Research articles for the 2020-11-02

A Convergent Linear Regression Method for Forward-Backward Stochastic Differential Equations with Jumps
Tingting Ye,Liangliang Zhang

In this paper, we introduce a large class of convergent numerical methods, based on (linear) basis function regression technique, to approximate the solution to a forward-backward stochastic differential equation with jumps (FBSDEJ hereafter). Numerical experiment shows good applicability of the proposed method.

A Dual Characterisation of Regulatory Arbitrage for Coherent Risk Measures
Herdegen, Martin,Khan, Nazem
We revisit mean-risk portfolio selection in a one-period financial market where risk is quantified by a positively homogeneous risk measure ρ on L1. We first show that under mild assumptions, the set of optimal portfolios for a fixed return is nonempty and compact. However, unlike in classical mean-variance portfolio selection, it can happen that no efficient portfolios exist. We call this situation regulatory arbitrage, and prove that it cannot be excluded â€" unless ρ is as conservative as the worst-case risk measure.After providing a primal characterization, we focus our attention on coherent risk measures, and give a necessary and sufficient characterization for regulatory arbitrage. We show that the presence or absence of regulatory arbitrage for ρ is intimately linked to the interplay between the set of equivalent martingale measures (EMMs) for the discounted risky assets and the set of absolutely continuous measures in the dual representation of ρ. A special case of our result shows that the market does not admit regulatory arbitrage for Expected Shortfall at level α if and only if there exists an EMM Q ≈ P such that ll dQ/dP ll∞ < 1/α.

A note on the option price and "Mass at zero in the uncorrelated SABR model and implied volatility asymptotics"
Jaehyuk Choi,Lixin Wu

Gulisashvili et al. [Quant. Finance, 2018, 18(10), 1753-1765] provide a small-time asymptotics for the mass at zero under the uncorrelated SABR model by approximating the integrated variance with a moment-matched lognormal distribution. We improve the accuracy of the numerical integration by using the Gauss-Hermite quadrature. We further obtain the option price by integrating the CEV option prices in the same manner without resorting to the small-strike volatility smile asymptotics of De Marco et al. [SIAM J. Financ. Math., 2017, 8(1), 709-737]. For the uncorrelated SABR model, the new method of option pricing is accurate and arbitrage-free across all strike prices.

Adaptive Bernstein Copulas and Risk Management
Dietmar Pfeifer,Olena Ragulina

We present a constructive approach to Bernstein copulas with an admissible discrete skeleton in arbitrary dimensions when the underlying marginal grid sizes are smaller than the number of observations. This prevents an overfitting of the estimated dependence model and reduces the simulation effort for Bernstein copulas a lot. In a case study, we compare different approaches of Bernstein and Gaussian copulas w.r.t. the estimation of risk measures in risk management.

An Analysis of Public Sector Banks’ Performance using CAMEL Rating Model
Singhal, Parmod Kumar
Banks form the fundamental component of the financial system of any economy. Soundness of the banking sector is, therefore, essential for a healthy and vibrant economy. Nowadays, the financial system of the Indian economy is completely interlinked with the banking sector. If something goes wrong with the banking industry, the entire financial system will collapse. So, it is necessary to evaluate and measure the strength of the banking industry so that our economy improves efficiently. In this study, an attempt has been made to measure the financial position and performance of public sector banks, ranking them accordingly. For this purpose 21 Indian public sector banks have been taken into consideration, over a period of ten years, i.e. 2008-2009 to 2018-2019. The study is based on secondary data which has been collected through capitaline database and annual financial statements of the respective banks. The CAMEL model has been used to measure the performance of the banks. Findings from the analysis indicates that Indian public sector banks are making an effort toward maintaining adequate capital, and in years to come, all banks should strive toward achieving more than the required level. Public sector banks need to brainstorm innovative ideas, which can help them deploy funds after proper analysis of the risk exposure.

Asset Allocation via Machine Learning and Applications to Equity Portfolio Management
Qing Yang,Zhenning Hong,Ruyan Tian,Tingting Ye,Liangliang Zhang

In this paper, we document a novel machine learning based bottom-up approach for static and dynamic portfolio optimization on, potentially, a large number of assets. The methodology overcomes many major difficulties arising in current optimization schemes. For example, we no longer need to compute the covariance matrix and its inverse for mean-variance optimization, therefore the method is immune from the estimation error on this quantity. Moreover, no explicit calls of optimization routines are needed.

Applications to a bottom-up mean-variance-skewness-kurtosis or CRRA (Constant Relative Risk Aversion) optimization with short-sale portfolio constraints in both simulation and real market (China A-shares and U.S. equity markets) environments are studied and shown to perform very well.

Asset Protection-State Guarantee Schemes in Systemic European Non-Performing Loans Securitisations: Contractual Structure, State Aid and Bank Corporate Law Issues
Linaritis, Ioannis
In the prolonged battle against european non-performing loans (NPLs) and systemic risk, Authorities have ultimately devised and made available to the affected credit institutions an additional resolution tool. Securitisation schemes, backed by a limited State guarantee, only for the senior tranche part under detailed conditions, have been legislated almost identically in Italy and Greece. Those “Asset Protection Schemes” are viewed as laboratory cases for a model co-investment (private-public) strategy, with the ambition to transform the EU banking environment and correct national NPL markets failures. The Article, originating from the distinctive implications of impaired loan portfolios’ securitisations, focuses on the contractual architecture of the Schemes and the roles of major contracting parties (originating credit institution, Issuer, Noteholders, Servicer, State, Rating Agency etc.). Funding of the portfolio acquisition is discussed from both legal and financial perspectives, revealing the important differences of securities tranches (senior, mezzanine, junior notes), their economic function and appeal to investors. Designated State involvement is depicted with emphasis on the legal nature and conditions of the offered “first-demand” guarantee, including its relevant remuneration. From the EU state-aid perspective, Schemes are assessed as aid-free measures, consistent with potential private operators’ commercial activity under normal market conditions. Such a conclusion is drawn after appraisal ofmodel securitisation’s voluntary nature, risk allocation structure, a model-based approach for the calculation of State guarantee fee (factoring appropriate risk premia with adjusted benchmarking), and additional mechanisms to control and mitigate State’s risk.Implementation of Schemes is advocated, on the condition that bank executives and board members comply with detailed organizational and procedural requirements of EU banking regulation, to ensure prudent risk management and financial stability. Competence of the Board and pursuit of corporate best interests are being challenged in cases of largest NPL securitisations, involving substantial bank assets which may provoke ample one-off accounting losses or even risk-weighted capital depletion. Sound business judgment is associated with an objective evaluation of existing NPL resolution alternative options, careful measurement of medium-to-long-term benefits of the cornerstone securitisation transaction along with its imminent consequences, risks, and inherently limited accessibility of the State guarantee regime. Due fulfillment of bank directors and executives’ obligations extends to the application of a coherent methodology in the preparation, structuring and execution of securitisations. They should apply a transparent and efficient investor-selection procedure, and employ internal resources and specialist financial and legal advisors to obtain expert advice on best calibration of securitisation particulars, fair and reasonable terms of the transaction, and to maximize total divestment proceeds. Legal agreements and related capital implications should be carefully and timely consulted with the Authorities, to ensure securitisation significant risk transfer recognition and avoid its potential adverse unwinding. Overall, transaction losses must prove proportionate to the deleverage benefits for the credit institution itself and the enhancement of financial stability. In those respects, the Article contributes to the evaluation of such newly established EU public policy measure for NPL resolution, particularly from the involved bank corporate and market participants’ perspective, along with its technical roadmap for dueimplementation.

