Algorithmic Trading & Quantitative Analysis Using Python

Mayank Rasu, Experienced Quant Researcher

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69 Lessons (12h 22m)
    • 1. Course Introduction

      4:19
    • 2. What Is Covered in this Course?

      4:31
    • 3. Course Prerequisites

      1:57
    • 4. Is it For Me?

      1:39
    • 5. How To Get Help

      2:42
    • 6. Pandas Datareader - Introduction

      9:23
    • 7. Pandas Datareader - Deep Dive

      11:40
    • 8. Yahoofinancials Python Module - Intro

      11:45
    • 9. Yahoofinancials Python Module - Deep Dive

      21:16
    • 10. Intraday Data - Alphavantage Python Wrapper

      10:36
    • 11. Web Scraping Intro

      9:23
    • 12. Using Web Scraping to Extract Fundamental Data - I

      16:02
    • 13. Using Web Scraping to Extract Stock Fundamental Data - II

      23:43
    • 14. Updated Web-Scraping Code - Yahoo-Finance Webpage Changes

      12:35
    • 15. Data Handling

      11:24
    • 16. Basic Statistics - Familiarize Yourself With Your Data

      10:46
    • 17. Rolling Operations - Data In Motion

      15:01
    • 18. Visualization Basics - I

      10:18
    • 19. Visualization Basics - II

      13:51
    • 20. Technical Indicators - Intro

      9:11
    • 21. MACD Overview

      8:31
    • 22. MACD Implementation in Python

      11:10
    • 23. ATR and Bollinger Bands Overview

      6:08
    • 24. ATR and Bollinger Bands Implementation in Python

      14:00
    • 25. RSI Overview and Excel Implementation

      11:58
    • 26. RSI Implementation in Python

      11:27
    • 27. ADX Overview

      4:13
    • 28. ADX Implementation in Excel

      12:55
    • 29. ADX Implementation in Python

      13:40
    • 30. OBV Overview and Excel Implementation

      6:36
    • 31. OBV Implementation in Python

      3:07
    • 32. Slope in a Chart

      4:12
    • 33. Slope Implementation in Python

      23:03
    • 34. Renko Overview

      6:57
    • 35. Renko Implementation in Python

      14:27
    • 36. TA-Lib Introduction

      4:23
    • 37. TA-Lib Installation & Application

      17:53
    • 38. Introduction to Performance Measurement

      2:03
    • 39. CAGR Overview

      4:03
    • 40. CAGR Implementation in Python

      9:29
    • 41. How to Measure Volatility

      4:17
    • 42. Volatility Measures' Python Implementation

      2:27
    • 43. Sharpe Ratio and Sortino Ratio

      4:32
    • 44. Sharpe and Sortino in Python

      10:25
    • 45. Maximum Drawdown and Calmar Ratio

      3:58
    • 46. Maximum Drawdown and Calmar Ratio in Python

      11:10
    • 47. Why Should I Backtest My Strategies?

      6:53
    • 48. Strategy I - Portfolio Rebalancing

      7:03
    • 49. Strategy I in Python

      28:20
    • 50. Strategy II - Resistance Breakout

      8:27
    • 51. Strategy II in Python

      28:47
    • 52. Strategy III - Renko and OBV

      4:34
    • 53. Strategy III - Renko and OBV

      21:24
    • 54. Strategy IV - Renko and MACD

      5:19
    • 55. Strategy IV in Python

      12:54
    • 56. Value Investing Overview

      4:56
    • 57. Introduction to Magic Formula

      6:02
    • 58. Magic Formula Implementation in Python

      24:16
    • 59. Introduction to Piotroski F-Score

      7:20
    • 60. Piotroski F-Score Implementation in Python

      27:08
    • 61. Automated/Algorithmic Trading Overview

      13:48
    • 62. Using Time Module in Python

      12:44
    • 63. FXCM Overview

      7:01
    • 64. Introduction to FXCM Terminal

      12:34
    • 65. FXCM API

      22:06
    • 66. Building an Automated Trading System - part I

      8:08
    • 67. Building an Automated Trading System - part II

      11:14
    • 68. Building an Automated Trading System - part III

      11:23
    • 69. 7 9 Automated Trading Script 4

      10:50
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