Is there an Information Channel of Monetary Policy?
Oliver Holtemöller, Alexander Kriwoluzky, Boreum Kwak
IWH Discussion Papers,
No. 17,
2020
Abstract
Exploiting the heteroscedasticity of the changes in short-term and long-term interest rates and exchange rates around the FOMC announcement, we identify three structural monetary policy shocks. We eliminate the predictable part of the shocks and study their effects on financial variables and macro variables. The first shock resembles a conventional monetary policy shock, and the second resembles an unconventional monetary shock. The third shock leads to an increase in interest rates, stock prices, industrial production, consumer prices, and commodity prices. At the same time, the excess bond premium and uncertainty decrease, and the U.S. dollar depreciates. Therefore, this third shock combines all the characteristics of a central bank information shock.
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Private Equity and Portfolio Companies: Lessons From the Global Financial Crisis
Shai B. Bernstein, Josh Lerner, Filippo Mezzanotti
Journal of Applied Corporate Finance,
No. 3,
2020
Abstract
Critics of private equity have warned that the high leverage often used in PE-backed companies could contribute to the fragility of the financial system during economic crises. The proliferation of poorly structured transactions during booms could increase the vulnerability of the economy to downturns. The alternative hypothesis is that PE, with its operating capabilities, expertise in financial restructuring, and massive capital raised but not invested ("dry powder"), could increase the resilience of PE-backed companies. In their study of PE-backed buyouts in the U.K. - which requires and thereby makes accessible more information about private companies than, say, in the U.S. - the authors report finding that, during the 2008 global financial crisis, PE-backed companies decreased their overall investments significantly less than comparable, non-PE firms. Moreover, such PE-backed firms also experienced greater equity and debt inflows, higher asset growth, and increased market share. These effects were especially notable among smaller, riskier PE-backed firms with less access to capital, and also for those firms backed by PE firms with more dry powder at the crisis onset. In a survey of the partners and staff of some 750 PE firms, the authors also present compelling evidence that PEs firms play active financial and operating roles in preserving or restoring the profitability and value of their portfolio companies.
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To Securitise or to Price Credit Default Risk?
Huyen Nguyen, Danny McGowan
Abstract
We evaluate if lenders price or securitise mortgages to mitigate credit risk. Exploiting exogenous variation in regional credit risk created by differences in foreclosure law along US state borders, we find that financial institutions respond to the law in heterogeneous ways. In the agency market where Government Sponsored Enterprises (GSEs) provide implicit loan guarantees, lenders transfer credit risk using securitisation and do not price credit risk into mortgage contracts. In the non-agency market, where there is no such guarantee, lenders increase interest rates as they are unable to shift credit risk to loan purchasers. The results inform the debate about the design of loan guarantees, the common interest rate policy, and show that underpricing regional credit risk leads to an increase in the GSEs‘ debt holdings by $79.5 billion per annum, exposing taxpayers to preventable losses in the housing market.
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17.06.2020 • 10/2020
High risk of corporate bankruptcy due to the corona shutdown
The Corona shutdown increases the probability of corporate bankruptcy. An analysis based on corporate financial statements from 2014 to 2018 reveals that in the United Kingdom, 73% of shutdown firms are not able to cover interest expenses from earnings before interest and taxes if they lose one twelfth of annual turnover. In Germany, the fraction amounts to 81%.
Oliver Holtemöller
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Corona Shutdown and Bankruptcy Risk
Oliver Holtemöller, Yaz Gulnur Muradoglu
IWH Online,
No. 3,
2020
Abstract
This paper investigates the consequences of shutdowns during the Corona crisis on the risk of bankruptcy for firms in Germany and United Kingdom. We use financial statements from the period 2014 to 2018 to predict how pervasive risk of bankruptcy becomes for micro, small, medium, and large firms due to shutdown measures. We estimate distress for firms using their capacity to service their debt. Our results indicate that under three months of shutdown almost all firms in shutdown industries face high risk of bankruptcy. In Germany, about 99% of firms in shutdown industries and in the UK about 98% of firms in shutdown industries are predicted to be under distress. The furlough schemes reduce the risk of bankruptcy only marginally to 97% of firms in shutdown industries in Germany and 95% of firms in shutdown industries in the United Kingdom in case of a three-month shutdown. In sectors that are not shutdown under conservative estimates of contagion of sales losses, our results indicate considerable risk of widespread bankruptcies ranging from 76% of firms in Germany to 69% of firms in the United Kingdom. These early findings suggest that the impact of corona crisis on corporate sector via shutdowns can be severe and subsequent policy should be designed accordingly.
