Python For Finance And Algorithmic Trading
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Python For Finance And Algorithmic Trading
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Author : Lucas INGLESE
language : fr
Publisher:
Release Date : 2021-09-25
Python For Finance And Algorithmic Trading written by Lucas INGLESE and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-25 with categories.
The financial sector is undergoing significant restructuring. Traders and portfolio managers are increasingly becoming financial data scientists. Banks, investment funds, and fintech are increasingly automating their investments by integrating machine learning and deep learning algorithms into their decision-making process. The book presents the benefits of portfolio management, statistics, and machine learning applied to live trading with MetaTrader 5. *Learn portfolio management technics and how to implement your optimization criterion *How to backtest a strategy using the most valuable metrics in trading *Import data from your broker to be as close as possible to the market *Learn statistical arbitrage through pair trading strategies *Generate market predictions using machine learning, deep learning, and time series analysis *Learn how to find the best take profit, stop loss, and leverage for your strategies *Combine trading strategies using portfolio management to increase the robustness of the strategies *Connect your Python algorithm to your MetaTrader 5 and run it with a demo or live trading account *Use all codes in the book for live trading or screener if you prefer manual trading
Python For Algorithmic Trading
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Author : Yves Hilpisch
language : en
Publisher: O'Reilly Media
Release Date : 2020-11-12
Python For Algorithmic Trading 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 2020-11-12 with Computers categories.
Algorithmic trading, once the exclusive domain of institutional players, is now open to small organizations and individual traders using online platforms. The tool of choice for many traders today is Python and its ecosystem of powerful packages. In this practical book, author Yves Hilpisch shows students, academics, and practitioners how to use Python in the fascinating field of algorithmic trading. You'll learn several ways to apply Python to different aspects of algorithmic trading, such as backtesting trading strategies and interacting with online trading platforms. Some of the biggest buy- and sell-side institutions make heavy use of Python. By exploring options for systematically building and deploying automated algorithmic trading strategies, this book will help you level the playing field. Set up a proper Python environment for algorithmic trading Learn how to retrieve financial data from public and proprietary data sources Explore vectorization for financial analytics with NumPy and pandas Master vectorized backtesting of different algorithmic trading strategies Generate market predictions by using machine learning and deep learning Tackle real-time processing of streaming data with socket programming tools Implement automated algorithmic trading strategies with the OANDA and FXCM trading platforms
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 Algorithmic Trading
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Author : J P Morgan
language : en
Publisher: Independently Published
Release Date : 2024-08-06
Python For Algorithmic Trading written by J P Morgan and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-06 with Computers categories.
Unlock the Secrets of Python for Algorithmic Trading: A Step-by-Step Guide to Consistent Profits Discover the power of Python for Algorithmic Trading and elevate your trading game with "Python for Algorithmic Trading: Mastering Strategies for Consistent Profits." This comprehensive guide provides step-by-step instructions on creating and implementing advanced algorithmic trading strategies. Whether you're a Python programmer, web developer, trading enthusiast, student, or professional, this book is your ticket to navigating the complexities of the trading world and boosting your profitability. Key Features and Benefits: Step-by-Step Guidance: Create Advanced Strategies: Develop sophisticated strategies with clear, easy-to-follow instructions in this python for algorithmic trading book. Implement with Confidence: Learn to implement your strategies effectively, minimizing errors and maximizing efficiency using algorithmic trading python code. Enhance Trading Efficiency: Automate Your Trades: Leverage Python to automate trading processes, reducing manual intervention and increasing accuracy with algorithmic trading python libraries. Optimize Performance: Fine-tune your algorithms to enhance trading performance and ensure consistent results in your algorithmic trading python projects. Boost Your Profitability: Maximize Returns: Discover techniques to maximize your trading returns through data-driven strategies. Minimize Risks: Learn to identify and mitigate potential risks, ensuring more reliable and profitable trades. Navigate Complexities: Comprehensive Coverage: Gain a thorough understanding of the complexities involved in algorithmic trading with Python for algorithmic trading from idea to cloud deployment. Practical Insights: Benefit from practical