G14 Information and Market Efficiency; Event Studies
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This paper documents that ECB announcements on monetary policy increase stock market volatility in the euro area (EA) using several volatility measures from January 1999 to December 2019. Employing event study methods, a more pronounced impact exists following the global financial crisis starting in 2007. All assets react similarly so that no national peculiarities arise. The effects also spill over to 12 non-EA markets analyzed. Stock markets are more sensitive to negative monetary policy news than to positive ones. Further weighting the announcements by financial market reactions, stock markets behave in a more heterogeneous way.
This study provides novel insights to the ongoing debate how market efficiency is challenged by investor behavior. Applying search engine data we find that retail investor attention can enhance market efficiency. High attention is associated with better incorporation of idiosyncratic stock information, which we interpret as improved pricing efficiency. This effect is even more pronounced in bullish markets. In bearish markets, however, retail investor attention leads to a deterioration of pricing efficiency, which might be explained with herding behavior. Our evidence holds for a broad sample of European and US stocks.
In search of alpha
(2015)
In this study we develop a trading strategy that exploits limited investor attention. Trading signals for US S&P 500 stocks stocks are derived from Google Search Volume data, taking a long position if investor attention for the corresponding security was abnormally low in the past week. Our strategy generates 19% average annual return and thereby outperforms a simple market buy-and-hold strategy. After controlling for the well-known risk factors, a significant alpha (abnormal return) of 10% p.a. remains. Returns are sufficiently large to cover transaction costs.
This study revisits prior research on the valuation of dividends in an accounting-based valuation framework. Using a battery of tests, we show that market value deflation is essential in market-based tests of dividend displacement and signaling because it controls for ‘stale’ information in addition to scale (size) differences across firms. For U.S. firms, we show that after controlling for ‘stale’ information, the empirical association between dividends and market values switches from positive to negative. This switch is not explained by scale differences across firms. Further, we show that after controlling for staleness, the valuation of dividends remains positive for European firms. This result is explained by the relatively stronger association of dividends with future earnings in these settings (i.e., signaling). Lastly, our country-specific estimates of dividend valuation provide a potentially valuable index for studies aimed at examining the effects of accounting and securities regulation on information asymmetries in an international context.
This paper employs event study methods to evaluate the effects of ECB’s nonstandard monetary policy program announcements on 10-year government bond yields of euro area member states. It covers data from 11 euro area countries from January 1, 2007 to August 31, 2017 and distinguishes between the more solvent countries (Austria, Belgium, Finland, France, Germany, the Netherlands) and the less solvent ones (Greece, Ireland, Italy, Portugal, Spain). The paper makes three contributions to the literature. First, it is the first paper to reveal that measurable effects of announcements arise with a one-day delay meaning that government bond markets take some time to react to ECB announcements. Second, it quantifies the country-specific extent of yield reduction which seems inversely related to the solvency rating of the corresponding countries. The reduction of the spread between both groups in response to an event is due to a stronger decrease in the less solvent group. Third, this result is confirmed by letting the announcement variable interact with the spread level, which is an innovation in this strand of literature. By employing different data as control variables, it turns out that the results are robust for a given event set.