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Build Technical Indicators In Python
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Book Synopsis Build Technical Indicators in Python by : Domenico Starnini
Download or read book Build Technical Indicators in Python written by Domenico Starnini and published by Domenico Starnini. This book was released on with total page 92 pages. Available in PDF, EPUB and Kindle. Book excerpt: Transform your trading game with 'Build Technical Indicators in Python.' This comprehensive guide offers practical, hands-on guidance for traders and analysts of all levels. With a focus on implementing technical analysis with Python libraries such as TA-Lib and Pandas TA-Lib, you'll gain the skills and knowledge to optimize your trading strategies and improve your success rate. With easy-to-follow instructions and real-world examples, this book is a must-have resource for anyone looking to succeed in today's fast-paced financial markets. Don't miss out on this opportunity to take your trading to the next level. Purchase 'Build Technical Indicators in Python' today and start your journey towards trading success!
Book Synopsis New Technical Indicators in Python by : Sofien Kaabar
Download or read book New Technical Indicators in Python written by Sofien Kaabar and published by . This book was released on 2021-02-18 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: What is this book all about?This book is a modest attempt at presenting a more modern version of Technical Analysis based on objective measures rather than subjective ones. A sizeable chunk of this beautiful type of analysis revolves around technical indicators which is exactly the purpose of this book. I believe it is time to be creative and invent our own indicators that fit our profiles. Having had more success with custom indicators than conventional ones, I have decided to share my findings. The following chapters present new indicators that are the fruit of my research as well as indicators created by brilliant people. I also include the functions to create the indicators in Python and provide how to best use them as well as back-testing results. What am I going to gain?You will gain exposure to many new indicators and concepts that will change the way you think about trading and you will find yourself busy experimenting and choosing the strategy that suits you the best. How is it organized?The order of chapters is not important, although reading the introductory technical chapter is helpful. The book is divided into three parts: part 1 deals with trend-following indicators, part 2 deals with contrarian indicators, part 3 deals with market timing indicators, and finally, part 4 deals with risk and performance indicators.What do you mean when you say this book is dynamic and not static?This means that everything inside gets updated regularly with new material on my Medium profile. I always publish new findings and strategies. Make sure to follow me.What level of knowledge do I need to follow this book?Although a basic or a good understanding of trading and coding is considered very helpful, it is not necessary. At the beginning of the book, I have included a chapter that deals with some Python concepts, but this book is not about Python.
Book Synopsis Python for Finance Cookbook by : Eryk Lewinson
Download or read book Python for Finance Cookbook written by Eryk Lewinson and published by Packt Publishing Ltd. This book was released on 2020-01-31 with total page 426 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis The Book of Trading Strategies by : Sofien Kaabar
Download or read book The Book of Trading Strategies written by Sofien Kaabar and published by . This book was released on 2021-07-06 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: Trading strategies come in different shapes and colors, and having a detailed view on their structure and functioning is very useful towards the path of creating a robust and profitable trading system. The book presents various technical strategies and the way to back-test them in Python. You can think of the book as a mix between introductory Python and an Encyclopedia of trading strategies with a touch of reality.
Book Synopsis Trend Following Strategies in Python by : Sofien Kaabar
Download or read book Trend Following Strategies in Python written by Sofien Kaabar and published by Independently Published. This book was released on 2021-10-31 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: What is this book all about? This book is a modest attempt at presenting a more modern version of technical analysis based on objective measures rather than subjective ones. A sizeable chunk of this beautiful type of analysis revolves around trend-following technical indicators which is what this book covers. I believe it is time to be creative with indicators. The following chapters present trend-following indicators and how to code/use them. The code included in the book is available in the GitHub repository. A QR code link will be provided in the book. What am I going to gain? You will gain exposure to many new indicators and strategies that will change the way you think about trading, and you will find yourself busy experimenting and choosing the strategy that suits you the best. How is it organized? The order of the chapter is not very important, although reading the introductory Python chapter is helpful. The book is divided into four parts: Part 1 deals with different types of moving averages, Part 2 deals with trend-following indicators, Part3 deals with market regime detection techniques, and finally, Part 4 will present many different trend-following technical strategies. What level of knowledge do I need to follow this book? Although a basic or a good understanding of trading and coding is considered very helpful, it is not necessary. At the beginning of the book, I have included a chapter that deals with some Python concepts, but this book is not about Python.
