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Author: Sofien Kaabar
Publisher: Independently Published
ISBN:
Category :
Languages : en
Pages : 218
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Book Description
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.
Author: Sofien Kaabar
Publisher: Independently Published
ISBN:
Category :
Languages : en
Pages : 218
Get Book
Book Description
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.
Author: Andreas F. Clenow
Publisher: John Wiley & Sons
ISBN: 1118410858
Category : Business & Economics
Languages : en
Pages : 309
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Book Description
During bull and bear markets, there is a group of hedge funds and professional traders which have been consistently outperforming traditional investment strategies for the past 30 odd years. They have shown remarkable uncorrelated performance and in the great bear market of 2008 they had record gains. These traders are highly secretive about their proprietary trading algorithms and often employ top PhDs in their research teams. Yet, it is possible to replicate their trading performance with relatively simplistic models. These traders are trend following cross asset futures managers, also known as CTAs. Many books are written about them but none explain their strategies in such detail as to enable the reader to emulate their success and create their own trend following trading business, until now. Following the Trend explains why most hopefuls fail by focusing on the wrong things, such as buy and sell rules, and teaches the truly important parts of trend following. Trading everything from the Nasdaq index and T-bills to currency crosses, platinum and live hogs, there are large gains to be made regardless of the state of the economy or stock markets. By analysing year by year trend following performance and attribution the reader will be able to build a deep understanding of what it is like to trade futures in large scale and where the real problems and opportunities lay. Written by experienced hedge fund manager Andreas Clenow, this book provides a comprehensive insight into the strategies behind the booming trend following futures industry from the perspective of a market participant. The strategies behind the success of this industry are explained in great detail, including complete trading rules and instructions for how to replicate the performance of successful hedge funds. You are in for a potentially highly profitable roller coaster ride with this hard and honest look at the positive as well as the negative sides of trend following.
Author: Nick Radge
Publisher: Radge Publishing
ISBN:
Category : Business & Economics
Languages : en
Pages :
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Book Description
The Weekend Trend Trader is a trading strategy designed for people who want a simple to follow trading plan that trades just once a week. An ideal investment strategy for people who work full time but are actively planning for their retirement. Weekend Trend Trader is designed for and tested on the US stock Market. The Weekend Trend Trader strategy is a turnkey strategy that uses no discretion. In other words the strategy has a set of rules and users should understand why they entered a trade and when and how they will exit. Because the rules are strictly and mathematically defined we are able to back test the strategy on historical data. This enables us to understand the strategy’s nuances and therefore better understand how the journey to success will be travelled. The strategy is a combination of several tools that: * ensures you will always be aligned with the trend of the broader market * enters positions at specific points and with reasonable confirmation * manages existing positions with a trailing stop loss * defends existing positions if the trend of the broader market reverses * outlines how much to invest in each position. We will fully step through each of these points in detail and slowly build the system from the ground up.
Author: Robert Carver
Publisher: Harriman House Limited
ISBN: 085719500X
Category : Business & Economics
Languages : en
Pages : 247
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Book Description
This is not just another book with yet another trading system. This is a complete guide to developing your own systems to help you make and execute trading and investing decisions. It is intended for everyone who wishes to systematise their financial decision making, either completely or to some degree. Author Robert Carver draws on financial theory, his experience managing systematic hedge fund strategies and his own in-depth research to explain why systematic trading makes sense and demonstrates how it can be done safely and profitably. Every aspect, from creating trading rules to position sizing, is thoroughly explained. The framework described here can be used with all assets, including equities, bonds, forex and commodities. There is no magic formula that will guarantee success, but cutting out simple mistakes will improve your performance. You'll learn how to avoid common pitfalls such as over-complicating your strategy, being too optimistic about likely returns, taking excessive risks and trading too frequently. Important features include: - The theory behind systematic trading: why and when it works, and when it doesn't. - Simple and effective ways to design effective strategies. - A complete position management framework which can be adapted for your needs. - How fully systematic traders can create or adapt trading rules to forecast prices. - Making discretionary trading decisions within a systematic framework for position management. - Why traditional long only investors should use systems to ensure proper diversification, and avoid costly and unnecessary portfolio churn. - Adapting strategies depending on the cost of trading and how much capital is being used. - Practical examples from UK, US and international markets showing how the framework can be used. Systematic Trading is detailed, comprehensive and full of practical advice. It provides a unique new approach to system development and a must for anyone considering using systems to make some, or all, of their investment decisions.