insights and real-world examples that illustrate key concepts and techniques. Tailored for All Skill Levels: Beginner-Friendly: Start with the basics and gradually progress to more advanced topics, making it suitable for all skill levels. Expert Tips: Access tips and tricks from seasoned professionals to take your trading strategies to the next level, aligning with what you'd find in a Python for algorithmic trading course. Who Should Read This Book? Python Programmers: Enhance your programming skills with finance-specific applications using Python for finance and algorithmic trading. Web Developers: Integrate financial analytics and trading systems into your projects with ease. Trading Enthusiasts: Develop and implement data-driven trading strategies to improve your trading game. Students: Build a solid foundation in algorithmic trading, preparing you for a successful career in finance and technology. Technology Professionals: Stay ahead in your field by mastering the latest tools and techniques in algorithmic trading. Why Choose This Book? Expert Author: Learn from an experienced professional who has successfully implemented algorithmic trading strategies in real-world scenarios. Hands-On Learning: Engage with practical examples and projects that provide real-world applications of the concepts covered. Optimized for Success: Whether you're new to algorithmic trading or looking to refine your strategies, this book offers valuable insights and guidance to help you succeed. Order your copy today and unlock the potential of algorithmic trading with Python!
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 Computers 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
Reinforcement Learning For Finance
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Author : Yves J. Hilpisch
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2024-10-14
Reinforcement Learning For Finance written by Yves J. 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 2024-10-14 with Business & Economics categories.
Reinforcement learning (RL) has led to several breakthroughs in AI. The use of the Q-learning (DQL) algorithm alone has helped people develop agents that play arcade games and board games at a superhuman level. More recently, RL, DQL, and similar methods have gained popularity in publications related to financial research. This book is among the first to explore the use of reinforcement learning methods in finance. Author Yves Hilpisch, founder and CEO of The Python Quants, provides the background you need in concise fashion. ML practitioners, financial traders, portfolio managers, strategists, and analysts will focus on the implementation of these algorithms in the form of self-contained Python code and the application to important financial problems. This book covers: Reinforcement learning Deep Q-learning Python implementations of these algorithms How to apply the algorithms to financial problems such as algorithmic trading, dynamic hedging, and dynamic asset allocation This book is the ideal reference on this topic. You'll read it once, change the examples according to your needs or ideas, and refer to it whenever you work with RL for finance. Dr. Yves Hilpisch is founder and CEO of The Python Quants, a group that focuses on the use of open source technologies for financial data science, AI, asset management, algorithmic trading, and computational finance.
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.
Artificial Intelligence In Finance
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Author : Yves Hilpisch
language : en
Publisher: O'Reilly Media
Release Date : 2020-10-14
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 2020-10-14 with Business & Economics categories.
The widespread adoption of AI and machine learning is revolutionizing many industries today. Once these technologies are combined with the programmatic availability of historical and real-time financial data, the financial industry will also change fundamentally. With this practical book, you'll learn 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 practical ways to apply machine learning and deep learning algorithms to finance. Thanks to lots of self-contained Python examples, you'll be able to replicate all results and figures presented in the book. In five parts, this guide helps you: Learn central notions and algorithms from AI, including recent breakthroughs on the way to artificial general intelligence (AGI) and superintelligence (SI) Understand why data-driven finance, AI, and machine learning will have a lasting impact on financial theory and practice Apply neural networks and reinforcement learning to discover statistical inefficiencies in financial markets Identify and exploit economic inefficiencies through backtesting and algorithmic trading--the automated execution of trading strategies Understand how AI will influence the competitive dynamics in the financial industry and what the potential emergence of a financial singularity might bring about
Python For Algorithmic Trading Cookbook
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Author : Jason Strimpel
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-08-16
Python For Algorithmic Trading Cookbook written by Jason Strimpel 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 2024-08-16 with Business & Economics categories.
