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GetFreeCourses.Co-Udemy-Algorithmic Stock Trading and Equity Investing with Python

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文件列表

  1. 3. Equity Markets and Stock TradingInvesting/5. Investing vs. Trading.mp4 137MB
  2. 5. Equity Analysis with Python (Part 1)/4. yfinance API - first steps.mp4 104MB
  3. 7. Equity Analysis with Python (Part 2)/5. Market Value vs. Book Value (Part 1).mp4 102MB
  4. 6. Excursus How to avoid and debug Coding Errors (don´t skip!)/11. How to traceback more complex Errors.mp4 97MB
  5. 11. Financial Data Analysis and Performance Evaluation/16. (Non-) Normality of Financial Returns.mp4 97MB
  6. 9. Introduction to Interactive Brokers (IKBR) and API Trading/18. Market Orders and Trades.mp4 89MB
  7. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/50. Customization of Plots.mp4 84MB
  8. 30. Appendix 5 Object Oriented Programming (OOP)/12. Inheritance.mp4 84MB
  9. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/30. Slicing Rows and Columns with loc (label-based indexing).mp4 81MB
  10. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/13. Coding Exercise 7.mp4 77MB
  11. 5. Equity Analysis with Python (Part 1)/10. Stock Splits.mp4 75MB
  12. 17. Equity Portfolio Optimization and Analysis/5. Portfolio Optimization.mp4 74MB
  13. 5. Equity Analysis with Python (Part 1)/9. What´s the Adjusted Close Price.mp4 74MB
  14. 3. Equity Markets and Stock TradingInvesting/1. Asset Classes - Overview.mp4 73MB
  15. 23. Stock trading with Technical Indicators - Backtesting/3. Defining an SMA Crossover Strategy.mp4 72MB
  16. 9. Introduction to Interactive Brokers (IKBR) and API Trading/9. Trading Costs - Commissions.mp4 72MB
  17. 15. ETF Investing and Index Replication Tracking/3. The S&P500 Index and its ETFs - Full Replication.mp4 72MB
  18. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/33. Analyzing Numerical Series with unique(), nunique() and value_counts().mp4 72MB
  19. 11. Financial Data Analysis and Performance Evaluation/14. Comparing the Performance of Financial Instruments.mp4 71MB
  20. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/55. Categorical Seaborn Plots.mp4 71MB
  21. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/27. Selecting Rows with iloc (position-based indexing).mp4 69MB
  22. 29. Appendix 4 Advanced Pandas Time Series Topics/2. Filling NA Values with bfill, ffill and interpolation.mp4 68MB
  23. 30. Appendix 5 Object Oriented Programming (OOP)/1. Introduction to OOP and examples for Classes.mp4 68MB
  24. 5. Equity Analysis with Python (Part 1)/13. Saving and Loading Data (Local Files).mp4 68MB
  25. 7. Equity Analysis with Python (Part 2)/3. Price vs. Value and Market Efficiency.mp4 67MB
  26. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/56. Seaborn Regression Plots.mp4 66MB
  27. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/21. Create your very first Pandas DataFrame (from csv).mp4 66MB
  28. 15. ETF Investing and Index Replication Tracking/7. Index Tracking with Optimization (Part 1).mp4 66MB
  29. 5. Equity Analysis with Python (Part 1)/8. Dividends.mp4 65MB
  30. 11. Financial Data Analysis and Performance Evaluation/19. Rolling Statistics.mp4 64MB
  31. 1. Getting started/1. Did you know... (a Sneak Preview on Stock Investing).mp4 63MB
  32. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/38. Changing Row Index with set_index() and reset_index().mp4 63MB
  33. 11. Financial Data Analysis and Performance Evaluation/9. Discrete Compounding.mp4 63MB
  34. 9. Introduction to Interactive Brokers (IKBR) and API Trading/16. Contracts (Advanced).mp4 63MB
  35. 22. Technical Analysis with Python - Introduction/3. Technical Analysis - Applications and Use Cases.mp4 62MB
  36. 7. Equity Analysis with Python (Part 2)/6. Market Value vs. Book Value (Part 2).mp4 61MB
  37. 4. Installing Python and Jupyter Notebooks/2. Download and Install Anaconda.mp4 61MB
  38. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/46. Handling NA Values missing Values.mp4 60MB
  39. 3. Equity Markets and Stock TradingInvesting/2. Equities vs. Fixed Income.mp4 60MB
  40. 11. Financial Data Analysis and Performance Evaluation/5. Price changes and Financial Returns.mp4 60MB
  41. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/23. First Data Inspection.mp4 60MB
  42. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/49. Visualization with Matplotlib (Intro).mp4 59MB
