Udemy - Technical Analysis with Python for Algorithmic Trading by Tyler Aaron

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Udemy - Technical Analysis with Python for Algorithmic Trading by Tyler Aaron (Size: 856.1 MB)
  1. Critical role python programming plays in algo trading.mp4 231.1 MB
  1. Critical role python programming plays in algo trading.srt 13.8 KB
  1. How does quantitative trading work.html 6.5 KB
  2. Benefits and strategies of algorithmic trading in python.mp4 214.5 MB
  2. Benefits and strategies of algorithmic trading in python.srt 13.7 KB
  2. Quantitative trading systems.html 5.8 KB
  3. Benefits of longterm vs short term capital gains.mp4 95.8 MB
  3. Benefits of longterm vs short term capital gains.srt 5.8 KB
  3. Quantitative trading strategies.html 7.6 KB
  4. Am I trader or investor.mp4 44.9 MB
  4. Am I trader or investor.srt 2.6 KB
  4. What is Quantitative Trading.html 2.1 KB
  5. Can an Individual run a Quantitative Trading Strategy.html 2.2 KB
  5. Pros and cons of mark to market accounting.mp4 87.9 MB
  5. Pros and cons of mark to market accounting.srt 5.1 KB
  6. Ten commandments of crypto security.mp4 181.9 MB
  6. Ten commandments of crypto security.srt 13.1 KB
  Bonus Resources.txt 307.2 B
  Get Bonus Downloads Here.url 204.8 B
  ▲ 19 total files

Description


Technical Analysis with Python for Algorithmic Trading by Tyler Aaron
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 16 lectures (1h 26m) | Size: 855.6 MB
Use Technical Analysis and Indicators for (Day) Trading. Create, backtest and optimize TA Trading Strategies with Python
What you'll learn:
Convert Technical Indictors into sound Trading Strategies with Python.
Make proper use of Technical Analysis and Technical Indicators.
Create and backtest combined Strategies with two or many Technical Indicators.
Visualize Technical Indicators and Trend/Support/Resistance Lines with Python and Plotly.
Exponential Moving Average (EMA) strategies
Relative Strength Index (RSI) strategies
Backtest and Forward Test Trading Strategies that are based on Technical Analysis/Indicators.
Create interactive Charts (Line, Volume, OHLC, etc.) with Python and Plotly.
Use Pandas, Numpy and Object Oriented Programming (OOP) for Technical Analysis and Trading.

Requirements
An internet connection capable of streaming HD videos.
A desktop computer (Windows, Mac, or Linux) capable of storing and running Anaconda. The course will walk you through installing the necessary free software.
Basic Coding Skills in Pandas, Numpy and Matplotlib

Description
This course clearly goes beyond rules, theories, vague forecasts, and nice-looking charts. (These are useful but traders need more than that.) This is the first 100% data-driven course on Technical Analysis. We´ll use rigorous Backtesting / Forward Testing to identify and optimize proper Trading Strategies that are based on Technical Analysis / Indicators.

This course will allow you to test and challenge your trading ideas and hypothesis. It provides Python Coding Frameworks and Templates that will enable you to code and test thousands of trading strategies within minutes. Identify the profitable strategies and scrap the unprofitable ones!

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