Book Synopsis Python Algorithmic Trading Cookbook by : Pushpak Dagade
Download or read book Python Algorithmic Trading Cookbook written by Pushpak Dagade and published by Packt Publishing Ltd. This book was released on 2020-08-28 with total page 528 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build a solid foundation in algorithmic trading by developing, testing and executing powerful trading strategies with real market data using Python Key FeaturesBuild a strong foundation in algorithmic trading by becoming well-versed with the basics of financial marketsDemystify jargon related to understanding and placing multiple types of trading ordersDevise trading strategies and increase your odds of making a profit without human interventionBook Description If you want to find out how you can build a solid foundation in algorithmic trading using Python, this cookbook is here to help. Starting by setting up the Python environment for trading and connectivity with brokers, you’ll then learn the important aspects of financial markets. As you progress, you’ll learn to fetch financial instruments, query and calculate various types of candles and historical data, and finally, compute and plot technical indicators. Next, you’ll learn how to place various types of orders, such as regular, bracket, and cover orders, and understand their state transitions. Later chapters will cover backtesting, paper trading, and finally real trading for the algorithmic strategies that you've created. You’ll even understand how to automate trading and find the right strategy for making effective decisions that would otherwise be impossible for human traders. By the end of this book, you’ll be able to use Python libraries to conduct key tasks in the algorithmic trading ecosystem. Note: For demonstration, we're using Zerodha, an Indian Stock Market broker. If you're not an Indian resident, you won't be able to use Zerodha and therefore will not be able to test the examples directly. However, you can take inspiration from the book and apply the concepts across your preferred stock market broker of choice. What you will learnUse Python to set up connectivity with brokersHandle and manipulate time series data using PythonFetch a list of exchanges, segments, financial instruments, and historical data to interact with the real marketUnderstand, fetch, and calculate various types of candles and use them to compute and plot diverse types of technical indicatorsDevelop and improve the performance of algorithmic trading strategiesPerform backtesting and paper trading on algorithmic trading strategiesImplement real trading in the live hours of stock marketsWho this book is for If you are a financial analyst, financial trader, data analyst, algorithmic trader, trading enthusiast or anyone who wants to learn algorithmic trading with Python and important techniques to address challenges faced in the finance domain, this book is for you. Basic working knowledge of the Python programming language is expected. Although fundamental knowledge of trade-related terminologies will be helpful, it is not mandatory.
Book Synopsis Technical Indicators With Formula by :
Download or read book Technical Indicators With Formula written by and published by Zex Spyder. This book was released on with total page 39 pages. Available in PDF, EPUB and Kindle. Book excerpt: Technical indicators can inform you about different aspects of the market, such as trend, volatility, momentum, market strength, cycle, and so on. They are mathematical calculations that can be applied to a stock's price, volume, or, even, to another technical indicator. The result is a value that is used to anticipate future changes in prices. Indicators serve three broad functions-to alert, to confirm and to predict. When choosing an indicator to use for analysis, try to choose indicators that complement each other, instead of those that generate the same signals such as Stochastics and RSI, which are good for showing overbought and oversold levels. For analyzing trends, use trend following indicators like moving averages. For trading ranges, use oscillators like RSI. There are 42 technical indicators in this ebook with brief description and mathematical formula of each. Finding potential stocks are easy using these indicators especially if you have charting software which allows you to create your own filters. As always in technical analysis, learning how to read indicators is more of an art than a science.
