Time-Varying Dynamic Factor Models: Measuring Financial Connectedness

This paper introduces a time-varying general dynamic factor model (TV-GDFM) for measuring financial connectedness. This method, a type of multivariate time series analysis, captures the dynamic relationships between multiple financial variables. It identifies common factors and how changes in these factors influence different financial variables.

The TV-GDFM offers several advantages over traditional methods. It provides a more comprehensive and accurate measure of financial connectedness by considering interactions between multiple financial variables. This allows for a better reflection of the complex relationships within financial markets.

The paper presents research examples using the TV-GDFM in stock markets, bond markets, and foreign exchange markets. These studies demonstrate the effectiveness of the model in capturing changes and connections in financial markets. This makes it a valuable tool for financial decision-making and risk management.

Overall, this paper introduces a novel approach to measuring financial connectedness with significant practical value and research implications.