[FreeCourseSite.com] Udemy - Algorithmic Trading A-Z with Python, Machine Learning & AWS

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[FreeCourseSite.com] Udemy - Algorithmic Trading A-Z with Python, Machine Learning & AWS

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收录时间：2023-12-19
最近下载：2025-09-24

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文件列表

  • 30 - A Machine Learning-powered Strategy A-Z (DNN)/013 Implementation (Oanda & FXCM).mp4 104.0 MB
  • 32 - Adding Stop Loss and Take Profit to the Trading Bot/014 IBKR How to create Stop Loss and Take Profit Orders.mp4 94.1 MB
  • 08 - API Trading with Python and Online Brokers- an Introduction/019 IBKR Creating Orders (Stock Trading).mp4 90.8 MB
  • 23 - Implementation and Automation with OANDA (UPDATED!)/017 Trade Monitoring and Reporting.mp4 85.6 MB
  • 03 - Day Trading with OANDA A-Z a Deep Dive/001 OANDA at a first glance.mp4 85.5 MB
  • 12 - Financial Data Analysis with Python and Pandas - a (deep) Introduction/004 Initial Inspection and Visualization.mp4 82.3 MB
  • 14 - Object Oriented Programming (OOP) Creating a Financial Analysis Class/012 Inheritance.mp4 79.9 MB
  • 24 - Implementation and Automation with IBKR/010 Trade Monitoring and Reporting.mp4 79.6 MB
  • 12 - Financial Data Analysis with Python and Pandas - a (deep) Introduction/003 Loading Financial Data from the Web.mp4 78.0 MB
  • 06 - Installing Python and Jupyter Notebooks/003 How to open Jupyter Notebooks.mp4 77.2 MB
  • 32 - Adding Stop Loss and Take Profit to the Trading Bot/011 Oanda Adding Stop Loss & Take Profit.mp4 75.3 MB
  • 20 - Trading Strategies powered by Machine Learning - Classification/007 Generalization with OOP A Classification Backtesting Class in action.mp4 72.7 MB
  • 12 - Financial Data Analysis with Python and Pandas - a (deep) Introduction/021 (Non-) Normality of Financial Returns.mp4 72.5 MB
  • 07 - Excursus How to avoid and debug Coding Errors (don´t skip!)/011 How to traceback more complex Errors.mp4 71.5 MB
  • 04 - Stocks and FOREX Trading with Interactive Brokers (IBKR)/008 Trading Costs (Stocks) - Commissions.mp4 70.8 MB
  • 03 - Day Trading with OANDA A-Z a Deep Dive/008 Margin and Leverage.mp4 70.7 MB
  • 12 - Financial Data Analysis with Python and Pandas - a (deep) Introduction/020 Comparing the Performance of Financial Instruments.mp4 70.7 MB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/056 Customization of Plots.mp4 69.1 MB
  • 23 - Implementation and Automation with OANDA (UPDATED!)/004 Historical Data, real-time Data and Orders (Recap).mp4 66.5 MB
  • 08 - API Trading with Python and Online Brokers- an Introduction/017 IBKR Contracts (advanced).mp4 65.0 MB
  • 32 - Adding Stop Loss and Take Profit to the Trading Bot/016 IBKR Adding Stop Loss & Take Profit.mp4 64.5 MB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/030 Selecting Rows with iloc (position-based indexing).mp4 64.3 MB
  • 29 - Working with two or many Strategies (Combination)/008 Strategy Optimization.mp4 64.2 MB
  • 13 - Advanced Topics/001 Importing Financial Data from Excel.mp4 62.4 MB
  • 23 - Implementation and Automation with OANDA (UPDATED!)/022 Machine Learning Strategies (2) - Implementation.mp4 62.4 MB
  • 12 - Financial Data Analysis with Python and Pandas - a (deep) Introduction/014 Discrete Compounding.mp4 62.4 MB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/044 Changing Row Index with set_index() and reset_index().mp4 61.7 MB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/023 Create your very first Pandas DataFrame (from csv).mp4 61.6 MB
  • 05 - FOREX Day Trading with FXCM/002 FXCM at a first glance.mp4 60.9 MB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/039 Analyzing Numerical Series with unique(), nunique() and value_counts().mp4 60.4 MB
  • 08 - API Trading with Python and Online Brokers- an Introduction/006 OANDA How to load Historical Price Data (Part 1).mp4 60.1 MB
  • 21 - Advanced Backtesting Techniques/013 Adding the Iterative Backtest Child Class for SMA (Part 2).mp4 60.1 MB
  • 16 - Defining and Backtesting SMA Strategies/005 Generalization with OOP An SMA Backtesting Class in action.mp4 59.5 MB
  • 31 - Error Handling How to make your Trading Bot more stable and reliable/013 Oanda Error Handling (Part 2).mp4 59.4 MB
  • 32 - Adding Stop Loss and Take Profit to the Trading Bot/007 Oanda How to create Stop Loss and Take Profit Orders.mp4 59.0 MB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/034 Slicing Rows and Columns with loc (label-based indexing).mp4 58.7 MB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/061 Categorical Seaborn Plots.mp4 58.5 MB
  • 26 - Cloud Deployment (AWS) Scheduling Trading Sessions Full Automation/004 How to create an EC2 Instance.mp4 58.3 MB
  • 17 - Defining and Backtesting simple MomentumContrarian Strategies/007 Trades and Trading Costs (Part 1).mp4 58.1 MB
  • 11 - Introduction to Time Series Data in Pandas/004 Downsampling Time Series with resample().mp4 58.1 MB
  • 14 - Object Oriented Programming (OOP) Creating a Financial Analysis Class/001 Introduction to OOP and examples for Classes.mp4 57.6 MB
  • 24 - Implementation and Automation with IBKR/004 Streaming Bar Data.mp4 56.8 MB
  • 25 - Implementation and Automation with FXCM/015 Trade Monitoring and Reporting.mp4 56.4 MB
  • 12 - Financial Data Analysis with Python and Pandas - a (deep) Introduction/033 Margin Trading and Levered Returns (Part 2).mp4 56.2 MB
  • 18 - Defining and Backtesting Mean-Reversion Strategies (Bollinger)/004 Defining a Bollinger Bands Mean-Reversion Strategy (Part 2).mp4 55.8 MB
  • 25 - Implementation and Automation with FXCM/002 Historical Data, real-time Data and Orders (Recap).mp4 54.8 MB
  • 02 - +++ PART 1 Day Trading, Online Brokers and APIs +++/003 Spot Trading vs. Derivatives Trading (Part 1).mp4 54.7 MB
  • 25 - Implementation and Automation with FXCM/019 Machine Learning Strategies (2) - Implementation.mp4 54.5 MB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/055 Visualization with Matplotlib (Intro).mp4 54.2 MB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/062 Seaborn Regression Plots.mp4 53.9 MB
  • 25 - Implementation and Automation with FXCM/008 Storing and resampling real-time tick data (Part 2).mp4 53.8 MB
  • 08 - API Trading with Python and Online Brokers- an Introduction/015 IBKR How to get Market Data.mp4 53.0 MB
  • 16 - Defining and Backtesting SMA Strategies/007 Creating the Class (Part 2).mp4 52.6 MB
  • 06 - Installing Python and Jupyter Notebooks/004 How to work with Jupyter Notebooks.mp4 52.5 MB
  • 02 - +++ PART 1 Day Trading, Online Brokers and APIs +++/004 Spot Trading vs. Derivatives Trading (Part 2).mp4 52.4 MB
  • 08 - API Trading with Python and Online Brokers- an Introduction/030 FXCM How to load Historical Price Data (Part 1).mp4 51.7 MB
  • 32 - Adding Stop Loss and Take Profit to the Trading Bot/008 Oanda Stop Loss and Take Profit Orders - Pitfalls.mp4 51.6 MB
  • 25 - Implementation and Automation with FXCM/006 Storing and resampling real-time tick data (Part 1).mp4 51.4 MB
  • 23 - Implementation and Automation with OANDA (UPDATED!)/010 Storing and resampling real-time tick data (Part 4).mp4 51.1 MB
  • 21 - Advanced Backtesting Techniques/010 Creating an Iterative Base Class (Part 7).mp4 49.8 MB
  • 21 - Advanced Backtesting Techniques/015 OOP Challenge Add Contrarian and Bollinger Strategies.mp4 49.8 MB
  • 12 - Financial Data Analysis with Python and Pandas - a (deep) Introduction/008 Price changes and Financial Returns.mp4 49.0 MB
  • 26 - Cloud Deployment (AWS) Scheduling Trading Sessions Full Automation/002 Demonstration AWS EC2 for Algorithmic Trading live in action.mp4 48.7 MB
  • 17 - Defining and Backtesting simple MomentumContrarian Strategies/009 Generalization with OOP A Contrarian Backtesting Class in action.mp4 47.8 MB
  • 16 - Defining and Backtesting SMA Strategies/003 Vectorized Strategy Backtesting.mp4 47.8 MB
  • 08 - API Trading with Python and Online Brokers- an Introduction/005 OANDA Connecting to the APIServer.mp4 47.5 MB
  • 16 - Defining and Backtesting SMA Strategies/004 Finding the optimal SMA Strategy.mp4 47.1 MB
  • 25 - Implementation and Automation with FXCM/014 Placing Orders and Executing Trades.mp4 47.0 MB
  • 08 - API Trading with Python and Online Brokers- an Introduction/021 IBKR CFD Trade Information.mp4 46.8 MB
  • 15 - +++ PART 3 Defining and Testing Trading Strategies +++/002 Trading Strategies - an Overview.mp4 46.4 MB
  • 25 - Implementation and Automation with FXCM/011 Working with historical data and real-time tick data (Part 2).mp4 46.3 MB
  • 23 - Implementation and Automation with OANDA (UPDATED!)/025 Running a Python Trader Script.mp4 46.1 MB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/025 First Data Inspection.mp4 45.7 MB
  • 34 - Appendix 1 Python (& Finance) Basics/041 Coding Exercise 3.mp4 45.2 MB
  • 04 - Stocks and FOREX Trading with Interactive Brokers (IBKR)/009 Trading Costs (Stocks) - other (hidden) Costs.mp4 45.1 MB
  • 03 - Day Trading with OANDA A-Z a Deep Dive/005 Our second Trade - EURUSD FOREX Trading.mp4 45.0 MB
  • 21 - Advanced Backtesting Techniques/011 Creating an Iterative Base Class (Part 8).mp4 45.0 MB
  • 32 - Adding Stop Loss and Take Profit to the Trading Bot/005 SL & TP - Use Cases and Conclusion.mp4 44.8 MB
  • 03 - Day Trading with OANDA A-Z a Deep Dive/007 Trading Costs and Performance Attribution.mp4 44.6 MB
  • 24 - Implementation and Automation with IBKR/009 Creating Orders and Executing Trades.mp4 44.2 MB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/050 Advanced Filtering with between(), isin() and ~.mp4 43.9 MB
  • 08 - API Trading with Python and Online Brokers- an Introduction/032 FXCM Streaming high-frequency real-time Data.mp4 43.8 MB
  • 08 - API Trading with Python and Online Brokers- an Introduction/023 IBKR Historical Bars.mp4 43.7 MB
  • 04 - Stocks and FOREX Trading with Interactive Brokers (IBKR)/001 IBKR at a first glance.mp4 43.4 MB
  • 02 - +++ PART 1 Day Trading, Online Brokers and APIs +++/005 Overview & the Brokers OANDA, IBKR and FXCM.mp4 43.2 MB
  • 14 - Object Oriented Programming (OOP) Creating a Financial Analysis Class/013 Inheritance and the super() Function.mp4 43.2 MB
  • 04 - Stocks and FOREX Trading with Interactive Brokers (IBKR)/010 FOREX Trading Cash vs. CFD.mp4 43.0 MB
  • 04 - Stocks and FOREX Trading with Interactive Brokers (IBKR)/005 The first Trade (buying Stocks).mp4 43.0 MB
  • 25 - Implementation and Automation with FXCM/005 Collecting and storing real-time tick data.mp4 42.9 MB
  • 12 - Financial Data Analysis with Python and Pandas - a (deep) Introduction/023 Resampling Smoothing of Financial Data.mp4 42.4 MB
  • 08 - API Trading with Python and Online Brokers- an Introduction/033 FXCM How to place Orders and execute Trades.mp4 42.3 MB
  • 12 - Financial Data Analysis with Python and Pandas - a (deep) Introduction/030 Covariance and Correlation.mp4 42.1 MB
  • 12 - Financial Data Analysis with Python and Pandas - a (deep) Introduction/007 Coding Challenge #1.mp4 41.6 MB
  • 30 - A Machine Learning-powered Strategy A-Z (DNN)/010 Prediction & Out-Sample Forward Testing.mp4 41.2 MB
  • 24 - Implementation and Automation with IBKR/013 Running a Python Trader Script.mp4 41.2 MB
  • 01 - Getting Started/003 Did you know... (what Data can tell us about Day Trading).mp4 41.1 MB
  • 14 - Object Oriented Programming (OOP) Creating a Financial Analysis Class/014 Adding meaningful Docstrings.mp4 41.1 MB
  • 21 - Advanced Backtesting Techniques/012 Adding the Iterative Backtest Child Class for SMA (Part 1).mp4 41.1 MB
  • 18 - Defining and Backtesting Mean-Reversion Strategies (Bollinger)/006 Generalization with OOP A Bollinger Bands Backtesting Class in action.mp4 40.9 MB
  • 30 - A Machine Learning-powered Strategy A-Z (DNN)/009 Creating and Fitting the DNN Model.mp4 40.8 MB
  • 18 - Defining and Backtesting Mean-Reversion Strategies (Bollinger)/001 Mean-Reversion Strategies - Overview.mp4 40.7 MB
  • 19 - Trading Strategies powered by Machine Learning - Regression/002 Linear Regression with scikit-learn - a simple Introduction.mp4 40.6 MB
  • 16 - Defining and Backtesting SMA Strategies/001 SMA Crossover Strategies - Overview.mp4 40.6 MB
  • 26 - Cloud Deployment (AWS) Scheduling Trading Sessions Full Automation/011 How to stop Trading Sessions (OANDA).mp4 40.3 MB
  • 01 - Getting Started/001 What is Algorithmic Trading Course Overview.mp4 40.1 MB
  • 25 - Implementation and Automation with FXCM/004 Preview A Trader Class live in action.mp4 40.1 MB
  • 23 - Implementation and Automation with OANDA (UPDATED!)/015 Defining a simple Contrarian Strategy.mp4 39.9 MB
  • 11 - Introduction to Time Series Data in Pandas/002 Converting strings to datetime objects with pd.to_datetime().mp4 39.8 MB
  • 19 - Trading Strategies powered by Machine Learning - Regression/008 A simple Linear Model to predict Financial Returns (Part 2).mp4 39.7 MB
  • 07 - Excursus How to avoid and debug Coding Errors (don´t skip!)/005 Omitting cells, changing the sequence and more.mp4 39.4 MB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/054 Summary Statistics and Accumulations.mp4 39.3 MB
  • 08 - API Trading with Python and Online Brokers- an Introduction/022 IBKR Positions and Account Values.mp4 39.3 MB
  • 11 - Introduction to Time Series Data in Pandas/003 Indexing and Slicing Time Series.mp4 39.3 MB
  • 34 - Appendix 1 Python (& Finance) Basics/014 Coding Exercise 1.mp4 39.2 MB
  • 25 - Implementation and Automation with FXCM/021 Running a Python Script.mp4 38.9 MB
  • 21 - Advanced Backtesting Techniques/014 Using Modules and adding Docstrings.mp4 38.8 MB
  • 34 - Appendix 1 Python (& Finance) Basics/049 Coding Exercise 4.mp4 38.5 MB
  • 12 - Financial Data Analysis with Python and Pandas - a (deep) Introduction/011 Investment Multiple and CAGR.mp4 38.4 MB
