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Piotr Karasinski: Random Walk from Physics to Finance
1:35
Piotr Karasinski: Random Walk from Physics to Finance
Antoine Savine and Brian Norsk Huge: AAD & Differential ML
1:27
Antoine Savine and Brian Norsk Huge: AAD & Differential ML
Irene Aldridge: Noise Dynamics in Big Data Inference
1:02
Irene Aldridge: Noise Dynamics in Big Data Inference
Andrew Addison and Alexander Tsyplikhin: MIMD Architecture & Opportunities for Optimisation
1:00
Andrew Addison and Alexander Tsyplikhin: MIMD Architecture & Opportunities for Optimisation
Jesper Andreasen (Kwant Daddy): Next Generation Local Volatility
1:07
Jesper Andreasen (Kwant Daddy): Next Generation Local Volatility
Dr Jochen Papenbrock: Explainable, accelerated machine intelligence
1:12
Dr Jochen Papenbrock: Explainable, accelerated machine intelligence
Prof. Rolf Poulsen: Tales of Innumeracy
1:05
Prof. Rolf Poulsen: Tales of Innumeracy
Rob Carver: Risk targeting: Infinity war
1:34
Rob Carver: Risk targeting: Infinity war
Claudio Albanese: Model Risk and Reverse Stress Testing
1:32
Claudio Albanese: Model Risk and Reverse Stress Testing
David Foster: Generative Deep Learning – The Key to Unlocking AGI
1:15
David Foster: Generative Deep Learning – The Key to Unlocking AGI
Jörg Kienitz: General Stochastic Volatility – new models and DNN
0:57
Jörg Kienitz: General Stochastic Volatility – new models and DNN
Jens Nordvig: Forecasting the dollar using capital flow data
1:02
Jens Nordvig: Forecasting the dollar using capital flow data
Yves Hilpisch: RL: From Games to Intraday Algorithmic Trading
1:35
Yves Hilpisch: RL: From Games to Intraday Algorithmic Trading
Panel: Alexander Denev and Saeed Amen: The Book of Alternative Data
1:21
Panel: Alexander Denev and Saeed Amen: The Book of Alternative Data
Lee, Munoz Constantine & Pervushyna: ML with MlFinLab Python library
1:23
Lee, Munoz Constantine & Pervushyna: ML with MlFinLab Python library
Jay Cao, Jacky Chen, John Hull, Zissis Poulos: Deep Hedging Using RL
1:22
Jay Cao, Jacky Chen, John Hull, Zissis Poulos: Deep Hedging Using RL
Panel: Matthew Dixon, Igor Halperin, and Paul Bilokon: ML in Finance
1:28
Panel: Matthew Dixon, Igor Halperin, and Paul Bilokon: ML in Finance
Blanka Horvath: A Data-driven Market Simulator
1:14
Blanka Horvath: A Data-driven Market Simulator
Daniele Bernardi : Bitcoin’s Price prediction
1:05
Daniele Bernardi : Bitcoin’s Price prediction
Grady Booch: Software Architecture for AI-intensive Systems
0:59
Grady Booch: Software Architecture for AI-intensive Systems
Luigi Ballabio: A Short Introduction to QuantLib
1:23
Luigi Ballabio: A Short Introduction to QuantLib
Cetin Karakus: Anatomy of a Distributed Options Market Making System
1:55
Cetin Karakus: Anatomy of a Distributed Options Market Making System
Ernest Chan: Tail Hedging in the Age of Machine Learning
1:06
Ernest Chan: Tail Hedging in the Age of Machine Learning
Daniel Duffy: Some Perspectives on Computational Finance and ML
2:12
Daniel Duffy: Some Perspectives on Computational Finance and ML
Thomas Wiecki: Bayesian Portfolio Allocation
1:29
Thomas Wiecki: Bayesian Portfolio Allocation
Christina Qi: Starting a Modern Hedge Fund
1:30
Christina Qi: Starting a Modern Hedge Fund