Book Synopsis Machine Learning for Algorithmic Trading by : Stefan Jansen
Download or read book Machine Learning for Algorithmic Trading written by Stefan Jansen and published by Packt Publishing Ltd. This book was released on 2020-07-31 with total page 822 pages. Available in PDF, EPUB and Kindle. Book excerpt: Leverage machine learning to design and back-test automated trading strategies for real-world markets using pandas, TA-Lib, scikit-learn, LightGBM, SpaCy, Gensim, TensorFlow 2, Zipline, backtrader, Alphalens, and pyfolio. Purchase of the print or Kindle book includes a free eBook in the PDF format. Key FeaturesDesign, train, and evaluate machine learning algorithms that underpin automated trading strategiesCreate a research and strategy development process to apply predictive modeling to trading decisionsLeverage NLP and deep learning to extract tradeable signals from market and alternative dataBook Description The explosive growth of digital data has boosted the demand for expertise in trading strategies that use machine learning (ML). This revised and expanded second edition enables you to build and evaluate sophisticated supervised, unsupervised, and reinforcement learning models. This book introduces end-to-end machine learning for the trading workflow, from the idea and feature engineering to model optimization, strategy design, and backtesting. It illustrates this by using examples ranging from linear models and tree-based ensembles to deep-learning techniques from cutting edge research. This edition shows how to work with market, fundamental, and alternative data, such as tick data, minute and daily bars, SEC filings, earnings call transcripts, financial news, or satellite images to generate tradeable signals. It illustrates how to engineer financial features or alpha factors that enable an ML model to predict returns from price data for US and international stocks and ETFs. It also shows how to assess the signal content of new features using Alphalens and SHAP values and includes a new appendix with over one hundred alpha factor examples. By the end, you will be proficient in translating ML model predictions into a trading strategy that operates at daily or intraday horizons, and in evaluating its performance. What you will learnLeverage market, fundamental, and alternative text and image dataResearch and evaluate alpha factors using statistics, Alphalens, and SHAP valuesImplement machine learning techniques to solve investment and trading problemsBacktest and evaluate trading strategies based on machine learning using Zipline and BacktraderOptimize portfolio risk and performance analysis using pandas, NumPy, and pyfolioCreate a pairs trading strategy based on cointegration for US equities and ETFsTrain a gradient boosting model to predict intraday returns using AlgoSeek's high-quality trades and quotes dataWho this book is for If you are a data analyst, data scientist, Python developer, investment analyst, or portfolio manager interested in getting hands-on machine learning knowledge for trading, this book is for you. This book is for you if you want to learn how to extract value from a diverse set of data sources using machine learning to design your own systematic trading strategies. Some understanding of Python and machine learning techniques is required.
Book Synopsis Hands-On Financial Trading with Python by : Jiri Pik
Download or read book Hands-On Financial Trading with Python written by Jiri Pik and published by Packt Publishing Ltd. This book was released on 2021-04-29 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build and backtest your algorithmic trading strategies to gain a true advantage in the market Key FeaturesGet quality insights from market data, stock analysis, and create your own data visualisationsLearn how to navigate the different features in Python's data analysis librariesStart systematically approaching quantitative research and strategy generation/backtesting in algorithmic tradingBook Description Creating an effective system to automate your trading can help you achieve two of every trader's key goals; saving time and making money. But to devise a system that will work for you, you need guidance to show you the ropes around building a system and monitoring its performance. This is where Hands-on Financial Trading with Python can give you the advantage. This practical Python book will introduce you to Python and tell you exactly why it's the best platform for developing trading strategies. You'll then cover quantitative analysis using Python, and learn how to build algorithmic trading strategies with Zipline using various market data sources. Using Zipline as the backtesting library allows access to complimentary US historical daily market data until 2018. As you advance, you will gain an in-depth understanding of Python libraries such as NumPy and pandas for analyzing financial datasets, and explore Matplotlib, statsmodels, and scikit-learn libraries for advanced analytics. As you progress, you'll pick up lots of skills like time series forecasting, covering pmdarima and Facebook Prophet. By the end of this trading book, you will be able to build predictive trading signals, adopt basic and advanced algorithmic trading strategies, and perform portfolio optimization to help you get —and stay—ahead of the markets. What you will learnDiscover how quantitative analysis works by covering financial statistics and ARIMAUse core Python libraries to perform quantitative research and strategy development using real datasetsUnderstand how to access financial and economic data in PythonImplement effective data visualization with MatplotlibApply scientific computing and data visualization with popular Python librariesBuild and deploy backtesting algorithmic trading strategiesWho this book is for If you're a financial trader or a data analyst who wants a hands-on introduction to designing algorithmic trading strategies, then this book is for you. You don't have to be a fully-fledged programmer to dive into this book, but knowing how to use Python's core libraries and a solid grasp on statistics will help you get the most out of this book.