  • 12 - Financial Data Analysis with Python and Pandas - a (deep) Introduction/006 Normalizing Time Series to a Base Value (100).mp4 38.4 MB
  • 13 - Advanced Topics/004 Filling NA Values with bfill, ffill and interpolation.mp4 37.9 MB
  • 01 - Getting Started/002 How to get the best out of this course.mp4 37.6 MB
  • 08 - API Trading with Python and Online Brokers- an Introduction/009 OANDA How to place Orders and execute Trades.mp4 37.4 MB
  • 12 - Financial Data Analysis with Python and Pandas - a (deep) Introduction/024 Rolling Statistics.mp4 37.2 MB
  • 31 - Error Handling How to make your Trading Bot more stable and reliable/015 Implementation with IBKR Errors and Connectivity Issues.mp4 37.1 MB
  • 26 - Cloud Deployment (AWS) Scheduling Trading Sessions Full Automation/006 Getting the Instance Ready for Algorithmic Trading.mp4 37.1 MB
  • 04 - Stocks and FOREX Trading with Interactive Brokers (IBKR)/004 TWS - First Steps.mp4 36.8 MB
  • 16 - Defining and Backtesting SMA Strategies/009 Creating the Class (Part 4).mp4 36.6 MB
  • 19 - Trading Strategies powered by Machine Learning - Regression/001 Machine Learning - an Overview.mp4 36.3 MB
  • 08 - API Trading with Python and Online Brokers- an Introduction/028 FXCM Connecting to the APIServer.mp4 36.0 MB
  • 26 - Cloud Deployment (AWS) Scheduling Trading Sessions Full Automation/012 How to stop Trading Sessions (FXCM).mp4 35.9 MB
  • 31 - Error Handling How to make your Trading Bot more stable and reliable/012 Oanda Error Handling (Part 1).mp4 35.9 MB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/052 Handling NA Values missing Values.mp4 35.8 MB
  • 23 - Implementation and Automation with OANDA (UPDATED!)/007 Storing and resampling real-time tick data (Part 1).mp4 35.6 MB
  • 03 - Day Trading with OANDA A-Z a Deep Dive/009 Margin Closeout and more.mp4 35.5 MB
  • 23 - Implementation and Automation with OANDA (UPDATED!)/005 Preview A Trader Class live in action.mp4 35.3 MB
  • 07 - Excursus How to avoid and debug Coding Errors (don´t skip!)/010 Getting help on StackOverflow.com.mp4 34.5 MB
  • 03 - Day Trading with OANDA A-Z a Deep Dive/012 Netting vs. Hedging.mp4 34.5 MB
  • 34 - Appendix 1 Python (& Finance) Basics/044 Intro to Strings.mp4 34.3 MB
  • 12 - Financial Data Analysis with Python and Pandas - a (deep) Introduction/015 Continuous Compounding.mp4 34.3 MB
  • 03 - Day Trading with OANDA A-Z a Deep Dive/011 Our third Trade A-Z - Going Short EURUSD.mp4 33.9 MB
  • 07 - Excursus How to avoid and debug Coding Errors (don´t skip!)/002 Test your debugging skills!.mp4 33.9 MB
  • 23 - Implementation and Automation with OANDA (UPDATED!)/006 How to collect and store real-time tick data.mp4 33.5 MB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/067 Splitting with many Keys.mp4 33.5 MB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/068 split-apply-combine.mp4 33.5 MB
  • 17 - Defining and Backtesting simple MomentumContrarian Strategies/006 Changing the Window Parameter.mp4 33.4 MB
  • 32 - Adding Stop Loss and Take Profit to the Trading Bot/009 Oanda Setting SL Distances and TP Prices in real-time.mp4 33.3 MB
  • 31 - Error Handling How to make your Trading Bot more stable and reliable/016 IBKR Error Handling.mp4 33.3 MB
  • 15 - +++ PART 3 Defining and Testing Trading Strategies +++/001 Introduction to Part 3.mp4 33.3 MB
  • 19 - Trading Strategies powered by Machine Learning - Regression/004 Overfitting.mp4 33.0 MB
  • 21 - Advanced Backtesting Techniques/008 Creating an Iterative Base Class (Part 5).mp4 32.8 MB
  • 07 - Excursus How to avoid and debug Coding Errors (don´t skip!)/004 The most commonly made Errors at a glance.mp4 32.7 MB
  • 31 - Error Handling How to make your Trading Bot more stable and reliable/011 Implementation with Oanda V20 Connection Issues.mp4 32.7 MB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/036 Summary, Best Practices and Outlook.mp4 32.5 MB
  • 02 - +++ PART 1 Day Trading, Online Brokers and APIs +++/002 Long Term Investing vs. (Algorithmic) Day Trading.mp4 32.4 MB
  • 31 - Error Handling How to make your Trading Bot more stable and reliable/018 FXCM Error Handling (Part 1).mp4 32.3 MB
  • 34 - Appendix 1 Python (& Finance) Basics/024 Coding Exercise 2.mp4 31.8 MB
  • 03 - Day Trading with OANDA A-Z a Deep Dive/006 How to calculate Profit & Loss of a Trade.mp4 31.6 MB
  • 15 - +++ PART 3 Defining and Testing Trading Strategies +++/006 Performance Metrics.mp4 31.5 MB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/024 Pandas Display Options and the methods head() & tail().mp4 31.4 MB
  • 24 - Implementation and Automation with IBKR/006 Preparing the Data for Day Trading.mp4 31.2 MB
  • 03 - Day Trading with OANDA A-Z a Deep Dive/004 FOREX Currency Exchange Rates explained.mp4 31.2 MB
  • 25 - Implementation and Automation with FXCM/017 SMA Crossover and Bollinger Bands (Solution).mp4 31.1 MB
  • 23 - Implementation and Automation with OANDA (UPDATED!)/021 Machine Learning Strategies (1) - Model Fitting.mp4 31.1 MB
  • 32 - Adding Stop Loss and Take Profit to the Trading Bot/015 IBKR Stop Loss and Take Profit Orders - Pitfalls.mp4 31.1 MB
  • 12 - Financial Data Analysis with Python and Pandas - a (deep) Introduction/017 Simple Returns vs Log Returns ( Part 1).mp4 30.9 MB
  • 24 - Implementation and Automation with IBKR/011 How to Stop a Trading Session.mp4 30.9 MB
  • 21 - Advanced Backtesting Techniques/007 Creating an Iterative Base Class (Part 4).mp4 30.8 MB
  • 35 - Appendix 2 User-defined Functions (required for OOP)/003 What´s the difference between Positional Arguments vs. Keyword Arguments.mp4 30.7 MB
  • 31 - Error Handling How to make your Trading Bot more stable and reliable/019 FXCM Error Handling (Part 2).mp4 30.7 MB
  • 08 - API Trading with Python and Online Brokers- an Introduction/014 IBKR Contracts.mp4 30.6 MB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/003 Numpy Arrays.mp4 30.6 MB
  • 23 - Implementation and Automation with OANDA (UPDATED!)/016 Placing Orders and Executing Trades.mp4 30.4 MB
  • 24 - Implementation and Automation with IBKR/002 Streaming Tick Data.mp4 30.2 MB
  • 19 - Trading Strategies powered by Machine Learning - Regression/011 Out-Sample Forward Testing.mp4 30.2 MB
  • 08 - API Trading with Python and Online Brokers- an Introduction/026 FXCM How to install the FXCM API Wrapper.mp4 30.1 MB
  • 29 - Working with two or many Strategies (Combination)/004 Combining both Strategies - Alternative 1.mp4 30.1 MB
  • 03 - Day Trading with OANDA A-Z a Deep Dive/010 Introduction to Charting.mp4 29.9 MB
  • 16 - Defining and Backtesting SMA Strategies/011 Creating the Class (Part 6).mp4 29.6 MB
  • 06 - Installing Python and Jupyter Notebooks/002 Download and Install Anaconda.mp4 29.5 MB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/013 Creating Numpy Arrays from Scratch.mp4 29.5 MB
  • 32 - Adding Stop Loss and Take Profit to the Trading Bot/002 Stop Loss Orders - Theory.mp4 28.9 MB
  • 11 - Introduction to Time Series Data in Pandas/005 Coding Exercise 1.mp4 28.6 MB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/043 First Steps with Pandas Index Objects.mp4 28.5 MB
  • 03 - Day Trading with OANDA A-Z a Deep Dive/003 How to create an Account Update May 2023.mp4 27.9 MB
  • 26 - Cloud Deployment (AWS) Scheduling Trading Sessions Full Automation/005 How to connect to your EC2 Instance.mp4 27.8 MB
  • 13 - Advanced Topics/006 Timezones and Converting (Part 2).mp4 27.8 MB
  • 14 - Object Oriented Programming (OOP) Creating a Financial Analysis Class/008 The methods plot_prices() and plot_returns().mp4 27.7 MB
  • 23 - Implementation and Automation with OANDA (UPDATED!)/013 Working with historical data and real-time tick data (Part 2).mp4 27.6 MB
  • 24 - Implementation and Automation with IBKR/003 Streaming Tick Data for multiple Symbols.mp4 27.3 MB
  • 21 - Advanced Backtesting Techniques/009 Creating an Iterative Base Class (Part 6).mp4 27.2 MB
  • 23 - Implementation and Automation with OANDA (UPDATED!)/012 Working with historical data and real-time tick data (Part 1).mp4 26.8 MB
  • 24 - Implementation and Automation with IBKR/008 Define an SMA Day Trading Strategy.mp4 26.6 MB
  • 20 - Trading Strategies powered by Machine Learning - Classification/008 The Classification Backtesting Class explained (Part 1).mp4 26.5 MB
  • 05 - FOREX Day Trading with FXCM/003 How to create an Account.mp4 26.5 MB
  • 16 - Defining and Backtesting SMA Strategies/002 Defining an SMA Crossover Strategy.mp4 26.4 MB
  • 30 - A Machine Learning-powered Strategy A-Z (DNN)/003 Installation of Tensorflow & Keras (Part 2).mp4 26.3 MB
  • 16 - Defining and Backtesting SMA Strategies/013 Creating the Class (Part 8).mp4 26.3 MB
  • 32 - Adding Stop Loss and Take Profit to the Trading Bot/010 Oanda Check for SLTP Events.mp4 26.2 MB
  • 12 - Financial Data Analysis with Python and Pandas - a (deep) Introduction/001 Introduction and Overview.mp4 26.0 MB
  • 14 - Object Oriented Programming (OOP) Creating a Financial Analysis Class/004 The special method __init__().mp4 25.8 MB
  • 14 - Object Oriented Programming (OOP) Creating a Financial Analysis Class/011 Adding more methods and performance metrics.mp4 25.8 MB
  • 14 - Object Oriented Programming (OOP) Creating a Financial Analysis Class/005 The method get_data().mp4 25.7 MB
  • 23 - Implementation and Automation with OANDA (UPDATED!)/008 Storing and resampling real-time tick data (Part 2).mp4 25.6 MB
  • 12 - Financial Data Analysis with Python and Pandas - a (deep) Introduction/012 Compound Returns & Geometric Mean Return.mp4 25.4 MB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/051 Intro to NA Values missing Values.mp4 25.2 MB
  • 23 - Implementation and Automation with OANDA (UPDATED!)/011 Storing and resampling real-time tick data (Part 5).mp4 25.0 MB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/047 Filtering DataFrames (one Condition).mp4 25.0 MB
  • 31 - Error Handling How to make your Trading Bot more stable and reliable/014 Oanda Error Handling (Part 3).mp4 24.8 MB
  • 34 - Appendix 1 Python (& Finance) Basics/038 Adding and removing Elements fromto Lists.mp4 24.8 MB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/064 Removing Columns.mp4 24.7 MB
  • 12 - Financial Data Analysis with Python and Pandas - a (deep) Introduction/018 Simple Returns vs Log Returns ( Part 2).mp4 24.6 MB
  • 12 - Financial Data Analysis with Python and Pandas - a (deep) Introduction/027 Short Selling and Short Position Returns (Part 2).mp4 24.5 MB
  • 17 - Defining and Backtesting simple MomentumContrarian Strategies/005 Vectorized Strategy Backtesting.mp4 24.5 MB
  • 24 - Implementation and Automation with IBKR/007 Improving Code Efficiency.mp4 24.5 MB
  • 21 - Advanced Backtesting Techniques/001 Introduction to Iterative Backtesting (event-driven).mp4 24.4 MB
  • 12 - Financial Data Analysis with Python and Pandas - a (deep) Introduction/028 Short Selling and Short Position Returns (Part 3).mp4 24.3 MB
  • 08 - API Trading with Python and Online Brokers- an Introduction/031 FXCM How to load Historical Price Data (Part 2).mp4 24.2 MB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/011 Advanced Filtering & Bitwise Operators.mp4 24.1 MB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/017 How to slice 2-dim Numpy Arrays (Part 1).mp4 24.0 MB
  • 18 - Defining and Backtesting Mean-Reversion Strategies (Bollinger)/005 Vectorized Strategy Backtesting.mp4 23.7 MB
  • 25 - Implementation and Automation with FXCM/012 Working with historical data and real-time tick data (Part 3).mp4 23.7 MB
  • 25 - Implementation and Automation with FXCM/009 Storing and resampling real-time tick data (Part 3).mp4 23.7 MB
  • 35 - Appendix 2 User-defined Functions (required for OOP)/009 Scope - easily explained.mp4 23.6 MB
  • 25 - Implementation and Automation with FXCM/007 A Trader Class.mp4 23.5 MB
  • 23 - Implementation and Automation with OANDA (UPDATED!)/014 Working with historical data and real-time tick data (Part 3).mp4 23.5 MB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/066 Understanding the GroupBy Object.mp4 23.5 MB
  • 35 - Appendix 2 User-defined Functions (required for OOP)/002 Defining your first user-defined Function.mp4 23.3 MB
  • 30 - A Machine Learning-powered Strategy A-Z (DNN)/005 Adding LabelsFeatures.mp4 23.3 MB
  • 34 - Appendix 1 Python (& Finance) Basics/050 Conditional Statements.mp4 23.3 MB
  • 20 - Trading Strategies powered by Machine Learning - Classification/002 Logistic Regression with scikit-learn - a simple Introduction (Part 2).mp4 22.6 MB
  • 19 - Trading Strategies powered by Machine Learning - Regression/009 A Multiple Regression Model to predict Financial Returns.mp4 22.6 MB
  • 23 - Implementation and Automation with OANDA (UPDATED!)/020 Implementing a Bollinger Bands Strategy (Solution).mp4 22.6 MB
  • 35 - Appendix 2 User-defined Functions (required for OOP)/007 Sequences as arguments and args.mp4 22.3 MB
  • 13 - Advanced Topics/003 Helpful DatetimeIndex Attributes and Methods.mp4 22.3 MB
  • 20 - Trading Strategies powered by Machine Learning - Classification/004 Predicting Market Direction with Logistic Regression.mp4 22.2 MB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/046 Renaming Index & Column Labels with rename().mp4 22.1 MB
  • 25 - Implementation and Automation with FXCM/013 Defining a Simple Contrarian Trading Strategy.mp4 22.0 MB
  • 34 - Appendix 1 Python (& Finance) Basics/048 Comparison, Logical and Membership Operators in Action.mp4 22.0 MB
  • 15 - +++ PART 3 Defining and Testing Trading Strategies +++/005 A simple Buy and Hold Strategy.mp4 22.0 MB
  • 28 - Trading Hours, Spreads and Granularity - control and limit Trading Costs!/005 The Impact of Granularity.mp4 21.9 MB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/027 Selecting Columns.mp4 21.8 MB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/002 Modules, Packages and Libraries - No need to reinvent the Wheel.mp4 21.8 MB
