Published 12/2022Created by Alexander HagmannMP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 ChGenre: eLearning | Language: English | Duration: 370 Lectures ( 31h 8m ) | Size: 11.6 GB
Algorithmic Stock Trading with Python and the Interactive Brokers (IBKR) API Automated ETF & Equity Portfolio Investing Equity Portfolio Optimization, Management & Rebalancing Backtesting and Implementation of Trading & Investment Strats Technical Analysis and Indicators Stock Indices and Index Tracking / Replication How to measure and improve the Performance of your Equity Portfolio Loading and analysing Stock Data from (free) Web Sources API Trading with Interactive Brokers Python Basics & Numpy, Pandas, Matplotlib Truly Data-driven Trading and Investing Black-Litterman Model No Python experience needed. This course provides a Python Crash Course. No Finance/Investment knowledge required. You will learn everything you need to know. A desktop computer (Windows, Mac, or Linux) capable of storing and running Anaconda. The course will walk you through installing the necessary free software. An internet connection capable of streaming HD videos. Some high school level math skills would be great (not mandatory, but it helps). Welcome to the most comprehensive and complete course on (automated) Stock Trading and Equity Investing!This course coversAutomated Stock Trading for Income Generation (Algo Trading, Day Trading & more)Automated Equity Portfolio Investing for long-term wealth accumulation (Portfolio Optimization, Management & Rebalancing incl. ETF)with Python and Interactive Brokers (IBKR) It is the only Stock Trading/Investing course that covers all four aspects required for long-term success:Theory (Finance & Investing 101): What you really need to know before you trade/invest stocksdata: Successful Investment and Trading Strats are data-driven. API Trading with Interactive Brokers: Automated Real Trading & Paper Trading with low Spreads and CommissionsPython: The right tool that integrates Theory, Data, and API Trading. This course covers everything you need to know in a Python Crash Course (Appendix).Some Highlights:Load and analyze Data (historical prices, financial statements, ratios, valuation multiples) for thousands of stocks Trade stocks on various exchanges and from various world regions (United States, Europe, India, Australia, etc.)Use Fundamental Analysis, Technical Indicators, and Optimization Techniques.What else should you know about me and the course?The course shows how to do things right. But equally important, it highlights the most commonly made mistakes in Trading & Investing. There is hardly any other business where bners make so many mistakes. Why is that? A lack of skills, expertise, and experience. And: Overconfidence and overreliance on intuition. As a finance professional with an extensive acad background (MSc in Finance, CFA) my clear message is: For Trading and Investing, intuition and common sense are not your best friends. Very often, the most intuitive solution is not the correct solution! This course is "not only" a Stock trading and Equity investing course but also an in-depth Python Course that goes beyond what you can typically see in other courses. Create hands-on Applications with Python and use it for your Trading & Investing Business!What are you waiting for? Join now!Thanks and looking forward to seeing you in the Course! Bners who want to start with Stocks/equities and want to do it right straight way (avoiding common mistakes). Stock Traders and Investors who want to professionalize and automate their Business. Finance & Investment Professionals who want to step into Data-driven Finance. Data Scientists and Machine Learning Professionals with an interest in Investing into Stocks/Equities. HomePage: gfxtra__Algorithmi.part01.rar.html gfxtra__Algorithmi.part02.rar.html gfxtra__Algorithmi.part03.rar.html gfxtra__Algorithmi.part04.rar.html gfxtra__Algorithmi.part05.rar.html gfxtra__Algorithmi.part06.rar.html gfxtra__Algorithmi.part07.rar.html gfxtra__Algorithmi.part08.rar.html gfxtra__Algorithmi.part09.rar.html gfxtra__Algorithmi.part10.rar.html 
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