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We analyze the relationship between asset price bubbles and systemic risk, using bank-level data covering almost 30 years. Banks’ systemic risk already rises during a bubble’s buildup and even more so during its bust. The increase in risk strongly differs across banks and by bubble. It depends on bank characteristics (especially bank size) and bubble characteristics and can become very large: in a median real estate bust, systemic risk increases by almost 70% of the median for banks with unfavorable characteristics. These results emphasize the importance of bank-level factors in the buildup of financial fragility during bubble episodes.Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

Many business sectors and households face an unprecedented loss of income in the current COVID-19 recession, triggering financial distress, separations, and bankruptcy. Rather than stimulating demand, government policy’s main aim should be to provide insurance to firms and workers to avoid undue scarring that will hamper a recovery once the pandemic is past. We develop a corporate finance framework to guide interventions in credit markets to avoid such scarring. We emphasize three main results. First, policy should inject liquidity into small and medium-sized firms that are liquidity constrained and for which social costs of bankruptcy are high. Second, large firms for whom solvency is the dominant issue require a more nuanced approach. Debt overhang creates a distortion, leading these firms to fire workers, forgo expenditures that maintain enterprise value, and delay filing for a Chapter 11 bankruptcy longer than is socially efficient. Government resources toward reducing the legal and financial costs of bankruptcy are unambiguously beneficial. Policies that reduce funding costs are only socially desirable if the pandemic is expected to be short-lived and if bankruptcy costs are high. Last, transfers necessary to avoid bankruptcy allow borrowers to continue paying their mortgages or credit card bills and ultimately benefit owners of assets such as real estate or credit card receivables. Taxes to fund transfers should be raised from these asset owners. © 2020, Brookings Institution Press. All rights reserved.

This paper examines the contribution of non-interest income to systemic bank risk. Using the ∆CoVaR measure of Adrian and Brunnermeier (2010) as our proxy for systemic risk, we find banks with a higher non-interest income to interest income ratio have a higher contribution to systemic risk. This suggests that activities that are not traditionally associated with banks (such as deposit taking and lending) are associated with a larger contribution to systemic risk. When we decompose total non-interest income into three components, we find trading income and investment banking and venture capital income to be significantly related to systemic risk. The economic impact on systemic risk of investment banking and venture capital income is higher than that of trading income. Finally we find the impact of non-interest income on systemic risk to be prevalent in the 1990 and 2007 financial crises (which were bank based) and not in the case before the 2001 high tech bubble bust. These effects occur one-year before each crisis and not during the recession, showing their countercyclical contribution to systemic risk build-up.

China's economic model involves active government intervention in financial markets. We develop a theoretical framework in which interventions prevent a market breakdown and a volatility explosion caused by the reluctance of short-term investors to trade against noise traders. In the presence of information frictions, the government can alter market dynamics since the noise in its intervention program becomes an additional factor driving asset prices. More importantly, this may divert investor attention away from fundamentals and totally toward government interventions (as a result of complementarity in investors' information acquisition). A trade-off arises: government's objective to reduce asset price volatility may worsen, rather than improve, information efficiency of asset prices.

Great power competition is back. As China and the United States ramp up their strategic rivalry, the search is on for a vision of what their evolving great power competition will look like in a glo...

The ongoing digital revolution may lead to a radical departure from the traditional model of monetary exchange. We may see an unbundling of the separate roles of money, creating fiercer competition among specialized currencies. On the other hand, digital currencies associated with large platform ecosystems may lead to a re-bundling of money in which payment services are packaged with an array of data services, encouraging differentiation but discouraging interoperability between platforms. Digital currencies may also cause an upheaval of the international monetary system: countries that are socially or digitally integrated with their neighbors may face digital dollarization, and the prevalence of systemically important platforms could lead to the emergence of digital currency areas that transcend national borders. Central bank digital currency (CBDC) ensures that public money remains a relevant unit of account.

This paper studies a major financial panic, the run on the German banking system in 1931, to distinguish between banking theories that view depositors as demanders of liquidity and those that view them as providers of discipline. Our empirical approach exploits the fact that the German Crisis of 1931 was system-wide with cross-sectional variation in deposit flows as well as bank distress and took place in absence of a deposit insurance scheme. We find that interbank deposit flows predict subsequent bank distress early on. In contrast, wholesale depositors are more likely to withdraw from distressed banks at later stages of the run and only after the interbank market has started to collapse. Retail deposits are—despite the absence of deposit insurance—largely stable. Our findings emphasize the heterogeneity in depositor roles, with discipline being best provided through the interbank market.

