This paper attempts to identify the market surprise level by dynamically estimating the market beta (risk premium) with the Kalman Filter.The Kalman filter approach enables the calculation of the Kalman Gain, which can be interpreted as the market surprise level.Dynamic systematic risk was estimated for firms listed on the Japanese equity market based on daily data for a period that includes the three financial crises that occurred in 1990, 2000 and 2008.The industry sector of firms that had demonstrated a high market surprise level provides some evidence on how market surprises propagated through the financial system.Finally, this research proposes an information portfolio that can potentially earn abnormal profits from the additional risk premium derived from dynamic estimation.
竹澤 et al. (Sun,) studied this question.