  43. 23. Stock trading with Technical Indicators - Backtesting/4. Vectorized Strategy Backtesting.mp4 59MB
  44. 22. Technical Analysis with Python - Introduction/8. Bar Size Granularity.mp4 59MB
  45. 6. Excursus How to avoid and debug Coding Errors (don´t skip!)/2. Test your debugging skills!.mp4 59MB
  46. 9. Introduction to Interactive Brokers (IKBR) and API Trading/20. Historical Data (Bars).mp4 58MB
  47. 30. Appendix 5 Object Oriented Programming (OOP)/13. Inheritance and the super() Function.mp4 58MB
  48. 26. Appendix 1 Python (& Finance) Basics/38. Coding Exercise 3.mp4 57MB
  49. 11. Financial Data Analysis and Performance Evaluation/27. Margin Trading and Levered Returns (Part 2).mp4 57MB
  50. 23. Stock trading with Technical Indicators - Backtesting/7. The Backtester Class.mp4 57MB
  51. 5. Equity Analysis with Python (Part 1)/7. Data Frequency.mp4 56MB
  52. 8. Keystone Project - Loading Data and Stock Analysis/5. Stock Analysis and Comparison.mp4 55MB
  53. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/44. Advanced Filtering with between(), isin() and ~.mp4 54MB
  54. 15. ETF Investing and Index Replication Tracking/5. The Russell 3000 Index and its ETFs - Representative Sampling.mp4 54MB
  55. 17. Equity Portfolio Optimization and Analysis/2. Creating Random Portfolios (Part 1).mp4 54MB
  56. 9. Introduction to Interactive Brokers (IKBR) and API Trading/5. The first Trades on TWS.mp4 54MB
  57. 30. Appendix 5 Object Oriented Programming (OOP)/14. Adding meaningful Docstrings.mp4 54MB
  58. 9. Introduction to Interactive Brokers (IKBR) and API Trading/10. Trading Costs - other (hidden) Costs.mp4 53MB
  59. 5. Equity Analysis with Python (Part 1)/6. Analysis Period.mp4 53MB
  60. 4. Installing Python and Jupyter Notebooks/4. How to work with Jupyter Notebooks.mp4 53MB
  61. 9. Introduction to Interactive Brokers (IKBR) and API Trading/14. How to get Market Data.mp4 53MB
  62. 11. Financial Data Analysis and Performance Evaluation/24. Covariance and Correlation.mp4 53MB
  63. 11. Financial Data Analysis and Performance Evaluation/18. Resampling Smoothing of Financial Data.mp4 52MB
  64. 5. Equity Analysis with Python (Part 1)/1. Yahoo Finance - Overview.mp4 52MB
  65. 14. How to build and analyze a Stock Index/1. Financial Indices - an Overview.mp4 52MB
  66. 17. Equity Portfolio Optimization and Analysis/8. The Efficient Frontier.mp4 51MB
  67. 8. Keystone Project - Loading Data and Stock Analysis/2. How to load the Dow Jones Constituents from the Web.mp4 51MB
  68. 4. Installing Python and Jupyter Notebooks/3. How to open Jupyter Notebooks.mp4 51MB
  69. 18. Portfolio Optimization Theory and practical Pitfalls/15. Introduction of a Risk-Free Asset.mp4 51MB
  70. 6. Excursus How to avoid and debug Coding Errors (don´t skip!)/5. Omitting cells, changing the sequence and more.mp4 50MB
  71. 26. Appendix 1 Python (& Finance) Basics/12. Coding Exercise 1.mp4 49MB
  72. 3. Equity Markets and Stock TradingInvesting/3. Equities - Categories and Sub Classes.mp4 49MB
  73. 5. Equity Analysis with Python (Part 1)/12. Multiple Tickers.mp4 49MB
  74. 15. ETF Investing and Index Replication Tracking/8. Index Tracking with Optimization (Part 2).mp4 49MB
  75. 9. Introduction to Interactive Brokers (IKBR) and API Trading/17. Coding Challenge Get Contracts for all DJIA Constituents.mp4 49MB
  76. 30. Appendix 5 Object Oriented Programming (OOP)/11. Adding more methods and performance metrics.mp4 49MB
  77. 18. Portfolio Optimization Theory and practical Pitfalls/13. Forward-looking Mean-Variance Optimization (MVO) Pitfalls (1).mp4 48MB
  78. 21. Trading Strategies - Overview/2. How to create your own Trading Strategies.mp4 48MB
  79. 11. Financial Data Analysis and Performance Evaluation/3. Normalizing Time Series to a Base Value (100).mp4 47MB
  80. 11. Financial Data Analysis and Performance Evaluation/7. Investment Multiple and CAGR.mp4 47MB
  81. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/48. Summary Statistics and Accumulations.mp4 47MB
  82. 15. ETF Investing and Index Replication Tracking/6. ETF Investing with IBKR.mp4 47MB
  83. 9. Introduction to Interactive Brokers (IKBR) and API Trading/6. Trading Hours.mp4 47MB
  84. 13. PART 2 ETF Trading & Equity Portfolio Investing with Python and IBKR/2. Investment Strategies, Indices, Portfolios & Benchmarks.mp4 46MB