Asymptotics for volatility derivatives in multi-factor rough volatility models
Chloe Lacombe,Aitor Muguruza,Henry Stone

We present small-time implied volatility asymptotics for Realised Variance (RV) and VIX options for a number of (rough) stochastic volatility models via large deviations principle. We provide numerical results along with efficient and robust numerical recipes to compute the rate function; the backbone of our theoretical framework. Based on our results, we further develop approximation schemes for the density of RV, which in turn allows to express the volatility swap in close-form. Lastly, we investigate different constructions of multi-factor models and how each of them affects the convexity of the implied volatility smile. Interestingly, we identify the class of models that generate non-linear smiles around-the-money.

Banks as Liquidity Multipliers
Carre, Sylvain,Klossner, Damien
Banks hold large amounts of high-quality liquid assets while relying predominantly on deposit funding. The return on these assets is often lower than the cost of deposits. Why do banks engage in such a negative carry trade? Using a novel observation on global games, we build a tractable model where banks manage liquidity risk by adjusting the size of their short-term liabilities and of their liquid reserves consisting of safe, liquid government bonds. Banks are the natural buyers of government bonds because holding these assets enables them to "multiply liquidity'': using one unit of bonds to back more than one unit of short-term debt while keeping their liquidity risk unchanged. How much more is measured by the slope of an endogenous iso-risk curve. This liquidity multiplier is key to understand a bank's joint choice of leverage and liquid reserves and how these decisions connect to the pricing of liquid assets. In turn, this provides an explanation of the negative carry puzzle.

Bear Markets and Recessions versus Bull Markets and Expansions
Abdulnasser Hatemi-J

This paper examines the dynamic interaction between falling and rising markets for both the real and the financial sectors of the largest economy in the world using asymmetric causality tests. These tests require that each underlying variable in the model be transformed into partial sums of the positive and negative components. The positive components represent the rising markets and the negative components embody the falling markets. The sample period covers some part of the COVID19 pandemic. Since the data is non normal and the volatility is time varying, the bootstrap simulations with leverage adjustments are used in order to create reliable critical values when causality tests are conducted. The results of the asymmetric causality tests disclose that the bear markets are causing the recessions as well as the bull markets are causing the economic expansions. The causal effect of bull markets on economic expansions is higher compared to the causal effect of bear markets on economic recessions. In addition, it is found that economic expansions cause bull markets but recessions do not cause bear markets. Thus, the policies that remedy the falling financial markets can also help the economy when it is in a recession.

Benchmarking Intensity
Pavlova, Anna,Sikorskaya, Taisiya
A fund manager evaluated relative to a benchmark index optimally invests a fraction of the fund's assets under management (AUM) in her benchmark, and such demand is inelastic. Using a dataset of 33 U.S. equity indices, we construct a stock-level measure of benchmarking intensity (BMI), which captures the inelastic component of fund managers' demand. The BMI of a stock is computed as the cumulative weight of the stock in all benchmarks, weighted by AUM following each benchmark. We extract benchmark histories from fund prospectuses available as unstructured text. Exploiting a variation in the BMIs of stocks that transition between the Russell 1000 and Russell 2000 indices, we confirm the prediction of our theory that stocks with higher BMIs have lower long-run returns. Furthermore, using fund holdings around the index cutoff, we find evidence of inelastic demand of active managers for stocks in their benchmarks. The change in BMI resulting from an index reconstitution is positively related to the size of the index effect and allows us to compute the price elasticity of demand more accurately than in the literature. Finally, we show how considerations of optimized sampling and the growth of the CRSP indices may affect identification in studies that exploit the Russell cutoff.

Born in Crisis: Early Impact of COVID-19 Pandemic on P2P Lending Market
Nigmnov, Asror,Shams, Syed,Alam, Khorshed
This paper empirically investigates the impact of COVID-19 pandemic on liquidity risk incurred by peer-to-peer (P2P) lending market. As the COVID-19 pandemic adversely affects the financial markets, there is a need for better understanding of the dynamics of successful P2P lending under the conditions of financial distress. Using the secondary market listings dataset of Bondora P2P lending platform based in Estonia, we provide evidence of the pandemic induced exposure to liquidity risk in P2P lending market. Despite increased volatility in the financial markets, the results show that COVID-19 risk increases the probability of successful listing during the period of a pandemic. Further analysis shows that there is a negative association between COVID-19 risk and share of overdue loans and average overdue days in the secondary market listings. Our results are robust to sample selection bias through Heckman two-stage regression models and bootstrapping. The findings of this study imply certain early tendencies in the financial market during the pandemic induced turmoil and open broad room for further research.

Bounds on Multi-asset Derivatives via Neural Networks
Luca De Gennaro Aquino,Carole Bernard

Using neural networks, we compute bounds on the prices of multi-asset derivatives given information on prices of related payoffs. As a main example, we focus on European basket options and include information on the prices of other similar options, such as spread options and/or basket options on subindices. We show that, in most cases, adding further constraints gives rise to bounds that are considerably tighter and discuss the maximizing/minimizing copulas achieving such bounds. Our approach follows the literature on constrained optimal transport and, in particular, builds on a recent paper by Eckstein and Kupper (2019, Appl. Math. Optim.).

