Download or read book Python Pour le management l conomie et la finance written by Miia Chabot and published by De Boeck Supérieur. This book was released on 2023-01-09 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt: Ce manuel introductif est conçu pour répondre aux attentes d'étudiants en économie - gestion débutant sur Python et aux élèves-ingénieurs en spécialisation finance. Les thèmes couverts sont les suivants : • introduction à Python et à son univers ; • gestion des données économiques, comptables et financières ; • gestion de portefeuille, trading algorithmique, modèles d'évaluation du prix des options, ESG investing ; • algorithmes de traitement de données qualitatives sous forme de word-clouds ; • réalisation de cartographies de risques professionnelles et de heatmaps, gestion de projets, etc. L'originalité majeure du livre est de proposer différents parcours de lecture, tous appliqués au management, à l'économie et à la finance. Chaque parcours s'accompagne de conseils pour se familiariser avec le langage de programmation, d'exercices corrigés, ainsi que d'outils d'évaluation de la compréhension. Pour chacun des thèmes traités, les codes sont mis à la disposition des lecteurs et les données utilisées dans l'ensemble des applications proposées sont libres d'accès. Le lecteur dispose ainsi d'une véritable boîte à outils qu'il pourra s'approprier puis faire évoluer en fonction de ses besoins et/ou de ses missions en entreprise.
Download or read book Applied Quantitative Finance written by Mauricio Garita and published by Springer Nature. This book was released on 2021-09-03 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Python for Finance written by Dmytro Zherlitsyn and published by BPB Publications. This book was released on 2024-07-30 with total page 480 pages. Available in PDF, EPUB and Kindle. Book excerpt: DESCRIPTION Python's intuitive syntax and beginner-friendly nature makes it an ideal programming language for financial professionals. It acts as a bridge between the world of finance and data analysis. This book will introduce essential concepts in financial analysis methods and models, covering time-series analysis, graphical analysis, technical and fundamental analysis, asset pricing and portfolio theory, investment and trade strategies, risk assessment and prediction, and financial ML practices. The Python programming language and its ecosystem libraries, such as Pandas, NumPy, SciPy, Statsmodels, Matplotlib, Seaborn, Scikit-learn, Prophet, and other data science tools will demonstrate these rooted financial concepts in practice examples. This book will help you understand the concepts of financial market dynamics, estimate the metrics of financial asset profitability, predict trends, evaluate strategies, optimize portfolios, and manage financial risks. You will also learn data analysis techniques using Python programming language to understand the basics of data preparation, visualization, and manipulation in the world of financial data. KEY FEATURES ● Comprehensive guide to Python for financial data analysis and modeling. ● Practical examples and real-world applications for immediate implementation. ● Covers advanced topics like regression, Machine Learning and time series forecasting. WHAT YOU WILL LEARN ● Learn financial data analysis using Python data science libraries and techniques. ● Learn Python visualization tools to justify investment and trading strategies. ● Learn asset pricing and portfolio management methods with Python. ● Learn advanced regression and time series models for financial forecasting. ● Learn risk assessment and volatility modeling methods with Python. WHO THIS BOOK IS FOR This book is designed for financial analysts and other professionals interested in the financial industry with a basic understanding of Python programming and statistical analysis. It is also suitable for students in finance and data science who wish to apply Python tools to financial data analysis and decision-making. TABLE OF CONTENTS 1. Getting Started with Python for Finance 2. Python Tools for Data Analysis: Primer to Pandas and NumPy 3. Financial Data Manipulation with Python 4. Exploratory Data Analysis for Finance 5. Investment and Trading Strategies 6. Asset Pricing and Portfolio Management 7. Time Series Analysis and Financial Data Forecasting 8. Risk Assessment and Volatility Modelling 9. Machine Learning and Deep Learning in Finance 10. Time Series Analysis and Forecasting with FB Prophet Library Appendix A: Python Code Examples for Finance Appendix B: Glossary Appendix C: Valuable Resources
Download or read book Financial Modelling in Python written by Shayne Fletcher and published by John Wiley & Sons. This book was released on 2010-10-28 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt: "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.
Download or read book Python for Finance written by Yves Hilpisch and published by O'Reilly Media. This book was released on 2018-12-05 with total page 714 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Python for Accounting and Finance written by Sunil Kumar and published by Springer Nature. This book was released on with total page 502 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Python for Finance written by Yves Hilpisch and published by "O'Reilly Media, Inc.". This book was released on 2014-12-11 with total page 750 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Download or read book Python for Finance written by Yuxing Yan and published by Packt Publishing Ltd. This book was released on 2017-06-30 with total page 586 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn and implement various Quantitative Finance concepts using the popular Python libraries About 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 finance Who This Book Is For This 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 programs In Detail This 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 approach This 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.
