The Python for Traders Masterclass

[b]The Python for Traders Masterclass Original Price: $49 You Just Pay: $29.95 (One Time 90% OFF) Author: James [/b] Sale Page:_n/a Product Delivery : You will receive a receipt with download link through email. Contact me for the proof and payment detail: [b] [email protected] Or Skype_Macbus87 [/b] The Python for Traders Masterclass 8 Modules 4 Projects 105 Lessons 248 Code Examples 34 Hours of Content Module 1: Introduction 1.1. Welcome to the Python for Traders Masterclass(2:14)PREVIEW 1.2. Why learn to code as a trader?(7:15)PREVIEW 1.3. Why should traders learn Python?(4:23)PREVIEW 1.4. What will I gain from this course?PREVIEW 1.5. What topics will be covered?PREVIEW 1.6. Who is the intended audience for this course?PREVIEW 1.7. How much finance knowledge do I need?(1:40)PREVIEW 1.8. How much coding knowledge do I need?(1:37)PREVIEW 1.9. Placement Quiz: Am I a good fit for this course?PREVIEW 1.10. Module QuizSTART Module 2: Python Fundamentals for Finance 2.1. Python Installation and SetupSTART 2.2. Running Python CodeSTART 2.3. Basic Python(26:34)START 2.4. Intermediate Python(5:07)START 2.5. Advanced PythonSTART 2.6. Data Science in PythonSTART 2.7. Key library: PandasSTART 2.8. Key library: NumPySTART 2.9. Key library: MatplotlibSTART 2.10. Key library: StatsmodelsSTART 2.11. Key library: Scikit-learnSTART Module 3: Working with Financial Data 3.1. Introduction to Financial Data: Time Series and Cross-SectionsSTART 3.2. Data Acquisition and Cleaning(18:09)START 3.3. Time Series Analysis(13:38)START 3.4. Understanding Stationarity(11:55)START 3.5. Time Series ForecastingSTART 3.6. Exploratory Data AnalysisSTART 3.7. Section summarySTART Module 4: How to Code and Backtest a Trading Algorithm 4.1. So what is a trading algorithm?START 4.2. Algorithm Design PrinciplesSTART 4.3. Data Management Module(15:12)START 4.4. Signal Generation Module(15:12)START 4.5. Risk Management Module(10:58)START 4.6. Trade Execution Module(10:27)START 4.7. Portfolio Management Module(11:05)START 4.8. Backtesting BasicsSTART 4.9. Backtesting SoftwareSTART 4.10. Advanced Backtesting TechniquesSTART 4.11. Optimization and Parameter TuningSTART Project 1: Research & Backtest a Realistic Trading Algorithm Project Overview(6:57)START Step 1: Getting Started on QuantConnect(6:53)START Step 2: Formulate a StrategySTART Solution: Formulate a StrategySTART Step 3: Develop the AlgorithmSTART Solution: Develop the AlgorithmSTART Step 4: Run a Backtesting AnalysisSTART Solution 4: Run a Backtesting AnalysisSTART Project SummarySTART Module 5: Automated Data Collection, Cleaning, and Storage 5.1. Sourcing financial data(5:38)START 5.2. Working with CSVsSTART 5.3. Working with JSONSTART 5.4. Scraping data from APIs(51:35)START 5.5. Scraping data from websitesSTART 5.6. Persisting data: files and databasesSTART 5.7. Section summarySTART Module 6: Analyzing Fundamentals in Python 6.1. Structured vs. Unstructured DataSTART 6.2. Types of Fundamental DataSTART 6.3. Gathering & Cleaning Fundamental DataSTART 6.4. Automated Screening & FilteringSTART 6.5. Statistical Analysis of Fundamental DataSTART 6.6. Natural Language Processing on News ArticlesSTART 6.7. Natural Language Processing on Annual ReportsSTART 6.8. Using LLMs for Natural Language ProcessingSTART Module 7: Options & Derivatives Pricing Models 7.1. Introduction to Options & DerivativesSTART 7.2. Basics of Option PricingSTART 7.3. The Binomial Options Pricing ModelSTART 7.4. The Black-Scholes-Merton ModelSTART 7.5. Monte Carlo Simulation for Option PricingSTART 7.6. Introduction to Exotic OptionsSTART 7.7. Interest Rate Derivatives and Term StructureSTART 7.8. Implementing Finite Difference Methods for Option PricingSTART 7.9. Volatility and Implied VolatilitySTART 7.10. Advanced Topics and Modern Developments (Optional)START Project 2: Volatility Surface Analysis Tool Project OverviewSTART Step 1: Fetching Options DataSTART Solution: Fetching Options DataSTART Step 2: Calculating Implied VolatilitiesSTART Solution: Calculating Implied VolatilitiesSTART Step 3: Plot a 3D Volatility SurfaceSTART Solution: Plot a 3D Volatility SurfaceSTART Project SummarySTART Module 8: Introduction to High-Frequency Trading 8.1. What is High Frequency Trading (HFT)?START 8.2. Handling High-Frequency Tick DataSTART 8.3. Latency Measurement and SimulationSTART 8.4. Understanding the HFT Market Making StrategySTART 8.5. Understanding Statistical Arbitrage with High-Frequency DataSTART 8.6. Signal Processing for HFTSTART 8.7. Real-time News ProcessingSTART 8.8. Section summarySTART Project 3: Design & Build a Limit Order Book Project OverviewSTART Step 1: Design the Data StructureSTART Solution: Design the Data StructureSTART Step 2: Add FunctionalitySTART Solution: Add FunctionalitySTART Step 3: Simulate Live OrdersSTART Solution: Simulate Live OrdersSTART Project SummarySTART Capstone Project: Coding a Simple HFT Market Making Bot Project OverviewSTART Step 1: Define a System and Class ArchitectureSTART Solution: Define a System and Class ArchitectureSTART Step 2: Define the Event LoopSTART Solution: Define the Event LoopSTART Step 3: Implement the Data FeedsSTART Solution: Implement the Data FeedsSTART Step 4: Implement the Order ManagerSTART Solution: Implement the Order ManagerSTART Step 5: Add Alpha to the Pricing StrategySTART Solution: Add Alpha to the Pricing StrategySTART Project SummarySTART