21st Python For Quant Finance Meetup (Virtual)
Webinar
Wednesday, July 22, 2020 - 04:00 PM
Until: Wednesday, July 22, 2020 - 06:00 PM
(Adjusted for timezone: Europe/London)
Categories
Dear All.
This is our 3rd virtual cross-Meetup group event.
Please register under:
https://attendee.gotowebinar.com/register/7563395760074711310
Agenda:
OPENING:
Dr. Yves Hilpisch (TPQ | The AI Machine): Introduction
TALK 1:
How to Create a Sustainable and Risk Optimized Portfolio | Dr. Jennifer Rasch and Dr. Caroline Löbhard
Combining a Markowitz Model with Monte Carlo Simulations and different risk measures applied on a sustainable stocks universe, we show you how we created a portfolio.
TALK 2:
Forecasting Stock Market Data with AI (The YUCE-8 Approach) | Torsten Langer
The nature of stock market data is determined by ups and downs. Today you have access to Terabytes of data in real time. But the human brain is not capable of processing this amount of information. Whilst the human brain gets overrun by the amount of data that is produced per second another technology is waiting for its deployment: AI. AI is able to learn from the past in order to predict the future. But financial data is difficult to predict.
In this talk Torsten will talk about the journey he went on in order to create an API based set of TensorFlow based AI models and the promising results that this library, called YUCE-8, delivers today – 1.5 years later. The demo will be run in Python (Google Colab).
CLOSING:
Closing Remarks
See you all online on Wednesday, 22nd July 2020!
Yves & Jason
For more information and to register visit https://www.meetup.com/Python-for-Quant-Finance-London/events/271837354/.
This is our 3rd virtual cross-Meetup group event.
Please register under:
https://attendee.gotowebinar.com/register/7563395760074711310
Agenda:
OPENING:
Dr. Yves Hilpisch (TPQ | The AI Machine): Introduction
TALK 1:
How to Create a Sustainable and Risk Optimized Portfolio | Dr. Jennifer Rasch and Dr. Caroline Löbhard
Combining a Markowitz Model with Monte Carlo Simulations and different risk measures applied on a sustainable stocks universe, we show you how we created a portfolio.
TALK 2:
Forecasting Stock Market Data with AI (The YUCE-8 Approach) | Torsten Langer
The nature of stock market data is determined by ups and downs. Today you have access to Terabytes of data in real time. But the human brain is not capable of processing this amount of information. Whilst the human brain gets overrun by the amount of data that is produced per second another technology is waiting for its deployment: AI. AI is able to learn from the past in order to predict the future. But financial data is difficult to predict.
In this talk Torsten will talk about the journey he went on in order to create an API based set of TensorFlow based AI models and the promising results that this library, called YUCE-8, delivers today – 1.5 years later. The demo will be run in Python (Google Colab).
CLOSING:
Closing Remarks
See you all online on Wednesday, 22nd July 2020!
Yves & Jason
For more information and to register visit https://www.meetup.com/Python-for-Quant-Finance-London/events/271837354/.