  85. 30. Appendix 5 Object Oriented Programming (OOP)/5. The method get_data().mp4 46MB
  86. 14. How to build and analyze a Stock Index/4. Building the Dow Jones Industrial Average Index from scratch.mp4 46MB
  87. 11. Financial Data Analysis and Performance Evaluation/4. Coding Challenge #1.mp4 46MB
  88. 11. Financial Data Analysis and Performance Evaluation/21. Introduction to Currencies (Forex) and Trading.mp4 46MB
  89. 22. Technical Analysis with Python - Introduction/1. Technical Analysis vs Fundamental Analysis.mp4 45MB
  90. 26. Appendix 1 Python (& Finance) Basics/46. Coding Exercise 4.mp4 45MB
  91. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/41. Filtering DataFrames (one Condition).mp4 45MB
  92. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/31. Summary, Best Practices and Outlook.mp4 45MB
  93. 5. Equity Analysis with Python (Part 1)/11. Stocks from other Countries Exchanges.mp4 44MB
  94. 7. Equity Analysis with Python (Part 2)/8. Market Value vs. Book Value (Part 3).mp4 44MB
  95. 7. Equity Analysis with Python (Part 2)/9. How to load Financial Statements.mp4 44MB
  96. 26. Appendix 1 Python (& Finance) Basics/41. Intro to Strings.mp4 43MB
  97. 23. Stock trading with Technical Indicators - Backtesting/5. Strategy Optimization.mp4 43MB
  98. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/22. Pandas Display Options and the methods head() & tail().mp4 43MB
  99. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/61. Splitting with many Keys.mp4 42MB
  100. 11. Financial Data Analysis and Performance Evaluation/13. Simple Returns vs Log Returns ( Part 2).mp4 42MB
  101. 18. Portfolio Optimization Theory and practical Pitfalls/7. Crash Course Statistics Covariance and Correlation (Part 1).mp4 42MB
  102. 8. Keystone Project - Loading Data and Stock Analysis/7. Hot Topic How to load all exchange tickers (Indian Stock Market).mp4 42MB
  103. 15. ETF Investing and Index Replication Tracking/2. Index Replication Tracking - Intro.mp4 42MB
  104. 26. Appendix 1 Python (& Finance) Basics/48. Keywords pass, continue and break.mp4 42MB
  105. 15. ETF Investing and Index Replication Tracking/10. Index Tracking with Optimization (Part 4).mp4 42MB
  106. 26. Appendix 1 Python (& Finance) Basics/47. Conditional Statements.mp4 41MB
  107. 26. Appendix 1 Python (& Finance) Basics/35. Adding and removing Elements fromto Lists.mp4 41MB
  108. 11. Financial Data Analysis and Performance Evaluation/10. Continuous Compounding.mp4 41MB
  109. 15. ETF Investing and Index Replication Tracking/1. Why ETF Investing.mp4 41MB
  110. 14. How to build and analyze a Stock Index/8. Creating a Market Value-Weighted Stock Index with Python (Part 1).mp4 41MB
  111. 8. Keystone Project - Loading Data and Stock Analysis/3. Historical Prices (Time-Series Data).mp4 41MB
  112. 26. Appendix 1 Python (& Finance) Basics/22. Coding Exercise 2.mp4 41MB
  113. 7. Equity Analysis with Python (Part 2)/7. Liquidation Value.mp4 40MB
  114. 18. Portfolio Optimization Theory and practical Pitfalls/10. Correlation and the Portfolio Diversification Effect.mp4 40MB
  115. 15. ETF Investing and Index Replication Tracking/12. Index Tracking with Optimization (Part 6).mp4 40MB
  116. 9. Introduction to Interactive Brokers (IKBR) and API Trading/4. TWS - First Steps.mp4 40MB
  117. 9. Introduction to Interactive Brokers (IKBR) and API Trading/1. Welcome to IKBR.mp4 40MB
  118. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/62. split-apply-combine.mp4 40MB
  119. 23. Stock trading with Technical Indicators - Backtesting/6. Transaction & Trading Costs (Part 1).mp4 40MB
  120. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/12. Creating Numpy Arrays from Scratch.mp4 40MB
  121. 30. Appendix 5 Object Oriented Programming (OOP)/16. Coding Exercise Create your own Class.mp4 40MB
  122. 6. Excursus How to avoid and debug Coding Errors (don´t skip!)/10. Getting help on StackOverflow.com.mp4 40MB
  123. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/60. Understanding the GroupBy Object.mp4 39MB
  124. 7. Equity Analysis with Python (Part 2)/2. Price, Shares Outstanding & Market Capitalization.mp4 39MB
  125. 11. Financial Data Analysis and Performance Evaluation/2. Initial Data Inspection and Visualization.mp4 39MB
  126. 27. Appendix 2 User-defined Functions/2. What´s the difference between Positional Arguments vs. Keyword Arguments.mp4 39MB