Harness the power of Python libraries to transform freely available financial market data into algorithmic trading strategies and deploy them into a live trading environment Get With Your Book: PDF Copy, AI Assistant, and Next-Gen Reader Free Key Features Follow practical Python recipes to acquire, visualize, and store market data for market research Design, backtest, and evaluate the performance of trading strategies using professional techniques Deploy trading strategies built in Python to a live trading environment with API connectivity Book DescriptionDiscover how Python has made algorithmic trading accessible to non-professionals with unparalleled expertise and practical insights from Jason Strimpel, founder of PyQuant News and a seasoned professional with global experience in trading and risk management. This book guides you through from the basics of quantitative finance and data acquisition to advanced stages of backtesting and live trading. Detailed recipes will help you leverage the cutting-edge OpenBB SDK to gather freely available data for stocks, options, and futures, and build your own research environment using lightning-fast storage techniques like SQLite, HDF5, and ArcticDB. This book shows you how to use SciPy and statsmodels to identify alpha factors and hedge risk, and construct momentum and mean-reversion factors. You’ll optimize strategy parameters with walk-forward optimization using VectorBT and construct a production-ready backtest using Zipline Reloaded. Implementing all that you’ve learned, you’ll set up and deploy your algorithmic trading strategies in a live trading environment using the Interactive Brokers API, allowing you to stream tick-level data, submit orders, and retrieve portfolio details. By the end of this algorithmic trading book, you'll not only have grasped the essential concepts but also the practical skills needed to implement and execute sophisticated trading strategies using Python.What you will learn Acquire and process freely available market data with the OpenBB Platform Build a research environment and populate it with financial market data Use machine learning to identify alpha factors and engineer them into signals Use VectorBT to find strategy parameters using walk-forward optimization Build production-ready backtests with Zipline Reloaded and evaluate factor performance Set up the code framework to connect and send an order to Interactive Brokers Who this book is for Python for Algorithmic Trading Cookbook equips traders, investors, and Python developers with code to design, backtest, and deploy algorithmic trading strategies. You should have experience investing in the stock market, knowledge of Python data structures, and a basic understanding of using Python libraries like pandas. This book is also ideal for individuals with Python experience who are already active in the market or are aspiring to be.
Algorithmic Trading Technical Indicators
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Author : SQ2 SYSTEMS AB
language : en
Publisher: SQ2 SYSTEMS AB
Release Date : 2023-09-20
Algorithmic Trading Technical Indicators written by SQ2 SYSTEMS AB and has been published by SQ2 SYSTEMS AB this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-20 with Business & Economics categories.
"Algorithmic Trading: Technical Indicators" is your go-to guide for unraveling the power of technical indicators in algorithmic trading. If you're intrigued by data-driven signals that inform trading decisions, this book is your key to mastering the art of technical analysis. Designed for traders and investors seeking a practical introduction to technical indicators, this book simplifies the complex world of charts, patterns, and signals. It provides clear insights into how historical price and volume data can drive trading strategies. Explore the fundamental principles of technical analysis, where historical data becomes your ally in making informed trading decisions. Delve into the secrets of candlestick patterns, moving averages, Relative Strength Index (RSI), Moving Average Convergence Divergence (MACD), and Bollinger Bands. These indicators will become your trusted tools for identifying trends, overbought or oversold conditions, and potential reversals. "Algorithmic Trading: Technical Indicators" offers practical guidance on incorporating these indicators into your trading strategy. Discover how to recognize entry and exit points, effectively manage risk with stop-loss and take-profit levels, and enhance your decision-making. This book provides accessible insights without delving into complex technical examples or deep understanding. It's perfect for beginners curious about the power of technical analysis or experienced traders looking to refine their algorithmic strategies. Whether you're new to technical indicators or seeking to enhance your trading skills, "Algorithmic Trading: Technical Indicators" equips you with the knowledge and tools to confidently navigate the world of algorithmic trading through the lens of technical analysis. Join us in harnessing the potential of data-driven trading signals in today's dynamic financial markets.