, and retail. This book uses a hands-on approach by providing case studies from each of these domains: you'll see examples that demonstrate how to use machine learning as a tool for business enhancement. As a domain expert, you will not only discover how machine learning is used in finance, healthcare, and retail, but also work through practical case studies where machine learning has been implemented. Machine Learning Applications Using Python is divided into three sections, one for each of the domains (healthcare, finance, and retail). Each section starts with an overview of machine learning and key technological advancements in that domain. You'll then learn more by using case studies on how organizations are changing the game in their chosen markets. This book has practical case studies with Python code and domain-specific innovative ideas for monetizing machine learning. Discover applied machine learning proces ...
Gain practical skills in machine learning for finance, healthcare, and retail. This book uses a hands-on approach by providing case studies from each of these domains: you'll see examples that demonstrate how to use machine learning as a tool for business enhancement. As a domain expert, you will not only discover how machine learning is used in finance, healthcare, and retail, but also work through practical case studies where machine learning has been implemented. Machine Learning Applications Using Python is divided into three sections, one for each of the domains (healthcare, finance, and retail). Each section starts with an overview of machine learning and key technological advancements in that domain. You'll then learn more by using case studies on how organizations are changing the game in their chosen markets. This book has practical case studies with Python code and domain-specific innovative ideas for monetizing machine learning. Discover applied machine learning proces ...
Machine Learning for Finance
Machine Learning for Finance explores new advances in machine learning and shows how they can be applied across the financial sector, including insurance, transactions, and lending. This book explains the concepts and algorithms behind the main machine learning techniques and provides example Python code for implementing the models yourself. The book is based on Jannes Klaas experience of running machine learning training courses for financial professionals. Rather than providing ready-made financial algorithms, the book focuses on advanced machine learning concepts and ideas that can be applied in a wide variety of ways. The book systematically explains how machine learning works on structured data, text, images, and time series. You'll cover generative adversarial learning, reinforcement learning, debugging, and launching machine learning products. Later chapters will discuss how to fight bias in machine learning. The book ends with an exploration of Bayesian inference and prob ...
Machine Learning for Finance explores new advances in machine learning and shows how they can be applied across the financial sector, including insurance, transactions, and lending. This book explains the concepts and algorithms behind the main machine learning techniques and provides example Python code for implementing the models yourself. The book is based on Jannes Klaas experience of running machine learning training courses for financial professionals. Rather than providing ready-made financial algorithms, the book focuses on advanced machine learning concepts and ideas that can be applied in a wide variety of ways. The book systematically explains how machine learning works on structured data, text, images, and time series. You'll cover generative adversarial learning, reinforcement learning, debugging, and launching machine learning products. Later chapters will discuss how to fight bias in machine learning. The book ends with an exploration of Bayesian inference and prob ...