Research articles for the 2020-06-02

Algorithmic Opacity, Private Accountability, and Corporate Social Disclosure in the Age of Artificial intelligence
Lu, Sylvia
SSRN

Asset Pricing in Mercati Completi (Asset Pricing in Complete Markets)
Miceli, Maria-Augusta
SSRN
Italian abstract: L'obiettivo Ã¨ spiegare in maniera succinta l'asset pricing nell'ipotesi di mercati completi. Dopo aver dato notazioni e definizioni, viene esposto il Terema fondamentale dell'Asset Pricing, il Risk-Neutral Pricing e le condizioni di non-arbitraggio. Date queste nozioni, il pricing delle attivitÃ  finanziarie a reddito fisso diventa un facile risultato di calcolo matriciale.Per il caso di mercati incompleti, vengono esposti alcuni metodi di completamento del mercato mediante derivati.English abstract: Asset pricing in complete markets is explained. The essential definitions and price relationships leading to the "Fundamental Theorem of Asset Pricing" and the "Risk Neutral Pricing" are set, followed by the "no-arbitrage conditions of I and II type. Given these ingredients fixed income asset pricing in complete markets is a straightforward result.Under Incomplete markets, some methods of market completion through the use of derivatives are explained.

COVID-19 Pandemic: A Snapshot of Global Economic Repercussions and Possible Retaliations
Amir, Md. Khaled Bin
SSRN
Both human and economic cost of COVID-19 tsunami has continued to peak as nobody can even envisage when and how the shock will be solved. The value of life is uncountable on the other hand every sign clears that economic plunge will be prolonged and painful. The purpose of this paper is to provide a snapshot of global economic disaster, focusing especially on major regions (China, USA, and Italy) due to COVID-19 and possible economic responses to mitigate the severity of this pandemic. The paper first provides an overview of global economic imbalances reflected by growing medical and financial emergencies, falling asset prices, tightening financial conditions, abatement of global GDP, world trade and supply chain disruptions, the constraint on tourism and traveling, raising uneven inflation, augmenting poverty, the suffering of migrants, political discord and antagonism may lead to being the unexpected worst economic downturn in the history. Along with identifying these imbalances, possible economic responses have been presented amid the shock of COVID-19 and strategies for recoveries. The paper concludes that containing initiatives and economics of pandemics is not enough to beat the novel coronavirus (COVID-19) without solidarity and consensus among nations around the globe.