Causal Campbell-Goodhart's law and Reinforcement Learning
Hal Ashton

Campbell-Goodhart's law relates to the causal inference error whereby decision-making agents aim to influence variables which are correlated to their goal objective but do not reliably cause it. This is a well known error in Economics and Political Science but not widely labelled in Artificial Intelligence research. Through a simple example, we show how off-the-shelf deep Reinforcement Learning (RL) algorithms are not necessarily immune to this cognitive error. The off-policy learning method is tricked, whilst the on-policy method is not. The practical implication is that naive application of RL to complex real life problems can result in the same types of policy errors that humans make. Great care should be taken around understanding the causal model that underpins a solution derived from Reinforcement Learning.

Competition and Exchange Data Fees
Brogaard, Jonathan,Brugler, James
Exchanges are monopolist suppliers of their own order book data. We examine three events where exchanges begin charging a fee for order book data for the first time and test whether or not these fees affect their market share in a difference-in-differences setting. We find that the introduction of fees leads to a fall of market share of around 5-8 percent. Examining average trading costs, price impact and dealer revenue per trade around the events indicates that order routing decisions of informed traders are relatively more sensitive to order book data fees than other trader categories.

Competition in Fund Management and Forward Relative Performance Criteria
Michail Anthropelos,Tianran Geng,Thaleia Zariphopoulou

In an Ito-diffusion market, two fund managers trade under relative performance concerns. For both the asset specialization and diversification settings, we analyze the passive and competitive cases. We measure the performance of the managers' strategies via forward relative performance criteria, leading to the respective notions of forward best-response criterion and forward Nash equilibrium. The motivation to develop such criteria comes from the need to relax various crucial, but quite stringent, existing assumptions -- such as, the a priori choices of both the market model and the investment horizon, the commonality of the latter for both managers as well as the full a priori knowledge of the competitor's policies for the best-response case. We focus on locally riskless criteria and deduce the random forward equations. We solve the CRRA cases, thus also extending the related results in the classical setting. An important by-product of the work herein is the development of forward performance criteria for investment problems in Ito-diffusion markets under the presence of correlated random endowment process for both the perfectly and the incomplete market cases.

Confirmation Bias in Analysts’ Response to Consensus Forecasts
Cai, Huan,Yao, Tong,Zhang, Xiaodi
This paper provides evidence of confirmation bias by sell-side analysts in their earnings forecasts. We show that analysts tend to put higher weight on public information when the current forecast consensus is more consistent with their previous forecasts. Our results further suggest that the effect of confirmation bias on analyst forecasts is distinct from that of conservatism, self-attribution bias, or overconfidence. We find that analysts with better forecasting performance, shorter experience following a firm, providing earlier forecasts, or facing more dispersion in peer forecasts, tend to be less subject to confirmation bias, consistent with existing cognitive and social psychology theories.

Cross-Border M&A and Currency Returns
Riddiough, Steven,Zhang, Huizhong
We uncover a novel source of currency return predictability stemming from cross-border merger and acquisition (M&A) activity: abnormally large M&A inflows lead exchange rate appreciations, while depreciations follow unusually large M&A outflows. We show that a simple cross-sectional currency strategy exploiting this predictability generates a Sharpe ratio of over 0.70 and is orthogonal to existing currency strategies. The portfolio weights are found to coincide with local extremes in macroeconomic fundamentals: countries experiencing the largest abnormal M&A outflows are growing most above their economic growth trend---a pattern that reverses following portfolio formation---while the opposite reversal in macroeconomic fundamentals is observed in countries experiencing unusually large M&A inflows.

Did the Federal Reserve Break the Phillips Curve? Theory and Evidence of Anchoring Inflation Expectations
Bundick, Brent,Smith, Andrew
In a macroeconomic model with drifting long-run inflation expectations, the anchoring of inflation expectations manifests in two testable predictions. First, expectations about inflation far in the future should no longer respond to news about current inflation. Second, better anchored inflation expectations weaken the relationship between unemployment and inflation, flattening the reduced-form Phillips curve. We evaluate both predictions and find that communication of a numerical inflation objective better anchored inflation expectations in the US but failed to anchor expectations in Japan. Moreover, the improved anchoring of US inflation expectations can account for much of the observed flattening of the Phillips curve. Finally, we present evidence that initial Federal Reserve communication around its longer-run inflation objective may have led inflation expectations to anchor at a level below 2 percent.

Duality and deep learning for optimal consumption with randomly terminating income
Ashley Davey,Michael Monoyios,Harry Zheng

We establish a rigorous duality theory for a finite horizon problem of optimal consumption in the presence of an income stream that can terminate randomly at an exponentially distributed time, independent of the asset prices. We thus close a duality gap encountered by Vellekoop and Davis in an infinite horizon version of this problem. Nearly all the classical tenets of duality theory are found to hold, with the notable exception that the marginal utility of initial wealth at zero is finite. The intuition is that the agent will receive some income, no matter how early it terminates, so is not infinitely penalised for having zero initial capital. We then solve the problem numerically, with an additional terminal wealth objective, using deep learning. We transform the problem with randomly terminating income into one that no longer depends on the jump component but has an additional inter-temporal wealth objective. We then numerically solve the second order backward stochastic differential equations (2BSDEs), in both the primal and dual dimensions, to find the optimal control and tight lower and upper bounds for the value function.

Economic Consequences of Auditor Reputation Loss: Evidence from the Audit Inspection Scandal
McKenna, Francine,Pevzner, Mikhail,Sheneman, Amy,Zach, Tzachi
We examine whether the 2017 audit inspection scandal affected KPMG’s client relationships andaudit quality. Using the trial transcripts, we construct a novel dataset of KPMG clients whose auditengagements were compromised by information leakage from the PCAOB (Transcript Sample). We then examine KPMG’s response to this regulatory data theft scandal. Our findings suggest anincreased departure rate following the public revelation of the scandal of clients in the TranscriptSample but not in the broad portfolio of KPMG clients. While KPMG’s audit fees do not appearto have changed, we find a reduction of KPMG’s non-audit fees, which is concentrated in theTranscript Sample clients. Finally, we find that the quality of loan loss provisions of banking clients in the Transcript Sample decreased after the scandal. Overall, our results suggest the audit inspection scandal has imposed costs on both KPMG and its PCAOB-inspected clients whose identities were exposed.

Equity warrant pricing under subdiffusive fractional Brownian motion of the short rate
Foad Shokrollahi,Marcin Marcin Magdziarz

In this paper we propose an extension of the Merton model. We apply the subdiffusive mechanism to analyze equity warrant in a fractional Brownian motion environment, when the short rate follows the subdiffusive fractional Black-Scholes model. We obtain the pricing formula for zero-coupon bond in the introduced model and derive the partial differential equation with appropriate boundary conditions for the valuation of equity warrant. Finally, the pricing formula for equity warrant is provided under subdiffusive fractional Brownian motion model of the short rate.