  • 08 - API Trading with Python and Online Brokers- an Introduction/013 IBKR Connecting to the API.mp4 21.7 MB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/033 Selecting Rows with loc (label-based indexing).mp4 21.2 MB
  • 03 - Day Trading with OANDA A-Z a Deep Dive/013 Market, Limit and Stop Orders.mp4 21.2 MB
  • 14 - Object Oriented Programming (OOP) Creating a Financial Analysis Class/016 Coding Exercise 3 Create your own Class.mp4 21.1 MB
  • 28 - Trading Hours, Spreads and Granularity - control and limit Trading Costs!/001 Introduction and Preparing the Data.mp4 21.1 MB
  • 11 - Introduction to Time Series Data in Pandas/001 Importing Time Series Data from csv-files.mp4 21.1 MB
  • 34 - Appendix 1 Python (& Finance) Basics/053 Introduction to while loops.mp4 21.0 MB
  • 34 - Appendix 1 Python (& Finance) Basics/051 Keywords pass, continue and break.mp4 20.9 MB
  • 25 - Implementation and Automation with FXCM/018 Machine Learning Strategies (1) - Model Fitting.mp4 20.9 MB
  • 31 - Error Handling How to make your Trading Bot more stable and reliable/017 Implementation with FXCM APIServer Issues.mp4 20.9 MB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/063 Seaborn Heatmaps.mp4 20.8 MB
  • 16 - Defining and Backtesting SMA Strategies/008 Creating the Class (Part 3).mp4 20.8 MB
  • 12 - Financial Data Analysis with Python and Pandas - a (deep) Introduction/009 Reward and Risk of Financial Instruments.mp4 20.8 MB
  • 04 - Stocks and FOREX Trading with Interactive Brokers (IBKR)/006 Trading Hours.mp4 20.6 MB
  • 34 - Appendix 1 Python (& Finance) Basics/032 More on Lists.mp4 20.3 MB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/006 Changing Elements in Numpy Arrays & Mutability.mp4 20.3 MB
  • 14 - Object Oriented Programming (OOP) Creating a Financial Analysis Class/010 The method set_ticker().mp4 20.3 MB
  • 34 - Appendix 1 Python (& Finance) Basics/039 Mutable vs. immutable Objects (Part 1).mp4 20.2 MB
  • 14 - Object Oriented Programming (OOP) Creating a Financial Analysis Class/009 Encapsulation and protected Attributes.mp4 20.2 MB
  • 24 - Implementation and Automation with IBKR/001 IBKR API - Recap.mp4 20.2 MB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/040 Analyzing non-numerical Series with unique(), nunique(), value_counts().mp4 20.0 MB
  • 30 - A Machine Learning-powered Strategy A-Z (DNN)/001 Project Overview.mp4 19.7 MB
  • 23 - Implementation and Automation with OANDA (UPDATED!)/009 Storing and resampling real-time tick data (Part 3).mp4 19.5 MB
  • 32 - Adding Stop Loss and Take Profit to the Trading Bot/004 Take Profit Orders - Theory.mp4 19.5 MB
  • 35 - Appendix 2 User-defined Functions (required for OOP)/004 How to work with Default Arguments.mp4 19.3 MB
  • 21 - Advanced Backtesting Techniques/002 A first Intuition on Iterative Backtesting (Part 1).mp4 19.2 MB
  • 23 - Implementation and Automation with OANDA (UPDATED!)/019 Implementing an SMA Crossover Strategy (Solution).mp4 19.2 MB
  • 25 - Implementation and Automation with FXCM/010 Working with historical data and real-time tick data (Part 1).mp4 19.2 MB
  • 03 - Day Trading with OANDA A-Z a Deep Dive/015 A more general Example.mp4 19.1 MB
  • 35 - Appendix 2 User-defined Functions (required for OOP)/005 The Default Argument None.mp4 19.1 MB
  • 04 - Stocks and FOREX Trading with Interactive Brokers (IBKR)/003 How to Install the IB Trader Workstation (TWS).mp4 19.0 MB
  • 07 - Excursus How to avoid and debug Coding Errors (don´t skip!)/012 Problems with the Python Installation.mp4 19.0 MB
  • 34 - Appendix 1 Python (& Finance) Basics/008 Introduction to Variables.mp4 19.0 MB
  • 07 - Excursus How to avoid and debug Coding Errors (don´t skip!)/006 IndexErrors.mp4 18.9 MB
  • 26 - Cloud Deployment (AWS) Scheduling Trading Sessions Full Automation/001 Introduction and Motivation.mp4 18.8 MB
  • 21 - Advanced Backtesting Techniques/003 A first Intuition on Iterative Backtesting (Part 2).mp4 18.8 MB
  • 16 - Defining and Backtesting SMA Strategies/012 Creating the Class (Part 7).mp4 18.8 MB
  • 31 - Error Handling How to make your Trading Bot more stable and reliable/008 Try again (...until it works).mp4 18.8 MB
  • 34 - Appendix 1 Python (& Finance) Basics/043 Dictionaries.mp4 18.7 MB
  • 34 - Appendix 1 Python (& Finance) Basics/021 Calculate FV and PV for many Cashflows.mp4 18.7 MB
  • 18 - Defining and Backtesting Mean-Reversion Strategies (Bollinger)/007 OOP Challenge Create the Bollinger Bands Backtesting Class (incl. Solution).mp4 18.6 MB
  • 08 - API Trading with Python and Online Brokers- an Introduction/007 OANDA How to load Historical Price Data (Part 2).mp4 18.5 MB
  • 08 - API Trading with Python and Online Brokers- an Introduction/004 OANDA Getting the API Key & other Preparations.mp4 18.3 MB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/059 Scatterplots.mp4 18.3 MB
  • 18 - Defining and Backtesting Mean-Reversion Strategies (Bollinger)/003 Defining a Bollinger Bands Mean-Reversion Strategy (Part 1).mp4 18.2 MB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/042 Sorting of Series and Introduction to the inplace - parameter.mp4 18.1 MB
  • 34 - Appendix 1 Python (& Finance) Basics/019 For Loops - Iterating over Lists.mp4 18.0 MB
  • 17 - Defining and Backtesting simple MomentumContrarian Strategies/010 OOP Challenge Create the Contrarian Backtesting Class (incl. Solution).mp4 17.9 MB
  • 20 - Trading Strategies powered by Machine Learning - Classification/003 Getting and Preparing the Data.mp4 17.8 MB
  • 34 - Appendix 1 Python (& Finance) Basics/042 Tuples.mp4 17.8 MB
  • 04 - Stocks and FOREX Trading with Interactive Brokers (IBKR)/011 A complete CFD FOREX Trade.mp4 17.5 MB
  • 24 - Implementation and Automation with IBKR/012 Trading other Strategies - Coding Challenge.mp4 17.3 MB
  • 12 - Financial Data Analysis with Python and Pandas - a (deep) Introduction/032 Margin Trading and Levered Returns (Part 1).mp4 17.1 MB
  • 29 - Working with two or many Strategies (Combination)/007 Combining both Strategies - Alternative 2.mp4 17.1 MB
  • 16 - Defining and Backtesting SMA Strategies/006 Creating the Class (Part 1).mp4 17.0 MB
  • 19 - Trading Strategies powered by Machine Learning - Regression/010 In-Sample Backtesting and the Look-ahead-bias.mp4 16.8 MB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/041 The copy() method.mp4 16.7 MB
  • 12 - Financial Data Analysis with Python and Pandas - a (deep) Introduction/022 Annualizing Return and Risk.mp4 16.7 MB
  • 16 - Defining and Backtesting SMA Strategies/010 Creating the Class (Part 5).mp4 16.6 MB
  • 20 - Trading Strategies powered by Machine Learning - Classification/009 The Classification Backtesting Class explained (Part 2).mp4 16.5 MB
  • 05 - FOREX Day Trading with FXCM/008 Order Types at a glance.mp4 16.2 MB
  • 34 - Appendix 1 Python (& Finance) Basics/022 The Net Present Value - NPV (Theory).mp4 16.1 MB
  • 28 - Trading Hours, Spreads and Granularity - control and limit Trading Costs!/003 The best time to trade (Part 2).mp4 16.1 MB
  • 17 - Defining and Backtesting simple MomentumContrarian Strategies/003 Excursus Your FAQs answered.mp4 16.1 MB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/058 Histogramms (Part 2).mp4 16.1 MB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/020 How to perform row-wise and column-wise Operations.mp4 15.8 MB
  • 26 - Cloud Deployment (AWS) Scheduling Trading Sessions Full Automation/010 How to schedule Trading sessions with the Task Scheduler.mp4 15.7 MB
  • 23 - Implementation and Automation with OANDA (UPDATED!)/023 Importing a Trader Module Class.mp4 15.7 MB
  • 34 - Appendix 1 Python (& Finance) Basics/030 Floats.mp4 15.6 MB
  • 34 - Appendix 1 Python (& Finance) Basics/028 Build-in Functions.mp4 15.3 MB
  • 13 - Advanced Topics/005 Timezones and Converting (Part 1).mp4 15.3 MB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/038 First Steps with Pandas Series.mp4 15.2 MB
  • 08 - API Trading with Python and Online Brokers- an Introduction/003 OANDA How to install the OANDA API Wrapper.mp4 14.9 MB
  • 14 - Object Oriented Programming (OOP) Creating a Financial Analysis Class/002 The Financial Analysis Class live in action (Part 1).mp4 14.9 MB
  • 30 - A Machine Learning-powered Strategy A-Z (DNN)/006 Adding lags.mp4 14.7 MB
  • 04 - Stocks and FOREX Trading with Interactive Brokers (IBKR)/007 Cash Account vs. Margin Account.mp4 14.6 MB
  • 07 - Excursus How to avoid and debug Coding Errors (don´t skip!)/009 TypeErrors and ValueErrors.mp4 14.6 MB
  • 30 - A Machine Learning-powered Strategy A-Z (DNN)/011 Saving Model and Parameters.mp4 14.6 MB
  • 31 - Error Handling How to make your Trading Bot more stable and reliable/006 try, except, else.mp4 14.3 MB
  • 08 - API Trading with Python and Online Brokers- an Introduction/020 IBKR Creating Orders (CFD Trading).mp4 14.1 MB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/012 Determining a Project´s Payback Period with np.where().mp4 14.1 MB
  • 14 - Object Oriented Programming (OOP) Creating a Financial Analysis Class/007 String representation and the special method __repr__().mp4 14.1 MB
  • 19 - Trading Strategies powered by Machine Learning - Regression/003 Making Predictions with Linear Regression.mp4 14.0 MB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/031 Slicing Rows and Columns with iloc (position-based indexing).mp4 13.9 MB
  • 05 - FOREX Day Trading with FXCM/004 Example Trade Buying EURUSD.mp4 13.8 MB
  • 13 - Advanced Topics/002 Merging Aligning Financial Time Series (hands-on).mp4 13.7 MB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/049 Filtering DataFrames by many Conditions (OR).mp4 13.7 MB
  • 12 - Financial Data Analysis with Python and Pandas - a (deep) Introduction/031 Portfolios and Portfolio Returns.mp4 13.7 MB
  • 28 - Trading Hours, Spreads and Granularity - control and limit Trading Costs!/006 Conclusions.mp4 13.7 MB
  • 04 - Stocks and FOREX Trading with Interactive Brokers (IBKR)/002 How to create a (Paper Trading) Account.mp4 13.7 MB
  • 19 - Trading Strategies powered by Machine Learning - Regression/005 Underfitting.mp4 13.7 MB
  • 30 - A Machine Learning-powered Strategy A-Z (DNN)/008 Feature ScalingEngineering.mp4 13.7 MB
  • 08 - API Trading with Python and Online Brokers- an Introduction/027 FXCM Getting the Access Token & other Preparations.mp4 13.5 MB
  • 20 - Trading Strategies powered by Machine Learning - Classification/001 Logistic Regression with scikit-learn - a simple Introduction (Part 1).mp4 13.4 MB
  • 34 - Appendix 1 Python (& Finance) Basics/011 More on Variables and Memory.mp4 13.4 MB
  • 17 - Defining and Backtesting simple MomentumContrarian Strategies/008 Trades and Trading Costs (Part 2).mp4 13.2 MB
  • 35 - Appendix 2 User-defined Functions (required for OOP)/006 How to unpack Iterables.mp4 13.1 MB
  • 34 - Appendix 1 Python (& Finance) Basics/052 Calculate a Project´s Payback Period.mp4 13.0 MB
  • 34 - Appendix 1 Python (& Finance) Basics/025 Data Types in Action.mp4 13.0 MB
  • 08 - API Trading with Python and Online Brokers- an Introduction/008 OANDA Streaming high-frequency real-time Data.mp4 12.9 MB
  • 29 - Working with two or many Strategies (Combination)/002 Strategy 1 SMA.mp4 12.9 MB
  • 14 - Object Oriented Programming (OOP) Creating a Financial Analysis Class/003 The Financial Analysis Class live in action (Part 2).mp4 12.9 MB
  • 08 - API Trading with Python and Online Brokers- an Introduction/012 IBKR How to download and install the API Wrapper & other Preparations.mp4 12.8 MB
  • 03 - Day Trading with OANDA A-Z a Deep Dive/014 Take-Profit and Stop-Loss Orders.mp4 12.8 MB
  • 07 - Excursus How to avoid and debug Coding Errors (don´t skip!)/015 Summary and Debugging Flow-Chart.mp4 12.8 MB
  • 26 - Cloud Deployment (AWS) Scheduling Trading Sessions Full Automation/009 How to start Trading sessions with Batch (.bat) Files.mp4 12.8 MB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/005 Vectorized Operations with Numpy Arrays.mp4 12.7 MB
  • 08 - API Trading with Python and Online Brokers- an Introduction/016 IBKR Data Streaming for Multiple Tickers.mp4 12.7 MB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/060 First Steps with Seaborn.mp4 12.7 MB
  • 26 - Cloud Deployment (AWS) Scheduling Trading Sessions Full Automation/008 How to run Python Scripts in a Windows Command Prompt.mp4 12.6 MB
  • 21 - Advanced Backtesting Techniques/004 Creating an Iterative Base Class (Part 1).mp4 12.3 MB
  • 23 - Implementation and Automation with OANDA (UPDATED!)/002 Updating the Wrapper Package (Part 2).mp4 12.2 MB
  • 34 - Appendix 1 Python (& Finance) Basics/040 Mutable vs. immutable Objects (Part 2).mp4 12.2 MB
  • 05 - FOREX Day Trading with FXCM/005 Trade Analysis.mp4 11.9 MB
  • 34 - Appendix 1 Python (& Finance) Basics/009 Excursus How to add inline comments.mp4 11.8 MB
  • 15 - +++ PART 3 Defining and Testing Trading Strategies +++/004 Getting the Data.mp4 11.7 MB
  • 20 - Trading Strategies powered by Machine Learning - Classification/005 In-Sample Backtesting and the Look-ahead-bias.mp4 11.7 MB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/057 Histogramms (Part 1).mp4 11.5 MB
  • 14 - Object Oriented Programming (OOP) Creating a Financial Analysis Class/015 Creating and Importing Python Modules (.py).mp4 11.5 MB
  • 22 - +++ PART 4 Real-time Implementation and Automation of Strategies +++/001 Introduction and Overview.mp4 11.5 MB
  • 17 - Defining and Backtesting simple MomentumContrarian Strategies/004 Defining a simple Contrarian Strategy.mp4 11.4 MB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/019 Recap Changing Elements in a Numpy Array slice.mp4 11.4 MB
  • 14 - Object Oriented Programming (OOP) Creating a Financial Analysis Class/006 The method log_returns().mp4 11.4 MB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/008 Numpy Array Methods and Attributes.mp4 11.4 MB
