Speaker: Bernd Wilfling (Münster School of Business and Economics)
Venue: MNB-Visitor Centre
Time: 15:15 pm, Wednesday March 3, 2010
Abstract:
In this paper we use a state-space model with Markov-switching to detect speculative bubbles in stock-price data. Our two innovations are to adapt this technology to the state-space representation of a well-known present-value stock-price model, and to estimate the model via Kalman-filtering using a plethora of artificial as well as real-world data sets that are known to contain bubble periods. Analyzing the smoothed regime probabilities, we find that our technology is well suited to detecting stock-price bubbles in both types of data sets.
JEL-classification codes: C22; G12
Key words: Stock market dynamics; Detection of speculative bubbles; Present value models; State-space models with Markov-switching