Fencing Off Silicon Valley: Cross-Border Venture Capital and Technology Spillovers
Akcigit, Ufuk,Ates, Sina,Lerner, Josh,Townsend, Richard,Zhestkova, Yulia
The treatment of foreign investors has been a contentious topic in U.S. entrepreneurship policy in recent years. This paper examines foreign corporate investments in Silicon Valley from a theoretical and empirical perspective. We model a setting where such funding may allow U.S. entrepreneurs to pursue technologies that they could not otherwise, but may also lead to spillovers to the overseas firm providing the financing and the nation where it is based. We show that despite the benefits from such inbound investments for U.S. firms, it may be optimal for the U.S. government to raise their costs to deter investments. Using as comprehensive as possible a sample of investments by non-U.S. corporate investors in U.S. start-ups between 1976 and 2015, we find evidence consistent with the presence of knowledge spill-overs to foreign investors.

Financial Literacy, Internet Dependency, and Internet Finance
Ran, Zhenkai
Does the digital transformation of financial services make the financial system more inclusive? Utilizing the China Household Finance Survey (CHFS) data, this study explores the impact of financial literacy and the degree of Internet dependency on household financial asset allocation. The study finds that Internet finance mainly attracts investors with a lower financial sophistication, a stark contrast to my finding concerning participation in the traditional financial market. This result suggests that Internet finance can fill the funding gaps where investors traditionally face high participation costs and, thus, improve financial inclusion. Moreover, I show that one's degree of Internet dependency is positively associated with the participation in Internet finance, indicating that local Internet infrastructure can be an essential prerequisite for an economy to promote financial inclusion through the Internet finance. Meanwhile, a digital transformation of an economy may potentially result in an over-allocation of capital to risky assets, provided that Internet finance is often associated with high 'long tail' risks. My conclusion remains robust to investigating 'exclusive' participation in each financial asset class and using alternative measures of Internet dependency and financial literacy.

Fund Flows and Performance Under Dynamic Unobservable Managing Ability
Feldman, David,Xu, Jingrui
We introduce continuous-time rational models of dynamic unobservable fund manager abilities with risk-neutral or risk-averse investors. We follow the innovative Berk and Green (2004) and subsequent models, where risk-neutral investors learn, with monotonic precisions, managers’ abilities. Our investors, in contrast, forever face ability-tracking problems. Precision of inferred abilities and their sensitivities to fund returns’ innovation shocks may increase/decrease/be nonmonotonic or stay constant over time, leading to higher/lower/nonmonotonic or constant fund flows’ sensitivities to performance, respectively. Our empirical evidence supports nonmonotonic dynamic manager abilities over constant/monotonic ones. We offer further empirical insights, including whether flow-performance relations are linear or convex.

Gamblers Learn from Experience
Joshua E. Blumenstock,Matthew Olckers

Mobile phone-based gambling has grown wildly popular in Africa. Commentators worry that low ability gamblers will not learn from experience, and may rely on debt to gamble. Using data on financial transactions for over 50 000 Kenyan smartphone users, we find that gamblers do learn from experience. Gamblers are less likely to bet following poor results and more likely to bet following good results. The reaction to positive and negative feedback is of equal magnitude, and is consistent with a model of Bayesian updating. Using an instrumental variables strategy, we find no evidence that increased gambling leads to increased debt.

Generalised geometric Brownian motion: Theory and applications to option pricing
Viktor Stojkoski,Trifce Sandev,Lasko Basnarkov,Ljupco Kocarev,Ralf Metzler

Classical option pricing schemes assume that the value of a financial asset follows a geometric Brownian motion (GBM). However, a growing body of studies suggest that a simple GBM trajectory is not an adequate representation for asset dynamics due to irregularities found when comparing its properties with empirical distributions. As a solution, we develop a generalisation of GBM where the introduction of a memory kernel critically determines the behavior of the stochastic process. We find the general expressions for the moments, log-moments, and the expectation of the periodic log returns, and obtain the corresponding probability density functions by using the subordination approach. Particularly, we consider subdiffusive GBM (sGBM), tempered sGBM, a mix of GBM and sGBM, and a mix of sGBMs. We utilise the resulting generalised GBM (gGBM) to examine the empirical performance of a selected group of kernels in the pricing of European call options. Our results indicate that the performance of a kernel ultimately depends on the maturity of the option and its moneyness.

Heterogeneous effects of waste pricing policies
Marica Valente

Using machine learning methods in a quasi-experimental setting, I study the heterogeneous effects of introducing waste prices---unit prices on household unsorted waste disposal---on waste demands and social welfare. First, using a unique panel of Italian municipalities with large variation in prices and observables, I show that waste demands are nonlinear. I find evidence of nudge effects at low prices, and increasing elasticities at high prices driven by income effects and waste habits before policy. Second, I estimate policy impacts on pollution and municipal management costs, and compute the overall social cost savings for each municipality. Social welfare effects become positive for most municipalities after three years of adoption, when waste prices cause significant waste avoidance.

IT Shields: Technology Adoption and Economic Resilience during the COVID-19 Pandemic
Pierri, Nicola,Timmer, Yannick
We study the economic effects of information technology (IT) adoption during the COVID-19 pandemic. Using data on IT adoption covering almost three million establishments in the US, we find that technology adoption can partly shield the economy from the impact of the pandemic. In areas where firms adopted more IT the unemployment rate rose less in response to social distancing. Our estimates imply that if the pandemic had hit the world 5 years ago, the resulting unemployment rate would have been 2 percentage points higher during April and May 2020 (16% vs. 14%), due to the lower availability of IT. Local IT adoption mitigates the labor market consequences of the pandemic for all individuals, regardless of gender and race, except those with the lowest level of educational attainment.

Insights from Optimal Pandemic Shielding in a Multi-Group SEIR Framework
Philipp Bach,Victor Chernozhukov,Martin Spindler

The COVID-19 pandemic constitutes one of the largest threats in recent decades to the health and economic welfare of populations globally. In this paper, we analyze different types of policy measures designed to fight the spread of the virus and minimize economic losses. Our analysis builds on a multi-group SEIR model, which extends the multi-group SIR model introduced by Acemoglu et al.~(2020). We adjust the underlying social interaction patterns and consider an extended set of policy measures. The model is calibrated for Germany. Despite the trade-off between COVID-19 prevention and economic activity that is inherent to shielding policies, our results show that efficiency gains can be achieved by targeting such policies towards different age groups. Alternative policies such as physical distancing can be employed to reduce the degree of targeting and the intensity and duration of shielding. Our results show that a comprehensive approach that combines multiple policy measures simultaneously can effectively mitigate population mortality and economic harm.