Book Synopsis Python for Algorithmic Trading by : Yves Hilpisch
Download or read book Python for Algorithmic Trading written by Yves Hilpisch and published by O'Reilly Media. This book was released on 2020-11-12 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Book Synopsis Advances in Financial Machine Learning by : Marcos Lopez de Prado
Download or read book Advances in Financial Machine Learning written by Marcos Lopez de Prado and published by John Wiley & Sons. This book was released on 2018-01-23 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning (ML) is changing virtually every aspect of our lives. Today ML algorithms accomplish tasks that until recently only expert humans could perform. As it relates to finance, this is the most exciting time to adopt a disruptive technology that will transform how everyone invests for generations. Readers will learn how to structure Big data in a way that is amenable to ML algorithms; how to conduct research with ML algorithms on that data; how to use supercomputing methods; how to backtest your discoveries while avoiding false positives. The book addresses real-life problems faced by practitioners on a daily basis, and explains scientifically sound solutions using math, supported by code and examples. Readers become active users who can test the proposed solutions in their particular setting. Written by a recognized expert and portfolio manager, this book will equip investment professionals with the groundbreaking tools needed to succeed in modern finance.
Book Synopsis Building Predictive Models for Algorithmic Trading with Python by : Quinton Bruner
Download or read book Building Predictive Models for Algorithmic Trading with Python written by Quinton Bruner and published by Independently Published. This book was released on 2023-12 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unlock the secrets of algorithmic trading with this comprehensive guide on constructing powerful predictive models using Python. Delve into the world of financial markets and learn how to leverage cutting-edge techniques to enhance your trading strategies. In "Building Predictive Models for Algorithmic Trading with Python," we take you on a journey through the fundamentals of algorithmic trading and empower you to make data-driven decisions in the dynamic realm of finance. Whether you're a seasoned trader or a budding enthusiast, this book equips you with the knowledge and skills to develop robust predictive models that can analyze market trends, identify patterns, and make informed predictions. Key Features: Python Programming for Finance: Gain proficiency in using Python, one of the most popular programming languages, to analyze financial data and implement algorithmic trading strategies. Understanding Market Dynamics: Explore the intricacies of financial markets, including stock prices, volatility, and economic indicators. Learn how to extract meaningful insights from market data to inform your trading decisions. Data Preprocessing and Feature Engineering: Master the art of preparing and refining data for predictive modeling. Discover essential techniques for feature selection and engineering to enhance the performance of your algorithms. Machine Learning for Trading: Dive into machine learning algorithms such as regression, classification, and time-series forecasting to build predictive models tailored for algorithmic trading. Understand how to choose the right model for specific market conditions. Backtesting and Performance Evaluation: Validate the effectiveness of your models by implementing rigorous backtesting procedures. Learn how to assess and optimize the performance of your trading strategies to ensure robust and reliable results. Risk Management Strategies: Explore advanced risk management techniques to safeguard your investments. Understand how to implement stop-loss mechanisms, position sizing, and other risk mitigation strategies to enhance the resilience of your trading systems. Real-world Applications: Apply your newfound knowledge to real-world scenarios with practical examples and case studies. Gain insights into how successful traders and hedge funds leverage predictive modeling for profitable trading. Continuous Learning: Stay at the forefront of algorithmic trading by exploring emerging trends, tools, and technologies. The book provides a foundation for ongoing learning and adaptation in the ever-evolving landscape of financial markets. Whether you're a quantitative analyst, a finance professional, or a Python enthusiast looking to enter the world of algorithmic trading, "Building Predictive Models for Algorithmic Trading with Python" offers a comprehensive and hands-on approach to mastering the art and science of algorithmic trading. Elevate your trading strategies, minimize risks, and maximize returns with the practical insights and techniques shared in this invaluable resource.