International capital flows are fickle. Short-term debt funding is especially subject to sudden stops. Sudden flight into safe-haven currencies can cause large disruptions and sharp currency movements ultimately leading to a crisis. When markets shift from a risk-on to a risk-off mood cross-country capital flows are triggered if the safe asset is not supplied symmetrically across counties. Advanced economies which supply safe assets experience capital inflows while most emerging economies suffer sudden outflows. Hence the design of global safe assets is paramount in creating a stable global financial architecture.

Why do some firms, especially financial institutions, finance themselves so shortterm? We show that extreme reliance on short-term financing may be the outcome of a maturity rat race: a borrower may have an incentive to shorten the maturity of an individual creditor’s debt contract because this dilutes other creditors. In response, other creditors opt for shorter maturity contracts as well. This dynamic toward short maturities is present whenever interim information is mostly about the probability of default rather than the recovery in default. For borrowers that cannot commit to a maturity structure, equilibrium financing is inefficiently short-term. ONE OF THE CENTRAL lessons of the financial crisis of 2007‐2009 is the importance of maturity structure for financial stability: the crisis vividly exposed the vulnerability of institutions with strong maturity mismatch—those who finance themselves short-term and invest long-term—to disruptions in their funding liquidity. This raises the question of why firms and, in particular, financial institutions, use so much short-term financing, even if this exposes them to significant rollover risk? In this paper, we argue that excessive reliance on short-term financing may be the outcome of an inefficient dynamic that we call the maturity rat race. To demonstrate this point, we develop a model of the equilibrium maturity structure for a borrower who borrows from multiple creditors to finance longterm investments. When this borrower cannot commit to an aggregate maturity structure, the equilibrium maturity structure may be inefficiently shortterm—leading to excessive maturity mismatch, unnecessary rollover risk, and inefficient creditor runs. This dynamic may be particularly hard to counteract for financial institutions, for which it is especially difficult and often privately undesirable to commit to a maturity structure in order to prevent this dynamic.

What is the role of leaders in large organizations? We propose a model in which a leader helps to overcome a misalignment of followers' incentives that inhibits coordination, while adapting the organization to a changing environment. Good leadership requires vision and special personality traits such as conviction or resoluteness to enhance the credibility of mission statements and to effectively rally agents around them. Resoluteness allows leaders to overcome a time-consistency problem that arises from the fact that leaders learn about the best course of action for the organization over time. However, resoluteness also inhibits bottom-up information flow from followers. The optimal level of resoluteness depends on followers' signal quality and the corporate culture of the organization. Copyright 2013, Oxford University Press.

We propose a simple model of the sovereign-bank diabolic loop, and establish four results. First, the diabolic loop can be avoided by restricting banks’ domestic sovereign exposures relative to their equity. Second, equity requirements can be lowered if banks only hold senior domestic sovereign debt. Third, such requirements shrink even further if banks only hold the senior tranche of an internationally diversified sovereign portfolio – known as ESBies in the euro-area context. Finally, ESBies generate more safe assets than domestic debt tranching alone; and, insofar as the diabolic loop is defused, the junior tranche generated by the securitization is itself risk-free.

The euro crisis was fueled by the diabolic loop between sovereign risk and bank risk, coupled with cross-border flight-to-safety capital flows. European Safe Bonds (ESBies), a union-wide safe asset without joint liability, would help to resolve these problems. We make three contributions. First, numerical simulations show that ESBies would be at least as safe as German bunds and approximately double the supply of euro safe assets when protected by a 30%-thick junior tranche. Second, a model shows how, when and why the two features of ESBies – diversification and seniority – can weaken the diabolic loop and its diffusion across countries. Third, we propose a step-by-step guide on how to create ESBies, starting with limited issuance by public or private-sector entities.

This chapter puts forward a manual for how to setup and solve a continuous time model that allows to analyze endogenous (1) level and risk dynamics. The latter includes (2) tail risk and crisis probability as well as (3) the Volatility Paradox. Concepts such as (4) illiquidity and liquidity mismatch, (5) endogenous leverage, (6) the Paradox of Prudence, (7) undercapitalized sectors (8) time-varying risk premia, and (9) the external funding premium are part of the analysis. Financial frictions also give rise to an endogenous (10) value of money.