  • 31 - Error Handling How to make your Trading Bot more stable and reliable/010 Waiting periods between re-tries.mp4 11.3 MB
  • 34 - Appendix 1 Python (& Finance) Basics/031 How to round Floats (and Integers) with round().mp4 11.3 MB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/007 View vs. copy - potential Pitfalls when slicing Numpy Arrays.mp4 11.3 MB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/016 2-dimensional Numpy Arrays.mp4 11.2 MB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/022 Intro to Tabular Data Pandas.mp4 11.1 MB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/045 Changing Column Labels.mp4 11.0 MB
  • 25 - Implementation and Automation with FXCM/016 Trading other Strategies - Coding Challenge.mp4 10.9 MB
  • 20 - Trading Strategies powered by Machine Learning - Classification/006 Out-Sample Forward Testing.mp4 10.8 MB
  • 34 - Appendix 1 Python (& Finance) Basics/033 Lists and Element-wise Operations.mp4 10.8 MB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/048 Filtering DataFrames by many Conditions (AND).mp4 10.6 MB
  • 08 - API Trading with Python and Online Brokers- an Introduction/018 IBKR FOREX and CFD Contracts.mp4 10.4 MB
  • 17 - Defining and Backtesting simple MomentumContrarian Strategies/001 Simple ContrarianMomentum Strategies - Overview.mp4 10.3 MB
  • 34 - Appendix 1 Python (& Finance) Basics/012 Variables - Dos, Don´ts and Conventions.mp4 10.2 MB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/010 Boolean Arrays and Conditional Filtering.mp4 10.1 MB
  • 17 - Defining and Backtesting simple MomentumContrarian Strategies/002 Getting the Data.mp4 10.1 MB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/015 How to work with nested Lists.mp4 10.0 MB
  • 34 - Appendix 1 Python (& Finance) Basics/020 The range Object - another Iterable.mp4 9.9 MB
  • 19 - Trading Strategies powered by Machine Learning - Regression/007 A simple Linear Model to predict Financial Returns (Part 1).mp4 9.8 MB
  • 34 - Appendix 1 Python (& Finance) Basics/045 String Replacement.mp4 9.7 MB
  • 05 - FOREX Day Trading with FXCM/007 Closing Positions vs. Hedging Positions.mp4 9.7 MB
  • 34 - Appendix 1 Python (& Finance) Basics/034 Slicing Lists.mp4 9.7 MB
  • 23 - Implementation and Automation with OANDA (UPDATED!)/018 Trading other Strategies - Coding Challenge.mp4 9.6 MB
  • 31 - Error Handling How to make your Trading Bot more stable and reliable/007 finally.mp4 9.6 MB
  • 34 - Appendix 1 Python (& Finance) Basics/013 The print() Function.mp4 9.5 MB
  • 34 - Appendix 1 Python (& Finance) Basics/007 Calculate Interest Rates and Returns with Python.mp4 9.4 MB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/009 Numpy Universal Functions.mp4 9.4 MB
  • 31 - Error Handling How to make your Trading Bot more stable and reliable/001 Introduction.mp4 9.4 MB
  • 34 - Appendix 1 Python (& Finance) Basics/004 NEW Udemy Online Coding Exercises - Intro.mp4 9.3 MB
  • 12 - Financial Data Analysis with Python and Pandas - a (deep) Introduction/016 Log Returns.mp4 9.3 MB
  • 27 - +++ PART 5 Expert Tips & Tricks, Case Studies and more +++/001 Overview.mp4 9.2 MB
  • 21 - Advanced Backtesting Techniques/006 Creating an Iterative Base Class (Part 3).mp4 9.2 MB
  • 32 - Adding Stop Loss and Take Profit to the Trading Bot/006 Oanda Contrader Class without Take Profit & Stop Loss (Recap).mp4 9.2 MB
  • 29 - Working with two or many Strategies (Combination)/005 Taking into account busy Trading Hours.mp4 9.1 MB
  • 29 - Working with two or many Strategies (Combination)/003 Strategy 2 Mean Reversion.mp4 9.1 MB
  • 26 - Cloud Deployment (AWS) Scheduling Trading Sessions Full Automation/003 Amazon Web Services (AWS) - Overview and how to create a Free Trial Account.mp4 9.0 MB
  • 12 - Financial Data Analysis with Python and Pandas - a (deep) Introduction/026 Short Selling and Short Position Returns (Part 1).mp4 8.9 MB
  • 34 - Appendix 1 Python (& Finance) Basics/002 Intro to the Time Value of Money (TVM) Concept (Theory).mp4 8.9 MB
  • 34 - Appendix 1 Python (& Finance) Basics/003 Calculate Future Values (FV) with Python Compounding.mp4 8.6 MB
  • 28 - Trading Hours, Spreads and Granularity - control and limit Trading Costs!/002 The best time to trade (Part 1).mp4 8.5 MB
  • 07 - Excursus How to avoid and debug Coding Errors (don´t skip!)/013 External Factors and Issues.mp4 8.4 MB
  • 04 - Stocks and FOREX Trading with Interactive Brokers (IBKR)/012 CFD Trade Analysis.mp4 8.4 MB
  • 34 - Appendix 1 Python (& Finance) Basics/023 Calculate an Investment Project´s NPV.mp4 8.4 MB
  • 34 - Appendix 1 Python (& Finance) Basics/018 Indexing Lists.mp4 8.4 MB
  • 32 - Adding Stop Loss and Take Profit to the Trading Bot/013 IBKR Contrader Class without Take Profit & Stop Loss (Recap).mp4 8.3 MB
  • 28 - Trading Hours, Spreads and Granularity - control and limit Trading Costs!/004 Spreads during the busy hours.mp4 8.2 MB
  • 02 - +++ PART 1 Day Trading, Online Brokers and APIs +++/001 Our very first Trade.mp4 8.0 MB
  • 07 - Excursus How to avoid and debug Coding Errors (don´t skip!)/008 Misuse of function names and keywords.mp4 7.9 MB
  • 30 - A Machine Learning-powered Strategy A-Z (DNN)/007 Splitting into Train and Test Set.mp4 7.8 MB
  • 34 - Appendix 1 Python (& Finance) Basics/037 Sorting and Reversing Lists.mp4 7.6 MB
  • 07 - Excursus How to avoid and debug Coding Errors (don´t skip!)/014 Errors related to the course content (Transcription Errors).mp4 7.6 MB
  • 35 - Appendix 2 User-defined Functions (required for OOP)/008 How to return many results.mp4 7.4 MB
  • 07 - Excursus How to avoid and debug Coding Errors (don´t skip!)/001 Introduction.mp4 7.4 MB
  • 34 - Appendix 1 Python (& Finance) Basics/006 Interest Rates and Returns (Theory).mp4 7.4 MB
  • 34 - Appendix 1 Python (& Finance) Basics/036 Changing Elements in Lists.mp4 7.3 MB
  • 21 - Advanced Backtesting Techniques/005 Creating an Iterative Base Class (Part 2).mp4 7.2 MB
  • 10 - +++ PART 2 Pandas for Financial Data Analysis and Introduction to OOP +++/001 Introduction and Downloads Part 2 Updated March 2023.mp4 7.2 MB
  • 18 - Defining and Backtesting Mean-Reversion Strategies (Bollinger)/002 Getting the Data.mp4 7.2 MB
  • 07 - Excursus How to avoid and debug Coding Errors (don´t skip!)/007 Indentation Errors.mp4 7.1 MB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/004 Indexing and Slicing Numpy Arrays.mp4 6.9 MB
  • 30 - A Machine Learning-powered Strategy A-Z (DNN)/004 Getting and Preparing the Data.mp4 6.7 MB
  • 31 - Error Handling How to make your Trading Bot more stable and reliable/009 How to limit the number of retries.mp4 6.7 MB
  • 34 - Appendix 1 Python (& Finance) Basics/047 Operators (Theory).mp4 6.5 MB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/029 Zero-based Indexing and Negative Indexing.mp4 6.4 MB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/053 Exporting DataFrames to csv.mp4 6.4 MB
  • 34 - Appendix 1 Python (& Finance) Basics/029 Integers.mp4 6.3 MB
  • 34 - Appendix 1 Python (& Finance) Basics/015 TVM Problems with many Cashflows.mp4 6.2 MB
  • 05 - FOREX Day Trading with FXCM/006 Charting.mp4 6.1 MB
  • 12 - Financial Data Analysis with Python and Pandas - a (deep) Introduction/002 Installing and importing required LibrariesPackages.mp4 6.1 MB
  • 24 - Implementation and Automation with IBKR/005 How to create a live Candle Stick Chart.mp4 6.1 MB
  • 19 - Trading Strategies powered by Machine Learning - Regression/006 Getting the Data.mp4 6.0 MB
  • 32 - Adding Stop Loss and Take Profit to the Trading Bot/001 Introduction.mp4 5.9 MB
  • 34 - Appendix 1 Python (& Finance) Basics/005 Calculate Present Values (PV) with Python Discounting.mp4 5.7 MB
  • 34 - Appendix 1 Python (& Finance) Basics/026 The Data Type Hierarchy (Theory).mp4 5.5 MB
  • 34 - Appendix 1 Python (& Finance) Basics/046 Booleans.mp4 5.4 MB
  • 29 - Working with two or many Strategies (Combination)/001 Introduction.mp4 5.3 MB
  • 31 - Error Handling How to make your Trading Bot more stable and reliable/003 try and except.mp4 5.3 MB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/018 How to slice 2-dim Numpy Arrays (Part 2).mp4 4.8 MB
  • 29 - Working with two or many Strategies (Combination)/006 Strategy Backtesting.mp4 4.6 MB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/028 Selecting one Column with the dot notation.mp4 4.6 MB
  • 06 - Installing Python and Jupyter Notebooks/001 Introduction.mp4 4.4 MB
  • 34 - Appendix 1 Python (& Finance) Basics/016 Intro to Python Lists.mp4 4.4 MB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/065 Introduction to GroupBy Operations.mp4 4.2 MB
  • 34 - Appendix 1 Python (& Finance) Basics/017 Zero-based Indexing and negative Indexing in Python (Theory).mp4 4.0 MB
  • 31 - Error Handling How to make your Trading Bot more stable and reliable/004 Catching specific Errors.mp4 3.7 MB
  • 31 - Error Handling How to make your Trading Bot more stable and reliable/002 Python Errors (Exceptions).mp4 3.6 MB
  • 33 - +++ APPENDIX Python Crash Course +++/001 Overview.mp4 3.2 MB
  • 34 - Appendix 1 Python (& Finance) Basics/027 Excursus Dynamic Typing in Python.mp4 3.1 MB
  • 31 - Error Handling How to make your Trading Bot more stable and reliable/005 The Exception class.mp4 2.9 MB
  • 34 - Appendix 1 Python (& Finance) Basics/010 Variables and Memory (Theory).mp4 2.9 MB
  • 06 - Installing Python and Jupyter Notebooks/005 Tips for Python Beginners.mp4 2.6 MB
  • 07 - Excursus How to avoid and debug Coding Errors (don´t skip!)/003 Major reasons for Coding Errors.mp4 2.5 MB
  • 15 - +++ PART 3 Defining and Testing Trading Strategies +++/003 Part3-Materials.zip 2.3 MB
  • 08 - API Trading with Python and Online Brokers- an Introduction/001 Overview.mp4 2.2 MB
  • 27 - +++ PART 5 Expert Tips & Tricks, Case Studies and more +++/002 Part5-Materials.zip 1.9 MB
  • 09 - Conclusion and Outlook/001 Conclusion and Outlook.mp4 1.8 MB
  • 10 - +++ PART 2 Pandas for Financial Data Analysis and Introduction to OOP +++/001 Part2-Materials.zip 1.1 MB
  • 22 - +++ PART 4 Real-time Implementation and Automation of Strategies +++/002 Part4-Materials.zip 761.8 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/001 Appendix3-Materials.zip 671.1 kB
  • 02 - +++ PART 1 Day Trading, Online Brokers and APIs +++/002 Trading-vs-investing.pdf 542.5 kB
  • 19 - Trading Strategies powered by Machine Learning - Regression/001 ML.pdf 493.8 kB
  • 14 - Object Oriented Programming (OOP) Creating a Financial Analysis Class/001 OOP.pdf 491.0 kB
  • 01 - Getting Started/001 Overview.pdf 488.2 kB
  • 30 - A Machine Learning-powered Strategy A-Z (DNN)/001 DNN.pdf 441.4 kB
  • 01 - Getting Started/003 did-you-know.pdf 439.6 kB
  • 15 - +++ PART 3 Defining and Testing Trading Strategies +++/002 strategy-overview.pdf 410.7 kB
  • 21 - Advanced Backtesting Techniques/001 Event-Driven-BT.pdf 394.9 kB
  • 04 - Stocks and FOREX Trading with Interactive Brokers (IBKR)/008 IBKR-Stocks.xlsx 379.5 kB
  • 26 - Cloud Deployment (AWS) Scheduling Trading Sessions Full Automation/001 cloud.pdf 375.2 kB
  • 02 - +++ PART 1 Day Trading, Online Brokers and APIs +++/003 Spot-vs-Futures.pdf 259.8 kB
  • 34 - Appendix 1 Python (& Finance) Basics/022 NPV.pdf 251.6 kB
  • 34 - Appendix 1 Python (& Finance) Basics/002 TVM.pdf 200.5 kB
  • 34 - Appendix 1 Python (& Finance) Basics/021 PV-FV-many.pdf 199.2 kB
  • 34 - Appendix 1 Python (& Finance) Basics/006 Interest-Rates.pdf 192.3 kB
  • 08 - API Trading with Python and Online Brokers- an Introduction/011 Interactive-Brokers-firststeps.zip 184.5 kB
  • 34 - Appendix 1 Python (& Finance) Basics/015 FV-many.pdf 180.2 kB
  • 34 - Appendix 1 Python (& Finance) Basics/040 Python-for-Finance-Mutability.pdf 170.7 kB
  • 34 - Appendix 1 Python (& Finance) Basics/026 Type-Hierarchy.pdf 166.3 kB
  • 34 - Appendix 1 Python (& Finance) Basics/047 Operators.pdf 149.1 kB
  • 34 - Appendix 1 Python (& Finance) Basics/010 Variables.pdf 146.4 kB
  • 34 - Appendix 1 Python (& Finance) Basics/017 Indexing.pdf 125.8 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/007 Slicing-arrays.pdf 125.5 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/006 Mutability-arrays.pdf 124.7 kB
  • 03 - Day Trading with OANDA A-Z a Deep Dive/004 Currency.pdf 116.4 kB
  • 03 - Day Trading with OANDA A-Z a Deep Dive/007 spread.pdf 114.9 kB
  • 34 - Appendix 1 Python (& Finance) Basics/035 Slicing-cheatsheet.pdf 107.8 kB
  • 34 - Appendix 1 Python (& Finance) Basics/028 Built-in-func.pdf 94.8 kB
  • 03 - Day Trading with OANDA A-Z a Deep Dive/010 Candlestick.pdf 94.8 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/032 pandas-iloc.pdf 73.7 kB
  • 34 - Appendix 1 Python (& Finance) Basics/012 keywords.pdf 71.1 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/035 Pandas-loc.pdf 69.4 kB
  • 04 - Stocks and FOREX Trading with Interactive Brokers (IBKR)/010 IBKR-CFD.xlsx 63.0 kB
  • 03 - Day Trading with OANDA A-Z a Deep Dive/006 Long-EUR.xlsx 41.0 kB
  • 03 - Day Trading with OANDA A-Z a Deep Dive/011 Short-EUR.xlsx 36.3 kB
  • 05 - FOREX Day Trading with FXCM/005 Long-EUR-fxcm.xlsx 27.0 kB
  • 06 - Installing Python and Jupyter Notebooks/004 How to work with Jupyter Notebooks_en.srt 20.5 kB
  • 34 - Appendix 1 Python (& Finance) Basics/001 Appendix1-Materials.zip 19.4 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/061 Categorical Seaborn Plots_en.srt 17.2 kB
  • 11 - Introduction to Time Series Data in Pandas/004 Downsampling Time Series with resample()_en.srt 17.1 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/039 Analyzing Numerical Series with unique(), nunique() and value_counts()_en.srt 16.5 kB