Author: Andreas F. Clenow
Publisher:
ISBN: 9781091983786
Category :
Languages : en
Pages : 442
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Book Description
Systematic trading allows you to test and evaluate your trading ideas before risking your money. By formulating trading ideas as concrete rules, you can evaluate past performance and draw conclusions about the viability of your trading plan. Following systematic rules provides a consistent approach where you will have some degree of predictability of returns, and perhaps more importantly, it takes emotions and second guessing out of the equation. From the onset, getting started with professional grade development and backtesting of systematic strategies can seem daunting. Many resort to simplified software which will limit your potential. Trading Evolved will guide you all the way, from getting started with the industry standard Python language, to setting up a professional backtesting environment of your own. The book will explain multiple trading strategies in detail, with full source code, to get you well on the path to becoming a professional systematic trader. This is a highly practical book, where every aspect is explained, all source code shown and no holds barred. Written by Andreas F. Clenow, author of the international best sellers Following the Trend and Stocks on the Move, Trading Evolved goes into greater depth and covers strategies for trading both futures and equities. "Trading Evolved is an incredible resource for aspiring quants. Clenow does an excellent job making complex subjects easy to access and understand. Bravo." -- Wes Gray, PhD, CEO Alpha Architect
Author: Sofien Kaabar
Publisher:
ISBN:
Category :
Languages : en
Pages : 330
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Book Description
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.
Author: Robert Carver
Publisher: Harriman House Limited
ISBN: 0857197223
Category : Business & Economics
Languages : en
Pages : 277
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Book Description
With the right broker, and just a few hundred dollars or pounds, anyone can become a leveraged trader. The products and tools needed are accessible to all: FX, a margin account, CFDs, spread-bets and futures. But this level playing field comes with great risks. Trading with leverage is inherently dangerous. With leverage, losses and costs – the two great killers for traders – are magnified. This does not mean leverage must be avoided altogether, but it does mean that it needs to be used safely. In Leveraged Trading, Robert Carver shows you how to do exactly that, by using a trading system. A trading system can be employed to tackle those twin dangers of serious losses and high costs. The trading systems introduced in this book are simple and carefully designed to use the correct amount of leverage and trade at a suitable frequency. Robert shows how to trade a simple Starter System on its own, on a single instrument and with a single rule for opening positions. He then moves on to show how the Starter System can be adapted, as you gain experience and confidence. The system can be diversified into multiple instruments and new trading rules can be added. For those who wish to go further still, advice on making more complex improvements is included: how to develop your own trading systems, and how to combine a system with your own human judgement, using an approach Robert calls Semi-Automatic Trading. For those trading with leverage, looking for a way to take a controlled approach and manage risk, a properly designed trading system is the answer. Pick up Leveraged Trading and learn how.
Author: Jiri Pik
Publisher: Packt Publishing Ltd
ISBN: 1838988807
Category : Computers
Languages : en
Pages : 360
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Book Description
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.
Author: Sourav Ghosh
Publisher:
ISBN: 9781789348347
Category : Computers
Languages : en
Pages : 394
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Book Description
Understand the fundamentals of algorithmic trading to apply algorithms to real market data and analyze the results of real-world trading strategies Key Features Understand the power of algorithmic trading in financial markets with real-world examples Get up and running with the algorithms used to carry out algorithmic trading Learn to build your own algorithmic trading robots which require no human intervention Book Description It's now harder than ever to get a significant edge over competitors in terms of speed and efficiency when it comes to algorithmic trading. Relying on sophisticated trading signals, predictive models and strategies can make all the difference. This book will guide you through these aspects, giving you insights into how modern electronic trading markets and participants operate. You'll start with an introduction to algorithmic trading, along with setting up the environment required to perform the tasks in the book. You'll explore the key components of an algorithmic trading business and aspects you'll need to take into account before starting an automated trading project. Next, you'll focus on designing, building and operating the components required for developing a practical and profitable algorithmic trading business. Later, you'll learn how quantitative trading signals and strategies are developed, and also implement and analyze sophisticated trading strategies such as volatility strategies, economic release strategies, and statistical arbitrage. Finally, you'll create a trading bot from scratch using the algorithms built in the previous sections. By the end of this book, you'll be well-versed with electronic trading markets and have learned to implement, evaluate and safely operate algorithmic trading strategies in live markets. What you will learn Understand the components of modern algorithmic trading systems and strategies Apply machine learning in algorithmic trading signals and strategies using Python Build, visualize and analyze trading strategies based on mean reversion, trend, economic releases and more Quantify and build a risk management system for Python trading strategies Build a backtester to run simulated trading strategies for improving the performance of your trading bot Deploy and incorporate trading strategies in the live market to maintain and improve profitability Who this book is for This book is for software engineers, financial traders, data analysts, and entrepreneurs. Anyone who wants to get started with algorithmic trading and understand how it works; and learn the components of a trading system, protocols and algorithms required for black box and gray box trading, and techniques for building a completely automated and profitable trading business will also find this book useful.
Author: Stefan Jansen
Publisher: Packt Publishing Ltd
ISBN: 1839216786
Category : Business & Economics
Languages : en
Pages : 822
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Book Description
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.