  127. 29. Appendix 4 Advanced Pandas Time Series Topics/4. Timezones and Converting (Part 2).mp4 39MB
  128. 9. Introduction to Interactive Brokers (IKBR) and API Trading/19. Positions and Account Values.mp4 38MB
  129. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/2. Numpy Arrays.mp4 38MB
  130. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/45. Intro to NA Values missing Values.mp4 38MB
  131. 26. Appendix 1 Python (& Finance) Basics/50. Introduction to while loops.mp4 38MB
  132. 26. Appendix 1 Python (& Finance) Basics/45. Comparison, Logical and Membership Operators in Action.mp4 38MB
  133. 27. Appendix 2 User-defined Functions/8. Scope - easily explained.mp4 38MB
  134. 1. Getting started/2. How to get the best out of this course.mp4 37MB
  135. 30. Appendix 5 Object Oriented Programming (OOP)/4. The special method __init__().mp4 37MB
  136. 9. Introduction to Interactive Brokers (IKBR) and API Trading/13. Contracts (Introduction).mp4 37MB
  137. 29. Appendix 4 Advanced Pandas Time Series Topics/1. Helpful DatetimeIndex Attributes and Methods.mp4 37MB
  138. 11. Financial Data Analysis and Performance Evaluation/12. Simple Returns vs Log Returns ( Part 1).mp4 37MB
  139. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/37. First Steps with Pandas Index Objects.mp4 37MB
  140. 7. Equity Analysis with Python (Part 2)/1. Getting more Information on Stocks - the Ticker Object.mp4 37MB
  141. 15. ETF Investing and Index Replication Tracking/13. Optimization and out-sample Testing (Part 1).mp4 37MB
  142. 18. Portfolio Optimization Theory and practical Pitfalls/4. Portfolio Return (2-Asset-Case).mp4 37MB
  143. 30. Appendix 5 Object Oriented Programming (OOP)/8. The methods plot_prices() and plot_returns().mp4 37MB
  144. 26. Appendix 1 Python (& Finance) Basics/36. Mutable vs. immutable Objects (Part 1).mp4 36MB
  145. 14. How to build and analyze a Stock Index/7. Market Value-Weighted Index - Theory.mp4 36MB
  146. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/34. Analyzing non-numerical Series with unique(), nunique(), value_counts().mp4 36MB
  147. 26. Appendix 1 Python (& Finance) Basics/19. Calculate FV and PV for many Cashflows.mp4 36MB
  148. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/57. Seaborn Heatmaps.mp4 36MB
  149. 6. Excursus How to avoid and debug Coding Errors (don´t skip!)/4. The most commonly made Errors at a glance.mp4 36MB
  150. 22. Technical Analysis with Python - Introduction/6. How to customize Plotly Charts.mp4 35MB
  151. 26. Appendix 1 Python (& Finance) Basics/20. The Net Present Value - NPV (Theory).mp4 35MB
  152. 18. Portfolio Optimization Theory and practical Pitfalls/12. Forward-looking Optimization.mp4 35MB
  153. 22. Technical Analysis with Python - Introduction/7. Candlestick and OHLC Bar Charts.mp4 35MB
  154. 15. ETF Investing and Index Replication Tracking/4. Active Return and Active Risk (Tracking Error).mp4 35MB
  155. 19. Reverse Optimization and the Black-Litterman model/1. Introduction and Motivation.mp4 34MB
  156. 18. Portfolio Optimization Theory and practical Pitfalls/14. Forward-looking Mean-Variance Optimization (MVO) Pitfalls (2).mp4 34MB
  157. 14. How to build and analyze a Stock Index/9. Creating a Market Value-Weighted Stock Index with Python (Part 2).mp4 34MB
  158. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/1. Modules, Packages and Libraries - No need to reinvent the Wheel.mp4 34MB
  159. 6. Excursus How to avoid and debug Coding Errors (don´t skip!)/12. Problems with the Python Installation.mp4 34MB
  160. 19. Reverse Optimization and the Black-Litterman model/4. Black-Litterman Step 2 Incorporating Investor Opinions.mp4 33MB
  161. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/36. Sorting of Series and Introduction to the inplace - parameter.mp4 33MB
  162. 26. Appendix 1 Python (& Finance) Basics/40. Dictionaries.mp4 33MB
  163. 11. Financial Data Analysis and Performance Evaluation/6. Reward and Risk of Financial Instruments.mp4 33MB
  164. 22. Technical Analysis with Python - Introduction/2. Technical Analysis and the Efficient Market Hypothesis.mp4 33MB
  165. 11. Financial Data Analysis and Performance Evaluation/8. Compound Returns & Geometric Mean Return.mp4 32MB
  166. 1. Getting started/3. Course Overview.mp4 32MB
  167. 26. Appendix 1 Python (& Finance) Basics/17. For Loops - Iterating over Lists.mp4 32MB
  168. 8. Keystone Project - Loading Data and Stock Analysis/4. Cross-Sectional Data.mp4 32MB
