Quantitative Finance With Python
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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.
Quantitative Finance With Case Studies In Python
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Author : Chris Kelliher
language : en
Publisher: CRC Press
Release Date : 2025-12-29
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 2025-12-29 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 and mortgage-backed securitie, more trade ideas embedded in each chapter and also via a dedicated chapter analyzing a set of derivatives trades. There are additional examples throughout based on recent market dynamics, including the post-Covid inflation shock and its impact on risk parity strategies. 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]
Applied Quantitative Finance
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Author : Mauricio Garita
language : en
Publisher:
Release Date : 2021
Applied Quantitative Finance written by Mauricio Garita and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with categories.
This book provides conceptual knowledge on quantitative finance and a hands-on experience using Python. It begins with a description of concepts prior to the application of Python with the purpose of understanding how to compute and also the interpretation of the results. The book will satisfy the lack of information 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 advance finance as it gives a descriptive process for students, academics and practitioners. .
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 Computers 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
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.
Python For Finance
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Author : Yuxing Yan
language : en
Publisher:
Release Date : 2017-06-30
Python For Finance written by Yuxing Yan and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-06-30 with Computers categories.
Learn and implement various Quantitative Finance concepts using the popular Python librariesAbout This Book* Understand the fundamentals of Python data structures and work with time-series data* Implement key concepts in quantitative finance using popular Python libraries such as NumPy, SciPy, and matplotlib* A step-by-step tutorial packed with many Python programs that will help you learn how to apply Python to financeWho This Book Is ForThis book assumes that the readers have some basic knowledge related to Python. However, he/she has no knowledge of quantitative finance. In addition, he/she has no knowledge about financial data.What You Will Learn* Become acquainted with Python in the first two chapters* Run CAPM, Fama-French 3-factor, and Fama-French-Carhart 4-factor models* Learn how to price a call, put, and several exotic options* Understand Monte Carlo simulation, how to write a Python program to replicate the Black-Scholes-Merton options model, and how to price a few exotic options* Understand the concept of volatility and how to test the hypothesis that volatility changes over the years* Understand the ARCH and GARCH processes and how to write related Python programsIn DetailThis book uses Python as its computational tool. Since Python is free, any school or organization can download and use it.This book is organized according to various finance subjects. In other words, the first edition focuses more on Python, while the second edition is truly trying to apply Python to finance.The book starts by explaining topics exclusively related to Python. Then we deal with critical parts of Python, explaining concepts such as time value of money stock and bond evaluations, capital asset pricing model, multi-factor models, time series analysis, portfolio theory, options and futures.This book will help us to learn or review the basics of quantitative finance and apply Python to solve various problems, such as estimating IBM's market risk, running a Fama-French 3-factor, 5-factor, or Fama-French-Carhart 4 factor model, estimating the VaR of a 5-stock portfolio, estimating the optimal portfolio, and constructing the efficient frontier for a 20-stock portfolio with real-world stock, and with Monte Carlo Simulation. Later, we will also learn how to replicate the famous Black-Scholes-Merton option model and how to price exotic options such as the average price call option.Style and approachThis book takes a step-by-step approach in explaining the libraries and modules in Python, and how they can be used to implement various aspects of quantitative finance. Each concept is explained in depth and supplemented with code examples for better understanding.
Python For Finance
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Author : Yuxing Yan
language : en
Publisher: Packt Publishing Ltd
Release Date : 2014-04-25
Python For Finance written by Yuxing Yan 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 2014-04-25 with Computers categories.
A hands-on guide with easy-to-follow examples to help you learn about option theory, quantitative finance, financial modeling, and time series using Python. Python for Finance is perfect for graduate students, practitioners, and application developers who wish to learn how to utilize Python to handle their financial needs. Basic knowledge of Python will be helpful but knowledge of programming is necessary.
Stochastic Finance With Python
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Author : Avishek Nag
language : en
Publisher: Springer Nature
Release Date : 2024-12-13
Stochastic Finance With Python written by Avishek Nag and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-13 with Computers categories.
Journey through the world of stochastic finance from learning theory, underlying models, and derivations of financial models (stocks, options, portfolios) to the almost production-ready Python components under cover of stochastic finance. This book will show you the techniques to estimate potential financial outcomes using stochastic processes implemented with Python. The book starts by reviewing financial concepts, such as analyzing different asset types like stocks, options, and portfolios. It then delves into the crux of stochastic finance, providing a glimpse into the probabilistic nature of financial markets. You’ll look closely at probability theory, random variables, Monte Carlo simulation, and stochastic processes to cover the prerequisites from the applied perspective. Then explore random walks and Brownian motion, essential in understanding financial market dynamics. You’ll get a glimpse of two vital modelling tools used throughout the book - stochastic calculus and stochastic differential equations (SDE). Advanced topics like modeling jump processes and estimating their parameters by Fourier-transform-based density recovery methods can be intriguing to those interested in full-numerical solutions of probability models. Moving forward, the book covers options, including the famous Black-Scholes model, dissecting it from both risk-neutral probability and PDE perspectives. A chapter at the end also covers the discovery of portfolio theory, beginning with mean-variance analysis and advancing to portfolio simulation and the efficient frontier. What You Will Learn Understand applied probability and statistics with finance Design forecasting models of the stock price with the stochastic process, Monte-Carlo simulation. Option price estimation with both risk-neutral probabilistic and PDE-driven approach. Use Object-oriented Python to design financial models with reusability. Who This Book Is For Data scientists, quantitative researchers and practitioners, software engineers and AI architects interested in quantitative finance
Mathematical Modeling And Computation In Finance With Exercises And Python And Matlab Computer Codes
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Author : Cornelis W Oosterlee
language : en
Publisher: World Scientific
Release Date : 2019-10-29
Mathematical Modeling And Computation In Finance With Exercises And Python And Matlab Computer Codes written by Cornelis W Oosterlee and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-29 with Business & Economics categories.
This book discusses the interplay of stochastics (applied probability theory) and numerical analysis in the field of quantitative finance. The stochastic models, numerical valuation techniques, computational aspects, financial products, and risk management applications presented will enable readers to progress in the challenging field of computational finance.When the behavior of financial market participants changes, the corresponding stochastic mathematical models describing the prices may also change. Financial regulation may play a role in such changes too. The book thus presents several models for stock prices, interest rates as well as foreign-exchange rates, with increasing complexity across the chapters. As is said in the industry, 'do not fall in love with your favorite model.' The book covers equity models before moving to short-rate and other interest rate models. We cast these models for interest rate into the Heath-Jarrow-Morton framework, show relations between the different models, and explain a few interest rate products and their pricing.The chapters are accompanied by exercises. Students can access solutions to selected exercises, while complete solutions are made available to instructors. The MATLAB and Python computer codes used for most tables and figures in the book are made available for both print and e-book users. This book will be useful for people working in the financial industry, for those aiming to work there one day, and for anyone interested in quantitative finance. The topics that are discussed are relevant for MSc and PhD students, academic researchers, and for quants in the financial industry.
Applied Quantitative Finance In Python Selected Theories And Examples
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Author : Aleš Kresta
language : en
Publisher:
Release Date : 2024
Applied Quantitative Finance In Python Selected Theories And Examples written by Aleš Kresta and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024 with categories.