COVID-19 Response Needs to Broaden Financial Inclusion to Curb the Rise in Poverty
Ahamed, Mostak,Gutierrez-Romero, Roxana
SSRN
The ongoing COVID-19 pandemic risks wiping out years of progress made in reducing global poverty. In this paper, we explore to what extent financial inclusion could help mitigate the increase in poverty using cross-country data across 78 low- and lower-middle-income countries. Unlike other recent cross-country studies, we show that financial inclusion is a key driver of poverty reduction in these countries. This effect is not direct, but indirect, by mitigating the detrimental effect that inequality has on poverty. Our findings are consistent across all the different measures of poverty used. Our forecasts suggest that the worldâ€™s population living on less than $1.90 per day could increase from 8% to 14% by 2021, pushing nearly 400 million people into poverty. However, urgent improvements in financial inclusion could substantially reduce the impact on poverty. COVID-19 and Market Expectations: Evidence from Option-Implied Densities Hanke, Michael,Kosolapova, Maria,Weissensteiner, Alex SSRN We compare risk-neutral densities from equity index options across several markets during the early phase of the COVID-19 pandemic. These densities reflect market expectations regarding its economic impact. The markets reacted abruptly and simultaneously initially, but with a marked time lag after ignoring the first clear warning signs for several weeks. As the crisis unfolds, option prices increasingly reflect differences in anticipated impact on and economic resiliency of these markets. Disaster Recovery and the Term Structure of Dividend Strips Hasler, Michael,MarfÃ¨, Roberto SSRN Recent empirical findings document downward-sloping term structures of equity return volatility and risk premia. An equilibrium model with rare disasters followed by recoveries helps reconcile theory with empirical observations. Indeed, recoveries outweigh the upward-sloping effect of time-varying disaster intensity and expected growth, generating downward-sloping term structures of dividend growth risk, equity return volatility, and equity risk premia. In addition, the term structure of interest rates is upward-sloping when accounting for recoveries and downward-sloping otherwise. The model quantitatively reconciles high risk premia and a low risk-free rate with the shape of the term structures, which are at odds in other models. Do Private Household Transfers to the Elderly Respond to Public Pension Benefits? Evidence from Rural China Plamen Nikolov,Alan Adelman arXiv Exploiting a unique policy intervention in China, we examine using a difference-in-difference-in-differences (DDD) approach how a new pension program impacts inter vivos transfers. We show that pension benefits lower the propensity of receiving transfers from adult children in the context of a large middle-income country and we also estimate a small crowd-out effect. Taken together, these estimates fit the pattern of previous research in high-income countries, although our estimates of the crowd-out effect are significantly smaller than previous studies in both high-income and middle-income countries. Dynamic Attention Behavior under Return Predictability Andrei, Daniel,Hasler, Michael SSRN We investigate the dynamic problem of how much attention an investor should pay to news in order to learn about stock-return predictability and maximize expected lifetime utility. We show that the optimal amount of attention is U-shaped in the return predictor, increasing with both uncertainty and the magnitude of the predictive coefficient, and decreasing with stock-return volatility. The optimal risky asset position exhibits a negative hedging demand that is hump-shaped in the return predictor. Its magnitude is larger when uncertainty increases, but smaller when stock-return volatility increases. We test and find empirical support for these theoretical predictions. Economic Impact Analysis of the Coronavirus, An Alternative Data Perspective Zhang, Tony,Wang, Jiayue,Li, Yanjun,Zhang, Xiyuan,Li, Beibei,Xie, Danxia SSRN Alternative data is transforming the investment management process for financial industry, hedge funds, mutual funds, foundations, and pension funds. This paper describes the use of alternative data on the field of finance, particularly illustrating the complex forces driving the stock markets in China and the U.S., through the exploration of the alternative data through the outbreak of COVID-19. The analytic results demonstrate that the subway traffic and commercial housing deal area are positively correlated to the Chinese market in a rather weak level, and that search trends of coronavirus is negatively correlated to the American market with high reliability. The alternative data, which are closely connected with the situation of the coronavirus outbreak, have the ability of predicting where the markets are heading. Evolution of the Chinese Guarantee Network under Financial Crisis and Stimulus Program Yingli Wang,Qingpeng Zhang,Xiaoguang Yang arXiv Our knowledge about the evolution of guarantee network in downturn period is limited due to the lack of comprehensive data of the whole credit system. Here we analyze the dynamic Chinese guarantee network constructed from a comprehensive bank loan dataset that accounts for nearly 80% total loans in China, during 01/2007-03/2012. The results show that, first, during the 2007-2008 global financial crisis, the guarantee network became smaller, less connected and more stable because of many bankruptcies; second, the stimulus program encouraged mutual guarantee behaviors, resulting in highly reciprocal and fragile network structure; third, the following monetary policy adjustment enhanced the resilience of the guarantee network by reducing mutual guarantees. Interestingly, our work reveals that the financial crisis made the network more resilient, and conversely, the government bailout degenerated network resilience. These counterintuitive findings can provide new insight into the resilience of real-world credit system under external shocks or rescues. Existence of equivalent local martingale deflators in semimartingale market models Eckhard Platen,Stefan Tappe arXiv This paper offers a systematic investigation on the existence of equivalent local martingale deflators, which are multiplicative special semimartingales, in financial markets given by positive semimartingales. In particular, it shows that the existence of such deflators can be characterized by means of the modified semimartingale characteristics. Several examples illustrate our results. Furthermore, we provide interpretations of the deflators from an economic point of view. Explicit approximations for option prices via Malliavin calculus for the stochastic Verhulst volatility model Kaustav Das,Nicolas Langrené arXiv We consider explicit approximations for European put option prices within the stochastic Verhulst model with time-dependent parameters, where the volatility process follows the dynamics$dV_t = \kappa_t (\theta_t - V_t) V_t dt + \lambda_t V_t dB_t\$. Our methodology involves writing the put option price as an expectation of a Black-Scholes formula, reparameterising the volatility process and then performing a number of expansions. The difficulties faced are computing a number of expectations induced by the expansion procedure explicitly. We do this by appealing to techniques from Malliavin calculus. Moreover, we deduce that our methodology extends to models with more generic drift and diffusions for the volatility process. We obtain the explicit representation of the form of the error generated by the expansion procedure, and we provide sufficient ingredients in order to obtain a meaningful bound. Under the assumption of piecewise-constant parameters, our approximation formulas become closed-form, and moreover we are able to establish a fast calibration scheme. Furthermore, we perform a numerical sensitivity analysis to investigate the quality of our approximation formula in the stochastic Verhulst model, and show that the errors are well within the acceptable range for application purposes.

