Unified Tail Dependence Measures and Its Applications in High-Frequency Financial Data

Dr. Lei Hua
Associate Professor, Director of Statistical Consulting Service
Northern Illinois University

In this presentation, I will first motivate the necessity for a unified tail dependence measure, followed by an examination of the theoretical framework for developing such measures utilizing random variables characterized by regularly varying tails. Specific instances that result in unified tail dependence measures applicable in practical scenarios will be demonstrated. Ultimately, I will explore the application of the unified tail dependence measure in the analysis of high-frequency financial market data and discuss novel empirical insights from financial markets.