Algorithmic trading using Price action strategies
- Description
- Curriculum
- FAQ
- Reviews
Do you want to create algorithmic trading strategies?
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 price action to create robust 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 portfolio techniques to reduce the drawdown and maximize your returns.
You will learn and understand quantitative analysis used by portfolio managers and professional traders:
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Modeling: price action (Support, resistance) patterns detection (trading figures detection)
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Backtesting: Make a backtest properly without error and minimize the computation time (Vectorized Backtesting).
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Portfolio management: Combine strategies properly (Strategies portfolio).
Why this course and not another?
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This is not a programming course nor a trading course or a machine learning course. It is a course in which statistics, programming and financial theory are used for trading.
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This course is not created by a data scientist but by a degree in mathematics and economics specializing in mathematics applied to finance.
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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.
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3IntroductionVideo lesson
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4Type of object: NumberVideo lesson
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5Type of object: StringVideo lesson
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6Type of object: Logical operation / BooleanVideo lesson
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7Type of object: Variable assignentVideo lesson
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8Type of object: Tuple and listVideo lesson
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9Type of object: DictionaryVideo lesson
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10Type of object: SetVideo lesson
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11Python structures: IF / ELIF/ ELSEVideo lesson
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12Python structures: FORVideo lesson
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13Python structures: WHILEVideo lesson
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14Functions: Basics of functionVideo lesson
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15Functions: Local variableVideo lesson
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16Functions: Global variableVideo lesson
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17Functions: Lambda functionVideo lesson
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18IntroductionVideo lesson
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19Numpy: ArrayVideo lesson
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20Numpy: RandomVideo lesson
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21Numpy: Indexing / Slicing / TransformationVideo lesson
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22Pandas: Serie and DataFrameVideo lesson
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23Pandas: Cleaning and transformationVideo lesson
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24Pandas: Conditional selectionVideo lesson
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25Matplotlib: GraphVideo lesson
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26Matplotlib: ScatterVideo lesson
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27Matplotlib: ToolsVideo lesson
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38IntroductionVideo lesson
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39Sortino ratio computationVideo lesson
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40Beta ratio computation (CAPM metric)Video lesson
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41Alpha ratio computation (CAPM metric)Video lesson
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42Drawdown function: creationVideo lesson
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43Drawdown function: applicationVideo lesson
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44Backtesting function (1)Video lesson
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45Backtesting function (2)Video lesson
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46Backtest your strategyVideo lesson
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47IntroductionVideo lesson
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48Import the dataVideo lesson
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49Support & resistanceVideo lesson
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50Support & resistance trading strategyVideo lesson
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51Support & resistance + SMA trading strategyVideo lesson
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52Support & resistance + SMA + RSI trading strategyVideo lesson
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53Automate the processVideo lesson
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54Scalping trading strategy + Portfolio managementVideo lesson

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