Filling Open Price Gap on Intraday Timeframe: A Case Study for DJIA Index Stocks
Abidou, Maged
SSRN
Stock open price in a trading session is usually located within the trading range of previous day unless there is a good or a bad news about the stock. If it is good news, open price could be higher than the High price of previous day which causing â€œUp Open Gapâ€. If there is bad news, then open price could lower than the Low price of previous day which causing â€œDown Open Gapâ€.During the trading session which lasts for 390 minutes in US, stock trading will result in either closing the open gap or leave it opened.This research aims to quantify expected behavior and to find the time of filling the open gap, if it will be closed on the intraday time-frame. Research has used Dow Jones Industrial Average (DJIA) index stocks.

Financial Frictions and the Wealth Distribution
SSRN
We postulate a nonlinear DSGE model with a financial sector and heterogeneous households. In our model, the interaction between the supply of bonds by the financial sector and the precautionary demand for bonds by households produces significant endogenous aggregate risk. This risk induces an endogenous regime-switching process for output, the risk-free rate, excess returns, debt, and leverage. The regime-switching generates i) multimodal distributions of the variables above; ii) time-varying levels of volatility and skewness for the same variables; and iii) supercycles of borrowing and deleveraging. All of these are important properties of the data. In comparison, the representative household version of the model cannot generate any of these features. Methodologically, we discuss how nonlinear DSGE models with heterogeneous agents can be efficiently computed using machine learning and how they can be estimated with a likelihood function, using inference with diffusions.

Flexible Loans and Access to Agricultural Credit for Smallholder Farmers in Siaya County, Kenya
Odhiambo, Fredrick Onyango
SSRN

Global Financial Cycles Since 1880
Potjagailo, Galina,Wolters, Maik
SSRN
With the aim to provide a detailed understanding of global financial cycles and their relevance over time, we analyse co-movement in credit, house prices, equity prices, and interest rates across 17 advanced economies over 130 years. Using a time-varying dynamic factor model, we observe global co-movement across financial variables as well as variable-specific global cycles of different lengths and amplitudes. Global cycles have gained relevance over time. For equity prices, they now constitute the main driver of fluctuations in most countries. Global cycles in credit and housing have become much more pronounced and protracted since the 1980s, but their relevance increased for a sub-group of financially open and developed economies only. Panel regressions indicate that a countryâ€™s susceptibility to global financial cycles tends to increase with financial openness and financial integration, the extent of mortgage-related lending, and the efficiency of stock markets. Understanding the cross-country heterogeneity in financial market characteristics therefore matters for the design of appropriate financial stabilization policies across countries and sectors.

H1N1 Pandemic and Cash
SSRN
This study investigates firmsâ€™ response to the adverse shock arising from the H1N1 pandemic. We find that in comparison to firms whose employees can work remotely, firms with need for more on-site employees increase cash during the pandemic. This increase in cash is larger for firms that are more vulnerable to liquidity shocks. These firms increase cash by selling investments, reducing capital expenditures and dividends. During the pandemic, delistings, default risk, and volatility increase for firms with more on-site employees. We find similar results during the COVID-19 pandemic. These findings support the liquidity motive for cash, but not the investment motive.