  • 37 - What´s next (outlook and additional resources)/001 Bonus Lecture.html 15.5 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/025 First Data Inspection_en.srt 14.8 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/056 Customization of Plots_en.srt 14.8 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/062 Seaborn Regression Plots_en.srt 14.6 kB
  • 13 - Advanced Topics/001 Importing Financial Data from Excel_en.srt 14.2 kB
  • 12 - Financial Data Analysis with Python and Pandas - a (deep) Introduction/021 (Non-) Normality of Financial Returns_en.srt 14.2 kB
  • 12 - Financial Data Analysis with Python and Pandas - a (deep) Introduction/004 Initial Inspection and Visualization_en.srt 13.9 kB
  • 30 - A Machine Learning-powered Strategy A-Z (DNN)/013 Implementation (Oanda & FXCM)_en.srt 13.8 kB
  • 06 - Installing Python and Jupyter Notebooks/003 How to open Jupyter Notebooks_en.srt 13.7 kB
  • 34 - Appendix 1 Python (& Finance) Basics/041 Coding Exercise 3_en.srt 13.5 kB
  • 32 - Adding Stop Loss and Take Profit to the Trading Bot/014 IBKR How to create Stop Loss and Take Profit Orders_en.srt 13.4 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/052 Handling NA Values missing Values_en.srt 13.3 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/047 Filtering DataFrames (one Condition)_en.srt 13.1 kB
  • 32 - Adding Stop Loss and Take Profit to the Trading Bot/005 SL & TP - Use Cases and Conclusion_en.srt 13.0 kB
  • 16 - Defining and Backtesting SMA Strategies/004 Finding the optimal SMA Strategy_en.srt 12.9 kB
  • 03 - Day Trading with OANDA A-Z a Deep Dive/007 Trading Costs and Performance Attribution_en.srt 12.8 kB
  • 14 - Object Oriented Programming (OOP) Creating a Financial Analysis Class/001 Introduction to OOP and examples for Classes_en.srt 12.6 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/068 split-apply-combine_en.srt 12.5 kB
  • 12 - Financial Data Analysis with Python and Pandas - a (deep) Introduction/003 Loading Financial Data from the Web_en.srt 12.5 kB
  • 13 - Advanced Topics/004 Filling NA Values with bfill, ffill and interpolation_en.srt 12.3 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/044 Changing Row Index with set_index() and reset_index()_en.srt 12.1 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/054 Summary Statistics and Accumulations_en.srt 12.0 kB
  • 07 - Excursus How to avoid and debug Coding Errors (don´t skip!)/002 Test your debugging skills!_en.srt 11.9 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/034 Slicing Rows and Columns with loc (label-based indexing)_en.srt 11.9 kB
  • 20 - Trading Strategies powered by Machine Learning - Classification/007 Generalization with OOP A Classification Backtesting Class in action_en.srt 11.9 kB
  • 34 - Appendix 1 Python (& Finance) Basics/051 Keywords pass, continue and break_en.srt 11.9 kB
  • 03 - Day Trading with OANDA A-Z a Deep Dive/003 How to create an Account Update May 2023_en.srt 11.8 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/030 Selecting Rows with iloc (position-based indexing)_en.srt 11.8 kB
  • 34 - Appendix 1 Python (& Finance) Basics/014 Coding Exercise 1_en.srt 11.8 kB
  • 07 - Excursus How to avoid and debug Coding Errors (don´t skip!)/011 How to traceback more complex Errors_en.srt 11.8 kB
  • 34 - Appendix 1 Python (& Finance) Basics/038 Adding and removing Elements fromto Lists_en.srt 11.7 kB
  • 16 - Defining and Backtesting SMA Strategies/005 Generalization with OOP An SMA Backtesting Class in action_en.srt 11.6 kB
  • 11 - Introduction to Time Series Data in Pandas/002 Converting strings to datetime objects with pd.to_datetime()_en.srt 11.4 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/042 Sorting of Series and Introduction to the inplace - parameter_en.srt 11.3 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/051 Intro to NA Values missing Values_en.srt 11.3 kB
  • 03 - Day Trading with OANDA A-Z a Deep Dive/001 OANDA at a first glance_en.srt 11.2 kB
  • 34 - Appendix 1 Python (& Finance) Basics/049 Coding Exercise 4_en.srt 11.2 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/055 Visualization with Matplotlib (Intro)_en.srt 11.0 kB
  • 12 - Financial Data Analysis with Python and Pandas - a (deep) Introduction/020 Comparing the Performance of Financial Instruments_en.srt 10.8 kB
  • 34 - Appendix 1 Python (& Finance) Basics/050 Conditional Statements_en.srt 10.8 kB
  • 04 - Stocks and FOREX Trading with Interactive Brokers (IBKR)/008 Trading Costs (Stocks) - Commissions_en.srt 10.7 kB
  • 24 - Implementation and Automation with IBKR/010 Trade Monitoring and Reporting_en.srt 10.7 kB
  • 25 - Implementation and Automation with FXCM/002 Historical Data, real-time Data and Orders (Recap)_en.srt 10.7 kB
  • 08 - API Trading with Python and Online Brokers- an Introduction/009 OANDA How to place Orders and execute Trades_en.srt 10.7 kB
  • 12 - Financial Data Analysis with Python and Pandas - a (deep) Introduction/008 Price changes and Financial Returns_en.srt 10.7 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/023 Create your very first Pandas DataFrame (from csv)_en.srt 10.6 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/063 Seaborn Heatmaps_en.srt 10.6 kB
  • 34 - Appendix 1 Python (& Finance) Basics/039 Mutable vs. immutable Objects (Part 1)_en.srt 10.6 kB
  • 32 - Adding Stop Loss and Take Profit to the Trading Bot/016 IBKR Adding Stop Loss & Take Profit_en.srt 10.5 kB
  • 02 - +++ PART 1 Day Trading, Online Brokers and APIs +++/004 Spot Trading vs. Derivatives Trading (Part 2)_en.srt 10.4 kB
  • 18 - Defining and Backtesting Mean-Reversion Strategies (Bollinger)/004 Defining a Bollinger Bands Mean-Reversion Strategy (Part 2)_en.srt 10.3 kB
  • 01 - Getting Started/004 Student FAQ.html 10.3 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/066 Understanding the GroupBy Object_en.srt 10.3 kB
  • 17 - Defining and Backtesting simple MomentumContrarian Strategies/007 Trades and Trading Costs (Part 1)_en.srt 10.3 kB
  • 34 - Appendix 1 Python (& Finance) Basics/024 Coding Exercise 2_en.srt 10.3 kB
  • 29 - Working with two or many Strategies (Combination)/008 Strategy Optimization_en.srt 10.3 kB
  • 35 - Appendix 2 User-defined Functions (required for OOP)/009 Scope - easily explained_en.srt 10.3 kB
  • 12 - Financial Data Analysis with Python and Pandas - a (deep) Introduction/024 Rolling Statistics_en.srt 10.2 kB
  • 02 - +++ PART 1 Day Trading, Online Brokers and APIs +++/003 Spot Trading vs. Derivatives Trading (Part 1)_en.srt 10.2 kB
  • 11 - Introduction to Time Series Data in Pandas/001 Importing Time Series Data from csv-files_en.srt 10.2 kB
  • 23 - Implementation and Automation with OANDA (UPDATED!)/004 Historical Data, real-time Data and Orders (Recap)_en.srt 10.2 kB
  • 21 - Advanced Backtesting Techniques/013 Adding the Iterative Backtest Child Class for SMA (Part 2)_en.srt 10.2 kB
  • 34 - Appendix 1 Python (& Finance) Basics/044 Intro to Strings_en.srt 10.1 kB
  • 12 - Financial Data Analysis with Python and Pandas - a (deep) Introduction/033 Margin Trading and Levered Returns (Part 2)_en.srt 10.1 kB
  • 03 - Day Trading with OANDA A-Z a Deep Dive/004 FOREX Currency Exchange Rates explained_en.srt 10.0 kB
  • 34 - Appendix 1 Python (& Finance) Basics/019 For Loops - Iterating over Lists_en.srt 10.0 kB
  • 34 - Appendix 1 Python (& Finance) Basics/022 The Net Present Value - NPV (Theory)_en.srt 10.0 kB
  • 08 - API Trading with Python and Online Brokers- an Introduction/019 IBKR Creating Orders (Stock Trading)_en.srt 10.0 kB
  • 16 - Defining and Backtesting SMA Strategies/003 Vectorized Strategy Backtesting_en.srt 9.8 kB
  • 04 - Stocks and FOREX Trading with Interactive Brokers (IBKR)/010 FOREX Trading Cash vs. CFD_en.srt 9.8 kB
  • 34 - Appendix 1 Python (& Finance) Basics/048 Comparison, Logical and Membership Operators in Action_en.srt 9.7 kB
  • 32 - Adding Stop Loss and Take Profit to the Trading Bot/007 Oanda How to create Stop Loss and Take Profit Orders_en.srt 9.6 kB
  • 14 - Object Oriented Programming (OOP) Creating a Financial Analysis Class/012 Inheritance_en.srt 9.6 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/003 Numpy Arrays_en.srt 9.5 kB
  • 12 - Financial Data Analysis with Python and Pandas - a (deep) Introduction/014 Discrete Compounding_en.srt 9.5 kB
  • 32 - Adding Stop Loss and Take Profit to the Trading Bot/011 Oanda Adding Stop Loss & Take Profit_en.srt 9.5 kB
  • 23 - Implementation and Automation with OANDA (UPDATED!)/012 Working with historical data and real-time tick data (Part 1)_en.srt 9.5 kB
  • 32 - Adding Stop Loss and Take Profit to the Trading Bot/002 Stop Loss Orders - Theory_en.srt 9.4 kB
  • 23 - Implementation and Automation with OANDA (UPDATED!)/017 Trade Monitoring and Reporting_en.srt 9.4 kB
  • 19 - Trading Strategies powered by Machine Learning - Regression/002 Linear Regression with scikit-learn - a simple Introduction_en.srt 9.4 kB
  • 25 - Implementation and Automation with FXCM/008 Storing and resampling real-time tick data (Part 2)_en.srt 9.4 kB
  • 34 - Appendix 1 Python (& Finance) Basics/021 Calculate FV and PV for many Cashflows_en.srt 9.3 kB
  • 25 - Implementation and Automation with FXCM/006 Storing and resampling real-time tick data (Part 1)_en.srt 9.3 kB
  • 14 - Object Oriented Programming (OOP) Creating a Financial Analysis Class/004 The special method __init__()_en.srt 9.2 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/002 Modules, Packages and Libraries - No need to reinvent the Wheel_en.srt 9.2 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/050 Advanced Filtering with between(), isin() and ~_en.srt 9.2 kB
  • 26 - Cloud Deployment (AWS) Scheduling Trading Sessions Full Automation/004 How to create an EC2 Instance_en.srt 9.2 kB
  • 17 - Defining and Backtesting simple MomentumContrarian Strategies/009 Generalization with OOP A Contrarian Backtesting Class in action_en.srt 9.1 kB
  • 31 - Error Handling How to make your Trading Bot more stable and reliable/013 Oanda Error Handling (Part 2)_en.srt 9.0 kB
  • 23 - Implementation and Automation with OANDA (UPDATED!)/010 Storing and resampling real-time tick data (Part 4)_en.srt 9.0 kB
  • 07 - Excursus How to avoid and debug Coding Errors (don´t skip!)/015 Summary and Debugging Flow-Chart_en.srt 8.9 kB
  • 12 - Financial Data Analysis with Python and Pandas - a (deep) Introduction/023 Resampling Smoothing of Financial Data_en.srt 8.9 kB
  • 34 - Appendix 1 Python (& Finance) Basics/053 Introduction to while loops_en.srt 8.9 kB
  • 30 - A Machine Learning-powered Strategy A-Z (DNN)/009 Creating and Fitting the DNN Model_en.srt 8.8 kB
  • 23 - Implementation and Automation with OANDA (UPDATED!)/007 Storing and resampling real-time tick data (Part 1)_en.srt 8.8 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/040 Analyzing non-numerical Series with unique(), nunique(), value_counts()_en.srt 8.7 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/059 Scatterplots_en.srt 8.5 kB
  • 12 - Financial Data Analysis with Python and Pandas - a (deep) Introduction/030 Covariance and Correlation_en.srt 8.5 kB
  • 34 - Appendix 1 Python (& Finance) Basics/042 Tuples_en.srt 8.5 kB
  • 25 - Implementation and Automation with FXCM/014 Placing Orders and Executing Trades_en.srt 8.5 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/067 Splitting with many Keys_en.srt 8.5 kB
  • 08 - API Trading with Python and Online Brokers- an Introduction/006 OANDA How to load Historical Price Data (Part 1)_en.srt 8.5 kB
  • 16 - Defining and Backtesting SMA Strategies/007 Creating the Class (Part 2)_en.srt 8.5 kB
  • 03 - Day Trading with OANDA A-Z a Deep Dive/009 Margin Closeout and more_en.srt 8.4 kB
  • 08 - API Trading with Python and Online Brokers- an Introduction/015 IBKR How to get Market Data_en.srt 8.4 kB
  • 08 - API Trading with Python and Online Brokers- an Introduction/005 OANDA Connecting to the APIServer_en.srt 8.4 kB
  • 03 - Day Trading with OANDA A-Z a Deep Dive/008 Margin and Leverage_en.srt 8.4 kB
  • 11 - Introduction to Time Series Data in Pandas/003 Indexing and Slicing Time Series_en.srt 8.3 kB
  • 20 - Trading Strategies powered by Machine Learning - Classification/008 The Classification Backtesting Class explained (Part 1)_en.srt 8.3 kB
  • 14 - Object Oriented Programming (OOP) Creating a Financial Analysis Class/016 Coding Exercise 3 Create your own Class_en.srt 8.3 kB
  • 07 - Excursus How to avoid and debug Coding Errors (don´t skip!)/005 Omitting cells, changing the sequence and more_en.srt 8.3 kB
  • 30 - A Machine Learning-powered Strategy A-Z (DNN)/010 Prediction & Out-Sample Forward Testing_en.srt 8.3 kB
  • 08 - API Trading with Python and Online Brokers- an Introduction/028 FXCM Connecting to the APIServer_en.srt 8.3 kB
  • 21 - Advanced Backtesting Techniques/007 Creating an Iterative Base Class (Part 4)_en.srt 8.2 kB
  • 34 - Appendix 1 Python (& Finance) Basics/011 More on Variables and Memory_en.srt 8.2 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/058 Histogramms (Part 2)_en.srt 8.2 kB
  • 15 - +++ PART 3 Defining and Testing Trading Strategies +++/001 Introduction to Part 3_en.srt 8.2 kB
  • 03 - Day Trading with OANDA A-Z a Deep Dive/011 Our third Trade A-Z - Going Short EURUSD_en.srt 8.1 kB
  • 21 - Advanced Backtesting Techniques/015 OOP Challenge Add Contrarian and Bollinger Strategies_en.srt 8.1 kB
  • 25 - Implementation and Automation with FXCM/005 Collecting and storing real-time tick data_en.srt 8.1 kB
  • 19 - Trading Strategies powered by Machine Learning - Regression/001 Machine Learning - an Overview_en.srt 8.1 kB
  • 15 - +++ PART 3 Defining and Testing Trading Strategies +++/002 Trading Strategies - an Overview_en.srt 8.1 kB
  • 34 - Appendix 1 Python (& Finance) Basics/043 Dictionaries_en.srt 8.1 kB
  • 08 - API Trading with Python and Online Brokers- an Introduction/033 FXCM How to place Orders and execute Trades_en.srt 8.0 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/024 Pandas Display Options and the methods head() & tail()_en.srt 8.0 kB
