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Chapter 1 : Introduction to Artificial Intelligence and Quantitative Trading 5
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DocumentLecture1.1
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Q&ALecture1.2
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Artificial Intelligence for Quantitative trading (ดูตัวอย่างฟรี)Lecture1.3
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Introduction to Quantitative trading (ดูตัวอย่างฟรี)Lecture1.4
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Introduction to Artificial Intelligence (ดูตัวอย่างฟรี)Lecture1.5
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Chapter 2 : Course Overview 2
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Trader WorkflowLecture2.1
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Trade Signal – Problem and SolutionLecture2.2
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Chapter 3 : Supervised Learning Workflow 1
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Supervised Learning WorkflowLecture3.1
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Chapter 4 : Data Preparation Workflow 1
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Data Preparation WorkflowLecture4.1
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Chapter 5 : Trade Signal as Trigger 3
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EMA Crossover as TriggerLecture5.1
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Bollinger Band Touching as TriggerLecture5.2
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Candlestick Patterns as TriggerLecture5.3
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Chapter 6 : Labelling Financial Data 2
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Labelling by Trade SignalLecture6.1
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Labelling by Triple Barrier MethodLecture6.2
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Chapter 7 : Feature Selection for Financial Data 2
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Feature Selection ConceptLecture7.1
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Hypothesis for Feature SelectionLecture7.2
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Chapter 8 : Decision Tree : Foundation, Mathematics and Modelling 5
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Introduction to Decision TreeLecture8.1
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State Data, Model and PredictionLecture8.2
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Decision Tree ModellingLecture8.3
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Gini Impurity and Information GainLecture8.4
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Decision Tree ExamplesLecture8.5
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Chapter 9 : Decision Tree : Coding and Implementation for False Signal Detection 3
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Coding for Data PreparationLecture9.1
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Coding for Model Creation and Model EvaluationLecture9.2
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Result AnalysisLecture9.3
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Chapter 10 : Performance Improvement 3
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Non-Stationary Market DistributionLecture10.1
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Advanced Feature ExtractionLecture10.2
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Advanced Model SelectionLecture10.3
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