Python For Finance
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Python For Finance
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Author : Yves J. Hilpisch
language : en
Publisher: O'Reilly Media
Release Date : 2018-12-05
Python For Finance written by Yves J. Hilpisch and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-05 with Computers categories.
The financial industry has recently adopted Python at a tremendous rate, with some of the largest investment banks and hedge funds using it to build core trading and risk management systems. Updated for Python 3, the second edition of this hands-on book helps you get started with the language, guiding developers and quantitative analysts through Python libraries and tools for building financial applications and interactive financial analytics. Using practical examples throughout 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.
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.
Financial Theory With Python
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Author : Yves Hilpisch
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2021-09-23
Financial Theory With Python 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 2021-09-23 with Business & Economics categories.
Nowadays, finance, mathematics, and programming are intrinsically linked. This book provides the relevant foundations of each discipline to give you the major tools you need to get started in the world of computational finance. Using an approach where mathematical concepts provide the common background against which financial ideas and programming techniques are learned, this practical guide teaches you the basics of financial economics. Written by the best-selling author of Python for Finance, Yves Hilpisch, Financial Theory with Python explains financial, mathematical, and Python programming concepts in an integrative manner so that the interdisciplinary concepts reinforce each other. Draw upon mathematics to learn the foundations of financial theory and Python programming Learn about financial theory, financial data modeling, and the use of Python for computational finance Leverage simple economic models to better understand basic notions of finance and Python programming concepts Use both static and dynamic financial modeling to address fundamental problems in finance, such as pricing, decision-making, equilibrium, and asset allocation Learn the basics of Python packages useful for financial modeling, such as NumPy, pandas, Matplotlib, and SymPy
Financial Modelling In Python
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Author : Shayne Fletcher
language : en
Publisher: John Wiley & Sons
Release Date : 2010-10-28
Financial Modelling In Python written by Shayne Fletcher and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-10-28 with Business & Economics categories.
"Fletcher and Gardner have created a comprehensive resource that will be of interest not only to those working in the field of finance, but also to those using numerical methods in other fields such as engineering, physics, and actuarial mathematics. By showing how to combine the high-level elegance, accessibility, and flexibility of Python, with the low-level computational efficiency of C++, in the context of interesting financial modeling problems, they have provided an implementation template which will be useful to others seeking to jointly optimize the use of computational and human resources. They document all the necessary technical details required in order to make external numerical libraries available from within Python, and they contribute a useful library of their own, which will significantly reduce the start-up costs involved in building financial models. This book is a must read for all those with a need to apply numerical methods in the valuation of financial claims." –David Louton, Professor of Finance, Bryant University This book is directed at both industry practitioners and students interested in designing a pricing and risk management framework for financial derivatives using the Python programming language. It is a practical book complete with working, tested code that guides the reader through the process of building a flexible, extensible pricing framework in Python. The pricing frameworks' loosely coupled fundamental components have been designed to facilitate the quick development of new models. Concrete applications to real-world pricing problems are also provided. Topics are introduced gradually, each building on the last. They include basic mathematical algorithms, common algorithms from numerical analysis, trade, market and event data model representations, lattice and simulation based pricing, and model development. The mathematics presented is kept simple and to the point. The book also provides a host of information on practical technical topics such as C++/Python hybrid development (embedding and extending) and techniques for integrating Python based programs with Microsoft Excel.
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
Basic Python In Finance
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Author : Bob Mather
language : en
Publisher: Bob Mather
Release Date : 2019-10-30
Basic Python In Finance written by Bob Mather and has been published by Bob Mather this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-30 with Business & Economics categories.
Are you looking to automate your trading strategy? Are you looking for a more efficient way of completing your financial analysis? Python is the answer. While looking to gain summarize our knowledge on the subject, we realized that there was a lot of information available in books and the internet. However, there seemed to be too much information. There were 500-page textbooks on the subject that had very little practical use. They were pretty useless for beginners just like a dictionary is useless for anyone trying to learn a language. All these books had tons of theory with no step-by-step guide. There were a whole bunch of other blogs that had basic programming information with no relation to financial strategies. With this in mind, this book starts you off with a step-by-step guide to install Python on your computer; and plot/visualize relevant financial data. Later in the book, you can build on your basic knowledge to learn more about advanced financial analysis and trading strategies to move forward. This book is what you've been looking for.
Python For Finance Cookbook
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Author : Eryk Lewinson
language : en
Publisher: Packt Publishing Ltd
Release Date : 2022-12-30
Python For Finance Cookbook written by Eryk Lewinson 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 2022-12-30 with Computers categories.
Use modern Python libraries such as pandas, NumPy, and scikit-learn and popular machine learning and deep learning methods to solve financial modeling problems Purchase of the print or Kindle book includes a free eBook in the PDF format Key FeaturesExplore unique recipes for financial data processing and analysis with PythonApply classical and machine learning approaches to financial time series analysisCalculate various technical analysis indicators and backtest trading strategiesBook Description Python is one of the most popular programming languages in the financial industry, with a huge collection of accompanying libraries. In this new edition of the Python for Finance Cookbook, you will explore classical quantitative finance approaches to data modeling, such as GARCH, CAPM, factor models, as well as modern machine learning and deep learning solutions. You will use popular Python libraries that, in a few lines of code, provide the means to quickly process, analyze, and draw conclusions from financial data. In this new edition, more emphasis was put on exploratory data analysis to help you visualize and better understand financial data. While doing so, you will also learn how to use Streamlit to create elegant, interactive web applications to present the results of technical analyses. Using the recipes in this book, you will become proficient in financial data analysis, be it for personal or professional projects. You will also understand which potential issues to expect with such analyses and, more importantly, how to overcome them. What you will learnPreprocess, analyze, and visualize financial dataExplore time series modeling with statistical (exponential smoothing, ARIMA) and machine learning modelsUncover advanced time series forecasting algorithms such as Meta's ProphetUse Monte Carlo simulations for derivatives valuation and risk assessmentExplore volatility modeling using univariate and multivariate GARCH modelsInvestigate various approaches to asset allocationLearn how to approach ML-projects using an example of default predictionExplore modern deep learning models such as Google's TabNet, Amazon's DeepAR and NeuralProphetWho this book is for This book is intended for financial analysts, data analysts and scientists, and Python developers with a familiarity with financial concepts. You'll learn how to correctly use advanced approaches for analysis, avoid potential pitfalls and common mistakes, and reach correct conclusions for a broad range of finance problems. Working knowledge of the Python programming language (particularly libraries such as pandas and NumPy) is necessary.