Hedger of Last Resort: Evidence from Brazilian FX Interventions, Local Credit, and Global Financial Cycles
Gonzalez, Rodrigo,Khametshin, Dmitry,Peydro , Jose-Luis,Polo, Andrea
SSRN
We show that local central bank policies attenuate global financial cycle (GFC)â€™s spillovers. For identification, we exploit GFC shocks and Brazilian interventions in FX derivatives using three matched administrative registers: credit, foreign credit flows to banks, and employer-employee. After U.S. Federal Reserve Taper Tantrum (followed by strong Emerging Markets FX depreciation and volatility increase), Brazilian banks with larger ex-ante reliance on foreign debt strongly cut credit supply, thereby reducing firm-level employment. However, a large FX intervention program supplying derivatives against FX risks â€" hedger of last resort â€" halves the negative effects. Finally, a 2008-2015 panel exploiting GFC shocks and local related policies confirm these results.

Imposing Choice under Ambiguity: The Case of Dynamic Currency Conversion
Ewerhart, Christian,Li, Sheng
SSRN
It is a common experience for present-day consumers making an international payment via credit or debit card to be invited to choose the currency in which they wish to have the transaction executed. While this choice, made feasible by a technology known as dynamic currency conversion (DCC), seems to foster competition, we show that the opposite is the case. In fact, the unique pure-strategy Nash equilibrium in a natural fee-setting game turns out to be highly asymmetric, entailing fees for the service provider that always exceed the monopoly level. Although losses in welfare may be substantial, a regulatory solution is unlikely to come about due to a global free-rider problem.

Increasing Corporate Bond Liquidity Premium and Post-Crisis Regulations
Wu, Botao
SSRN

Liquidity in Competitive Dealer Markets
Peter Bank,Ibrahim Ekren,Johannes Muhle-Karbe
arXiv

We study a continuous-time version of the intermediation model of Grossman and Miller (1988). To wit, we solve for the competitive equilibrium prices at which liquidity takers' demands are absorbed by dealers with quadratic inventory costs, who can in turn gradually transfer these positions to an exogenous open market with finite liquidity. This endogenously leads to transient price impact in the dealer market. Smooth, diffusive, and discrete trades all incur finite but nontrivial liquidity costs, and can arise naturally from the liquidity takers' optimization.

Macroprudential Policy, Mortgage Cycles and Distributional Effects: Evidence from the UK
Peydro , Jose-Luis,Rodriguez Tous, Francesc,Tripathy, Jagdish,Uluc, Arzu
SSRN
Macroprudential regulators worldwide have introduced regulations to limit household leverage in light of existing evidence which suggests that high leverage is associated with household distress during crisis. We analyse the distributional effects of such a macroprudential policy on mortgage and house price cycles. For identification, we exploit the universe of UK mortgages and a 15%-limit imposed in 2014 on lenders â€" not households â€" for high loan-to-income ratio (LTI) mortgages. Despite some regulatory arbitrage (eg increases in LTV and average loan size), more-constrained lenders issue fewer high-LTI mortgages. Partial substitution by less-constrained lenders leads to overall credit contraction to low-income borrowers in local-areas more exposed to constrained-lenders, lowering house price growth. Following the Brexit referendum (which led to house-price correction), the 2014-policy strongly implies â€" via lower pre-correction debt â€" better house prices and mortgage defaults during an episode of house price correction.

Model Risk at Central Counterparties: Is Skin-in-The-Game a Game Changer?
Huang, Wenqian,TakÃ¡ts, ElÅ'd
SSRN
We investigate empirically how the balance sheet characteristics of central counterparties (CCPs) affect their modelling of credit risk. CCPs set initial margin (IM), i.e., the collateral for transactions, to limit counterparty credit risk. When a CCP's IM model fails on a large scale, the CCP could fail too, losing its skin-in-the-game capital. We find that higher skin-in-the-game is significantly associated with more p rudent modelling, in contrast to profits (a proxy for franchise value) and forms of capital other than skin-in-the-game. The results may help to inform the ongoing policy debate on how to incentivise prudent credit risk management at CCPs.