Kyle-Back Models with risk aversion and non-Gaussian Beliefs
Shreya Bose,Ibrahim Ekren

We show that the problem of existence of equilibrium in Kyle's continuous time insider trading model ([31]) can be tackled by considering a system of quasilinear parabolic equation and a Fokker-Planck equation coupled via a transport type constraint. By obtaining a stochastic representation for the solution of such a system, we show the well-posedness of solutions and study the properties of the equilibrium obtained for small enough risk aversion parameter. In our model, the insider has exponential type utility and the belief of the market on the distribution of the price at final time can be non-Gaussian.

Learning in a Small/Big World
Benson Tsz Kin Leung

Savage (1972) lays down the foundation of Bayesian decision theory, but asserts that it is not applicable in big worlds where the environment is complex. Using the theory of finite automaton to model belief formation, this paper studies the characteristics of optimal learning behavior in small and big worlds, where the complexity of the environment is low and high, respectively, relative to the cognitive ability of the decision maker. Confirming Savage's claim, optimal learning behavior is closed to Bayesian in small worlds but significantly different in big worlds. In addition, I show that in big worlds, the optimal learning behavior could exhibit a wide range of well-documented non-Bayesian learning behavior, including the use of heuristic, correlation neglect, persistent over-confidence, inattentive learning, and other behaviors of model simplification or misspecification. These results establish a clear and testable relationship between the prominence of non-Bayesian learning behavior, complexity and cognitive ability.

Level-k Predatory Thinking
Teeple, Keisuke
I extend the Brunnermeier and Pedersen (2005) predatory trading model with the level-k thinking solution concept to investigate the possibility of arbitraging arbitrageurs. For some parameter values, financial predators play a relatively docile unique Nash equilibrium strategy and prices do not exhibit overshooting. However as parameter values are perturbed, the system undergoes a bifurcation and predators select strategies from an equilibrium set whose elements are a noisy version of the Nash equilibrium strategy. In this more aggressive parameter range, price overshooting is reintroduced and a single shock can send predators into an oscillatory trading frenzy.

Liberty or death
Wright, Craig S
A review of "The Boat" by Le Nam.Nam Le's novella "The Boat" (Le) captures the pain and anguish of a group of people seeking to transform their life. The book is an anthology of stories and novellas covering a range of topics concerning the human condition (Bullock). The author captures the wide assortment of emotive and expressive human conditions through an analysis of honour and pride with the comparison of these uniquely human tendencies against those of love, duty and compassion and in how sacrifice transcends generations. In this paper, I shall be focusing on one specific novella contained within this anthology, the one after which the book is named. It is a story of a group of boat people who left Vietnam seeking freedom and risking everything to achieve it. "The Boat" is a story of hardship and sacrifice and a commitment to hazard everything for a meagre possibility at liberty and freedom for themselves and their families. Before we can genuinely understand Nam Le's story, we need to understand the world that led to a people willing to sacrifice everything to escape to the promise of a different world.

Localized Information Acquisition
Hollander, Stephan,Litjens, Robin
This study reveals previously undocumented geography-related diversity in information acquisition. Exploiting the Security and Exchange Commission (SEC)’s Electronic Data Gathering and Retrieval (EDGAR) server log, which tracks use by Internet Protocol (IP) address, we find that acquisition of information from historical filings by investors local to the firm increases significantly on days leading up to scheduled earnings announcements, which is triggered by inter-temporal changes in earnings uncertainty and varies predictably with exogenous firm relocation. Non-local investors, on the other hand, generally wait until the day of the earnings announcement, when new filings information becomes available. Greater pre-announcement information acquisition diversity is predicted to elicit stronger stock price reactions on earnings announcement days. Consistent with this prediction, we show that the earnings announcement-day premium is larger when pre-earnings announcement information acquisition by local investors is higher, controlling for time-variant and -invariant firm characteristics.

Marxism, Logic and the Rate of Profit
Robin Hirsch

It is argued that Marxism, being based on contradictions, is an illogical method. More specifically, we present a rejection of Marx's thesis that the rate of profit has a long-term tendency to fall.

Minimum Wage, Labor Equilibrium, and the Productivity Horizon: A Visual Examination
John R. Moser

In this paper, I present a visual representation of the relationship between mean hourly total compensation divided by per-capita GDP, hours worked per capita, and the labor share, and show the represented labor equilibrium equation is the definition of the labor share. I also present visual examination of the productivity horizon and wage compression, and use these to show the relationship between productivity, available employment per capita, and minimum wage. From this I argue that wages are measured in relation to per-capita GDP, and that minimum wage controls income inequality and productivity growth.

More Stories of Unconventional Monetary Policy
Karson, Evan,Neely, Christopher J.
This article extends the work of Fawley and Neely (2013) to describe how major central banks have evolved unconventional monetary policies to encourage real activity and maintain stable inflation rates from 2013 through 2019. By 2013, central banks were moving from lump-sum asset purchase programs to continuing asset purchase programs, which are conditioned on economic conditions, careful communication strategies, bank lending programs with incentives and negative interest rates. This article reviews how central banks tailored their unconventional monetary methods to their various challenges and the structures of their respective economies.

North Korean Legal Systems Regarding Foreign Investment
Jon, Woo-jung
In North Korea, the Equity Joint Venture Act was first enacted in 1984, and then the Socialist Constitution was revised to define the basic direction of foreign investment policy in 1992. With the enactment of the Foreign Investment Act in 1992, principles and basic matters related to foreign investment were stipulated, and at the same time, laws regarding the establishment of various foreign-invested companies were enacted. The Special Economic Zone laws were enacted in 1993. The most important factor for the success of North Korea’s Special Economic Zones depends on its commitment to denuclearization. North Korea is currently under U.N. sanctions over its nuclear and missile programs. Until Kim Jong-un dissolves his nuclear programs, foreign investors will stay away from North Korea due to these UN resolutions. The international community requests complete, verifiable, and irreversible dismantlement (CVID) of North Korea’s nuclear weapons. Furthermore, it is essential for North Korea to join the New York Convention (Convention on the Recognition and Enforcement of Foreign Arbitral Awards) and the ICSID Convention (Convention on the settlement of investment disputes between States and nationals of other States) to protect foreign investors’ legal rights.