Mastering Python For Finance
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Author : James Ma Weiming
language : en
Publisher: Packt Publishing Ltd
Release Date : 2019-04-30
Mastering Python For Finance written by James Ma Weiming 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 2019-04-30 with Computers categories.
Take your financial skills to the next level by mastering cutting-edge mathematical and statistical financial applications Key FeaturesExplore advanced financial models used by the industry and ways of solving them using PythonBuild state-of-the-art infrastructure for modeling, visualization, trading, and moreEmpower your financial applications by applying machine learning and deep learningBook Description The second edition of Mastering Python for Finance will guide you through carrying out complex financial calculations practiced in the industry of finance by using next-generation methodologies. You will master the Python ecosystem by leveraging publicly available tools to successfully perform research studies and modeling, and learn to manage risks with the help of advanced examples. You will start by setting up your Jupyter notebook to implement the tasks throughout the book. You will learn to make efficient and powerful data-driven financial decisions using popular libraries such as TensorFlow, Keras, Numpy, SciPy, and sklearn. You will also learn how to build financial applications by mastering concepts such as stocks, options, interest rates and their derivatives, and risk analytics using computational methods. With these foundations, you will learn to apply statistical analysis to time series data, and understand how time series data is useful for implementing an event-driven backtesting system and for working with high-frequency data in building an algorithmic trading platform. Finally, you will explore machine learning and deep learning techniques that are applied in finance. By the end of this book, you will be able to apply Python to different paradigms in the financial industry and perform efficient data analysis. What you will learnSolve linear and nonlinear models representing various financial problemsPerform principal component analysis on the DOW index and its componentsAnalyze, predict, and forecast stationary and non-stationary time series processesCreate an event-driven backtesting tool and measure your strategiesBuild a high-frequency algorithmic trading platform with PythonReplicate the CBOT VIX index with SPX options for studying VIX-based strategiesPerform regression-based and classification-based machine learning tasks for predictionUse TensorFlow and Keras in deep learning neural network architectureWho this book is for If you are a financial or data analyst or a software developer in the financial industry who is interested in using advanced Python techniques for quantitative methods in finance, this is the book you need! You will also find this book useful if you want to extend the functionalities of your existing financial applications by using smart machine learning techniques. Prior experience in Python is required.
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
Python Libraries For Finance
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Author : Reactive Publishing
language : en
Publisher: Independently Published
Release Date : 2024-06-02
Python Libraries For Finance written by Reactive Publishing and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-02 with Computers categories.
Reactive Publishing "Python Libraries for Finance" is a comprehensive guide designed for financial analysts, data scientists, and finance professionals seeking to leverage Python's powerful libraries to gain a competitive edge in the finance industry. This book bridges the gap between finance and technology, providing practical insights and hands-on examples to enhance financial modeling, risk management, algorithmic trading, and more. Target Audience Financial Analysts and Professionals Data Scientists specializing in finance Quantitative Analysts and Traders Academics and Students in Finance and Economics IT Professionals working in the finance sector Key Features Comprehensive Coverage: Detailed exploration of essential Python libraries including Pandas, NumPy, SciPy, Matplotlib, and more, tailored specifically for financial applications. Practical Examples: Real-world examples and case studies demonstrating the application of Python in various financial contexts, from portfolio optimization to time series analysis. Step-by-Step Guides: Clear, step-by-step instructions for setting up and using Python libraries, making it accessible for both beginners and experienced programmers. Advanced Techniques: In-depth coverage of advanced topics such as machine learning in finance, algorithmic trading strategies, and financial econometrics. Hands-On Projects: Interactive projects that allow readers to apply what they've learned, ensuring they gain practical experience and confidence in using Python for finance. Why This Book? Expertise: Written by a seasoned financial analyst with deep knowledge of both finance and Python programming. Relevance: Addresses the growing demand for tech-savvy finance professionals who can harness the power of Python to drive innovation and efficiency. Usability: Designed with a user-friendly approach, making complex concepts accessible through clear explanations and practical examples. Author's Credentials The author is a senior financial analyst with extensive experience in financial modeling, risk management, and algorithmic trading. Having authored several successful books on finance and Python, the author brings a wealth of knowledge and practical insights to this indispensable guide. Testimonials "A must-read for anyone looking to integrate Python into their financial toolkit. The practical examples and hands-on projects are invaluable." Johann Strauss- Financial Analyst. "This book demystifies the complexities of financial programming with Python. It's a game-changer for finance professionals." Vincent Bisette - Data Scientist. Unlock the potential of Python for finance. "Python Libraries for Finance" is your essential guide to mastering the tools that are revolutionizing the financial industry. Order your copy today and stay ahead in the fast-evolving world of finance.