What is this book all about? You can think of the book as a small encyclopedia of well-sorted trading strategies and ideas that are not very well-known or addressed to the public. The strategies are presented in an easy and clear way so as to make the reader curious about testing them. More
Trading has never been easy, especially that markets are now becoming more and more efficient, and we know that financial data mostly follow a somewhat random pattern. We have used the “somewhat random” term because it is our job to filter out the noise (randomness) in order to understand the patterns that will in turn help us become profitable overtime by giving us more predictive abilities either subjectively or technologically. Active managers these years rarely beat the market which is the first red flag to all classical trading strategies that are based on the purpose of generating alpha, but does that mean that active trading is over? We do not think so, as many of these managers weren’t actually trying to beat the market, also, a lot of professional (and some retail) traders are profitable for the most part of their career which is an indication that profitability in this field is more than just luck. What is their secret? the number one reason is proper risk management and the number two reason is knowing when to exit their positions (which is also a discipline in the risk management field). Another reason we should undoubtedly mention is having a consistent and profitable strategy that changes by time to adapt to changing market regimes. After all, if you use risk management to preserve capital, you need a method to try to increase that capital, otherwise, you would not need to protect it and it will get eroded by inflation over time. In this book, we will explore and apply many technical strategies that go beyond the usual support and resistance trading for technicians, and we also present many other sentiment and machine learning strategies. Sentiment analysis is the fourth type of analysis (after fundamental, technical, and quantitative) that aims to forecast the markets based on what the big players intend to do, some also classify it as a mix between technical and fundamental analysis. So, in its simplest form, sentiment analysis is all about following the smart money. In the third part we will talk about some concepts and methods of machine learning and deal with known issues in this highly complex field. A lot of these strategies have been tested personally and are showing a lot of potential and it will be wise to use some together to complement each other.
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