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Duration
35 hours
Delivery Method
Online
Available on
Lifetime Access
Accessibility
Desktop, Laptop
Language
English
Subtitles
English
Level
Beginner
Teaching Type
Self Paced
Video Content
35 hours
Course Description
Course Overview
International Faculty
Post Course Interactions
Hands-On Training,Instructor-Moderated Discussions
Case Studies, Captstone Projects
Skills You Will Gain
Prerequisites/Requirements
Working of the financial markets and familiarity with basic programming skills are recommended to fully appreciate the implementation of various strategies covered in this learning track
Even if you haven`t traded in financial markets nor coded in python, this learning track can be easily completed
What You Will Learn
Fetch tweets and news data and backtest an intraday strategy using the sentiment score
Train a machine learning model to calculate a sentiment from a news headline. Predict the stock returns and bond returns
Implement and compare the word embeddings methods such as Bag of Words (BoW), TF-IDF, Word2Vec and BERT
Work with time-series data and be able to manipulate it and incorporate transaction costs and slippage in backtesting
Analyze the trading strategies using various performance metrics
Create a trading strategy using sentiment indicators such as Put-Call ratio, TRIN and VIX indicators and analyze different types of risks involved in trading
Learn to live and paper trade the strategies covered in the course
Course Instructors
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