Advanced Crypto strategies for Algorithmic trading 2022
Do you want to create quantitative CRYPTO strategies to earn up to 79%/YEAR ?You already have some trading knowledge and you want to learn about quantitative trading/finance?You are simply a curious person who wants to get into this subject to monetize and diversify your knowledge?If you answer at least one of these questions, I welcome you to this course. All the applications of the course will be done using Python. However, for beginners in Python, don’t panic! There is a FREE python crash course included to master Python. In this course, you will learn how to use technical analysis and machine learning to create robust crypto strategies. You will perform quantitative analysis to find patterns in the data. Once you will have many profitable strategies, we will learn how to perform vectorized backtesting. Then you will apply risk management techniques to control the volatility in your crypto investment plan. You will learn and understand crypto quantitative analysis used by portfolio managers and professional traders: Modeling: Technical analysis (Support & resistance, Ichimoku), Machine Learning (Random Forest Classifier). Backtesting: Do a backtest properly without error and minimize the computation time (Vectorized Backtesting). Risk management: Manage the drawdown(Drawdown break strategy), combine strategies properly (Crypto strategies portfolio). Why this course and not another?This is not a programming course nor a trading course or a machine learning course. It is a course in which statistics, financial theory, and machine learning are used for trading. This course is not created by a data scientist but by a degree in mathematics and economics specializing in mathematics applied to finance. You can ask questions or read our quantitative finance articles simply by registering on our free Discord forum. Without forgetting that the course is satisfied or refunded for 30 days. Don’t miss an opportunity to improve your knowledge of this fascinating subject.