当地的机构所有权和围绕极端天气的挑战

Rob Bauer, Dirk Broeders, Flavio De Carolis AbstractIn this event study, we analyze the effect of market segmentation on stock returns in Europeamid extreme weather events. We show that local institutional ownership (LIO) mitigates thenegative effect of the uncertainty from the occurrence of extreme weather events on stockprices. We assess firms’ exposure to physical climate risks using the Eurosystem’s methodthat uses physical climate risk indicators. In a sample with materially exposed industries,we find a negative risk-adjusted abnormal return of 99 basis points for storms on the eventdate. This negative return is mitigated however by 1.3% for each percentage point increasein LIO. We confirm the mitigating role of LIO by testing the information hypothesis throughtwo channels: the distance between a firm’s headquarters and the affected facility and itsKeywords:extreme weather events, event study, asset pricing, market segmentation exposure to physical risk.JEL:C81, G11, G14, G32, Q54ECB Working Paper Series No 3069 Non-technical summaryFinancial asssets are increasingly exposed to climate risks, yet investor reactions to extremeweather events remain uncertain. This study explores how local institutional ownership (LIO)influences stock price movements during extreme weather events in Europe. We find that LIOplays a stabilizing role, helping to mitigate the negative impact of storms and floods on stockreturns. Using data from 2014 to 2022, we analyze publicly listed firms with varying levels ofLIO and assess their exposure to physical climate risks through the Eurosystem’s methodology.Our findings reveal that extreme weather events, particularly storms, lead to significantdeclines in stock prices. On average, stocks of affected companies experience a negative abnormalreturn of 99 basis points on the event date. However, this negative effect is reduced by 1.3percentage points for each additional percentage point of LIO. This suggests that local institutionalinvestors, who are more familiar with companies’ exposure to climate risks, incorporate thisknowledge into their investment decisions. As a result, firms with higher LIO experience lesspronounced price drops, as the risks are already reflected in stock valuations before the eventoccurs.Furthermore, our study highlights the importance of geographic proximity in mitigatinguncertainty. When a company’s affected facility is located farther from its headquarters, stockprice reactions tend to be stronger. This indicates that informational distance plays a crucial rolein investors’ ability to assess climate-related risks. Local institutional investors, who often havebetter access to firm-specific information, are more effective in stabilizing stock prices when theaffected assets are geographically closer.Interestingly, we also find a difference in how investors respond to different types of extremeweather events. While stock prices tend to react negatively to storms, the response to floods ismore mixed and depends on the severity of the event. A potential explanation lies in the natureof the events and the predictability of their impact. According to Merz et al. (2020), the mainuncertainty in storm forecasting concerns the storm track and the extent of its impact. Stormscan potentially affect large areas, making their consequences harder to predict. In contrast,floods, although often severe, tend to be more geographically localized and can be anticipatedwith greater accuracy. This is especially true when information such as flood risk maps and thelikelihood of government intervention is available in advance. However, the final impact of floodsstill depends on complex local conditions.ECB Working Paper Series No 3069 2 Our methodology combines financial market data, institutional ownership records, anddetailed climate risk assessments. We use facility-level data from the European Pollutant Releaseand Transfer Register (E-PRTR) and company ownership data from Amadeus to link firms to theirphysical assets. Additionally, we estimate expected annual losses due to extreme weather eventsusing the Eurosystem’s framework, which incorporates land use, historical weather patterns,and facility-specific exposure. By applying event study techniques, we measure abnormal stockreturns before and after extreme weather events, allowing us to quantify investor reactions.These findings have important implications for both investors and policymakers. For financialinstitutions, understanding the role of LIO can improve portfolio risk management and investmentstrategies in the face of climate-related uncertainty. Our results suggest that companies witha strong base of local institutional investors may be less vulnerable to abrupt price declinesfollowing extreme weather events. For regulators and policymakers, enhancing transparency inclimate risk disclosures and making facility-level climate exposure data more accessible couldhelp improve market efficiency.ECB Working Paper Series