This paper introduces notions from computational complexity into the study of financial derivatives. Traditional economics argues that derivatives, like CDOs and CDSs, ameliorate the negative costs imposed due to asymmetric information between buyers and sellers. This is because securitization via these derivatives allows the informed party to find buyers for the information-insensitive part of the cash flow stream of an asset (e.g., a mortgage) and retain the remainder. In this paper we show that this viewpoint may need to be revised once computational complexity is brought into the picture. Assuming reasonable complexity-theoretic conjectures, we show that derivatives can actually amplify the costs of asymmetric information instead of reducing them. We prove our results both in the worst-case setting, as well as the more realistic average case setting. In the latter case, to argue that our constructions result in derivatives that “look like” real-life derivatives, we use the notion of computational indistinguishability a la cryptography.

This paper documents that hedge funds did not exert a correcting force on stock prices during the technology bubble. Instead, they were heavily invested in technology stocks. This does not seem to be the result of unawareness of the bubble: Hedge funds captured the upturn, but, by reducing their positions in stocks that were about to decline, avoided much of the downturn. Our findings question the efficient markets notion that rational speculators always stabilize prices. They are consistent with models in which rational investors may prefer to ride bubbles because of predictable investor sentiment and limits to arbitrage. TECHNOLOGY STOCKS ON NASDAQ ROSE to unprecedented levels during the 2 years leading up to March 2000. Ofek and Richardson (2002) estimate that at the peak, the entire internet sector, comprising several hundred stocks, was priced as if the average future earnings growth rate across all these firms would exceed the growth rates experienced by some of the fastest growing individual firms in the past, and, at the same time, the required rate of return would be 0% for the next few decades. By almost any standard, these valuation levels are so extreme that this period appears to be another episode in the history of asset price bubbles. Shiller (2000) argues that the stock price increase was driven by irrational euphoria among individual investors, fed by an emphatic media, which maximized TV ratings and catered to investor demand for pseudonews. Of course, only few economists doubt that there are both rational and irrational market participants. However, there are two opposing views about whether rational traders correct the price impact of behavioral traders. Proponents of the

The recent financial crisis and the difficulty of using mainstream macroeconomic models to accurately monitor systemic risk have stimulated new analyses of how we measure economic activity and the development of more sophisticated models in which the financial sector plays a greater role. Markus Brunnermeier and Arvind Krishnamurthy have assembled contributions from researchers, central bankers, and other financial-market experts to explore the possibilities for advancing macroeconomic modeling in order to achieve more accurate measurement. Essays focus on the development of models capable of highlighting the vulnerabilities that have never been systematically measured before.

Financial institutions may be vulnerable to predatory short selling. When the stock of a financial institution is shorted aggressively, leverage constraints imposed by short-term creditors can force the institution to liquidate long-term investments at fire sale prices. For financial institutions that are sufficiently close to their leverage constraints, predatory short selling equilibria co-exist with no-liquidation equilibria (the vulnerability region), or may even be the unique equilibrium outcome (the doomed region). Increased coordination among short sellers expands the doomed region, where liquidation is the unique equilibrium. Our model provides a potential justification for temporary restrictions of short selling for vulnerable institutions and can be used to assess recent empirical evidence on short-sale bans.

This article surveys the macroeconomic implications of nancial frictions. Financial frictions lead to persistence and when combined with illiquidity to nonlinear amplication eects.

The purpose of this paper is to examine the measurement of liquidity in light of the academic research on liquidity. We present a theoretical liquidity measure, informed by the academic literature on liquidity, and analyze its benefits in terms of assessing liquidity risk both from a firm and macro-prudential perspective.

This chapter surveys the literature on bubbles, financial crises, and systemic risk. The first part of the chapter provides a brief historical account of bubbles and financial crisis. The second part of the chapter gives a structured overview of the literature on financial bubbles. The third part of the chapter discusses the literatures on financial crises and systemic risk, with particular emphasis on amplification and propagation mechanisms during financial crises, and the measurement of systemic risk. Finally, we point toward some questions for future research.

This paper documents that banks with higher non-interest income (noncore activities like investment banking, venture capital and trading activities) have a higher contribution to systemic risk than traditional banking (deposit taking and lending). After decomposing total non-interest income into two components, trading income and investment banking and venture capital income, we find that both components are roughly equally related to systemic risk. These results are robust to endogeneity concerns when we use a difference-in-difference approach with the Lehman bankruptcy proxying for an exogenous shock. We also find that banks with higher trading income one-year prior to the recession earned lower returns during the recession period. No such significant effect was found for investment banking and venture capital income.

At this year’s conference two panel discussions have been organized to address the most recent financial crisis and the associated policy implications. We recommend that you highlight your program schedule to ensure your participation in these engaging panel sessions.