  169. 26. Appendix 1 Python (& Finance) Basics/39. Tuples.mp4 32MB
  170. 29. Appendix 4 Advanced Pandas Time Series Topics/3. Timezones and Converting (Part 1).mp4 32MB
  171. 14. How to build and analyze a Stock Index/11. Comparison of weighting methods (Part 2).mp4 32MB
  172. 3. Equity Markets and Stock TradingInvesting/4. Top-Down vs. Bottom-Up.mp4 31MB
  173. 18. Portfolio Optimization Theory and practical Pitfalls/11. Multiple Asset Case.mp4 31MB
  174. 11. Financial Data Analysis and Performance Evaluation/1. Introduction and Overview.mp4 31MB
  175. 22. Technical Analysis with Python - Introduction/12. Support and Resistance Lines.mp4 31MB
  176. 6. Excursus How to avoid and debug Coding Errors (don´t skip!)/6. IndexErrors.mp4 31MB
  177. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/16. How to slice 2-dim Numpy Arrays (Part 1).mp4 31MB
  178. 11. Financial Data Analysis and Performance Evaluation/26. Margin Trading and Levered Returns (Part 1).mp4 31MB
  179. 11. Financial Data Analysis and Performance Evaluation/23. Short Selling and Short Position Returns (Part 3).mp4 31MB
  180. 21. Trading Strategies - Overview/1. Trading Strategies - Overview.mp4 31MB
  181. 23. Stock trading with Technical Indicators - Backtesting/2. A simple Buy and Hold Strategy.mp4 30MB
  182. 27. Appendix 2 User-defined Functions/3. How to work with Default Arguments.mp4 30MB
  183. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/10. Advanced Filtering & Bitwise Operators.mp4 30MB
  184. 8. Keystone Project - Loading Data and Stock Analysis/1. Project - Introduction.mp4 30MB
  185. 11. Financial Data Analysis and Performance Evaluation/17. Annualizing Return and Risk.mp4 30MB
  186. 18. Portfolio Optimization Theory and practical Pitfalls/9. Portfolio Risk (2-Asset-Case).mp4 30MB
  187. 14. How to build and analyze a Stock Index/3. Price-Weighted Index - Theory.mp4 30MB
  188. 5. Equity Analysis with Python (Part 1)/14. Coding Challenge.mp4 30MB
  189. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/58. Removing Columns.mp4 30MB
  190. 15. ETF Investing and Index Replication Tracking/11. Index Tracking with Optimization (Part 5).mp4 30MB
  191. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/40. Renaming Index & Column Labels with rename().mp4 30MB
  192. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/53. Scatterplots.mp4 29MB
  193. 18. Portfolio Optimization Theory and practical Pitfalls/5. Portfolio Risk (2-Asset-Case) - a (too) simple solution.mp4 29MB
  194. 27. Appendix 2 User-defined Functions/1. Defining your first user-defined Function.mp4 29MB
  195. 11. Financial Data Analysis and Performance Evaluation/22. Short Selling and Short Position Returns (Part 2).mp4 29MB
  196. 30. Appendix 5 Object Oriented Programming (OOP)/2. The Financial Analysis Class live in action (Part 1).mp4 29MB
  197. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/52. Histogramms (Part 2).mp4 29MB
  198. 7. Equity Analysis with Python (Part 2)/4. Equity Value, Firm Value and Financial Distress.mp4 29MB
  199. 15. ETF Investing and Index Replication Tracking/14. Optimization and out-sample Testing (Part 2).mp4 29MB
  200. 9. Introduction to Interactive Brokers (IKBR) and API Trading/7. Cash Account vs. Margin Account.mp4 29MB
  201. 27. Appendix 2 User-defined Functions/4. The Default Argument None.mp4 29MB
  202. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/24. Selecting Columns.mp4 28MB
  203. 27. Appendix 2 User-defined Functions/6. Sequences as arguments and args.mp4 28MB
  204. 14. How to build and analyze a Stock Index/12. Price Index vs. PerformanceTotal Return Index.mp4 28MB
  205. 19. Reverse Optimization and the Black-Litterman model/3. Black-Litterman Step 1 Reverse Optimization.mp4 27MB
  206. 30. Appendix 5 Object Oriented Programming (OOP)/10. The method set_ticker().mp4 27MB
  207. 26. Appendix 1 Python (& Finance) Basics/26. Build-in Functions.mp4 27MB
  208. 17. Equity Portfolio Optimization and Analysis/4. Performance Measurement The Risk-adjusted Return.mp4 27MB
  209. 9. Introduction to Interactive Brokers (IKBR) and API Trading/2. How to create a Paper Trading Account.mp4 26MB
  210. 8. Keystone Project - Loading Data and Stock Analysis/6. Hot Topic How to get complete Lists with Stock Tickers.mp4 26MB
  211. 6. Excursus How to avoid and debug Coding Errors (don´t skip!)/15. Summary and Debugging Flow-Chart.mp4 26MB
