What is it about?
Following the Great Financial crisis of 2008-09, the European Central Bank resorted to some innovative policies to restore liquidity in the system. Their so-called unconventional actions involved several market interventions to extend the credit-granting capabilities on banks. This has influenced financial markets, as portfolio-rebalancing opportunities arose because of the ECB stance. In our paper we adopt a model (called Multiplicative Error Model with asymmetry and policy effects – MAP) suitable to describe the dynamics of market volatility, making it the result of several components, one of which is tied to the days when the ECB made an announcement. The empirical application focuses on four Euro-area markets with different capabilities to withstand market turmoil, that is France and Germany on the one side and Italy and Spain on the other. We are capable of showing the superior performance in forecasting and the more marked volatility reduction induced by the ECB policies on debt-ridden countries.
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Why is it important?
The paper has the merit to establish an innovative way to model the link between a Central Bank announcements and the subsequent market movements. It is commonly accepted that the policy actions have indeed been successful in bringing a soothing effect on the financial system and on financial markets. With the increase in inflation and the energy crisis following the Russian aggression on Ukraine, the policies by Central Banks have reverted to interest rate increases. In the case of Europe, there is a marked fear of fragmentation, that is market movements that favor traditionally more solid economies: the challenge that our model is able to withstand is the possibility to analyze how successful the ECB is in its announcements, when facing the need to control inflation with the goal of not bringing about divergence in Euro-area markets.
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This page is a summary of: Unconventional policies effects on stock market volatility: The MAP approach, Journal of the Royal Statistical Society Series C (Applied Statistics), June 2022, Wiley, DOI: 10.1111/rssc.12574.
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