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How to Talk Down Your Stock Performance
Andreas Barth, Sasan Mansouri, Fabian Wöbbeking, Severin Zörgiebel
SSRN Discussion Papers,
2020
Abstract
We process the natural language of verbal firm disclosures in order to study the use of context specific language or jargon and its impact on financial performance. We observe that, within the Q&A of earnings conference calls, managers use less jargon in responses to tougher questions, and after a quarter of bad economic success. Moreover, markets interpret the lack of precise information as a bad signal: we find lower cumulative abnormal returns and a higher implied volatility following earnings calls where managers use less jargon. These results support the argument that context specific language or jargon helps to efficiently and precisely transfer information.
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Bank Accounting Regulations, Enforcement Mechanisms, and Financial Statement Informativeness: Cross-country Evidence
Augustine Duru, Iftekhar Hasan, Liang Song, Yijiang Zhao
Accounting and Business Research,
No. 3,
2020
Abstract
We construct measures of accounting regulations and enforcement mechanisms that are specific to a country's banking industry. Using a sample of major banks in 37 economies, we find that the informativeness of banks’ financial statements, measured by the value relevance of earnings and common equity, is higher in countries with stricter bank accounting regulations and countries with stronger enforcement. These findings suggest that superior bank accounting and enforcement mechanisms enhance the informativeness of banks’ financial statements. In addition, we find that the effects of bank accounting regulations are more pronounced in countries with stronger enforcement in the banking industry, suggesting that enforcement is complementary to bank accounting regulations in achieving higher value relevance of financial statements. Our study has important policy implications for bank regulators.
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The Value of Firm Networks: A Natural Experiment on Board Connections
Ester Faia, Maximilian Mayer, Vincenzo Pezone
CEPR Discussion Papers,
No. 14591,
2020
Abstract
This paper presents causal evidence of the effects of boardroom networks on firm value and compensation policies. We exploit exogenous variation in network centrality arising from a ban on interlocking directorates of Italian financial and insurance companies. We leverage this shock to show that firms whose centrality in the network rises after the reform experience positive abnormal returns around the announcement date and are better hedged against shocks. Information dissemination plays a central role: results are driven by firms that have higher idiosyncratic volatility, low analyst coverage, and more uncertainty surrounding their earnings forecasts. Firms benefit more from boardroom centrality when they are more central in the input-output network, hence more susceptible to upstream shocks, when they are less central in the cross-ownership network, or when they have low profitability or low growth opportunities. Network centrality also results in higher directors' compensation, due to rent sharing and improved executives' outside option, and more similar compensation policies between connected firms.
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Comparing Financial Transparency between For-profit and Nonprofit Suppliers of Public Goods: Evidence from Microfinance
John W. Goodell, Abhinav Goyal, Iftekhar Hasan
Journal of International Financial Markets, Institutions and Money,
January
2020
Abstract
Previous research finds market financing is favored over relationship financing in environments of better governance, since the transaction costs to investors of vetting asymmetric information are thereby reduced. For industries supplying public goods, for-profits rely on market financing, while nonprofits rely on relationships with donors. This suggests that for-profits will be more inclined than nonprofits to improve financial transparency. We examine the impact of for-profit versus nonprofit status on the financial transparency of firms engaged with supplying public goods. There are relatively few industries that have large number of both for-profit and nonprofit firms across countries. However, the microfinance industry provides the opportunity of a large number of both for-profit and nonprofit firms in relatively equal numbers, across a wide array of countries. Consistent with our prediction, we find that financial transparency is positively associated with a for-profit status. Results will be of broad interest both to scholars interested in the roles of transparency and transaction costs on market versus relational financing; as well as to policy makers interested in the impact of for-profit on the supply of public goods, and on the microfinance industry in particular.
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Does Machine Learning Help us Predict Banking Crises?
Johannes Beutel, Sophia List, Gregor von Schweinitz
Journal of Financial Stability,
December
2019
Abstract
This paper compares the out-of-sample predictive performance of different early warning models for systemic banking crises using a sample of advanced economies covering the past 45 years. We compare a benchmark logit approach to several machine learning approaches recently proposed in the literature. We find that while machine learning methods often attain a very high in-sample fit, they are outperformed by the logit approach in recursive out-of-sample evaluations. This result is robust to the choice of performance metric, crisis definition, preference parameter, and sample length, as well as to using different sets of variables and data transformations. Thus, our paper suggests that further enhancements to machine learning early warning models are needed before they are able to offer a substantial value-added for predicting systemic banking crises. Conventional logit models appear to use the available information already fairly efficiently, and would for instance have been able to predict the 2007/2008 financial crisis out-of-sample for many countries. In line with economic intuition, these models identify credit expansions, asset price booms and external imbalances as key predictors of systemic banking crises.
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