  212. 26. Appendix 1 Python (& Finance) Basics/30. More on Lists.mp4 26MB
  213. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/5. Changing Elements in Numpy Arrays & Mutability.mp4 26MB
  214. 26. Appendix 1 Python (& Finance) Basics/28. Floats.mp4 26MB
  215. 26. Appendix 1 Python (& Finance) Basics/23. Data Types in Action.mp4 26MB
  216. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/28. Slicing Rows and Columns with iloc (position-based indexing).mp4 26MB
  217. 17. Equity Portfolio Optimization and Analysis/9. Portfolio Optimization with frequent Rebalancing.mp4 26MB
  218. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/43. Filtering DataFrames by many Conditions (OR).mp4 26MB
  219. 30. Appendix 5 Object Oriented Programming (OOP)/9. Encapsulation and protected Attributes.mp4 26MB
  220. 22. Technical Analysis with Python - Introduction/10. Technical Indicators - Overview and Examples.mp4 26MB
  221. 22. Technical Analysis with Python - Introduction/5. Charting - Interactive Line Charts with Cufflinks and Plotly.mp4 25MB
  222. 25. APPENDIX Python Crash Course/1. Introduction and Overview.mp4 25MB
  223. 11. Financial Data Analysis and Performance Evaluation/25. Portfolios and Portfolio Returns.mp4 25MB
  224. 9. Introduction to Interactive Brokers (IKBR) and API Trading/11. How to download and install the API Wrapper & other Preparations.mp4 25MB
  225. 30. Appendix 5 Object Oriented Programming (OOP)/6. The method log_returns().mp4 25MB
  226. 17. Equity Portfolio Optimization and Analysis/10. Comparison daily Rebalancing vs. no Rebalancing.mp4 25MB
  227. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/11. Determining a Project´s Payback Period with np.where().mp4 24MB
  228. 5. Equity Analysis with Python (Part 1)/2. How to open and work with the Course Notebooks.mp4 24MB
  229. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/19. How to perform row-wise and column-wise Operations.mp4 24MB
  230. 2. PART 1 Basics and Prerequisites/1. Introduction and Overview PART 1.mp4 24MB
  231. 30. Appendix 5 Object Oriented Programming (OOP)/7. String representation and the special method __repr__().mp4 24MB
  232. 22. Technical Analysis with Python - Introduction/11. Trend Lines.mp4 24MB
  233. 26. Appendix 1 Python (& Finance) Basics/9. More on Variables and Memory.mp4 24MB
  234. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/7. Numpy Array Methods and Attributes.mp4 24MB
  235. 26. Appendix 1 Python (& Finance) Basics/49. Calculate a Project´s Payback Period.mp4 23MB
  236. 9. Introduction to Interactive Brokers (IKBR) and API Trading/3. How to Install the IB Trader Workstation (TWS).mp4 23MB
  237. 26. Appendix 1 Python (& Finance) Basics/37. Mutable vs. immutable Objects (Part 2).mp4 23MB
  238. 18. Portfolio Optimization Theory and practical Pitfalls/17. Portfolio Optimization with Risk-free Asset (Part 1).mp4 23MB
  239. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/29. Selecting Rows with loc (label-based indexing).mp4 23MB
  240. 18. Portfolio Optimization Theory and practical Pitfalls/2. Getting Started.mp4 23MB
  241. 26. Appendix 1 Python (& Finance) Basics/29. How to round Floats (and Integers) with round().mp4 22MB
  242. 17. Equity Portfolio Optimization and Analysis/3. Creating Random Portfolios (Part 2).mp4 22MB
  243. 30. Appendix 5 Object Oriented Programming (OOP)/15. Creating and Importing Python Modules (.py).mp4 22MB
  244. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/35. The copy() method.mp4 22MB
  245. 9. Introduction to Interactive Brokers (IKBR) and API Trading/12. Connecting to the API.mp4 22MB
  246. 15. ETF Investing and Index Replication Tracking/9. Index Tracking with Optimization (Part 3).mp4 22MB
  247. 14. How to build and analyze a Stock Index/5. Equal-Weighted Index - Theory.mp4 22MB
  248. 26. Appendix 1 Python (& Finance) Basics/32. Slicing Lists.mp4 22MB
  249. 22. Technical Analysis with Python - Introduction/9. Volume Charts.mp4 22MB
  250. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/42. Filtering DataFrames by many Conditions (AND).mp4 21MB
  251. 30. Appendix 5 Object Oriented Programming (OOP)/3. The Financial Analysis Class live in action (Part 2).mp4 21MB
  252. 11. Financial Data Analysis and Performance Evaluation/15. Price Return vs. Total Return (Stocks).mp4 21MB
  253. 9. Introduction to Interactive Brokers (IKBR) and API Trading/8. Fractional Trading.mp4 21MB