On the Continuity of the Root Barrier
Erhan Bayraktar,Thomas Bernhardt

We show that the barrier function in Root's solution to the Skorokhod embedding problem is continuous and finite at every point where the target measure has no atom and its absolutely continuous part is locally bounded away from zero.

Optimal Portfolio Using Factor Graphical Lasso
Tae-Hwy Lee,Ekaterina Seregina

Graphical models are a powerful tool to estimate a high-dimensional inverse covariance (precision) matrix, which has been applied for portfolio allocation problem. The assumption made by these models is a sparsity of the precision matrix. However, when the stock returns are driven by the common factors, this assumption does not hold. Our paper develops a framework for estimating a high-dimensional precision matrix which combines the benefits of exploring the factor structure of the stock returns and the sparsity of the precision matrix of the factor-adjusted returns. The proposed algorithm is called Factor Graphical Lasso (FGL). We study a high-dimensional portfolio allocation problem when the asset returns admit the approximate factor model. In high dimensions, when the number of assets is large relative to the sample size, the sample covariance matrix of the excess returns is subject to the large estimation uncertainty, which leads to unstable solutions for portfolio weights. To resolve this issue, we consider the decomposition of low-rank and sparse components. This strategy allows us to consistently estimate the optimal portfolio in high dimensions, even when the covariance matrix is ill-behaved. We establish consistency of the portfolio weights in a high-dimensional setting without assuming sparsity on the covariance or precision matrix of stock returns. Our theoretical results and simulations demonstrate that FGL is robust to heavy-tailed distributions, which makes our method suitable for financial applications. The empirical application uses daily and monthly data for the constituents of the S&P500 to demonstrate superior performance of FGL compared to the equal-weighted portfolio, index and some prominent precision and covariance-based estimators.

Payments Crises and Consequences
Chen, Qian,Koch, Christoffer,Richardson, Gary,Sharma, Padma
Banking-system shutdowns during contractions scar economies. Four times in the last forty years, governors suspended payments from state-insured depository institutions. Suspensions of payments in Nebraska (1983), Ohio (1985), and Maryland (1985), which were short and occurred during expansions, had little measurable impact on macroeconomic aggregates. Rhode Island’s payments crisis (1991), which was prolonged and occurred during a recession, lengthened and deepened the downturn. Unemployment increased. Output declined, possibly permanently relative to what might have been. We document these effects using a novel Bayesian method for synthetic control that characterizes the principal types of uncertainty in this form of analysis. Our findings suggest policies that ensurebanks continue to process payments during contractions â€" including the bailouts of financial institutions in 2008 and the unprecedented support of the financial system during the COVID crisis â€" have substantial value.

Presence of Women in Economics Academia: Evidence from India
Ambrish Dongre,Karan Singhal,Upasak Das

This paper documents the representation of women in Economics academia in India by analyzing the share of women in faculty positions, and their participation in a prestigious conference held annually. Data from the elite institutions shows that the presence of women as the Economics faculty members remains low. Of the authors of the papers which were in the final schedule of the prestigious research conference, the proportion of women authors is again found to be disproportionately low. Our findings from further analysis indicate that women are not under-represented at the post-graduate level. Further, the proportion of women in doctoral programmes has increased over time, and is now almost proportionate. Tendency of women who earn a doctorate abroad, to not return to India, time needed to complete a doctoral program, and responsibilities towards the family may explain lower presence of women in Economics academia in India.

Probabilistic Approach to Mean Field Games and Mean Field Type Control Problems with Multiple Populations
Masaaki Fujii

In this work, we systematically investigate mean field games and mean field type control problems with multiple populations using a coupled system of forward-backward stochastic differential equations of McKean-Vlasov type stemming from Pontryagin's stochastic maximum principle. Although the same cost functions as well as the coefficient functions of the state dynamics are shared among the agents within each population, they can be different population by population. We study the mean field limit for the three different situations; (i) every agent is non-cooperative; (ii) the agents within each population are cooperative; and (iii) the agents in some populations are cooperative but those in the other populations are not. We provide several sets of sufficient conditions for the existence of a mean field equilibrium for each of these cases. Furthermore, under appropriate conditions, we show that the mean field solution to each of these problems actually provides an approximate Nash equilibrium for the corresponding game with a large but finite number of agents.

Racial Disparities in Voting Wait Times: Evidence from Smartphone Data
M. Keith Chen,Kareem Haggag,Devin G. Pope,Ryne Rohla

Equal access to voting is a core feature of democratic government. Using data from millions of smartphone users, we quantify a racial disparity in voting wait times across a nationwide sample of polling places during the 2016 U.S. presidential election. Relative to entirely-white neighborhoods, residents of entirely-black neighborhoods waited 29% longer to vote and were 74% more likely to spend more than 30 minutes at their polling place. This disparity holds when comparing predominantly white and black polling places within the same states and counties, and survives numerous robustness and placebo tests. We shed light on the mechanism for these results and discuss how geospatial data can be an effective tool to both measure and monitor these disparities going forward.

Real-Time Real Economic Activity Entering the Pandemic Recession
Francis X. Diebold

Entering the Pandemic Recession, we study the high-frequency real-activity signals provided by a leading nowcast, the ADS Index of Business Conditions produced and released in real time by the Federal Reserve Bank of Philadelphia. We track the evolution of real-time vintage beliefs and compare them to a later-vintage chronology. Real-time ADS plunges and then swings as its underlying economic indicators swing, but the ADS paths quickly converge to indicate a return to brisk positive growth by mid-May. We show, moreover, that the daily real activity path was extremely highly correlated with the daily COVID-19 path. Finally, we provide a comparative assessment of the real-time ADS signals provided when exiting the Great Recession.