Network Valuation in Financial Systems
Paolo Barucca,Marco Bardoscia,Fabio Caccioli,Marco D'Errico,Gabriele Visentin,Guido Caldarelli,Stefano Battiston
arXiv

We introduce a general model for the balance-sheet consistent valuation of interbank claims within an interconnected financial system. Our model represents an extension of clearing models of interdependent liabilities to account for the presence of uncertainty on banks' external assets. At the same time, it also provides a natural extension of classic structural credit risk models to the case of an interconnected system. We characterize the existence and uniqueness of a valuation that maximises individual and total equity values for all banks. We apply our model to the assessment of systemic risk, and in particular for the case of stress-testing. Further, we provide a fixed-point algorithm to carry out the network valuation and the conditions for its convergence.

Option Pricing: Channels, Target Zones and Sideways Markets
SSRN
After a market downturn, especially in an uncertain economic environment such as the current state, there can be a relatively long period with a sideways market, where indexes, stocks, etc., move in channels with support and resistance levels. We discuss option pricing in such scenarios, in both cases of unattainable as well as attainable boundaries, and obtain closed-form option pricing formulas. Our results also apply to FX rates in target zones without interest rate pegging (USD/HKD, digital currencies, etc.).

Predicting Corporate Carbon Footprints for Climate Finance Risk Analyses: A Machine Learning Approach
Nguyen, Quyen,Diaz-Rainey, Ivan,Kuruppuarachchi, Duminda
SSRN
This paper uses machine learning to improve the prediction of corporate emissions so that financial regulators and investors can make better decisions about climate transition risk. The need for predictions arises because only a subset of global companies report emissions. The novelty is to use machine learning rather than the conventional regression approaches and naÃ¯ve models implemented by data providers. Our best-performing model is a two-step framework that applies a Meta-Elastic Net learner to combine predictions from multiple base-learners. It results in an accuracy gain based on mean absolute error of up to 30% as compared with the existing models. We find that prediction accuracy can be further improved by incorporating additional predictors (energy data) and additional firm disclosures in particular sectors (utilities and real estate) and regions (Asia and Latin America). This provides an indication of where policymakers should concentrate their efforts for greater disclosure.

Proxy Advice Industry and Its Growing Influence
Shu, Chong
SSRN
This paper documents the evolving proxy advice industry and its growing influence on investorsâ€™ votes. Using an innovative method, I identify mutual fundsâ€™ purchases of proxy advice. As of 2017, ISS controls 63% of the market for mutual funds in the U.S. and Glass Lewis controls 28% of the market. Over the years, the industry has become less concentrated: in 2007, ISS controlled 74% of the market. However, ISSâ€™s one-size-fits-all recommendation has a strong and growing influence over its customersâ€™ votes. From 2006 to 2017, the fraction of ISSâ€™s customers who robo-vote grows from 12% to 23%. The growing influence of ISS is manifested in director elections, say-on-pay proposals, and other shareholder-sponsored proposals.

Rational Learning and the Term Structures of Value and Growth Risk Premia
Hasler, Michael,Khapko, Mariana,MarfÃ¨, Roberto
SSRN
This paper studies the impact of information processing and rational learning about economic fundamentals on the level and timing of risk premium in the cross-section of firms. Learning helps explain the level of the value premium, and why the term structure of risk premium is increasing for value firms and decreasing for growth firms. Moreover, learning yields an upward-sloping term structure of interest rates and a downward-sloping term structure of market risk premium, whereas the full information economy predicts the opposite shapes. Therefore, rational learning helps understand the level and timing of expected returns observed in the cross-section of risky and risk-free assets.

Resolving asset pricing puzzles using price-impact
Xiao Chen,Jin Hyuk Choi,Kasper Larsen,Duane J. Seppi
arXiv

We solve in closed-form an equilibrium model in which a finite number of exponential investors continuously consume and trade with price-impact. Compared to the analogous Pareto-efficient equilibrium model, price-impact has an amplification effect on risk-sharing distortions that helps resolve the interest rate puzzle and the stock-price volatility puzzle and, to a lesser extent, affects the equity premium puzzle.