Download or read book Hands On Python for Finance written by Krish Naik and published by . This book was released on 2019-03-29 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn and implement quantitative finance using popular Python libraries like NumPy, pandas, and Keras Key Features Understand Python data structure fundamentals and work with time series data Use popular Python libraries including TensorFlow, Keras, and SciPy to deploy key concepts in quantitative finance Explore various Python programs and learn finance paradigms Book Description Python is one of the most popular languages used for quantitative finance. With this book, you'll explore the key characteristics of Python for finance, solve problems in finance, and understand risk management. The book starts with major concepts and techniques related to quantitative finance, and an introduction to some key Python libraries. Next, you'll implement time series analysis using pandas and DataFrames. The following chapters will help you gain an understanding of how to measure the diversifiable and non-diversifiable security risk of a portfolio and optimize your portfolio by implementing Markowitz Portfolio Optimization. Sections on regression analysis methodology will help you to value assets and understand the relationship between commodity prices and business stocks. In addition to this, you'll be able to forecast stock prices using Monte Carlo simulation. The book will also highlight forecast models that will show you how to determine the price of a call option by analyzing price variation. You'll also use deep learning for financial data analysis and forecasting. In the concluding chapters, you will create neural networks with TensorFlow and Keras for forecasting and prediction. By the end of this book, you will be equipped with the skills you need to perform different financial analysis tasks using Python What you will learn Clean financial data with data preprocessing Visualize financial data using histograms, color plots, and graphs Perform time series analysis with pandas for forecasting Estimate covariance and the correlation between securities and stocks Optimize your portfolio to understand risks when there is a possibility of higher returns Calculate expected returns of a stock to measure the performance of a portfolio manager Create a prediction model using recurrent neural networks (RNN) with Keras and TensorFlow Who this book is for This book is ideal for aspiring data scientists, Python developers and anyone who wants to start performing quantitative finance using Python. You can also make this beginner-level guide your first choice if you're looking to pursue a career as a financial analyst or a data analyst. Working knowledge of Python programming language is necessary.
Download or read book Python for Finance Cookbook written by Eryk Lewinson and published by Packt Publishing Ltd. This book was released on 2022-12-30 with total page 741 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Python pour la finance written by Yves Hilpisch and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Python for finance written by Yves J. Hilpisch and published by . This book was released on 2018 with total page 691 pages. Available in PDF, EPUB and Kindle. Book excerpt: "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."--ProQuest.
Download or read book Python for Finance written by Jay Chen and published by Createspace Independent Publishing Platform. This book was released on 2019-10-10 with total page 154 pages. Available in PDF, EPUB and Kindle. Book excerpt: A beginner's guide for learning Python in the context of finance and economics. Ideal for undergraduate and graduate students who want to learn coding, but have no experience before. The book has easy to understand step-by-step instructions and plenty of exercises.
Download or read book Python Libraries for Finance written by Reactive Publishing and published by Independently Published. This book was released on 2024-06-02 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Mastering Python for Finance written by James Ma and published by . This book was released on 2015-04-29 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Annotation If you are an undergraduate or graduate student, a beginner to algorithmic development and research, or a software developer in the financial industry who is interested in using Python for quantitative methods in finance, this is the book for you. It would be helpful to have a bit of familiarity with basic Python usage, but no prior experience is required.
Download or read book Python for Finance written by Yves Hilpisch and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Python pour la finance written by Yves Hilpisch and published by First Interactive. This book was released on 2024-10-03 with total page 1066 pages. Available in PDF, EPUB and Kindle. Book excerpt: Un livre unique pour opérer l'implémentation de Python dans les applications de core trading L'industrie de la finance a récemment adopté Python comme langage de développement pour toutes les applications d'analyse financière, de trading algorithmique et de gestion des risques. Basé sur la version 3 de Python, ce livre propose au lecteur de le guider dans le développement d'applications d'analyse quantitative à travers les différentes bibliothèques Python et les outils spécifiquement destinés aux applications financières et d'analyse financière interactive. A travers de nombreux exemples pratiques, Yves Hilpisch met également en avant le développement d'un outil destiné à la méthode de simulation de Monte-Carlo qui permet d'introduire une approche statistique du risque dans une décision financière.
