Terry Benzschawel – Natural Language Processing in Trading

Description

Natural Language Processing in Trading is all the required skill sets are covered in the foundation courses available in the learning track.

Who is Terry Benzschawel?

Terry Benzschawel is the founding member and chief executive officer of Benzschawel Scientific, LLC. Prior to that, Terry was a Managing Director at Citigroup’s Institutional Clients Business, where he oversaw the Quantitative Credit Trading group. Terry has served as a credit strategist in Citi’s Fixed Income Strategy department, focusing on client-centric solutions across all credit markets. Prior to that, he had worked for Chase Manhattan and Citi, where he developed algorithms to predict corporate bankruptcy and detect credit card fraud. Two books have been written by him on Credit Modeling.

Natural Language Processing in Trading with Terry Benzschawel

This is the right course for you if you want to trade based on the sentiments and opinions expressed in news headlines using cutting-edge natural language processing techniques. Utilizing powerful models such as Word2Vec, BERT, and XGBoost, learn to quantify news headlines and gain a trading advantage.

• Introduction to the Course
• Applications of Natural Language Processing
• Sources of News Headline Data
• Sentiment Score and Strategy Logic
• Sentiment Strategy on Stocks
• Sentiment Strategy on Bonds
• Introduction to Word Embeddings
• Bag of Words
• Predicting Sentiment Score Using XGBoost
• Sentiment Class of News Headlines
• TF-IDF
• WordVec
• BERT
• BERT Model Adaptation
• Result Analysis
• Python Installation
• Live Trading on IBridgePy
• Paper and Live Trading
• Capstone Project
• Course Summary

LIVE TRADING

• Train a machine learning model to calculate a news headline’s sentiment.
• Implement and compare word embedding techniques including Bag of Words (BoW), TF-IDF, Word2Vec, and BERT.
• Predict stock and bond returns based on the news headlines.
• Describe the uses for natural language processing
• Automate and paper trade the course-covered strategies.
• Retrieve the most recent news headlines
• Implement strategies on live markets and assess performance.

Refund is acceptable:

• Firstly, item is not as explained
• Secondly, Natural Language Processing in Trading do not work the way it should.
• Thirdly, and most importantly, support extension can not be used.

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