Reorganization without Bankruptcy: Untying the Gordian Knot That Destroys Firm Value
Sher, Noam
This article presents a new theory for analyzing bankruptcy-reorganization proceedings as well as a mechanism for public companies’ reorganization that may best meet the legislative objectives: maximizing firm value and dividing it according to the claimants’ legal priorities. Called Gordian knot theory, it suggests that there is a strong structural and material connection between reorganization stages, whereby bargaining and litigation between the claimants over the reorganization pie lead to progressive destruction of the firm’s value and infringement on their legal rights. To demonstrate this theory, the article focuses on the reorganization’s allocation and reallocation stages â€" where the claimants’ original and new rights are determined, respectively â€" and how the connection between them prevents the legislative objectives from being met. Alternative approaches suggested in the literature for attaining these objectives, including Roe’s, Bebchuk’s, Baird’s, Hart and Moore’s, and Adler and Ayres’ models, have focused on the firm’s valuation problem and suggested solving it by market mechanisms. The Gordian knot theory suggests, however, that it is impossible to attain the legislative objectives strictly by determining the firm’s value efficiently while leaving allocation problems to bargaining and litigation.The article further presents a new mechanism for public companies that overcomes this problem by structuring reorganization in a single shot that includes allocation and reallocation of rights, while eliminating the need for bargaining and court proceedings. It is based on the firm’s going-concern warning that the auditors have to issue, explicitly indicating that there is substantial doubt whether it could remain solvent over twelve months. Under this mechanism, the warning initiates twelve months of voluntary rehabilitation. Then, if the warning is still valid, the junior classes will be able to buy all seniors at a price of the latter’s claims, similar to Bebchuk’s options model. A successful buy erases the original debt, and if the claimants do not purchase the firm, it is considered insolvent. Here, it is called the reorganization without bankruptcy mechanism. The article presents the mechanism and discusses its advantages: inter alia, in the pre-bankruptcy period, the firm is solvent, it has not breached its contracts, and it is not involved in complex allocation disputes. These advantages enable attaining the legislative objectives, achieving rehabilitation including funding based on market mechanisms and the management’s sole discretion, providing the management with incentives for adequate disclosure, and initiating rehabilitation based on objective criteria â€" all free of bargaining and litigation biases.

Risk Factor Centrality and the Cross-Section of Expected Returns
Moraes, Fernando,De-Losso, Rodrigo
The Factor Zoo phenomenon calls for answers as to which risk factors are in fact capable of providing independent information on the cross-section of expected excess returns, while considering that asset-pricing literature has produced hundreds of candidates. In this paper, we propose a new methodology to reduce risk factor predictor dimensions by selecting the key component (most central element) of their precision matrix. Our approach yields a significant shrinkage in the original set of risk factors, enables investigations on different regions of the risk factor covariance matrix, and requires only a swift algorithm for implementation. Our findings lead to sparse models that pose higher average in samples R^2 and lower root mean square out of sample error than those attained with classic models, in addition to specific alternative methods documented by Factor Zoo-related research papers. We base our methodology on the CRSP monthly stock return dataset in the time frame ranging from January 1981 to December 2016, in addition to the 51 risk factors suggested by Kozak, Nagel, and Santosh (2020).

Risk Factors’ Cpdag Roots and the Cross-Section of Expected Returns
Moraes, Fernando,De-Losso, Rodrigo
The Asset pricing literature has produced hundreds of risk factor candidates aimed at explaining the cross-section of expected excess returns, although risk factors which are in fact capable of providing independent information remains an open question. Appling a sparse model, Kozak, Nagel, and Santosh (2020) achieve satisfactory results on explaining cross-sectional returns only with PCs (principal components). In this paper, we propose a new methodology that seeks to reduce risk factor predictor dimensions by estimating the joint risk factor distribution with CPDAG (complete partial directed acyclic graph), in addition to selecting the CPDAG root as the only new risk factor candidate set. Our approach yields a significant shrinkage in the original set of risk factors, whereas our findings lead to sparse models that pose better results than those attained with the standard models and with alternative methods proposed by PCs factor zoo-related research papers.

Sectoral Labor Mobility and Optimal Monetary Policy
Alessandro Cantelmo,Giovanni Melina

How should central banks optimally aggregate sectoral inflation rates in the presence of imperfect labor mobility across sectors? We study this issue in a two-sector New-Keynesian model and show that a lower degree of sectoral labor mobility, ceteris paribus, increases the optimal weight on inflation in a sector that would otherwise receive a lower weight. We analytically and numerically find that, with limited labor mobility, adjustment to asymmetric shocks cannot fully occur through the reallocation of labor, thus putting more pressure on wages, causing inefficient movements in relative prices, and creating scope for central banks intervention. These findings challenge standard central banks practice of computing sectoral inflation weights based solely on sector size, and unveil a significant role for the degree of sectoral labor mobility to play in the optimal computation. In an extended estimated model of the U.S. economy, featuring customary frictions and shocks, the estimated inflation weights imply a decrease in welfare up to 10 percent relative to the case of optimal weights.

Social networks, confirmation bias and shock elections
Edoardo Gallo,Alastair Langtry

In recent years online social networks have become increasingly prominent in political campaigns and, concurrently, several countries have experienced shock election outcomes. This paper proposes a model that links these two phenomena. In our set-up, the process of learning from others on a network is influenced by confirmation bias, i.e. the tendency to ignore contrary evidence and interpret it as consistent with one's own belief. When agents pay enough attention to themselves, confirmation bias leads to slower learning in any symmetric network, and it increases polarization in society. We identify a subset of agents that become more/less influential with confirmation bias. The socially optimal network structure depends critically on the information available to the social planner. When she cannot observe agents' beliefs, the optimal network is symmetric, vertex-transitive and has no self-loops. We explore the implications of these results for electoral outcomes and media markets. Confirmation bias increases the likelihood of shock elections, and it pushes fringe media to take a more extreme ideology.

The Impact of Data Aggregation and Risk Attributes on Stress Testing Models of Mortgage Default
Li, Feng,Zhang, Yan
Stress testing models have been developed at various levels of data aggregation with or without risk attributes, but there is limited research on the joint impact of these modeling choices. In this paper, we investigate how data aggregation and risk attributes affect the development and performance of stress testing models by studying residential mortgage loan defaults. We develop mortgage default models at various data aggregation levels including loan-level, segment-level, and top-down. We also compare the models with and without risk attributes as control variables. We assess model performance for goodness-of-fit, prediction accuracy, and projection sensitivity for stress testing purposes. We find that the loan-level models do not always win among models with various data aggregation levels, and including risk attributes greatly improves goodness-of-fit and projection accuracy for models of all data aggregation levels. The findings suggest that it is important to consider data aggregation and risk attributes in developing stress testing models.

