Join industry leaders and innovators at the GFMI 7th Annual Machine Learning in Quantitative Finance conference and explore the intersection of deep learning, machine learning, and quantitative finance. This event will bring together experts to discuss the practical application of AI models in trading, portfolio optimization, alternative data, and risk management. Hear from top executives and quants about how machine learning is revolutionizing trading strategies, and how firms can unlock alpha through advanced predictive modeling and alternative data processing. With a focus on real-world applications and implementation challenges, a key gathering for industry leaders committed to AI in finance.
Attending This Premier marcus evans Conference Will Enable You to:
- Gain a competitive market edge with machine learning
- Elevate predictive performance through nlp-integrated analytical frameworks
- Leverage graph attention networks (GAT) to unlock insights from financial networks
- Enhance risk management and quantitative analysis with deep learning integration
- Upgrade algorithm performance through data optimization
- Leverage deep learning to drive smarter investment strategies
Best Practices and Case Studies from:
- Ryan Preclaw, Managing Director, Global Head of Investment Sciences, Barclays
- Judith Gu, Managing Director, Head of Equities and eFX Quant Strategist, Scotiabank
- Cristian Homescu, Director, Portfolio Analytics, Chief Investment Office, Global wealth and Investment Management GWIM, Bank of America Merrill Lynch
- Jing Xu, Executive Director, Quantitative Research (Machine Learning Director), CIB, J.P. Morgan
- Alejandro Rodríguez, Head of Quantitative Analysis, Miraltabank
- Olga Yangol, Managing Director, Head of Emerging Markets Research and Strategy, Americas, Credit Agricole CIB - Americas
For more information please contact Ria Kiayia, Digital Media and PR Marketing Manager at riak@marcusevanscy.com or visit: https://shorturl.at/G82cM
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