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We study whether prices of traded options contain information about future extreme market events. Our option-implied conditional expectation of market loss due to tail events, or tail loss measure, predicts future market returns, magnitude, and probability of the market crashes, beyond and above other option-implied variables. Stock-specific tail loss measure predicts individual expected returns and magnitude of realized stock-specific crashes in the cross-section of stocks. An investor that cares about the left tail of her wealth distribution benefits from using the tail loss measure as an information variable to construct managed portfolios of a risk-free asset and market index.
We test whether investor mood affects trading with data on all stock market transactions in Finland, utilizing variation in daylight and local weather. We find some evidence that environmental mood variables (local weather, length of day, daylight saving and lunar phase) affect investors’ direction of trade and volume. The effect magnitudes are roughly comparable to those of classical seasonals, such as the Monday effect. The statistical significance of the mood variables is weak in many cases, however. Only very little of the day-to-day variation in trading is collectively explained by all mood variables and calendar effects, but lower frequency variation seems connected to holiday seasons.
We use unique data from financial advisers’ professional exam scores and combine it with other variables to create an index of financial sophistication. Using this index to explain long-term stock return expectations, we find that more sophisticated financial advisers tend to have lower return expectations. A one standard deviation increase in the sophistication index reduces expected returns by 1.1 percentage points. The effect is stronger for emerging market stocks (2.3 percentage points). The sophistication effect contributes 60% to the model fit, while employer fixed effects combined contribute less than 30%. These results help understand the formation of potentially excessively optimistic expectations.
A natural experiment in which customer-owned mutual companies converted to publicly listed firms created a plausibly exogenous shock to the stock market participation status of tens of thousands of people. We find the shock changed the way people vote in the affected areas, with a 10% increase in share-ownership rate being followed by a 1.3%–3.1% increase in right-of-center vote share. The institutional details and additional tests suggest that wealth, liquidity, and tax-related incentives cannot fully explain the results. A plausible explanation is that the associated increase in the salience of stock ownership causes a shift in voters’ attention.
The European Commission recently put forward a proposal for a regulation to amend and strengthen the 2009 version of the EU's rules on the regulation of credit rating agencies ("CRA3"). Among other things, Art. 35a of the draft proposal introduces strict liability for rating agencies. This liability proposal is at odds with the aim to strengthen competition in the rating sector and could have a chilling effect on capital markets. The paper analyses existing rules on civil liability of rating agencies under different legal systems. Subsequently, the provision under Art. 35a of the Draft Proposal is examinded more closely. Suggestions on possible improvemts of the proposal are made.
SAFE Newsletter : 2013, Q1
(2013)
SAFE Newsletter
(2013)
The Center of Excellence SAFE – “Sustainable Architecture for Finance in Europe” – is a cooperation of the Center for Financial Studies and Goethe University Frankfurt. It is funded by the LOEWE initiative of the State of Hessen (Landes-Offensive zur Entwicklung wissenschaftlich-ökonomischer Exzellenz). SAFE brings together more than 40 professors and just as many junior researchers who are all dedicated to conducting research in support of a sustainable financial architecture. The Center has two main pillars: excellent research on all important topics related to finance; and policy advice, including the dissemination of relevant research findings to European decision makers from the realms of politics, regulation and administration.
In order to promote a fruitful exchange with interested parties from politics, academia, business and the media, SAFE issues a newsletter on a quarterly basis. This aims to provide an overview of the Center‘s ongoing research and policy activities. The SAFE Newsletter succeeds the House of Finance Newsletter, which was published between 2009 and 2012.
SAFE is based at Goethe University’s House of Finance however extends beyond by drawing on scholars from other parts of Goethe University as well as from fellow research institutions. The Center builds on the reputation of the House of Finance institutions, serving as an interdisciplinary think tank on the issue of finance.
Debt-induced crises, including the subprime, are usually attributed exclusively to supply-side factors. We uncover an additional factor contributing to debt culture, namely social influences emanating from the perceived average income of peers. Using unique information from a representative household survey of the Dutch population that circumvents the need to define the social circle, we consider collateralized, consumer, and informal loans. We find robust social effects on borrowing – especially among those who consider themselves poorer than their peers – and on indebtedness, suggesting a link to financial distress. We check the robustness of our results using several approaches to rule out spurious associations and handle correlated effects.
In this paper, we provide some reflections on the development of monetary theory and monetary policy over the last 150 years. Rather than presenting an encompassing overview, which would be overambitious, we simply concentrate on a few selected aspects that we view as milestones in the development of this subject. We also try to illustrate some of the interactions with the political and financial system, academic discussion and the views and actions of central banks.
In this paper we investigate the comparative properties of empirically-estimated monetary models of the U.S. economy using a new database of models designed for such investigations. We focus on three representative models due to Christiano, Eichenbaum, Evans (2005), Smets and Wouters (2007) and Taylor (1993a). Although these models differ in terms of structure, estimation method, sample period, and data vintage, we find surprisingly similar economic impacts of unanticipated changes in the federal funds rate. However, optimized monetary policy rules differ across models and lack robustness. Model averaging offers an effective strategy for improving the robustness of policy rules.