What makes a good leader? A good leader is able to coordinate his followers around a credible mission statement, which communicates the future course of action of the organization. In practice, leaders learn about the best course of action for the organization over time. While learning helps improve the organization's goals it also creates a time-consistency problem. Leader overconfidence is a valuable attribute in such a setting, since it slows down the leader's learning and thus improves the credibility of the mission statement. But overconfident leaders also inhibit communication with followers and leader overconfidence is costly when followers have sufficiently valuable signals.

We provide a model that links an asset's market liquidity (i.e., the ease with which it is traded) and traders' funding liquidity (i.e., the ease with which they can obtain funding). Traders provide market liquidity, and their ability to do so depends on their availability of funding. Conversely, traders' funding, i.e., their capital and margin requirements, depends on the assets' market liquidity. We show that, under certain conditions, margins are destabilizing and market liquidity and funding liquidity are mutually reinforcing, leading to liquidity spirals. The model explains the empirically documented features that market liquidity (i) can suddenly dry up, (ii) has commonality across securities, (iii) is related to volatility, (iv) is subject to "flight to quality," and (v) co-moves with the market. The model provides new testable predictions, including that speculators' capital is a driver of market liquidity and risk premiums. The Author 2008. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please e-mail: journals.permissions@oxfordjournals.org., Oxford University Press.

Focuses on dynamic models. The emphasis is on explaining technical analysis. These models show that past prices still carry valuable information. Some of these models also explain why it is rational for some investors to ‘chase the trend’. Other models are devoted to the informational role of trading volume. The insiders’ optimal dynamic trading strategy over different trading periods is derived in a strategic model setting.

Ch. 2 first exposes the reader to a more tractable notion of common knowledge and the intuition behind proofs of the different no‐trade theorems. The no‐trade theorems state the specific conditions under which differences in information alone do not lead to trade. The next section sketches out a brief introduction of the basics of asset pricing under symmetric information and highlights the complications that can arise under asymmetric information. Information revelation by prices is closely linked to the security structure and market completeness. The chapter also provides definitions of bubbles and investigates the existence of bubbles under common knowledge. It then illustrates the importance of higher‐order uncertainty for the possible existence of bubbles.

Asset prices are driven by public news and information that is dispersed among many market participants. Traditional asset pricing theories have assumed that all investors hold symmetric information. Research in the past two decades has shown that the inclusion of asymmetric information drastically alters traditional results. This book provides a detailed up‐to‐date survey that serves as a map for students and other researchers navigating through this literature. The book starts by introducing the reader to different knowledge, equilibrium, and efficiency concepts. After explaining no‐trade theorems, it highlights the important role of asymmetric information in explaining the existence and anatomy of bubbles. The subsequent overview of market microstructure models shows how information is reflected in prices and how traders can infer it from prices. Insights derived from herding models are used to provide explanations for stock market crashes. If investors have short horizons, price correcting arbitrage activity is limited and investors have a tendency to focus on the same (possible unimportant) news, a phenomena that led Keynes to compare the stock market with a beauty contest. The book concludes with a brief summary of bank runs and their connection to financial crises. In summary, models with asymmetric information provide a better understanding of bubbles, crashes, and other market inefficiencies and frictions.

This chapter shows that herding can help to explain many empirical phenomena in finance, like stock market crashes. In a setting with widely dispersed information, even relatively unimportant news can lead to large price swings and crashes. Stock market crashes can also occur because of liquidity problems, bursting bubbles, and sunspots. Traders might also herd in information acquisition if they care about the short‐term price path as well as about the long‐run fundamental value. Under these circumstances all traders will try to gather the same piece of information. These models also provide a deeper understanding of Keynes’ comparison of the stock market with a beauty contest. Limits to arbitrage are discussed and it is shown that if investors focus on the short‐run, corporate decision‐making also becomes shortsighted. The chapter concludes with a brief summary of bank runs and its connection to financial crises.

We use a rational expectations model to examine how public disclosure requirements affect listing decisions by rent-seeking corporate insiders, and allocation decisions by liquidity traders seeking a minimize trading costs. We find that exchanges competing for trading volume engage in a ¶race for the top¶ whereunder disclosure requirements increase and trading costs fall. This result is robust to diversification incentives of risk-averse liquidity traders, institutional impediments that restrict the flow of liquidity, and listing costs. Under certain conditions, unrestricted liquidity flows to low disclosure exchanges. The consequences of cross-listing and harmonization of disclosure standards are modelled.