Book Synopsis The Little Book of Fundamental Indicators: Hands-On Market Analysis with Python by : Lucas Amunategui
Download or read book The Little Book of Fundamental Indicators: Hands-On Market Analysis with Python written by Lucas Amunategui and published by . This book was released on 2019-05-02 with total page 96 pages. Available in PDF, EPUB and Kindle. Book excerpt: The goal of this little book is to help you find your way around the chaotic world of the financial markets. Stop trusting other people's opinions and make your own. Here are tools to explore the markets and find answers to your fundamental stock-market questions.We'll start with the S&P 500, my favorite index and the world's economic barometer. This powerful and telling index comprise some 80% of all equity market value in the US and 30% of its revenue comes from outside the United States. It is also the benchmark against which all other financial products are measured. Most chapters in this book will use this index in one form or another. We'll continue by exploring the VIX, the Yield Curve, the Case-Shiller Home Price Index, the Consumer Price Index and much more. This book assumes that you have some Python experience, a working interpreter on your computer and the basics of operating a Jupyter notebook. I will show you in simple terms where to find market data, how to prepare it and visualize it using Python and Jupyter notebooks. You will find a link at the beginning of each chapter to access the source code and a paragraph explaining where and how to download the required market data.You won't find trading setups or financial advice here. This is exactly what this book isn't about. Instead, you will acquire a simple set of scripts and data sources to explore, learn and build anything you want.
Book Synopsis Trade Like a Stock Market Wizard: How to Achieve Super Performance in Stocks in Any Market by : Mark Minervini
Download or read book Trade Like a Stock Market Wizard: How to Achieve Super Performance in Stocks in Any Market written by Mark Minervini and published by McGraw Hill Professional. This book was released on 2013-04-19 with total page 353 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Minervini has run circles around most PhDs trying to design systems to beat the market." -- JACK SCHWAGER, bestselling author of Stock Market Wizards "Mark's book has to be on every investor's bookshelf. It is about the most comprehensive work I have ever read on investing in growth stocks." -- DAVID RYAN, three-time U.S. Investing Champion "[Minervini is] one of the most highly respected independent traders of our generation. His experience and past history of savvy market calls is legendary." -- CHARLES KIRK, The Kirk Report "One of Wall Street's most remarkable success stories." -- BEN POWER, Your Trading Edge THE INVESTOR'S GUIDE TO SUPERPERFORMANCE! Dramatically increase your stock market returns with the legendary SEPA system! For the first time ever, U.S. Investing Champion Mark Minervini reveals the proven, time-tested trading system he used to achieve triple-digit returns for five consecutive years, averaging 220% per year for a 33,500% compounded total return. In Trade Like a Stock Market Wizard, Minervini unveils his trademarked stock market method SEPA, which provides outsized returns in virtually every market by combining careful risk management, self-analysis, and perseverance. He explains in detail how to select precise entry points and preserve capital—for consistent triple- digit returns. Whether you're just getting started in the stock market or you're a seasoned pro, Minervini will show how you how to achieve SUPERPERFORMANCE! You'll gain valuable knowledge as he shares lessons, trading truths, and specific tactics--all derived from his 30-year career as one of America's most successful stock traders. Trade Like a Stock Market Wizard teaches you: How to find the best stocks before they make big price gains How to avoid costly mistakes made by most investors How to manage losses and protect profits How to avoid high-risk situations Precisely when to buy and when to sell How to buy an IPO Why traditional valuation doesn't work for fast-growing Superperformers Examples of Minervini's personal trades with his comments With more than 160 chart examples and numerous case studies proving the remarkable effectiveness of Minervini's methodology, Trade Like a Stock Market Wizard puts in your hands one of the most effective and--until now--secretive stock investing systems in the world. MARK MINERVINI has a trademarked stock market method that produces outsized returns in virtually every market. It's called Specific Entry Point Analysis--SEPA--and it has been proven effective for selecting precise entry points, preserving capital and profi ts with even more precise exit points--and consistently producing triple-digit returns. Now, in Trade Like a Stock Market Wizard, Minervini shares--for the fi rst time ever--his coveted methodology with investors like you!
