Speakers:

Dr. Yuri Katz

Topological Data Analysis of Financial Time Series

date:

Wednesday, Oct 16, 2019

Time:

3:55 pm

Track:

Room:

Premium 1

Summary:

In this session Yuri Katz will introduce a new method, based on the topological data analysis (TDA), to financial time series and detect early warning signals of approaching financial crashes. Analyzes of the time-series of daily log-returns of major US stock market indices and cryptocurrencies shows that in the vicinity of financial meltdowns, the Lp-norms of persistence topological landscapes exhibit strong growth. Remarkably, the average spectral density at low frequencies of the derived Lp-norms demonstrates a strong rising trend at least 100 trading days prior to either dotcom crash on 03/10/2000, or to the Lehman bankruptcy on 09/15/2008. The study suggests that TDA provides a new type of predictive analytics, which complements the standard statistical measures and ML-algorithms. The approach is very general and can be used beyond the analysis of financial time series.

Ready to attend?

Register now! Join your peers.

Register now View agenda
Newsletter

Knowledge is everything!
Sign up for our newsletter to receive:

  • 10% off your ticket!
  • insights, interviews, tips, news, and much more about Predictive Analytics World
  • price break reminders