Finance-Insurance
Time: 10.00 am
Date:02th of April 2026
Room 3001

Frederik KRABBE (Aarhus University) “Causal Non-causal State Space Models and the Modelling of Financial Bubbles”

Abstract : In this paper, we study causal non-causal state space models to model time series characterised by a local explosive increase followed by a sharp decrease such as stock prices. To motivate the use of causal non-causal state space models, we show that the causal non-causal convolution autoregressive model introduced by Gouriéroux and Zakoïan (2017) can be consistent with the rational expectations stock price model. As in a causal state space model, a central question is how to perform state and parameter inference in the causal non-causal state space model, which we discuss in the paper. We also study the causal non-causal convolution autoregressive model in more detail, providing some new results for the model. To illustrate the usefulness of causal non-causal state space models, we use the causal non-causal convolution autoregressive model to estimate the size of the dot-com bubble in both real time and a posteriori with the stable non-causal autoregressive model considered also by Gouriéroux and Zakoïan (2017) as a benchmark.

Organizers:  Jean-Michel ZAKOIAN & Christian FRANCQ