  254. 26. Appendix 1 Python (& Finance) Basics/5. Calculate Interest Rates and Returns with Python.mp4 20MB
  255. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/51. Histogramms (Part 1).mp4 20MB
  256. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/6. View vs. copy - potential Pitfalls when slicing Numpy Arrays.mp4 20MB
  257. 11. Financial Data Analysis and Performance Evaluation/20. Short Selling and Short Position Returns (Part 1).mp4 20MB
  258. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/32. First Steps with Pandas Series.mp4 20MB
  259. 14. How to build and analyze a Stock Index/2. Getting started.mp4 20MB
  260. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/4. Vectorized Operations with Numpy Arrays.mp4 20MB
  261. 27. Appendix 2 User-defined Functions/5. How to unpack Iterables.mp4 20MB
  262. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/14. How to work with nested Lists.mp4 20MB
  263. 26. Appendix 1 Python (& Finance) Basics/6. Introduction to Variables.mp4 19MB
  264. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/9. Boolean Arrays and Conditional Filtering.mp4 19MB
  265. 17. Equity Portfolio Optimization and Analysis/6. Minimum Variance Portfolio.mp4 19MB
  266. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/8. Numpy Universal Functions.mp4 19MB
  267. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/20. Intro to Tabular Data Pandas.mp4 19MB
  268. 26. Appendix 1 Python (& Finance) Basics/31. Lists and Element-wise Operations.mp4 19MB
  269. 26. Appendix 1 Python (& Finance) Basics/42. String Replacement.mp4 19MB
  270. 26. Appendix 1 Python (& Finance) Basics/11. The print() Function.mp4 19MB
  271. 26. Appendix 1 Python (& Finance) Basics/18. The range Object - another Iterable.mp4 18MB
  272. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/54. First Steps with Seaborn.mp4 18MB
  273. 26. Appendix 1 Python (& Finance) Basics/10. Variables - Dos, Don´ts and Conventions.mp4 18MB
  274. 18. Portfolio Optimization Theory and practical Pitfalls/19. Implications and the Two-Fund-Theorem.mp4 18MB
  275. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/39. Changing Column Labels.mp4 18MB
  276. 17. Equity Portfolio Optimization and Analysis/1. Getting Started.mp4 18MB
  277. 22. Technical Analysis with Python - Introduction/4. Getting started and simple Price Charts.mp4 18MB
  278. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/18. Recap Changing Elements in a Numpy Array slice.mp4 18MB
  279. 17. Equity Portfolio Optimization and Analysis/7. Maximum Return Portfolio.mp4 18MB
  280. 6. Excursus How to avoid and debug Coding Errors (don´t skip!)/13. External Factors and Issues.mp4 17MB
  281. 26. Appendix 1 Python (& Finance) Basics/1. Intro to the Time Value of Money (TVM) Concept (Theory).mp4 17MB
  282. 6. Excursus How to avoid and debug Coding Errors (don´t skip!)/1. Introduction.mp4 17MB
  283. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/15. 2-dimensional Numpy Arrays.mp4 17MB
  284. 18. Portfolio Optimization Theory and practical Pitfalls/18. Portfolio Optimization with Risk-free Asset (Part 2).mp4 17MB
  285. 6. Excursus How to avoid and debug Coding Errors (don´t skip!)/9. TypeErrors and ValueErrors.mp4 17MB
  286. 6. Excursus How to avoid and debug Coding Errors (don´t skip!)/14. Errors related to the course content (Transcription Errors).mp4 16MB
  287. 9. Introduction to Interactive Brokers (IKBR) and API Trading/15. Data Streaming for Mulitple Tickers.mp4 16MB
  288. 23. Stock trading with Technical Indicators - Backtesting/1. Getting started.mp4 16MB
  289. 26. Appendix 1 Python (& Finance) Basics/21. Calculate an Investment Project´s NPV.mp4 15MB
  290. 11. Financial Data Analysis and Performance Evaluation/11. Log Returns.mp4 15MB
  291. 26. Appendix 1 Python (& Finance) Basics/4. Interest Rates and Returns (Theory).mp4 15MB
  292. 26. Appendix 1 Python (& Finance) Basics/16. Indexing Lists.mp4 15MB
  293. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/3. Indexing and Slicing Numpy Arrays.mp4 15MB
  294. 23. Stock trading with Technical Indicators - Backtesting/8. Backtesting a Long-Only Strategy.mp4 14MB
  295. 27. Appendix 2 User-defined Functions/7. How to return many results.mp4 14MB
  296. 26. Appendix 1 Python (& Finance) Basics/34. Sorting and Reversing Lists.mp4 14MB
