Python For Finance Cookbook
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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.
Python For Finance Cookbook
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Author : Eryk Lewinson
language : en
Publisher: Packt Publishing Ltd
Release Date : 2020-01-31
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 2020-01-31 with Computers categories.
Solve common and not-so-common financial problems using Python libraries such as NumPy, SciPy, and pandas Key FeaturesUse powerful Python libraries such as pandas, NumPy, and SciPy to analyze your financial dataExplore unique recipes for financial data analysis and processing with PythonEstimate popular financial models such as CAPM and GARCH using a problem-solution approachBook Description Python is one of the most popular programming languages used in the financial industry, with a huge set of accompanying libraries. In this book, you'll cover different ways of downloading financial data and preparing it for modeling. You'll calculate popular indicators used in technical analysis, such as Bollinger Bands, MACD, RSI, and backtest automatic trading strategies. Next, you'll cover time series analysis and models, such as exponential smoothing, ARIMA, and GARCH (including multivariate specifications), before exploring the popular CAPM and the Fama-French three-factor model. You'll then discover how to optimize asset allocation and use Monte Carlo simulations for tasks such as calculating the price of American options and estimating the Value at Risk (VaR). In later chapters, you'll work through an entire data science project in the financial domain. You'll also learn how to solve the credit card fraud and default problems using advanced classifiers such as random forest, XGBoost, LightGBM, and stacked models. You'll then be able to tune the hyperparameters of the models and handle class imbalance. Finally, you'll focus on learning how to use deep learning (PyTorch) for approaching financial tasks. By the end of this book, you’ll have learned how to effectively analyze financial data using a recipe-based approach. What you will learnDownload and preprocess financial data from different sourcesBacktest the performance of automatic trading strategies in a real-world settingEstimate financial econometrics models in Python and interpret their resultsUse Monte Carlo simulations for a variety of tasks such as derivatives valuation and risk assessmentImprove the performance of financial models with the latest Python librariesApply machine learning and deep learning techniques to solve different financial problemsUnderstand the different approaches used to model financial time series dataWho this book is for This book is for financial analysts, data analysts, and Python developers who want to learn how to implement a broad range of tasks in the finance domain. Data scientists looking to devise intelligent financial strategies to perform efficient financial analysis will also find this book useful. Working knowledge of the Python programming language is mandatory to grasp the concepts covered in the book effectively.
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.
Basic Python In Finance
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Author : Bob Mather
language : en
Publisher:
Release Date : 2019-10-28
Basic Python In Finance written by Bob Mather and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-28 with 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. Here's What's Included In this Book: 5 Reasons why Python is the best programming language for implementing financial trading strategies 4 Basic Trading Strategies for Success that most people have forgotten The Importance of Time Series Data in Trading Analysis Step-by-Step Guide to Setting up your Python workspace How to Import Time Series Data from Global Databases into Python 4 Different Methods and Examples to Analyze Data with Python Pandas The Best Python Methods to Visualize Data to make Effective Decisions 4 Common Python Financial Analysis tools to decide which securities to invest in 5 Trading Strategies to forecast market trends Even if you have never touched a computer in your life so far, you will gain a lot from this book. Scroll up and click "Add to Cart" now
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
Hands On Python For Finance
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Author : Krish Naik
language : en
Publisher:
Release Date : 2019-03-29
Hands On Python For Finance written by Krish Naik and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-29 with Computers categories.
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.
Python For Finance
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Author : Yves Hilpisch
language : en
Publisher:
Release Date : 2014
Python For Finance written by Yves Hilpisch and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014 with Finance categories.
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.
Artificial Intelligence In Finance
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Author : Yves Hilpisch
language : en
Publisher: O'Reilly Media
Release Date : 2020-11-10
Artificial Intelligence In Finance written by Yves 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 2020-11-10 with Business & Economics categories.
Many industries have been revolutionized by the widespread adoption of AI and machine learning. The programmatic availability of historical and real-time financial data in combination with techniques from AI and machine learning will also change the financial industry in a fundamental way. This practical book explains how to use AI and machine learning to discover statistical inefficiencies in financial markets and exploit them through algorithmic trading. Author Yves Hilpisch shows practitioners, students, and academics in both finance and data science how machine and deep learning algorithms can be applied to finance. Thanks to lots of self-contained Python examples, you'll be able to replicate all results and figures presented in the book. Examine how data is reshaping finance from a theory-driven to a data-driven discipline Understand the major possibilities, consequences, and resulting requirements of AI-first finance Get up to speed on the tools, skills, and major use cases to apply AI in finance yourself Apply neural networks and reinforcement learning to discover statistical inefficiencies in financial markets Delve into the concepts of the technological singularity and the financial singularity