<img height="1" width="1" style="display:none" src="https://www.facebook.com/tr?id=648880075207035&amp;ev=PageView&amp;noscript=1">

BayesiaLab Webinar Series

Black Swans & Bayesian Networks

Recorded on July 19, 2019

 

Webinar Materials

Abstract

Rare events are typically difficult to model due to the lack of historical data. In fact, the events we are typically concerned about, e.g., catastrophic events, may never have happened before, and will hopefully never ever happen. On the other hand, frequent occurrences can be easily characterized by statistical models learned from data. Inevitably, such statistical models are bound to give us a false sense of security about never-seen-before situations.

Even though we may not have any actual observations, we can still speculate and hypothesize about possible rare events, i.e., we can reason on theoretical grounds as to what could possibly go wrong.
The objective of this webinar is to present Bayesian networks as a framework to merge machine-learned knowledge from data with theoretical knowledge from domain experts in order to produce a joint probability distribution that includes common and rare events at the same time.

The case study we present is addressing some of the challenges of Modern Portfolio Theory and was inspired by Rebonato & Denev's book, Portfolio Management Under Stress.

BayesiaLab Courses

Dates Location Program
At your convenience On your desktop/laptop Introductory Course (60-Day Self-Study Edition)
At your convenience On your desktop/laptop Advanced Course (60-Day Self-Study Edition)
March 24–26, 2020 — CANCELLED Boston, MA, USA 3-Day Introductory Course
April 7–9, 2020 — CANCELLED  Paris, France 3-Day Introductory Course
May 6–8, 2020 Seattle, WA, USA 3-Day Introductory Course
May 11–13, 2020 Seattle, WA, USA 3-Day Advanced Course
June 15–17, 2020 Paris, France 3-Day Advanced Course
October 5–7, 2020 Toronto, ON, Canada 3-Day Introductory Course
October 13–15, 2020 Toronto, ON, Canada 3-Day Advanced Course

8th Annual BayesiaLab Conference

October 5–7, 2020 Toronto, ON, Canada 3-Day Introductory Course
October 8–9, 2020 Toronto, ON, Canada 8th Annual BayesiaLab Conference
October 13–15, 2020 Toronto, ON, Canada 3-Day Advanced Course