  • 02 - +++ PART 1 Day Trading, Online Brokers and APIs +++/005 Overview & the Brokers OANDA, IBKR and FXCM_en.srt 7.9 kB
  • 34 - Appendix 1 Python (& Finance) Basics/028 Build-in Functions_en.srt 7.9 kB
  • 18 - Defining and Backtesting Mean-Reversion Strategies (Bollinger)/006 Generalization with OOP A Bollinger Bands Backtesting Class in action_en.srt 7.9 kB
  • 16 - Defining and Backtesting SMA Strategies/002 Defining an SMA Crossover Strategy_en.srt 7.9 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/036 Summary, Best Practices and Outlook_en.srt 7.9 kB
  • 24 - Implementation and Automation with IBKR/009 Creating Orders and Executing Trades_en.srt 7.9 kB
  • 31 - Error Handling How to make your Trading Bot more stable and reliable/015 Implementation with IBKR Errors and Connectivity Issues_en.srt 7.8 kB
  • 34 - Appendix 1 Python (& Finance) Basics/025 Data Types in Action_en.srt 7.7 kB
  • 30 - A Machine Learning-powered Strategy A-Z (DNN)/003 Installation of Tensorflow & Keras (Part 2)_en.srt 7.7 kB
  • 03 - Day Trading with OANDA A-Z a Deep Dive/012 Netting vs. Hedging_en.srt 7.7 kB
  • 34 - Appendix 1 Python (& Finance) Basics/002 Intro to the Time Value of Money (TVM) Concept (Theory)_en.srt 7.7 kB
  • 21 - Advanced Backtesting Techniques/010 Creating an Iterative Base Class (Part 7)_en.srt 7.7 kB
  • 35 - Appendix 2 User-defined Functions (required for OOP)/003 What´s the difference between Positional Arguments vs. Keyword Arguments_en.srt 7.7 kB
  • 03 - Day Trading with OANDA A-Z a Deep Dive/006 How to calculate Profit & Loss of a Trade_en.srt 7.6 kB
  • 05 - FOREX Day Trading with FXCM/003 How to create an Account_en.srt 7.6 kB
  • 35 - Appendix 2 User-defined Functions (required for OOP)/005 The Default Argument None_en.srt 7.6 kB
  • 07 - Excursus How to avoid and debug Coding Errors (don´t skip!)/012 Problems with the Python Installation_en.srt 7.6 kB
  • 19 - Trading Strategies powered by Machine Learning - Regression/008 A simple Linear Model to predict Financial Returns (Part 2)_en.srt 7.6 kB
  • 07 - Excursus How to avoid and debug Coding Errors (don´t skip!)/010 Getting help on StackOverflow.com_en.srt 7.6 kB
  • 14 - Object Oriented Programming (OOP) Creating a Financial Analysis Class/014 Adding meaningful Docstrings_en.srt 7.6 kB
  • 04 - Stocks and FOREX Trading with Interactive Brokers (IBKR)/009 Trading Costs (Stocks) - other (hidden) Costs_en.srt 7.6 kB
  • 15 - +++ PART 3 Defining and Testing Trading Strategies +++/006 Performance Metrics_en.srt 7.5 kB
  • 35 - Appendix 2 User-defined Functions (required for OOP)/002 Defining your first user-defined Function_en.srt 7.5 kB
  • 16 - Defining and Backtesting SMA Strategies/008 Creating the Class (Part 3)_en.srt 7.5 kB
  • 19 - Trading Strategies powered by Machine Learning - Regression/004 Overfitting_en.srt 7.5 kB
  • 12 - Financial Data Analysis with Python and Pandas - a (deep) Introduction/011 Investment Multiple and CAGR_en.srt 7.5 kB
  • 23 - Implementation and Automation with OANDA (UPDATED!)/022 Machine Learning Strategies (2) - Implementation_en.srt 7.5 kB
  • 08 - API Trading with Python and Online Brokers- an Introduction/023 IBKR Historical Bars_en.srt 7.4 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/011 Advanced Filtering & Bitwise Operators_en.srt 7.4 kB
  • 13 - Advanced Topics/003 Helpful DatetimeIndex Attributes and Methods_en.srt 7.4 kB
  • 20 - Trading Strategies powered by Machine Learning - Classification/002 Logistic Regression with scikit-learn - a simple Introduction (Part 2)_en.srt 7.4 kB
  • 08 - API Trading with Python and Online Brokers- an Introduction/032 FXCM Streaming high-frequency real-time Data_en.srt 7.4 kB
  • 06 - Installing Python and Jupyter Notebooks/002 Download and Install Anaconda_en.srt 7.4 kB
  • 23 - Implementation and Automation with OANDA (UPDATED!)/025 Running a Python Trader Script_en.srt 7.4 kB
  • 23 - Implementation and Automation with OANDA (UPDATED!)/013 Working with historical data and real-time tick data (Part 2)_en.srt 7.4 kB
  • 14 - Object Oriented Programming (OOP) Creating a Financial Analysis Class/013 Inheritance and the super() Function_en.srt 7.3 kB
  • 12 - Financial Data Analysis with Python and Pandas - a (deep) Introduction/017 Simple Returns vs Log Returns ( Part 1)_en.srt 7.3 kB
  • 26 - Cloud Deployment (AWS) Scheduling Trading Sessions Full Automation/011 How to stop Trading Sessions (OANDA)_en.srt 7.3 kB
  • 05 - FOREX Day Trading with FXCM/002 FXCM at a first glance_en.srt 7.3 kB
  • 30 - A Machine Learning-powered Strategy A-Z (DNN)/005 Adding LabelsFeatures_en.srt 7.2 kB
  • 04 - Stocks and FOREX Trading with Interactive Brokers (IBKR)/005 The first Trade (buying Stocks)_en.srt 7.1 kB
  • 24 - Implementation and Automation with IBKR/004 Streaming Bar Data_en.srt 7.1 kB
  • 21 - Advanced Backtesting Techniques/011 Creating an Iterative Base Class (Part 8)_en.srt 7.1 kB
  • 31 - Error Handling How to make your Trading Bot more stable and reliable/012 Oanda Error Handling (Part 1)_en.srt 7.1 kB
  • 26 - Cloud Deployment (AWS) Scheduling Trading Sessions Full Automation/002 Demonstration AWS EC2 for Algorithmic Trading live in action_en.srt 7.1 kB
  • 01 - Getting Started/002 How to get the best out of this course_en.srt 7.1 kB
  • 25 - Implementation and Automation with FXCM/021 Running a Python Script_en.srt 7.1 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/060 First Steps with Seaborn_en.srt 7.1 kB
  • 12 - Financial Data Analysis with Python and Pandas - a (deep) Introduction/006 Normalizing Time Series to a Base Value (100)_en.srt 7.0 kB
  • 08 - API Trading with Python and Online Brokers- an Introduction/030 FXCM How to load Historical Price Data (Part 1)_en.srt 7.0 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/043 First Steps with Pandas Index Objects_en.srt 7.0 kB
  • 34 - Appendix 1 Python (& Finance) Basics/030 Floats_en.srt 7.0 kB
  • 35 - Appendix 2 User-defined Functions (required for OOP)/004 How to work with Default Arguments_en.srt 7.0 kB
  • 21 - Advanced Backtesting Techniques/002 A first Intuition on Iterative Backtesting (Part 1)_en.srt 6.9 kB
  • 14 - Object Oriented Programming (OOP) Creating a Financial Analysis Class/005 The method get_data()_en.srt 6.9 kB
  • 12 - Financial Data Analysis with Python and Pandas - a (deep) Introduction/018 Simple Returns vs Log Returns ( Part 2)_en.srt 6.9 kB
  • 30 - A Machine Learning-powered Strategy A-Z (DNN)/001 Project Overview_en.srt 6.9 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/017 How to slice 2-dim Numpy Arrays (Part 1)_en.srt 6.9 kB
  • 25 - Implementation and Automation with FXCM/010 Working with historical data and real-time tick data (Part 1)_en.srt 6.9 kB
  • 25 - Implementation and Automation with FXCM/015 Trade Monitoring and Reporting_en.srt 6.9 kB
  • 07 - Excursus How to avoid and debug Coding Errors (don´t skip!)/004 The most commonly made Errors at a glance_en.srt 6.9 kB
  • 23 - Implementation and Automation with OANDA (UPDATED!)/016 Placing Orders and Executing Trades_en.srt 6.8 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/006 Changing Elements in Numpy Arrays & Mutability_en.srt 6.8 kB
  • 12 - Financial Data Analysis with Python and Pandas - a (deep) Introduction/009 Reward and Risk of Financial Instruments_en.srt 6.8 kB
  • 23 - Implementation and Automation with OANDA (UPDATED!)/015 Defining a simple Contrarian Strategy_en.srt 6.8 kB
  • 26 - Cloud Deployment (AWS) Scheduling Trading Sessions Full Automation/006 Getting the Instance Ready for Algorithmic Trading_en.srt 6.8 kB
  • 34 - Appendix 1 Python (& Finance) Basics/031 How to round Floats (and Integers) with round()_en.srt 6.7 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/027 Selecting Columns_en.srt 6.7 kB
  • 18 - Defining and Backtesting Mean-Reversion Strategies (Bollinger)/001 Mean-Reversion Strategies - Overview_en.srt 6.7 kB
  • 19 - Trading Strategies powered by Machine Learning - Regression/009 A Multiple Regression Model to predict Financial Returns_en.srt 6.7 kB
  • 21 - Advanced Backtesting Techniques/012 Adding the Iterative Backtest Child Class for SMA (Part 1)_en.srt 6.7 kB
  • 14 - Object Oriented Programming (OOP) Creating a Financial Analysis Class/011 Adding more methods and performance metrics_en.srt 6.6 kB
  • 34 - Appendix 1 Python (& Finance) Basics/032 More on Lists_en.srt 6.6 kB
  • 23 - Implementation and Automation with OANDA (UPDATED!)/021 Machine Learning Strategies (1) - Model Fitting_en.srt 6.6 kB
  • 25 - Implementation and Automation with FXCM/018 Machine Learning Strategies (1) - Model Fitting_en.srt 6.6 kB
  • 29 - Working with two or many Strategies (Combination)/004 Combining both Strategies - Alternative 1_en.srt 6.6 kB
  • 18 - Defining and Backtesting Mean-Reversion Strategies (Bollinger)/005 Vectorized Strategy Backtesting_en.srt 6.5 kB
  • 34 - Appendix 1 Python (& Finance) Basics/008 Introduction to Variables_en.srt 6.5 kB
  • 08 - API Trading with Python and Online Brokers- an Introduction/017 IBKR Contracts (advanced)_en.srt 6.5 kB
  • 08 - API Trading with Python and Online Brokers- an Introduction/021 IBKR CFD Trade Information_en.srt 6.5 kB
  • 24 - Implementation and Automation with IBKR/013 Running a Python Trader Script_en.srt 6.5 kB
  • 35 - Appendix 2 User-defined Functions (required for OOP)/007 Sequences as arguments and args_en.srt 6.5 kB
  • 23 - Implementation and Automation with OANDA (UPDATED!)/006 How to collect and store real-time tick data_en.srt 6.4 kB
  • 25 - Implementation and Automation with FXCM/011 Working with historical data and real-time tick data (Part 2)_en.srt 6.4 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/008 Numpy Array Methods and Attributes_en.srt 6.4 kB
  • 25 - Implementation and Automation with FXCM/007 A Trader Class_en.srt 6.4 kB
  • 25 - Implementation and Automation with FXCM/004 Preview A Trader Class live in action_en.srt 6.4 kB
  • 12 - Financial Data Analysis with Python and Pandas - a (deep) Introduction/015 Continuous Compounding_en.srt 6.4 kB
  • 32 - Adding Stop Loss and Take Profit to the Trading Bot/008 Oanda Stop Loss and Take Profit Orders - Pitfalls_en.srt 6.3 kB
  • 32 - Adding Stop Loss and Take Profit to the Trading Bot/009 Oanda Setting SL Distances and TP Prices in real-time_en.srt 6.3 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/064 Removing Columns_en.srt 6.3 kB
  • 31 - Error Handling How to make your Trading Bot more stable and reliable/001 Introduction_en.srt 6.3 kB
  • 21 - Advanced Backtesting Techniques/008 Creating an Iterative Base Class (Part 5)_en.srt 6.3 kB
  • 25 - Implementation and Automation with FXCM/019 Machine Learning Strategies (2) - Implementation_en.srt 6.3 kB
  • 01 - Getting Started/001 What is Algorithmic Trading Course Overview_en.srt 6.3 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/013 Creating Numpy Arrays from Scratch_en.srt 6.3 kB
  • 17 - Defining and Backtesting simple MomentumContrarian Strategies/006 Changing the Window Parameter_en.srt 6.3 kB
  • 03 - Day Trading with OANDA A-Z a Deep Dive/013 Market, Limit and Stop Orders_en.srt 6.2 kB
  • 34 - Appendix 1 Python (& Finance) Basics/006 Interest Rates and Returns (Theory)_en.srt 6.2 kB
  • 28 - Trading Hours, Spreads and Granularity - control and limit Trading Costs!/001 Introduction and Preparing the Data_en.srt 6.2 kB
  • 20 - Trading Strategies powered by Machine Learning - Classification/001 Logistic Regression with scikit-learn - a simple Introduction (Part 1)_en.srt 6.2 kB
  • 13 - Advanced Topics/002 Merging Aligning Financial Time Series (hands-on)_en.srt 6.2 kB
  • 31 - Error Handling How to make your Trading Bot more stable and reliable/016 IBKR Error Handling_en.srt 6.1 kB
  • 34 - Appendix 1 Python (& Finance) Basics/020 The range Object - another Iterable_en.srt 6.1 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/012 Determining a Project´s Payback Period with np.where()_en.srt 6.0 kB
  • 15 - +++ PART 3 Defining and Testing Trading Strategies +++/005 A simple Buy and Hold Strategy_en.srt 6.0 kB
  • 14 - Object Oriented Programming (OOP) Creating a Financial Analysis Class/008 The methods plot_prices() and plot_returns()_en.srt 6.0 kB
  • 34 - Appendix 1 Python (& Finance) Basics/040 Mutable vs. immutable Objects (Part 2)_en.srt 6.0 kB
  • 08 - API Trading with Python and Online Brokers- an Introduction/014 IBKR Contracts_en.srt 6.0 kB
  • 04 - Stocks and FOREX Trading with Interactive Brokers (IBKR)/011 A complete CFD FOREX Trade_en.srt 6.0 kB
  • 31 - Error Handling How to make your Trading Bot more stable and reliable/019 FXCM Error Handling (Part 2)_en.srt 6.0 kB
  • 11 - Introduction to Time Series Data in Pandas/005 Coding Exercise 1_en.srt 6.0 kB
  • 12 - Financial Data Analysis with Python and Pandas - a (deep) Introduction/007 Coding Challenge #1_en.srt 5.9 kB
  • 23 - Implementation and Automation with OANDA (UPDATED!)/005 Preview A Trader Class live in action_en.srt 5.9 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/007 View vs. copy - potential Pitfalls when slicing Numpy Arrays_en.srt 5.9 kB
  • 21 - Advanced Backtesting Techniques/003 A first Intuition on Iterative Backtesting (Part 2)_en.srt 5.9 kB
  • 32 - Adding Stop Loss and Take Profit to the Trading Bot/004 Take Profit Orders - Theory_en.srt 5.9 kB
  • 08 - API Trading with Python and Online Brokers- an Introduction/004 OANDA Getting the API Key & other Preparations_en.srt 5.9 kB
  • 23 - Implementation and Automation with OANDA (UPDATED!)/008 Storing and resampling real-time tick data (Part 2)_en.srt 5.9 kB
  • 03 - Day Trading with OANDA A-Z a Deep Dive/010 Introduction to Charting_en.srt 5.9 kB
  • 17 - Defining and Backtesting simple MomentumContrarian Strategies/010 OOP Challenge Create the Contrarian Backtesting Class (incl. Solution)_en.srt 5.8 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/049 Filtering DataFrames by many Conditions (OR)_en.srt 5.8 kB
