|New training offer in association with QuantInsti
As a Quants Hub Member claim 38% discount on Natural Language Processing in Trading
Coupon code details:
Valid until: 31st Dec, 19
Learn to use Natural Language Processing to trade based on market sentiments and opinions expressed in the news headlines.
Use powerful models like Word2Vec, BERT and XGBoost to quantify the market sentiment and add an edge to your trading.
What you will learn.
- Predict the stock returns and bond returns from the news headlines
- Train a machine learning model to calculate a sentiment from a news headline
- Implement and compare the word embeddings methods such as Bag of Words (BoW), TF-IDF, Word2Vec and BERT
Presenter: Terry Benzschawel
Terry Benzschawel is the Founder and Principal at Benzschawel Scientific, LLC. Before that, Terry had worked with Citigroup's Institutional Clients Business, as a Managing Director, heading the Quantitative Credit Trading group. In Citi’s Fixed Income Strategy department, Terry has worked as a credit strategist with a focus on client-oriented solutions across all credit markets. Prior to that, he had worked in Chase Manhattan and Citi to build algorithms to predict corporate bankruptcy and to detect credit fraud on card transactions. He has authored two books on Credit Modeling.