Book Synopsis Algorithmic Trading with Python by : Chris Conlan
Download or read book Algorithmic Trading with Python written by Chris Conlan and published by Independently Published. This book was released on 2020-04-09 with total page 126 pages. Available in PDF, EPUB and Kindle. Book excerpt: Algorithmic Trading with Python discusses modern quant trading methods in Python with a heavy focus on pandas, numpy, and scikit-learn. After establishing an understanding of technical indicators and performance metrics, readers will walk through the process of developing a trading simulator, strategy optimizer, and financial machine learning pipeline. This book maintains a high standard of reprocibility. All code and data is self-contained in a GitHub repo. The data includes hyper-realistic simulated price data and alternative data based on real securities. Algorithmic Trading with Python (2020) is the spiritual successor to Automated Trading with R (2016). This book covers more content in less time than its predecessor due to advances in open-source technologies for quantitative analysis.
Book Synopsis Forex Trading With Python Made Easy (The Python Forex Trader's Handbook) by : James Vega
Download or read book Forex Trading With Python Made Easy (The Python Forex Trader's Handbook) written by James Vega and published by Independently Published. This book was released on 2023-12-28 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Tired of staring at charts, chasing signals, and feeling lost in the volatile Forex market? Imagine... auto-pilot trading bots executing your precise strategies 24/7, lightning-fast analysis revealing hidden market patterns, and backtesting your ideas with pinpoint accuracy. Welcome to the world of algorithmic Forex trading with Python. This book is your Rosetta Stone, unlocking the Python code that can transform your trading journey. Forget manual analysis and emotional decisions; we'll equip you with the tools and knowledge to: Build your own automated trading bots: Craft Python scripts that execute your strategies with laser precision, freeing you from the shackles of manual trading. Master technical analysis with Python: Leverage powerful libraries like NumPy and pandas to perform complex analysis, identify profitable trends, and exploit hidden market inefficiencies. Backtest your strategies with confidence: Eliminate guesswork and optimize your approach with Python's robust backtesting capabilities. Test countless scenarios, refine your entries and exits, and build bulletproof trading systems. Gain an unfair advantage: Move beyond basic indicators and technical analysis. We'll delve into advanced techniques like machine learning and statistical arbitrage, giving you the edge over traditional traders. No prior coding experience? No problem. This book is your comprehensive guide, starting with the basics of Python and progressing to advanced algorithmic trading concepts. Learn at your own pace, with clear explanations, practical examples, and step-by-step instructions. More than just code, this book is your passport to trading freedom. Imagine the possibilities: Reclaim your time: Let your Python bots handle the heavy lifting, while you focus on what matters most. Trade with discipline: Eliminate emotional decision-making and stick to your proven strategies, consistently. Gain peace of mind: Know that your trades are executed flawlessly, even when you're asleep. Achieve financial freedom: Build a consistent income stream from the world's largest financial market. Ready to unlock the Python power within you and conquer the Forex market? Scroll up and grab your copy of Forex Trading With Python today!