  • 32 - Adding Stop Loss and Take Profit to the Trading Bot/015 IBKR Stop Loss and Take Profit Orders - Pitfalls_en.srt 5.8 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/022 Intro to Tabular Data Pandas_en.srt 5.8 kB
  • 16 - Defining and Backtesting SMA Strategies/001 SMA Crossover Strategies - Overview_en.srt 5.8 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/010 Boolean Arrays and Conditional Filtering_en.srt 5.8 kB
  • 21 - Advanced Backtesting Techniques/014 Using Modules and adding Docstrings_en.srt 5.7 kB
  • 35 - Appendix 2 User-defined Functions (required for OOP)/006 How to unpack Iterables_en.srt 5.7 kB
  • 26 - Cloud Deployment (AWS) Scheduling Trading Sessions Full Automation/012 How to stop Trading Sessions (FXCM)_en.srt 5.7 kB
  • 34 - Appendix 1 Python (& Finance) Basics/052 Calculate a Project´s Payback Period_en.srt 5.7 kB
  • 02 - +++ PART 1 Day Trading, Online Brokers and APIs +++/002 Long Term Investing vs. (Algorithmic) Day Trading_en.srt 5.7 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/020 How to perform row-wise and column-wise Operations_en.srt 5.7 kB
  • 12 - Financial Data Analysis with Python and Pandas - a (deep) Introduction/032 Margin Trading and Levered Returns (Part 1)_en.srt 5.7 kB
  • 13 - Advanced Topics/006 Timezones and Converting (Part 2)_en.srt 5.7 kB
  • 12 - Financial Data Analysis with Python and Pandas - a (deep) Introduction/022 Annualizing Return and Risk_en.srt 5.6 kB
  • 24 - Implementation and Automation with IBKR/011 How to Stop a Trading Session_en.srt 5.6 kB
  • 16 - Defining and Backtesting SMA Strategies/009 Creating the Class (Part 4)_en.srt 5.6 kB
  • 25 - Implementation and Automation with FXCM/013 Defining a Simple Contrarian Trading Strategy_en.srt 5.6 kB
  • 31 - Error Handling How to make your Trading Bot more stable and reliable/018 FXCM Error Handling (Part 1)_en.srt 5.6 kB
  • 01 - Getting Started/003 Did you know... (what Data can tell us about Day Trading)_en.srt 5.6 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/057 Histogramms (Part 1)_en.srt 5.5 kB
  • 16 - Defining and Backtesting SMA Strategies/011 Creating the Class (Part 6)_en.srt 5.5 kB
  • 34 - Appendix 1 Python (& Finance) Basics/033 Lists and Element-wise Operations_en.srt 5.5 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/015 How to work with nested Lists_en.srt 5.5 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/031 Slicing Rows and Columns with iloc (position-based indexing)_en.srt 5.5 kB
  • 13 - Advanced Topics/005 Timezones and Converting (Part 1)_en.srt 5.5 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/048 Filtering DataFrames by many Conditions (AND)_en.srt 5.5 kB
  • 31 - Error Handling How to make your Trading Bot more stable and reliable/008 Try again (...until it works)_en.srt 5.4 kB
  • 34 - Appendix 1 Python (& Finance) Basics/047 Operators (Theory)_en.srt 5.4 kB
  • 07 - Excursus How to avoid and debug Coding Errors (don´t skip!)/006 IndexErrors_en.srt 5.4 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/041 The copy() method_en.srt 5.4 kB
  • 08 - API Trading with Python and Online Brokers- an Introduction/031 FXCM How to load Historical Price Data (Part 2)_en.srt 5.4 kB
  • 24 - Implementation and Automation with IBKR/006 Preparing the Data for Day Trading_en.srt 5.4 kB
  • 23 - Implementation and Automation with OANDA (UPDATED!)/009 Storing and resampling real-time tick data (Part 3)_en.srt 5.4 kB
  • 14 - Object Oriented Programming (OOP) Creating a Financial Analysis Class/002 The Financial Analysis Class live in action (Part 1)_en.srt 5.4 kB
  • 07 - Excursus How to avoid and debug Coding Errors (don´t skip!)/013 External Factors and Issues_en.srt 5.3 kB
  • 21 - Advanced Backtesting Techniques/004 Creating an Iterative Base Class (Part 1)_en.srt 5.3 kB
  • 16 - Defining and Backtesting SMA Strategies/013 Creating the Class (Part 8)_en.srt 5.3 kB
  • 34 - Appendix 1 Python (& Finance) Basics/013 The print() Function_en.srt 5.3 kB
  • 07 - Excursus How to avoid and debug Coding Errors (don´t skip!)/014 Errors related to the course content (Transcription Errors)_en.srt 5.2 kB
  • 34 - Appendix 1 Python (& Finance) Basics/004 NEW Udemy Online Coding Exercises - Intro_en.srt 5.2 kB
  • 17 - Defining and Backtesting simple MomentumContrarian Strategies/003 Excursus Your FAQs answered_en.srt 5.2 kB
  • 04 - Stocks and FOREX Trading with Interactive Brokers (IBKR)/006 Trading Hours_en.srt 5.2 kB
  • 34 - Appendix 1 Python (& Finance) Basics/034 Slicing Lists_en.srt 5.1 kB
  • 26 - Cloud Deployment (AWS) Scheduling Trading Sessions Full Automation/010 How to schedule Trading sessions with the Task Scheduler_en.srt 5.1 kB
  • 32 - Adding Stop Loss and Take Profit to the Trading Bot/010 Oanda Check for SLTP Events_en.srt 5.1 kB
  • 21 - Advanced Backtesting Techniques/001 Introduction to Iterative Backtesting (event-driven)_en.srt 5.1 kB
  • 18 - Defining and Backtesting Mean-Reversion Strategies (Bollinger)/003 Defining a Bollinger Bands Mean-Reversion Strategy (Part 1)_en.srt 5.1 kB
  • 31 - Error Handling How to make your Trading Bot more stable and reliable/010 Waiting periods between re-tries_en.srt 5.1 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/038 First Steps with Pandas Series_en.srt 5.1 kB
  • 19 - Trading Strategies powered by Machine Learning - Regression/011 Out-Sample Forward Testing_en.srt 5.0 kB
  • 20 - Trading Strategies powered by Machine Learning - Classification/009 The Classification Backtesting Class explained (Part 2)_en.srt 5.0 kB
  • 34 - Appendix 1 Python (& Finance) Basics/045 String Replacement_en.srt 5.0 kB
  • 12 - Financial Data Analysis with Python and Pandas - a (deep) Introduction/027 Short Selling and Short Position Returns (Part 2)_en.srt 5.0 kB
  • 34 - Appendix 1 Python (& Finance) Basics/007 Calculate Interest Rates and Returns with Python_en.srt 5.0 kB
  • 25 - Implementation and Automation with FXCM/017 SMA Crossover and Bollinger Bands (Solution)_en.srt 5.0 kB
  • 12 - Financial Data Analysis with Python and Pandas - a (deep) Introduction/001 Introduction and Overview_en.srt 4.9 kB
  • 17 - Defining and Backtesting simple MomentumContrarian Strategies/005 Vectorized Strategy Backtesting_en.srt 4.9 kB
  • 28 - Trading Hours, Spreads and Granularity - control and limit Trading Costs!/005 The Impact of Granularity_en.srt 4.9 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/009 Numpy Universal Functions_en.srt 4.9 kB
  • 34 - Appendix 1 Python (& Finance) Basics/012 Variables - Dos, Don´ts and Conventions_en.srt 4.9 kB
  • 03 - Day Trading with OANDA A-Z a Deep Dive/005 Our second Trade - EURUSD FOREX Trading_en.srt 4.9 kB
  • 03 - Day Trading with OANDA A-Z a Deep Dive/015 A more general Example_en.srt 4.8 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/046 Renaming Index & Column Labels with rename()_en.srt 4.8 kB
  • 12 - Financial Data Analysis with Python and Pandas - a (deep) Introduction/028 Short Selling and Short Position Returns (Part 3)_en.srt 4.8 kB
  • 21 - Advanced Backtesting Techniques/009 Creating an Iterative Base Class (Part 6)_en.srt 4.8 kB
  • 18 - Defining and Backtesting Mean-Reversion Strategies (Bollinger)/007 OOP Challenge Create the Bollinger Bands Backtesting Class (incl. Solution)_en.srt 4.8 kB
  • 04 - Stocks and FOREX Trading with Interactive Brokers (IBKR)/002 How to create a (Paper Trading) Account_en.srt 4.8 kB
  • 24 - Implementation and Automation with IBKR/008 Define an SMA Day Trading Strategy_en.srt 4.8 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/016 2-dimensional Numpy Arrays_en.srt 4.7 kB
  • 19 - Trading Strategies powered by Machine Learning - Regression/010 In-Sample Backtesting and the Look-ahead-bias_en.srt 4.7 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/005 Vectorized Operations with Numpy Arrays_en.srt 4.7 kB
  • 04 - Stocks and FOREX Trading with Interactive Brokers (IBKR)/007 Cash Account vs. Margin Account_en.srt 4.7 kB
  • 15 - +++ PART 3 Defining and Testing Trading Strategies +++/004 Getting the Data_en.srt 4.7 kB
  • 12 - Financial Data Analysis with Python and Pandas - a (deep) Introduction/012 Compound Returns & Geometric Mean Return_en.srt 4.6 kB
  • 19 - Trading Strategies powered by Machine Learning - Regression/005 Underfitting_en.srt 4.6 kB
  • 34 - Appendix 1 Python (& Finance) Basics/015 TVM Problems with many Cashflows_en.srt 4.6 kB
  • 34 - Appendix 1 Python (& Finance) Basics/037 Sorting and Reversing Lists_en.srt 4.6 kB
  • 23 - Implementation and Automation with OANDA (UPDATED!)/011 Storing and resampling real-time tick data (Part 5)_en.srt 4.6 kB
  • 26 - Cloud Deployment (AWS) Scheduling Trading Sessions Full Automation/005 How to connect to your EC2 Instance_en.srt 4.5 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/019 Recap Changing Elements in a Numpy Array slice_en.srt 4.5 kB
  • 17 - Defining and Backtesting simple MomentumContrarian Strategies/001 Simple ContrarianMomentum Strategies - Overview_en.srt 4.5 kB
  • 14 - Object Oriented Programming (OOP) Creating a Financial Analysis Class/009 Encapsulation and protected Attributes_en.srt 4.5 kB
  • 07 - Excursus How to avoid and debug Coding Errors (don´t skip!)/009 TypeErrors and ValueErrors_en.srt 4.4 kB
  • 34 - Appendix 1 Python (& Finance) Basics/003 Calculate Future Values (FV) with Python Compounding_en.srt 4.4 kB
  • 34 - Appendix 1 Python (& Finance) Basics/026 The Data Type Hierarchy (Theory)_en.srt 4.4 kB
  • 23 - Implementation and Automation with OANDA (UPDATED!)/019 Implementing an SMA Crossover Strategy (Solution)_en.srt 4.4 kB
  • 14 - Object Oriented Programming (OOP) Creating a Financial Analysis Class/015 Creating and Importing Python Modules (.py)_en.srt 4.3 kB
  • 04 - Stocks and FOREX Trading with Interactive Brokers (IBKR)/004 TWS - First Steps_en.srt 4.3 kB
  • 31 - Error Handling How to make your Trading Bot more stable and reliable/014 Oanda Error Handling (Part 3)_en.srt 4.3 kB
  • 31 - Error Handling How to make your Trading Bot more stable and reliable/007 finally_en.srt 4.3 kB
  • 04 - Stocks and FOREX Trading with Interactive Brokers (IBKR)/001 IBKR at a first glance_en.srt 4.3 kB
  • 07 - Excursus How to avoid and debug Coding Errors (don´t skip!)/007 Indentation Errors_en.srt 4.3 kB
  • 26 - Cloud Deployment (AWS) Scheduling Trading Sessions Full Automation/009 How to start Trading sessions with Batch (.bat) Files_en.srt 4.2 kB
  • 12 - Financial Data Analysis with Python and Pandas - a (deep) Introduction/031 Portfolios and Portfolio Returns_en.srt 4.2 kB
  • 23 - Implementation and Automation with OANDA (UPDATED!)/014 Working with historical data and real-time tick data (Part 3)_en.srt 4.2 kB
  • 08 - API Trading with Python and Online Brokers- an Introduction/022 IBKR Positions and Account Values_en.srt 4.2 kB
  • 14 - Object Oriented Programming (OOP) Creating a Financial Analysis Class/003 The Financial Analysis Class live in action (Part 2)_en.srt 4.1 kB
  • 31 - Error Handling How to make your Trading Bot more stable and reliable/011 Implementation with Oanda V20 Connection Issues_en.srt 4.1 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/045 Changing Column Labels_en.srt 4.1 kB
  • 24 - Implementation and Automation with IBKR/002 Streaming Tick Data_en.srt 4.1 kB
  • 08 - API Trading with Python and Online Brokers- an Introduction/007 OANDA How to load Historical Price Data (Part 2)_en.srt 4.1 kB
  • 24 - Implementation and Automation with IBKR/003 Streaming Tick Data for multiple Symbols_en.srt 4.1 kB
  • 08 - API Trading with Python and Online Brokers- an Introduction/008 OANDA Streaming high-frequency real-time Data_en.srt 4.1 kB
  • 08 - API Trading with Python and Online Brokers- an Introduction/029 Troubleshooting FXCM Server Connection Issues.html 4.1 kB
  • 25 - Implementation and Automation with FXCM/003 Troubleshooting FXCM Server Connection Issues.html 4.1 kB
  • 19 - Trading Strategies powered by Machine Learning - Regression/007 A simple Linear Model to predict Financial Returns (Part 1)_en.srt 4.1 kB
  • 25 - Implementation and Automation with FXCM/012 Working with historical data and real-time tick data (Part 3)_en.srt 4.1 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/029 Zero-based Indexing and Negative Indexing_en.srt 4.1 kB
  • 05 - FOREX Day Trading with FXCM/008 Order Types at a glance_en.srt 4.1 kB
  • 05 - FOREX Day Trading with FXCM/005 Trade Analysis_en.srt 4.1 kB
  • 03 - Day Trading with OANDA A-Z a Deep Dive/014 Take-Profit and Stop-Loss Orders_en.srt 4.0 kB
  • 34 - Appendix 1 Python (& Finance) Basics/029 Integers_en.srt 4.0 kB
  • 14 - Object Oriented Programming (OOP) Creating a Financial Analysis Class/007 String representation and the special method __repr__()_en.srt 4.0 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/033 Selecting Rows with loc (label-based indexing)_en.srt 4.0 kB
  • 16 - Defining and Backtesting SMA Strategies/006 Creating the Class (Part 1)_en.srt 3.9 kB
  • 20 - Trading Strategies powered by Machine Learning - Classification/004 Predicting Market Direction with Logistic Regression_en.srt 3.9 kB
  • 17 - Defining and Backtesting simple MomentumContrarian Strategies/004 Defining a simple Contrarian Strategy_en.srt 3.9 kB
  • 26 - Cloud Deployment (AWS) Scheduling Trading Sessions Full Automation/008 How to run Python Scripts in a Windows Command Prompt_en.srt 3.9 kB
  • 08 - API Trading with Python and Online Brokers- an Introduction/013 IBKR Connecting to the API_en.srt 3.9 kB
  • 19 - Trading Strategies powered by Machine Learning - Regression/003 Making Predictions with Linear Regression_en.srt 3.9 kB
  • 04 - Stocks and FOREX Trading with Interactive Brokers (IBKR)/003 How to Install the IB Trader Workstation (TWS)_en.srt 3.9 kB
