In this paper, we develop a financial stress index for France that can be used as a real-time composite indicator for the state of financial stability in France. We take 17 financial variables from different market segments and extract a common stress component using a dynamic approximate factor model. We estimate the model with a combined maximum-likelihood and Expectation-Maximization algorithm allowing for mixed frequencies and an arbitrary pattern of missing data. Using a Markov-Switching Bayesian VAR model, we show that an episode of high financial stress is associated with significantly lower economic activity, whereas movements in the index in a low-stress regime do not incur significant changes in economic activity. Therefore, this index can be used in real time as an early warning signal of systemic risk in the French financial sector.
