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Clenow - Trading Evolved: Anyone can Build Killer Trading Strategies in Python

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Trading Evolved: Anyone can Build Killer Trading Strategies in Python: summary, description and annotation

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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

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Trading Evolved

Anyone can Build

Killer Trading Strategies

in Python

Book version 1.1


Copyright 2019 Andreas F. Clenow

Registered Office: Equilateral Capital Management GmbH, Lowenstrasse 1, 8001 Zurich, Switzerland

For details of editorial policies and information for how to apply for permission to reuse the copyright material in this book please see our website at www.FollowingTheTrend.com.

The right of the author to be identified as the author of this work has been asserted in accordance with the Copyright, Designs and Patents act 1998. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form by any means, electronic, mechanical, photocopying, teleportation, recording or otherwise except as permitted by the UK Copyright, Designs and Patents Act 1998 or other irrelevant but good sounding legal paragraphs, without the prior permission of the publisher. Doing so would make you a very naughty boy and you dont want that, do you.

Designations used by companies to distinguish their products are often claimed as trademarks. All brand names and product names used in this book are trade names, service marks, trademarks or registered trademarks of their respective owners. The publisher is not associated with any product or vendor mentioned in this book except if expressly stated.

Limit of Liability/Disclaimer of Warranty: While the publisher and the author have used their best efforts in preparing this book, they make no representations or warranties with the respect to the accuracy or completeness of the contents of this book and specifically disclaim any implied warranties of merchantability or fitness for a particular purpose. It is sold on the understanding that the publisher is not engaged in rendering professional services and neither the publisher nor the author shall be liable for damages arising herefrom. If professional advice or other expert assistance is required, the services of a competent professional should be sought.

ISBN: 9781091983786


To my wife Eng Cheng and my son Brandon, not only because of their love and support but also because they have been asking for months about whether they will get a dedication in this book.


About this Book

The Trading Strategies in this Book

How to Read this Book

How this book is written

How the code is written

Errata

Support

Systematic Trading

Trading Approach Validation

Scientific Approach

Consistent Methodology

Time Management

Developing Trading Models

Model Purpose

Rules and Variations

Handling Data

Asset Class

Investment Universe

Allocation and Risk Level

Entry and Exit Rules

Rebalancing

Financial Risk

Quantifying Risk

Mark to Market

Common Risk Fallacies

Risk as Currency to Buy Performance

Introduction to Python

Some Assembly Required

Python Emerges as the Logical Choice

Programming Teaching Approach

Installing Python on your Computer

Lets Run Some Code

Working with Jupyter Notebook

Dictionary Lookup

Conditional Logic

Common Mistakes

Installing Libraries

Bring out the Pandas

Documentation and Help

Simple Python Simulation

Making a Correlation Graph

Prettier Graphs

Backtesting Trading Strategies

Python Backtesting Engines

Zipline and Quantopian

Pros and Cons

Installing Zipline

Problems with Installing Zipline

Patching the Framework

Zipline and Data

Ingesting the Quandl Bundle

Installing Useful Libraries

Where to Write Backtest Algos

Your First Zipline Backtest

Portfolio Backtest

Data Used for this Book

Analyzing Backtest Results

Installing PyFolio

Portfolio Algorithm to Analyze

Analyzing Performance with PyFolio

Custom Analysis

Day Snapshot

Custom Time Series Analytics

Exchange Traded Funds

The Good

The Bad

The Worst

Shorting Exchange Traded Funds

Constructing ETF Models

Asset Allocation Model

Equities

The Most Difficult Asset Class

A word on Methodology

Equity Investment Universe

Dividends

Systematic Momentum

Replicating this Model

Momentum Model Rules Summary

Investment Universe

Momentum Ranking

Position Allocation

Momentum Model Logic

Downside Protection

Momentum Model Source Code

Performance

Equity Momentum Model Results

Futures Models

Futures Basics

Futures Mechanics and Terminology

Futures and Currency Exposure

Futures and Leverage

Futures Modeling and Backtesting

Continuations

Zipline Continuation Behavior

Contracts, Continuations and Rolling

Futures Trend Following

Principles of Trend Following

Revisiting the Core Trend Model

Model Purpose

Investment Universe

Trading Frequency

Position Allocation

Entry Rules

Exit Rules

Costs and Slippage

Interest on Liquidity

Trend Model Source Code

Core Trend Model Results

Time Return Trend Model

Investment Universe

Trading Frequency

Position Allocation

Trading Rules

Dynamic Performance Chart

Time Return Source Code

Time Return Model Performance

Rebalancing

Counter Trend Trading

Counter Model Logic

Quantifying Pullbacks

Rules Summary

Counter Trend Source Code

Counter Trend Results

Trading the Curve

Term Structure Basics

Quantifying Term Structure Effect

Curve Model Logic

Curve Trading Source Code

Curve Trading Results

Model Considerations

Comparing and Combining Models

Combining the Models

Implementing a Portfolio of Models

Performance Visualization and Combinations

Storing Model Results

How the Model Performance Analysis was done

How the Combined Portfolio Analysis was done

You cant beat all of the Monkeys all of the Time

Mr. Bubbles goes to Wall Street

The Problem is with the Index

Finding Mr. Bubbles

Guest Chapter: Measuring Relative Performance

Importing your Data

Making a Bundle

Zipline and Futures Data

Futures Data Bundle

Patching the Framework

Data and Databases

Your Very Own Securities Database

Installing MySQL Server

Making an Equities Time-Series Table

Populating the Database

Querying the Database

Making a Database Bundle

Final Words Path Forward

Build Your Own Models

Other Backtesting Engines

How to Make Money in the Markets

References

Index


While I would like to claim that I managed to write this book with absolutely no help from anyone, nothing could be farther from the truth. The help that Ive received along the way has been invaluable, and I couldnt have completed this book without it. Without these people, this book would either never have gotten off the ground or it would have ended up a total disaster. In no particular order, Id like to express my gratitude towards these people.

John Grover, Matthew Martelli, Robert Carver, Riccardo Ronco, Thomas Starke, Tomasz Mierzejewski, Erk Subasi and Jonathan Larkin.


About this Book

This book will guide you step by step on how to get familiar with Python, how to set up a local quant modeling environment and how to construct and analyze trading strategies. Its by no means an exhaustive book, either on Python, backtesting or trading. It wont make you an expert in either topic, but will aim for giving you a solid foundation in all of them.

When approaching something as complex as backtesting trading strategies, every step on the way can be done in a multitude of ways. This book does not attempt to cover all the different ways that you could approach Python trading strategies. A book like that would require many times the text mass of this book. But more importantly, a book of that type would likely scare away the bulk of the people that I want to address.

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