  • 34 - Appendix 1 Python (& Finance) Basics/018 Indexing Lists_en.srt 3.9 kB
  • 28 - Trading Hours, Spreads and Granularity - control and limit Trading Costs!/003 The best time to trade (Part 2)_en.srt 3.8 kB
  • 31 - Error Handling How to make your Trading Bot more stable and reliable/006 try, except, else_en.srt 3.8 kB
  • 07 - Excursus How to avoid and debug Coding Errors (don´t skip!)/001 Introduction_en.srt 3.8 kB
  • 28 - Trading Hours, Spreads and Granularity - control and limit Trading Costs!/002 The best time to trade (Part 1)_en.srt 3.8 kB
  • 24 - Implementation and Automation with IBKR/007 Improving Code Efficiency_en.srt 3.8 kB
  • 12 - Financial Data Analysis with Python and Pandas - a (deep) Introduction/026 Short Selling and Short Position Returns (Part 1)_en.srt 3.7 kB
  • 08 - API Trading with Python and Online Brokers- an Introduction/003 OANDA How to install the OANDA API Wrapper_en.srt 3.7 kB
  • 34 - Appendix 1 Python (& Finance) Basics/023 Calculate an Investment Project´s NPV_en.srt 3.7 kB
  • 20 - Trading Strategies powered by Machine Learning - Classification/006 Out-Sample Forward Testing_en.srt 3.7 kB
  • 25 - Implementation and Automation with FXCM/009 Storing and resampling real-time tick data (Part 3)_en.srt 3.6 kB
  • 30 - A Machine Learning-powered Strategy A-Z (DNN)/008 Feature ScalingEngineering_en.srt 3.6 kB
  • 20 - Trading Strategies powered by Machine Learning - Classification/003 Getting and Preparing the Data_en.srt 3.6 kB
  • 08 - API Trading with Python and Online Brokers- an Introduction/026 FXCM How to install the FXCM API Wrapper_en.srt 3.6 kB
  • 34 - Appendix 1 Python (& Finance) Basics/009 Excursus How to add inline comments_en.srt 3.6 kB
  • 14 - Object Oriented Programming (OOP) Creating a Financial Analysis Class/006 The method log_returns()_en.srt 3.6 kB
  • 24 - Implementation and Automation with IBKR/001 IBKR API - Recap_en.srt 3.6 kB
  • 14 - Object Oriented Programming (OOP) Creating a Financial Analysis Class/010 The method set_ticker()_en.srt 3.5 kB
  • 05 - FOREX Day Trading with FXCM/004 Example Trade Buying EURUSD_en.srt 3.5 kB
  • 17 - Defining and Backtesting simple MomentumContrarian Strategies/008 Trades and Trading Costs (Part 2)_en.srt 3.5 kB
  • 34 - Appendix 1 Python (& Finance) Basics/017 Zero-based Indexing and negative Indexing in Python (Theory)_en.srt 3.5 kB
  • 32 - Adding Stop Loss and Take Profit to the Trading Bot/001 Introduction_en.srt 3.5 kB
  • 08 - API Trading with Python and Online Brokers- an Introduction/027 FXCM Getting the Access Token & other Preparations_en.srt 3.4 kB
  • 35 - Appendix 2 User-defined Functions (required for OOP)/008 How to return many results_en.srt 3.4 kB
  • 23 - Implementation and Automation with OANDA (UPDATED!)/020 Implementing a Bollinger Bands Strategy (Solution)_en.srt 3.4 kB
  • 34 - Appendix 1 Python (& Finance) Basics/036 Changing Elements in Lists_en.srt 3.4 kB
  • 10 - +++ PART 2 Pandas for Financial Data Analysis and Introduction to OOP +++/001 Introduction and Downloads Part 2 Updated March 2023_en.srt 3.4 kB
  • 23 - Implementation and Automation with OANDA (UPDATED!)/002 Updating the Wrapper Package (Part 2)_en.srt 3.3 kB
  • 26 - Cloud Deployment (AWS) Scheduling Trading Sessions Full Automation/001 Introduction and Motivation_en.srt 3.3 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/004 Indexing and Slicing Numpy Arrays_en.srt 3.3 kB
  • 08 - API Trading with Python and Online Brokers- an Introduction/018 IBKR FOREX and CFD Contracts_en.srt 3.3 kB
  • 04 - Stocks and FOREX Trading with Interactive Brokers (IBKR)/012 CFD Trade Analysis_en.srt 3.3 kB
  • 08 - API Trading with Python and Online Brokers- an Introduction/012 IBKR How to download and install the API Wrapper & other Preparations_en.srt 3.3 kB
  • 07 - Excursus How to avoid and debug Coding Errors (don´t skip!)/008 Misuse of function names and keywords_en.srt 3.2 kB
  • 16 - Defining and Backtesting SMA Strategies/010 Creating the Class (Part 5)_en.srt 3.2 kB
  • 16 - Defining and Backtesting SMA Strategies/012 Creating the Class (Part 7)_en.srt 3.2 kB
  • 35 - Appendix 2 User-defined Functions (required for OOP)/001 Appendix2-Materials.zip 3.2 kB
  • 24 - Implementation and Automation with IBKR/012 Trading other Strategies - Coding Challenge_en.srt 3.2 kB
  • 31 - Error Handling How to make your Trading Bot more stable and reliable/003 try and except_en.srt 3.1 kB
  • 34 - Appendix 1 Python (& Finance) Basics/005 Calculate Present Values (PV) with Python Discounting_en.srt 3.1 kB
  • 30 - A Machine Learning-powered Strategy A-Z (DNN)/011 Saving Model and Parameters_en.srt 3.1 kB
  • 34 - Appendix 1 Python (& Finance) Basics/016 Intro to Python Lists_en.srt 3.1 kB
  • 29 - Working with two or many Strategies (Combination)/007 Combining both Strategies - Alternative 2_en.srt 3.0 kB
  • 29 - Working with two or many Strategies (Combination)/005 Taking into account busy Trading Hours_en.srt 3.0 kB
  • 21 - Advanced Backtesting Techniques/005 Creating an Iterative Base Class (Part 2)_en.srt 3.0 kB
  • 31 - Error Handling How to make your Trading Bot more stable and reliable/009 How to limit the number of retries_en.srt 3.0 kB
  • 17 - Defining and Backtesting simple MomentumContrarian Strategies/002 Getting the Data_en.srt 3.0 kB
  • 20 - Trading Strategies powered by Machine Learning - Classification/005 In-Sample Backtesting and the Look-ahead-bias_en.srt 2.9 kB
  • 23 - Implementation and Automation with OANDA (UPDATED!)/023 Importing a Trader Module Class_en.srt 2.9 kB
  • 29 - Working with two or many Strategies (Combination)/003 Strategy 2 Mean Reversion_en.srt 2.9 kB
  • 34 - Appendix 1 Python (& Finance) Basics/046 Booleans_en.srt 2.9 kB
  • 26 - Cloud Deployment (AWS) Scheduling Trading Sessions Full Automation/003 Amazon Web Services (AWS) - Overview and how to create a Free Trial Account_en.srt 2.9 kB
  • 31 - Error Handling How to make your Trading Bot more stable and reliable/017 Implementation with FXCM APIServer Issues_en.srt 2.9 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/028 Selecting one Column with the dot notation_en.srt 2.8 kB
  • 29 - Working with two or many Strategies (Combination)/002 Strategy 1 SMA_en.srt 2.8 kB
  • 21 - Advanced Backtesting Techniques/006 Creating an Iterative Base Class (Part 3)_en.srt 2.8 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/065 Introduction to GroupBy Operations_en.srt 2.8 kB
  • 30 - A Machine Learning-powered Strategy A-Z (DNN)/006 Adding lags_en.srt 2.7 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/053 Exporting DataFrames to csv_en.srt 2.7 kB
  • 12 - Financial Data Analysis with Python and Pandas - a (deep) Introduction/016 Log Returns_en.srt 2.7 kB
  • 01 - Getting Started/005 LEGAL DISCLAIMER (MUST READ!).html 2.6 kB
  • 05 - FOREX Day Trading with FXCM/007 Closing Positions vs. Hedging Positions_en.srt 2.6 kB
  • 29 - Working with two or many Strategies (Combination)/001 Introduction_en.srt 2.6 kB
  • 12 - Financial Data Analysis with Python and Pandas - a (deep) Introduction/002 Installing and importing required LibrariesPackages_en.srt 2.6 kB
  • 08 - API Trading with Python and Online Brokers- an Introduction/016 IBKR Data Streaming for Multiple Tickers_en.srt 2.5 kB
  • 34 - Appendix 1 Python (& Finance) Basics/010 Variables and Memory (Theory)_en.srt 2.5 kB
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/018 How to slice 2-dim Numpy Arrays (Part 2)_en.srt 2.5 kB
  • 28 - Trading Hours, Spreads and Granularity - control and limit Trading Costs!/006 Conclusions_en.srt 2.5 kB
  • 30 - A Machine Learning-powered Strategy A-Z (DNN)/007 Splitting into Train and Test Set_en.srt 2.4 kB
  • 32 - Adding Stop Loss and Take Profit to the Trading Bot/013 IBKR Contrader Class without Take Profit & Stop Loss (Recap)_en.srt 2.3 kB
  • 27 - +++ PART 5 Expert Tips & Tricks, Case Studies and more +++/001 Overview_en.srt 2.3 kB
  • 18 - Defining and Backtesting Mean-Reversion Strategies (Bollinger)/002 Getting the Data_en.srt 2.3 kB
  • 22 - +++ PART 4 Real-time Implementation and Automation of Strategies +++/001 Introduction and Overview_en.srt 2.3 kB
  • 25 - Implementation and Automation with FXCM/016 Trading other Strategies - Coding Challenge_en.srt 2.2 kB
  • 24 - Implementation and Automation with IBKR/005 How to create a live Candle Stick Chart_en.srt 2.2 kB
  • 02 - +++ PART 1 Day Trading, Online Brokers and APIs +++/001 Our very first Trade_en.srt 2.2 kB
  • 23 - Implementation and Automation with OANDA (UPDATED!)/018 Trading other Strategies - Coding Challenge_en.srt 2.1 kB
  • 06 - Installing Python and Jupyter Notebooks/001 Introduction_en.srt 2.1 kB
  • 28 - Trading Hours, Spreads and Granularity - control and limit Trading Costs!/004 Spreads during the busy hours_en.srt 2.1 kB
  • 34 - Appendix 1 Python (& Finance) Basics/027 Excursus Dynamic Typing in Python_en.srt 2.0 kB
  • 29 - Working with two or many Strategies (Combination)/006 Strategy Backtesting_en.srt 2.0 kB
  • 31 - Error Handling How to make your Trading Bot more stable and reliable/002 Python Errors (Exceptions)_en.srt 2.0 kB
  • 31 - Error Handling How to make your Trading Bot more stable and reliable/004 Catching specific Errors_en.srt 1.9 kB
  • 19 - Trading Strategies powered by Machine Learning - Regression/006 Getting the Data_en.srt 1.9 kB
  • 33 - +++ APPENDIX Python Crash Course +++/001 Overview_en.srt 1.9 kB
  • 32 - Adding Stop Loss and Take Profit to the Trading Bot/006 Oanda Contrader Class without Take Profit & Stop Loss (Recap)_en.srt 1.6 kB
  • 08 - API Trading with Python and Online Brokers- an Introduction/020 IBKR Creating Orders (CFD Trading)_en.srt 1.6 kB
  • 05 - FOREX Day Trading with FXCM/006 Charting_en.srt 1.5 kB
  • 07 - Excursus How to avoid and debug Coding Errors (don´t skip!)/003 Major reasons for Coding Errors_en.srt 1.5 kB
  • 08 - API Trading with Python and Online Brokers- an Introduction/027 FXCM-firststeps.zip 1.5 kB
  • 06 - Installing Python and Jupyter Notebooks/005 Tips for Python Beginners_en.srt 1.5 kB
  • 30 - A Machine Learning-powered Strategy A-Z (DNN)/004 Getting and Preparing the Data_en.srt 1.4 kB
  • 31 - Error Handling How to make your Trading Bot more stable and reliable/005 The Exception class_en.srt 1.4 kB
  • 08 - API Trading with Python and Online Brokers- an Introduction/001 Overview_en.srt 1.4 kB
  • 32 - Adding Stop Loss and Take Profit to the Trading Bot/003 Trailing Stop Loss Orders - Theory.html 1.2 kB
  • 03 - Day Trading with OANDA A-Z a Deep Dive/002 Creating a fully functional Demo Account - in all CountriesRegions!.html 1.2 kB
  • 08 - API Trading with Python and Online Brokers- an Introduction/004 Oanda-firststeps.zip 1.2 kB
  • 09 - Conclusion and Outlook/001 Conclusion and Outlook_en.srt 930 Bytes
  • 30 - A Machine Learning-powered Strategy A-Z (DNN)/012 Important Notices.html 816 Bytes
  • 30 - A Machine Learning-powered Strategy A-Z (DNN)/002 Installation of Tensorflow & Keras (Part 1).html 750 Bytes
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/035 Label-based Indexing Cheat Sheets.html 701 Bytes
  • 05 - FOREX Day Trading with FXCM/001 Important Info April 2023.html 652 Bytes
  • 08 - API Trading with Python and Online Brokers- an Introduction/024 FXCM Important Info April 2023.html 652 Bytes
  • 08 - API Trading with Python and Online Brokers- an Introduction/025 FXCM Commands to install required packages.html 626 Bytes
  • 12 - Financial Data Analysis with Python and Pandas - a (deep) Introduction/025 Coding Challenge #5.html 569 Bytes
  • 03 - Day Trading with OANDA A-Z a Deep Dive/016 Trading Challenge.html 563 Bytes
  • 23 - Implementation and Automation with OANDA (UPDATED!)/026 Outlook What is (still) missing.html 560 Bytes
  • 24 - Implementation and Automation with IBKR/014 Outlook What is (still) missing.html 560 Bytes
  • 23 - Implementation and Automation with OANDA (UPDATED!)/024 Excursus Printing all ticks in a Command PromptTerminal.html 533 Bytes
  • 25 - Implementation and Automation with FXCM/020 Excursus Printing all ticks in a Command PromptTerminal.html 533 Bytes
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  • 12 - Financial Data Analysis with Python and Pandas - a (deep) Introduction/034 Coding Challenge #7.html 444 Bytes
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  • 08 - API Trading with Python and Online Brokers- an Introduction/034 Trading Challenge.html 441 Bytes
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  • 08 - API Trading with Python and Online Brokers- an Introduction/011 IBKR API Downloads and required Commands to install the Wrapper.html 375 Bytes
  • 23 - Implementation and Automation with OANDA (UPDATED!)/003 Weekend and Bank Holiday Alert.html 375 Bytes
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  • 32 - Adding Stop Loss and Take Profit to the Trading Bot/017 IBKR Trading Bot Final Python Script.html 182 Bytes
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/026 Coding Exercise 9.html 157 Bytes
  • 36 - Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/037 Coding Exercise 10.html 157 Bytes
  • 34 - Appendix 1 Python (& Finance) Basics/054 Coding Exercise 5.html 156 Bytes
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  • 0. Websites you may like/[FreeCourseSite.com].url 127 Bytes
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  • 0. Websites you may like/[CourseClub.Me].url 122 Bytes
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  • 0. Websites you may like/[GigaCourse.Com].url 49 Bytes
  • 05 - FOREX Day Trading with FXCM/0. Websites you may like/[GigaCourse.Com].url 49 Bytes
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  • 23 - Implementation and Automation with OANDA (UPDATED!)/0. Websites you may like/[GigaCourse.Com].url 49 Bytes

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