Revisiting money and labor for valuing environmental goods and services in developing countries
Habtamu Tilahun Kassahun,Jette Bredahl Jacobsen,Charles F. Nicholson
arXiv

Many Stated Preference (SP) studies conducted in developing countries exhibit a low willingness to pay (WTP) for a wide range of goods and services. However, recent studies in these countries indicate that this may be a result of the choice of payment vehicle, not the preference for the good. Thus, low WTP may not indicate a low welfare effect for public projects in developing countries. We argue that in a setting where there is imperfect substitutability between money and other measures of wealth (e.g. labor), including two or more payment vehicles may be needed to obtain valid welfare estimates. Otherwise, we risk underestimating the welfare benefit of projects. We demonstrate this through a rural household contingent valuation (CV) survey designed to elicit the value of access to reliable irrigation water in Ethiopia. Our result shows that both absolute and relative endowment of labor and income highly influence respondents' choices. Of the total average annual WTP for access to reliable irrigation service, cash contribution comprises only 24.41\%. Our findings highlight the importance of accounting for cross payment vehicle correlation and potential endogeneity biases that arise in the sequence of WTP and Willingness to contribute (WTC) valuation questions. Keywords: Endogeneity; bivariate probit model; Contingent valuation; Stated preference methods; Irrigation service; Ethiopia; Developing countries

Robust Multiple Stopping -- A Pathwise Duality Approach
Roger J. A. Laeven,John G. M. Schoenmakers,Nikolaus F. F. Schweizer,Mitja Stadje
arXiv

In this paper we develop a solution method for general optimal stopping problems. Our general setting allows for multiple exercise rights, i.e., optimal multiple stopping, for a robust evaluation that accounts for model uncertainty, and for general reward processes driven by multi-dimensional jump-diffusions. Our approach relies on first establishing robust martingale dual representation results for the multiple stopping problem which satisfy appealing pathwise optimality (almost sure) properties. Next, we exploit these theoretical results to develop upper and lower bounds which, as we formally show, not only converge to the true solution asymptotically, but also constitute genuine upper and lower bounds. We illustrate the applicability of our general approach in a few examples and analyze the impact of model uncertainty on optimal multiple stopping strategies.

Set-Valued Risk Measures as Backward Stochastic Difference Inclusions and Equations
Çağın Ararat,Zachary Feinstein
arXiv

Scalar dynamic risk measures for univariate positions in continuous time are commonly represented as backward stochastic differential equations. In the multivariate setting, dynamic risk measures have been defined and studied as families of set-valued functionals in the recent literature. There are two possible extensions of scalar backward stochastic differential equations for the set-valued framework: (1) backward stochastic differential inclusions, which evaluate the risk dynamics on the selectors of acceptable capital allocations; or (2) set-valued backward stochastic differential equations, which evaluate the risk dynamics on the full set of acceptable capital allocations as a singular object. In this work, the discrete time setting is investigated with difference inclusions and difference equations in order to provide insights for such differential representations for set-valued dynamic risk measures in continuous time.

Should Investors Learn About the Timing of Equity Risk?
Hasler, Michael,Khapko, Mariana,MarfÃ¨, Roberto
SSRN
The term structure of equity risk has been shown to be downward sloping. We capture this feature using return dynamics driven by both a transitory and a permanent component. We study the asset allocation and portfolio performance when transitory and permanent components cannot be observed and therefore need to be estimated. Strategies that account for the observed timing of equity risk outperform those that do not, particularly so out of sample. Indeed, the mean (median) certainty equivalent return increases from about 13% (12%) to about 21% (15%) because properly modeling the timing of equity risk implies surges in portfolio returns.

Some pricing tools for the Variance Gamma model
Jean-Philippe Aguilar
arXiv

We establish several closed pricing formula for various path-independent payoffs, under an exponential L\'evy model driven by the Variance Gamma process. These formulas take the form of quickly convergent series and are obtained via tools from Mellin transform theory as well as from multidimensional complex analysis. Particular focus is made on the symmetric process, but extension to the asymmetric process is also provided. Speed of convergence and comparison with numerical methods (Fourier transform, quadrature approximations, Monte Carlo simulations) are also discussed; notable feature is the accelerated convergence of the series for short term options, which constitutes an interesting improvement of numerical Fourier inversion techniques.

