Quantitative Finance With Case Studies In Python

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Quantitative Finance With Case Studies In Python
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Author : Chris Kelliher
language : en
Publisher: CRC Press
Release Date : 2025-11-07
Quantitative Finance With Case Studies In Python written by Chris Kelliher and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-11-07 with Business & Economics categories.
Quantitative Finance with Case Studies in Python: A Practical Guide to Investment Management, Trading and Financial Engineering bridges the gap between the theory of mathematical finance and the practical applications of these concepts for derivative pricing and portfolio management. The book provides students with a very hands-on, rigorous introduction to foundational topics in quant finance, such as options pricing, portfolio optimization and machine learning. Simultaneously, the reader benefits from a strong emphasis on the practical applications of these concepts for institutional investors. This new edition includes brand new material on data science and AI concepts, including large language models, as well as updated content to reflect the transition from Libor to SOFR to bring the text right up to date. It also includes expanded material on inflation, mortgage-backed securities and counterparty risk. In addition, there is an increased emphasis on trade ideas, as well as examples throughout based on recent market dynamics, including the post-Covid inflation shock. Overall, the new edition is designed to be even more of a practical tool than the first edition, and more firmly rooted in real-world data, applications, and examples. Features - Useful as both a teaching resource and as a practical tool for professional investors - Ideal textbook for first year graduate students in quantitative finance programs, such as those in master's programs in Mathematical Finance, Quant Finance or Financial Engineering - Includes a perspective on the future of quant finance techniques, and in particular covers concepts of Machine Learning and Artificial Intelligence - Free-to-access repository with Python codes available at www.routledge.com/ 9781032014432 and on https: //github.com/lingyixu/Quant-Finance-With-Python-Code.[CK1]
Quantitative Finance With Python
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Author : Chris Kelliher
language : en
Publisher: CRC Press
Release Date : 2022-05-19
Quantitative Finance With Python written by Chris Kelliher and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-19 with Business & Economics categories.
Quantitative Finance with Python: A Practical Guide to Investment Management, Trading and Financial Engineering bridges the gap between the theory of mathematical finance and the practical applications of these concepts for derivative pricing and portfolio management. The book provides students with a very hands-on, rigorous introduction to foundational topics in quant finance, such as options pricing, portfolio optimization and machine learning. Simultaneously, the reader benefits from a strong emphasis on the practical applications of these concepts for institutional investors. Features Useful as both a teaching resource and as a practical tool for professional investors. Ideal textbook for first year graduate students in quantitative finance programs, such as those in master’s programs in Mathematical Finance, Quant Finance or Financial Engineering. Includes a perspective on the future of quant finance techniques, and in particular covers some introductory concepts of Machine Learning. Free-to-access repository with Python codes available at www.routledge.com/ 9781032014432 and on https://github.com/lingyixu/Quant-Finance-With-Python-Code.
Introduction To Python
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Author : Lilan Li
language : en
Publisher: Lan LI
Release Date : 2021-07-27
Introduction To Python written by Lilan Li and has been published by Lan LI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-27 with Computers categories.
It is a book for both beginners and experienced professionals who either have a relevant educational background or are interested in learning Python under the data science or quantitative finance background. No prior experience in Python is required. It is a practical book complete with working code that guides the reader through the basics of Python. Topics are introduced gradually, each building on the last. The examples are either run in a command line or an editor. Jupyter notebook examples are presented in later part of the book where mathematical models and data analysis of time series are introduced. BY THE END OF THIS BOOK, YOU WILL BE ABLE TO : •gain a general understanding of Python •write basic Python code •write Python function to perform efficient data analysis and simple financial model analysis for those who have prior knowledge of programming ( you could skip the first chapter) WHO IS THIS BOOK FOR This book is directed at both industry practitioners and students interested in learning python for financial modelling or/and data science purpose. It helps to advance your career either within the finance modelling arena or the Data science field! You will also find this book useful if you want to extend the your existing programming language knowledge in another application field.
Risk Analysis In Finance And Insurance
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Author : Alexander Melnikov
language : en
Publisher: CRC Press
Release Date : 2025-09-04
Risk Analysis In Finance And Insurance written by Alexander Melnikov and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-09-04 with Business & Economics categories.
Risk Analysis in Finance and Insurance, Third Edition presents an accessible yet comprehensive introduction to the main concepts and methods that transform risk management into a quantitative science. Considering the interdisciplinary nature of risk analysis, the author discusses many important ideas from stochastic analysis, mathematical finance and actuarial science in a simplified manner. He explores the interconnections among these disciplines and encourages readers toward further study of the subject. This edition continues to study risks associated with financial and insurance contracts, using an approach that estimates the value of future payments based on current financial, insurance, and other information. Features of the third edition 12 chapters instead of 8 of the 2nd editions. Two new chapters on Wiener process as a base for financial market modeling. Option pricing in the Bachelier model, the model of Black and Scholes, the Gram-Charlier model. American options and their pricing in the Black-Scholes model Several new notions, topics and results that are not reflected yet in other textbooks, and even in monographs (Binomial model with constraints, detailed exposition of quantile hedging technique, Conditional Value at Risk, Range of Value at Risk, applications to equity-linked life insurance) Can be regarded as a self-contained issue of courses on Mathematical Finance, Actuarial Science and Risk Management Replete with new exercises, problems, hints and solutions
Lecture Notes In Financial Modelling With Python
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Author : Fabio Dias
language : en
Publisher: Ink Magic Publishing
Release Date : 2024-10-31
Lecture Notes In Financial Modelling With Python written by Fabio Dias and has been published by Ink Magic Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-31 with Business & Economics categories.