  297. 18. Portfolio Optimization Theory and practical Pitfalls/8. Crash Course Statistics Covariance and Correlation (Part 2).mp4 14MB
  298. 26. Appendix 1 Python (& Finance) Basics/2. Calculate Future Values (FV) with Python Compounding.mp4 14MB
  299. 13. PART 2 ETF Trading & Equity Portfolio Investing with Python and IBKR/1. Introduction and Overview PART 2.mp4 13MB
  300. 14. How to build and analyze a Stock Index/10. Comparison of weighting methods (Part 1).mp4 13MB
  301. 6. Excursus How to avoid and debug Coding Errors (don´t skip!)/8. Misuse of function names and keywords.mp4 12MB
  302. 26. Appendix 1 Python (& Finance) Basics/44. Operators (Theory).mp4 12MB
  303. 5. Equity Analysis with Python (Part 1)/5. Excursus Versions and Package Updates.mp4 12MB
  304. 6. Excursus How to avoid and debug Coding Errors (don´t skip!)/7. Indentation Errors.mp4 12MB
  305. 14. How to build and analyze a Stock Index/6. Creating an Equal-Weighted Stock Index with Python.mp4 12MB
  306. 5. Equity Analysis with Python (Part 1)/3. How to Install yfinance.mp4 12MB
  307. 26. Appendix 1 Python (& Finance) Basics/7. Excursus How to add inline comments.mp4 12MB
  308. 4. Installing Python and Jupyter Notebooks/5. Tips for python beginners.mp4 12MB
  309. 18. Portfolio Optimization Theory and practical Pitfalls/16. The Sharpe Ratio Graphical Interpretation.mp4 12MB
  310. 26. Appendix 1 Python (& Finance) Basics/27. Integers.mp4 12MB
  311. 26. Appendix 1 Python (& Finance) Basics/24. The Data Type Hierarchy (Theory).mp4 11MB
  312. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/47. Exporting DataFrames to csv.mp4 11MB
  313. 19. Reverse Optimization and the Black-Litterman model/2. Getting started (Inputs for reverse Optimization).mp4 11MB
  314. 26. Appendix 1 Python (& Finance) Basics/13. TVM Problems with many Cashflows.mp4 11MB
  315. 26. Appendix 1 Python (& Finance) Basics/33. Changing Elements in Lists.mp4 11MB
  316. 26. Appendix 1 Python (& Finance) Basics/3. Calculate Present Values (PV) with Python Discounting.mp4 11MB
  317. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/26. Zero-based Indexing and Negative Indexing.mp4 11MB
  318. 20. PART 3 Algorithmic Stock Trading with Python and IKBR/1. Introduction and Overview PART 3.mp4 10MB
  319. 18. Portfolio Optimization Theory and practical Pitfalls/1. Introduction.mp4 10MB
  320. 26. Appendix 1 Python (& Finance) Basics/43. Booleans.mp4 9MB
  321. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/17. How to slice 2-dim Numpy Arrays (Part 2).mp4 9MB
  322. 18. Portfolio Optimization Theory and practical Pitfalls/6. Crash Course Statistics Variance and Standard Deviation.mp4 9MB
  323. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/25. Selecting one Column with the dot notation.mp4 9MB
  324. 4. Installing Python and Jupyter Notebooks/1. Introduction.mp4 9MB
  325. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/59. Introduction to GroupBy Operations.mp4 9MB
  326. 26. Appendix 1 Python (& Finance) Basics/14. Intro to Python Lists.mp4 8MB
  327. 26. Appendix 1 Python (& Finance) Basics/15. Zero-based Indexing and negative Indexing in Python (Theory).mp4 8MB
  328. 18. Portfolio Optimization Theory and practical Pitfalls/3. 2-Asset-Case (Intro).mp4 7MB
  329. 26. Appendix 1 Python (& Finance) Basics/8. Variables and Memory (Theory).mp4 6MB
  330. 26. Appendix 1 Python (& Finance) Basics/25. Excursus Dynamic Typing in Python.mp4 6MB
  331. 6. Excursus How to avoid and debug Coding Errors (don´t skip!)/3. Major reasons for Coding Errors.mp4 5MB
  332. 14. How to build and analyze a Stock Index/How you can help GetFreeCourses.Co.txt 182B
  333. 23. Stock trading with Technical Indicators - Backtesting/How you can help GetFreeCourses.Co.txt 182B
  334. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/How you can help GetFreeCourses.Co.txt 182B
  335. 6. Excursus How to avoid and debug Coding Errors (don´t skip!)/How you can help GetFreeCourses.Co.txt 182B
  336. How you can help GetFreeCourses.Co.txt 182B
  337. 14. How to build and analyze a Stock Index/GetFreeCourses.Co.url 116B
  338. 23. Stock trading with Technical Indicators - Backtesting/GetFreeCourses.Co.url 116B
  339. 28. Appendix 3 Numpy, Pandas, Matplotlib and Seaborn Crash Course/GetFreeCourses.Co.url 116B
  340. 6. Excursus How to avoid and debug Coding Errors (don´t skip!)/GetFreeCourses.Co.url 116B
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