Stock Market Liquidity, the Great Lockdown and the COVID-19 Global Pandemic Nexus in MENA Countries
Alaoui Mdaghri, Anas,Raghibi, Abdessamad,Nguyen, Thanh Cuong ,Oubdi, Lahsen
SSRN
The global pandemic of coronavirus has created an unprecedented economic lockdown. Although past pandemics have caused a short run market shock with quick recovery, this pandemic is believed to last as some sectors are deemed to disappear or change. Accordingly, this paper investigates the impact of the global Coronavirus (COVID-19) pandemic on stock market liquidity taking into account the depth and tightness dimension. We used a panel stock market data set representing 320 listed firms operating in six MENA countries from February to May 2020. The regression results on the overall sample indicates that liquidity using both depth and tightness measures is positively correlated to confirmed cases growth and death growth respectively. In addition to that, the stringency index is positively related to both liquidity measures. Our results also indicate that small cap firmsâ€™ liquidity is significantly impacted by the confirmed number of cases and death. Results were not statistically significant for big cap firms. Moreover, all industry sectorsâ€™ liquidity was significantly impacted by the growing confirmed cases except for the healthcare sector whose results were not significant. Hence, this paper confirmed that the global pandemic of coronavirus has decreased the stock market liquidity in both its depth and tightness dimension.

Systemic Risk: The Impact of COVID-19
SSRN
Banking sectors across the world are facing unprecedented challenges due to the COVID-19 pandemic and are under immense pressure. This study examines the impact of COVID-19 on the systemic risk in eight of the most affected countries. Results indicate a significant increase in systemic risk during the pandemic. All the sample countries exhibit stagnancy (at an elevated level) in systemic risk during April 2020 except for China which has shown some recovery. By using the spillover measures, we also identify the systemically important institutions. The findings of this study have valuable insights for the regulators

Term Structures of Equity and Interest Rates in Time-Varying Expected Growth Models
Hasler, Michael,Khapko, Mariana
SSRN
Equilibrium asset-pricing models with time-varying expected economic growth have been criticized for their apparent inability to generate an upward-sloping yield curve and downward-sloping term structures of equity risk and risk premium. We theoretically investigate the model-implied equilibrium relationships between the shape of these term structures, the dynamics of economic fundamentals, and the representative agent's preferences. We show that this class of models is, in fact, flexible in its ability to reproduce the aforementioned shapes, while also generating realistic asset-pricing moments.

The Agency Problems of Institutional Investors: Presentation Slides
Bebchuk, Lucian A.,Cohen, Alma,Hirst, Scott
SSRN
The presentation slides in this document provide an overview of our study The Agency Problems of Institutional Investors, which was published in the Journal of Economic Perspectives in its summer 2007 issue. The slides build on our presentations at the 2017 ALEA annual meeting.Our study focuses on how the rise of institutional investors has transformed the governance landscape. The study analyzes the agency problems that the investment managers of institutional investors have vis-Ã -vis their own investors. We develop an analytical framework for examining these agency problems and apply it to study several key types of investment managers.We analyze how the investment managers of mutual funds - both index funds and actively managed funds - have incentives to under-spend on stewardship and to side excessively with managers of corporations. We show that these incentives are especially acute for managers of index funds, and that the rise of such funds has system-wide adverse consequences for corporate governance. Activist hedge funds have substantially better incentives than managers of index funds or active mutual funds, but their activities do not provide a complete solution for the agency problems of institutional investors.Our analysis provides a framework for future work on institutional investors and their agency problems, and generates insights on a wide range of policy questions. We discuss implications for disclosure by institutional investors; regulation of their fees; stewardship codes; the rise of index investing; proxy advisors; hedge funds; wolf pack activism; and the allocation of power between corporate managers and shareholders.Our study is part of a larger project on the incentives of investment managers that also includes Index Funds and the Future of Corporate Governance: Theory, Evidence, and Policy and The Specter of the Giant Three.

The Drivers of Cyber Risk
Aldasoro, IÃ±aki,Gambacorta, Leonardo,Giudici, Paolo,Leach, Thomas
SSRN
Cyber incidents are becoming more sophisticated and their costs difficult to quantify. Using a unique database of more than 100,000 cyber events across sectors, we document the characteristics of cyber incidents. Cyber costs are higher for larger firms and for incidents that impact several organisations simultaneously. The financial sector is exposed to a larger number of cyber attacks but suffers lower costs, on average, thanks to proportionately greater investment in information technology (IT) security. The use of cloud services is associated with lower costs, especially when cyber incidents are relatively small. As cloud providers become systemically important, cloud dependence is likely to increase tail risks. Crypto-related activities, which are largely unregulated, are particularly vulnerable to cyber attacks.

