Quantitative methods for returns forecasting, financial instrument pricing and optimal portfolio allocation have been used in capital markets for several decades. Since early 2000, due to digitization and the launch of electronic platforms there has been a major increase in data collection capabilities. With easy availability of vast amounts of data on capital markets transactions and on economic fundamentals, it has become possible to train ML algorithms and use them for forecasting returns, in investment selection for optimal portfolio construction, for trading activities and efficient trade execution.
In this talk, Rachna will discuss a few use cases of ML in capital markets activities such as trading and investment along with discussion of associated risks and caveats.
- An overview of ML applications in trading and investment activities.
- Illustrative examples of a few recent innovative use cases of ML in trading and investments.
- Risks and caveats associated with these ML applications.
Have questions for the speakers? Leave a comment.
Rachna Maheshwari works as a Practice Lead in Financial Risk Modelling with Crisil (S&P Global) in their global risk consulting practice and teaches Quantitative Finance as visiting faculty at institutions in Mumbai. Currently, besides working as a quantitative finance consultant, she is working on thought leadership activities as well as capability development in applications of ML in finance to support her business vertical’s consulting practice in this area.
Rumanu will be moderating the talk. She is a Machine Learning Researcher who has spent her weekends for the past five years at tech meetups and conferences, her interest peaking at the intersection of adtech and data privacy preservation. She toys around with humor(ous?) NLP usecases when not hitting comedy open mics to be a better tech speaker.
This session will be held online on the 23rd of December from 4 pm - 5 pm. You can RSVP to participate via Zoom or watch the livestream on YouTube.
This session is part of the AI and Risk Mitigation series which will host meet-ups/talks on healthtech, fintech, agritech, and ed-tech and public services. These will be a mix of online and hybrid sessions. Takeaways from these sessions will be used to develop a knowledge repository in the form of practical guidelines and a self-regulated charter for Ethical AI.
- Post a comment here to suggest a topic you’d like to discuss. This should involve a brief outline of the use cases and challenges regarding AI implementation.
- Moderate/discuss a topic someone else is proposing.
- Spread the word among colleagues and friends.
- Join The Fifth Elephant Telegram group or WhatsApp group.
Anthill Inside is a community where topics in AI and Deep Learning such as tools and technologies, methodologies and strategies for incorporating AI and Deep Learning into various applications and businesses, and AI engineering are discussed. Furthermore, Anthill Inside places a strong emphasis on exploring and addressing ethical concerns, privacy, and the issue of bias both in practice and within AI products.