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Algorithmic Trading & Quantitative Analysis Using Python
BESTSELLER | Created by Mayank Rasu | Video: h264, 1280x720 | Audio: AAC 48KHz 2ch | Duration: 14:41 H/M | Lec: 86 | 10.6 GB | Language: English | Sub: English [Auto-generated]

Build fully automated trading system and Implement quantitative trading strategies using Python

What you'll learn
Algorithmic trading and quantitative analysis using python
Carrying out both technical analysis and fundamental analysis programatically
API trading

Intermediate level expertise in python
high school level familiarity with mathematics and statistics
Basic understanding of equity/forex trading

Build a fully automated trading bot on a shoestring budget. Learn quantitative analysis of financial data using python. Automate steps like extracting data, performing technical and fundamental analysis, generating signals, backtesting, API integration etc. You will learn how to code and back test trading strategies using python. The course will also give an introduction to relevant python libraries required to perform quantitative analysis. The USP of this course is delving into API trading and familiarizing students with how to fully automate their trading strategies.

You can expect to gain the following skills from this course

Extracting daily and intraday data for free using APIs and web-scraping

Working with JSON data

Incorporating technical indicators using python

Performing thorough quantitative analysis of fundamental data

Value investing using quantitative methods

Visualization of time series data

Measuring the performance of your trading strategies

Incorporating and backtesting your strategies using python

API integration of your trading script

Sentiment Analysis

Who this course is for?
traders looking to automate strategies and building automated trading stations, data scientists seeking to work with financial data, anyone curious about quantitative analysis

Algorithmic Trading & Quantitative Analysis Using Python

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Views: 64 | Tutorials/E-learnings
3-11-2019, 22:52
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