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Natural Language Processing in Trading | Masterclass

3 min read

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Session Outline

  • How is Natural Language Processing applied in financial markets?
  • Calculating Daily Sentiment Score on Quantra learning portal
  • Compare different word embedding methods with their pros and cons
  • How does Quantra learning portal provide a unique learning experience?

Who Should Attend?

  • Technology professionals, who want to leverage their technical skills to invest wisely in the financial markets
  • Discretionary/manual traders (ex. professional traders, part-time traders) who are looking to upskill and get better returns
  • Students and other enthusiasts who wish to excel at research work

Speaker Profiles

Terry Benzschawel

Terry Benzschawel

Founder and Principal at Benzschawel Scientific, LLC
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.

Before 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.

Ishan Shah

Ishan Shah

AVP, Content & Research at QuantInsti
Ishan Shah is AVP and leads the content & research team at Quantra by QuantInsti. Prior to that, he worked with Barclays in the Global Markets team & with Bank of America Merill Lynch. He has a rich experience in financial markets spanning across various asset classes in different roles.

Frequently Asked Questions (FAQ) about this session

How is Natural language processing used in financial markets?
  • Natural language processing focuses on the interaction between human language and computers. It enables machines to get closer to a human level understanding of the language text. It is easy for humans to understand the text and interpret the meaning of the same. But doing the same on the large corpus of data is not feasible.
  • In finance and trading, everyday, large amount of data is generated, and it is challenging for humans to find useful information and make trading decisions. This data comes in the form of News, scheduled economic releases, employment figures, interest rates, inflation and GDP figures. All such data moves the market. To deal with such a large amount of data and get important information natural language processing techniques are used.
What is a Sentiment Score?
  • A Sentiment Score is a quantitative value assigned to a piece of content/text which is used to make trading decisions. For example, the tweet "$AAPL is my best investment so far" has a positive sentiment score of 0.6369 indicating a bullish trend for Apple stock. On the other hand, the tweet "AAPL is not my best investment so far" has the calculated score of -0.5216 which is a negative score indicating the stock fall.
How to prepare for this session?
Certification of Participation
  • You will be awarded a certificate of participation if you attend the full webinar.

This event was conducted on:
Tuesday January 14, 2020
8:00 AM ET | 6:30 PM IST | 9:00 PM SGT

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