Book Synopsis Teach Yourself Python Backtrader by :
Download or read book Teach Yourself Python Backtrader written by and published by Independently Published. This book was released on 2022-01-30 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: Have you ever thought of a machine that could earn for you while you relax. There is no such machine but steps can be taken to build such a machine. It all depends on your skills and a winning strategy that can do trading on your behalf. Backtrader is python module used for creating custom indicators, trade alerts, creating strategies and back-testing them on historical and real data. After, gaining skill from this book you will be able to make your scripts for custom indicators and backtest strategies on historical data and real market. This book has been written in simple language so that readers with no prior background of python or computer programming are able to learn and build upon the basics. This book will also introduce you to basics of python programming need by the traders for coding on backtrader. Act now to have a copy of this book to test your strategies and build your skills. Table of Content INTRODUCTION CHAPTER 01: TAKING THE FIRST STEP Installation of python/Pycharm Exploring Pycharm CHAPTER 02: THE FIRST STEP TOWARDS CODING First Program in Python functions Python Modules Code Commenting Escape Character CHAPTER 03: THE BACKTRADER Installing BackTrader BackTrader Structure Adding/Plotting Data CHAPTER 04: DATA TYPES Type of data Variables Typecasting Input from user CHAPTER 05: READING DATA FROM A GENERIC CSV FILE Format of Date and time Resampling and Compression of Data CHAPTER 06: OPERATORS IN PYTHON Assignment/Arithmetic/Comparision/Logical Operator Other operators CHAPTER 07: USING CEREBRO ENGINE Adding Strategy to BackTrader Built-in Indicators of BackTrader Implementing - two SMAs, ATR, Bollingerbands CHAPTER 08: LOOPS IN PYTHON: ITERATION Flow Chart Creating loop in Python For Loop While loop Step increment in For Loop Break and continue statements CHAPTER 09: BACKTRADER CHART CUSTOMIZATION System-wide customization Chart Customization CHAPTER 10: CONTROL FLOW STATEMENTS "if" and "if... else" statement "elif" statement CHAPTER 11: ADDING LOGIC TO BACKTRADER STRATEGY Defining Strategy Adding RSI Adding doji logic to chart Backtrader Order - buy() and sell() Backtrader Position Adding Short and Long Condition Adding initial capital, Order Size Setting Order Size from Strategy/Cerebro CHAPTER 12: EXPLORING STRING Slicing Negative index in slicing Skipping characters in slicing Reversing string Common methods for String F-string formatting CHAPTER 13: LIST IN PYTHON Slicing of List Mix datatypes in List Methods supported by List Additional methods - List Tuple CHAPTER 14: DICTIONARY IN PYTHON Dictionary Methods supported by dictionary items() keys() update() get() pop() CHAPTER 15: CUSTOM INDICATOR: MARKING DOJI Structure of Indicator Doji Indicator Logic Full code for marking Doji CHAPTER 16: PYTHON FUNCTIONS Need for functions Understanding function Defining Custom Functions Function with and without input/output Doc String (__doc__) Scope of Variables Global keyword The *args and **kwargs CHAPTER 17: CLASS AND OBJECTS The Class Instantiating Class Class and instance variable Class constructors - self & __init__() Instance method Class/Static method Class method as Constructor Single/Multiple Inheritance CHAPTER 18: BACKTRADER ANALYZER Parameters for Strategy Evaluation Common Mistakes in Evaluation Adding Analyser to Cerebro TradeAnalyzer DrawDown AnnualReturn Transactions Improve Analyzer Display CHAPTER 19: SIMPLE CROSS-OVER STRATEGY The Basic Structure of Strategy Improving Strategy - adding size, short - exit on loss CHAPTER 20: ORDER MANAGEMENT notify_order() Logging Order Details Order.Stop Implementation cancel(order)