Lecture Notes in Financial Modelling with Python is an essential eBook that compiles a series of presentations by Fabio Dias, showcasing his approach to teaching financial modeling. Covering a wide range of foundational and advanced topics—including machine learning, portfolio selection, financial planning, panel data models, and value at risk (VaR)—this book is both a theoretical guide and practical resource. Each chapter is supported by code examples in Python, making it easy for readers to implement models and techniques on their own. Ideal for students, educators, and financial professionals, this eBook brings complex concepts to life, equipping readers with the tools and skills to tackle real-world financial challenges.
An Introduction To Machine Learning In Quantitative Finance
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Author : Hao Ni
language : en
Publisher: World Scientific
Release Date : 2021-04-07
An Introduction To Machine Learning In Quantitative Finance written by Hao Ni and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-07 with Business & Economics categories.
In today's world, we are increasingly exposed to the words 'machine learning' (ML), a term which sounds like a panacea designed to cure all problems ranging from image recognition to machine language translation. Over the past few years, ML has gradually permeated the financial sector, reshaping the landscape of quantitative finance as we know it.An Introduction to Machine Learning in Quantitative Finance aims to demystify ML by uncovering its underlying mathematics and showing how to apply ML methods to real-world financial data. In this book the authorsFeatured with the balance of mathematical theorems and practical code examples of ML, this book will help you acquire an in-depth understanding of ML algorithms as well as hands-on experience. After reading An Introduction to Machine Learning in Quantitative Finance, ML tools will not be a black box to you anymore, and you will feel confident in successfully applying what you have learnt to empirical financial data!
Python For Finance
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Author : Yves Hilpisch
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2014-12-11
Python For Finance written by Yves Hilpisch and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-12-11 with Business & Economics categories.
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. Much of the book uses interactive IPython Notebooks, with topics that include: Fundamentals: Python data structures, NumPy array handling, time series analysis with pandas, visualization with matplotlib, high performance I/O operations with PyTables, date/time information handling, and selected best practices Financial topics: mathematical techniques with NumPy, SciPy and SymPy such as regression and optimization; stochastics for Monte Carlo simulation, Value-at-Risk, and Credit-Value-at-Risk calculations; statistics for normality tests, mean-variance portfolio optimization, principal component analysis (PCA), and Bayesian regression Special topics: performance Python for financial algorithms, such as vectorization and parallelization, integrating Python with Excel, and building financial applications based on Web technologies
Applied Quantitative Finance
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Author : Mauricio Garita
language : en
Publisher: Springer Nature
Release Date : 2021-09-03
Applied Quantitative Finance written by Mauricio Garita and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-03 with Business & Economics categories.
This book provides both conceptual knowledge of quantitative finance and a hands-on approach to using Python. It begins with a description of concepts prior to the application of Python with the purpose of understanding how to compute and interpret results. This book offers practical applications in the field of finance concerning Python, a language that is more and more relevant in the financial arena due to big data. This will lead to a better understanding of finance as it gives a descriptive process for students, academics and practitioners.
Practical Quantitative Finance With Asp Net Core And Angular
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Author : Jack Xu
language : en
Publisher: UniCAD
Release Date : 2019-03
Practical Quantitative Finance With Asp Net Core And Angular written by Jack Xu and has been published by UniCAD this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03 with Business & Economics categories.
This book provides comprehensive details of developing ultra-modern, responsive single-page applications (SPA) for quantitative finance using ASP.NET Core and Angular. It pays special attention to create distributed web SPA applications and reusable libraries that can be directly used to solve real-world problems in quantitative finance. The book contains: Overview of ASP.NET Core and Angular, which is necessary to create SPA for quantitative finance. Step-by-step approaches to create a variety of Angular compatible real-time stock charts and technical indicators using ECharts and TA-Lib. Introduction to access market data from online data sources using .NET Web API and Angular service, including EOD, intraday, real-time stock quotes, interest rates. Detailed procedures to price equity options and fixed-income instruments using QuantLib, including European/American/Barrier/Bermudan options, bonds, CDS, as well as related topics such as cash flows, term structures, yield curves, discount factors, and zero-coupon bonds. Detailed explanation to linear analysis and machine learning in finance, which covers linear regression, PCA, KNN, SVM, and neural networks. In-depth descriptions of trading strategy development and back-testing for crossover and z-score based trading signals.
Advanced Quantitative Finance
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Author : William Johnson
language : en
Publisher: HiTeX Press
Release Date : 2024-10-18
Advanced Quantitative Finance written by William Johnson and has been published by HiTeX Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-18 with Business & Economics categories.
"Advanced Quantitative Finance: Trading, Risk, and Portfolio Optimization" unfolds as an essential guide for anyone eager to delve into the sophisticated world of modern finance. This comprehensive text blends theoretical underpinnings with practical insights, offering a robust exploration of the quantitative techniques driving today's markets. Each chapter systematically demystifies complex subjects—from risk management and derivatives pricing to algorithmic trading and asset pricing models—empowering readers to grasp the nuances of financial analysis with clarity and precision. Structured for both novices and seasoned professionals, the book navigates the latest advancements in machine learning, big data analytics, and behavioral finance, presenting them as indispensable tools for the contemporary financial landscape. With a focus on actionable knowledge and strategic applications, readers will gain the proficiency needed to enhance their decision-making, optimize investment portfolios, and effectively manage risk in an ever-evolving economic environment. This book is your invitation to not only understand quantitative finance but to excel in it, unlocking new levels of insight and innovation in your financial pursuits.