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.
Introduction:
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. It’s by no means an exhaustive book, either on Python, backtesting or trading. It won’t 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.
This is not a book full of super-secret trading strategies which will turn a thousand dollars into a million next week. While I like to think that there are some clever trading strategies in this book, it’s not meant to be cutting edge, revolutionary stuff. I would think that most readers will learn some interesting things about trading models, but that’s not the main point of this book.In order to teach you about using Python to test trading ideas, I need to show some trading ideas to test. I will show you a few models which I hope will be helpful. You will see complete trading models for ETFs, stocks and futures of varying degree of complexity. I will use these trading strategies as tools to explain what capabilities you will need and how to go about making these strategies real.
I often stress in my books that any trading strategy shown is a teaching tool and not meant for you to go out and trade. I will repeat this statement a few times throughout the book. I would strongly discourage anyone from copying anyone else’s trading strategies and blindly trading them. But this is after all where this book comes in. What I do recommend is that you read about other people’s trading strategies. Learn from them. Construct a suitable backtesting environment and model the strategies. Then figure out what you like and what you don’t like. Modify the parts you like, find ways to incorporate them into your own approach and come up with ways to improve the way you trade.You need to make the models your own to fully understand them, and you need to understand them to fully trust them. This book will give you the necessary tools and skillset to get this done.
Contents:
- SYSTEMATIC TRADING
- DEVELOPING TRADING MODELS
- FINANCIAL RISK
- INTRODUCTION TO PYTHON
- BRING OUT THE PANDAS
- BACKTESTING TRADING STRATEGIES
- ANALYZING BACKTEST RESULTS
- EXCHANGE TRADED FUNDS
- CONSTRUCTING ETF MODELS
- EQUITIES
- SYSTEMATIC MOMENTUM
- FUTURES MODELS
- FUTURES MODELING AND BACKTESTING
- FUTURES TREND FOLLOWING
- TIME RETURN TREND MODEL
- COUNTER TREND TRADING
- TRADING THE CURVE
- COMPARING AND COMBINING MODELS
- PERFORMANCE VISUALIZATION AND COMBINATIONS
- YOU CAN’T BEAT ALL OF THE MONKEYS ALL OF THE TIME
- GUEST CHAPTER: MEASURING RELATIVE PERFORMANCE
- IMPORTING YOUR DATA
- DATA AND DATABASES
Trading Evolved: Anyone can Build Killer Trading Strategies in Python By Andreas F. Clenow pdf