The Importance of Where Central Bank Digital Currencies Are Custodied: Exploring the Need of a Universal Access Device
Barresi, Rosa Giovanna,Zatti, Filippo
Distributed Ledger Technology (DLT) is out to change our future. Its scope is not limited to tokenizing physical objects. In the case of Central Bank Digital Currencies (hereinafter, CBDCs), they can change the way we look at money, one of the earliest inventions of humanity.As soon as digital asset trading evolved into a market, developers started releasing digital wallets for their storage. While these attempts are the recognition of users’ needs, their technical level still leaves some space for improvements. Among CBDC related issues, the development of a secure wallet infrastructure is gaining recognition as one way to solve key problems like ensuring equal access to banking facilities. Also, it can offer a novel way to approach digital identity and other functional problems connected to digital assets.Whenever we are executing a financial transaction, its consequences are not restricted to the monetary realm: issues about fair competition, ownership, and management of our personal information come into play. An infrastructure is needed to protect and support our digital rights. Technology is ready to support the development of a secure Universal Access Device (UAD), a single key tool for protecting and representing us, and the organization for supporting it from a network. This paper aims to explore the arising legal and economic issues following the adoption of UADs.

The implications of large-scale containment policies on global maritime trade during the COVID-19 pandemic
Jasper Verschuur,Elco Koks,Jim Hall

The implementation of large-scale containment measures by governments to contain the spread of the COVID-19 virus has resulted in a large supply and demand shock throughout the global economy. Here, we use empirical vessel tracking data and a newly developed algorithm to estimate the global maritime trade losses during the first eight months of the pandemic. Our results show widespread trade losses on a port level with the largest absolute losses found for ports in China, the Middle-East and Western Europe, associated with the collapse of specific supply-chains (e.g. oil, vehicle manufacturing). In total, we estimate that global maritime trade reduced by -7.0% to -9.6% during the first eight months of 2020, which is equal to around 206-286 million tonnes in volume losses and up to 225-412 billion USD in value losses. The fishery, mining and quarrying, electrical equipment and machinery manufacturing, and transport equipment manufacturing sectors are hit hardest, with losses up to 11.8%. Moreover, we find a large geographical disparity in losses, with some small islands developing states and low-income economies suffering the largest relative trade losses. We find a clear negative impact of COVID-19 related business and public transport closures on country-wide exports. Overall, we show how real-time indicators of economic activity can support governments and international organisations in economic recovery efforts and allocate funds to the hardest hit economies and sectors.

Two Stage Decumulation Strategies for DC Plan Investors: 'A Goal Properly Set Is Halfway Reached'
Forsyth, Peter
Optimal stochastic control methods are used to examine decumulation strategies for a defined contribution (DC) plan retiree. An initial investment horizon of fifteen years is considered, since the retiree will attain this age with high probability. The objective function reward measure is the expected sum of the withdrawals. The objective function tail risk measure is the expected linear shortfall with respect to a desired lower bound for wealth at fifteen years. The lower bound wealth level is the amount which is required to fund a lifelong annuity fifteen years after retirement, which generates the required minimum cash flows. This ameliorates longevity risk. The controls are the withdrawal amount each year, and the asset allocation strategy. Maximum and minimum withdrawal amounts are specified. Specifying a short initial decumulation horizon, results in the optimal strategy achieving: (i) median withdrawals at the maximum rate within 2-3 years of retirement (ii) terminal wealth larger than the desired lower bound at fifteen years, with greater than $90\%$ probability and (iii) median terminal wealth at fifteen years considerably larger than the desired lower bound. The controls are computed using a parametric model of historical stock and bond returns, and then tested in bootstrap resampled simulations using historical data. At the fifteen year investment horizon, the retiree has the option of (i) continuing to self-manage the decumulation policy or (ii) purchasing an annuity.

Using mixed-frequency and realized measures in quantile regression
Vincenzo Candila,Giampiero M. Gallo,Lea Petrella

Quantile regression is an efficient tool when it comes to estimate popular measures of tail risk such as the conditional quantile Value at Risk. In this paper we exploit the availability of data at mixed frequency to build a volatility model for daily returns with low-- (for macro--variables) and high--frequency (which may include an \virg{--X} term related to realized volatility measures) components. The quality of the suggested quantile regression model, labeled MF--Q--ARCH--X, is assessed in a number of directions: we derive weak stationarity properties, we investigate its finite sample properties by means of a Monte Carlo exercise and we apply it on financial real data. VaR forecast performances are evaluated by backtesting and Model Confidence Set inclusion among competitors, showing that the MF--Q--ARCH--X has a consistently accurate forecasting capability.

Weathering the COVID-19 Storm: The Case of Community Banks
Hassan, M. Kabir,Karim, Md. Sydul
We examine the immediate impacts of COVID-19 on FDIC chartered banks' performance. Our experimental design analyzes the performance of community banks and large banks before and during the COVID-19 pandemic. Community banks outperform large banks significantly in several key measures in the first two-quarters of COVID-19, consistent with the view that the advantages of strong customer relationships and a greater understanding of the local businesses pave the way during high externalities. This result is more pronounced for the community banks located in metropolitan areas. We find that the adversity of the pandemic on bank performance is resisted more in the states with high healthcare facilities. Besides, the performance of community banks varies across geography during this pandemic period. Further analyses reveal that the decline in risk-taking and de-risking of assets occurs faster in the community banks compared to the large banks. Our study expands the understanding of how community banks' performance and risk-taking changes during a pandemic period.

What Drives U.S. Treasury Re-Use?
Infante, Sebastian,Saravay, Zack
We study what drives the re-use of U.S. Treasury securities in the financial system. Using confidential supervisory data, we estimate the degree of collateral re-use at the dealer level through their collateral multiplier: the ratio between a dealer's secured funding and their outright holdings. We find that Treasury re-use increases as the supply of available securities decreases, especially when supply declines due to Federal Reserve asset purchases. We also find that non-U.S. dealers' re-use increases when profits from intermediating cash are high, U.S. dealers' re-use increases when demand to source on-the-run Treasuries is high, and both types of dealers' re-use can alleviate safe asset scarcity. Finally, we document a sharp drop in Treasury re-use at the onset of the COVID-19 pandemic, with a subsequent reversal after the Federal Reserve's intervention to support market functioning.

Why Have CEO Pay Levels Become Less Diverse?
Jochem, Torsten,Ormazabal, Gaizka,Rajamani, Anjana
We document that, over the last decade, the cross-sectional variation in CEO pay levels has declined precipitously, both at the economy level and within industry and industry-size groups. We find evidence consistent with one potential explanation for this pattern; reciprocal bench-marking (i.e., firms are more likely to include each other in the disclosed set of peers used to benchmark pay levels). We also find empirical support for three factors contributing to the increase in reciprocal bench-marking; the mandatory disclosure of compensation peer groups, say on pay, and proxy advisory influence. Finally, we find that reciprocal bench-marking has meaningful consequences on managerial behavior; it reduces risk-taking by weakening external tournament incentives.