The Dynamics of the Implied Volatility Surface: A Story of Rare Economic Events
Hasler, Michael,Jeanneret, Alexandre
SSRN
We propose a macro-finance model that rationalizes robust features in equity-index option markets. When rare disasters are followed by rapid economic recoveries, the slope of the implied volatility term structure is positive in good times but turns negative in bad times. Additionally, implied volatility decreases with moneyness in bad times (volatility skew), while the shape becomes a smile in good times in the presence of rare economic booms. Our theory contributes to understanding the dynamics of the implied volatility surface while keeping standard asset pricing moments realistic.

The Effect of the Central Bank Liquidity Support during Pandemics: Evidence from the 1918 Influenza Pandemic
SSRN
The coronavirus outbreak raises the question of how central bank liquidity support affects financial stability and promotes economic recovery. Using newly assembled data on cross-county flu mortality rates and state-charter bank balance sheets in New York State, we investigate the effects of the 1918 influenza pandemic on the banking system and the role of the Federal Reserve during the pandemic. We find that banks located in more severely affected areas experienced deposit withdrawals. Banks that were members of the Federal Reserve System were able to access central bank liquidity, enabling them to continue or even expand lending. Banks that were not System members, however, did not borrow on the interbank market, but rather curtailed lending, suggesting that there was little-to-no pass-through of central bank liquidity. Further, in the counties most affected by the 1918 pandemic, even banks with direct access to the discount window did not borrow enough to offset large deposit withdrawals and so liquidated assets, suggesting limits to the effectiveness of liquidity provision by the Federal Reserve. Finally, we show that the pandemic caused only a short-term disruption in the financial sector.

The Idiosyncratic Impact of an Aggregate Shock: The Distributional Consequences of COVID-19
Benzeval, Michaela ,Burton, Jonathan,Crossley, Thomas F.,Fisher, Paul, JÃ¤ckle, Annette,Low, Hamish,Read, Brendan
SSRN
Using new data from the Understanding Society: COVID 19 survey collected in April 2020, we show how the aggregate shock caused by the pandemic affects individuals across the distribution. The survey collects data from existing members of the Understanding Society panel survey who have been followed for up to 10 years. Understanding society is based on probability samples and the Understanding Society Covid19 Survey is carefully constructed to support valid population inferences. Further the panel allows comparisons with a pre-pandemic baseline. We document how the shock of the pandemic translates into different economic shocks for different types of worker: those with less education and precarious employment face the biggest economic shocks. Some of those affected are able to mitigate the impact of the economic shocks: universal credit protects those in the bottom quintile, for example. We estimate the prevalence of the different measures individuals and households take to mitigate the shocks. We show that the opportunities for mitigation are most limited for those most in need.

The Public Blockchain Ecosystem: An Empirical Analysis
SSRN
This paper offers an organizing empirical framework to understand the largely unexplored public block-chain ecosystem. Our framework casts block-chains in terms of their key economic attributes rather than as a set of disparate objects. The framework takes inspiration from the block-chain trilemma, constructing empirical analogs for each of its three attributes: (i) scale, (ii) security, and (iii) decentralization. Our analysis uncovers an association between these attributes and block-chain consensus protocols. We establish that Proof-of-Work (PoW) block-chains dominate on decentralization; Delegated Proof-of-Stake (DPoS) block-chains dominate on scale, and block-chains using non-standard protocols dominate on security. We find that a small group of block-chains form the ecosystem's frontier, but no particular block-chain, not even Bitcoin, leads on all three attributes.

The Resilience of French Companies to the COVID-19 Crisis
Garel, Alexandre,Petit-Romec, Arthur
SSRN
This paper explores the resilience of French listed companies to the COVID-19 shock. We examine the effect of numerous firm characteristics related to financial flexibility, ownership structure, corporate governance, and corporate social responsibility on the stock returns during the COVID-19 shock. Our results show that French companies with more debt and less profitability experience worse stock returns, indicating the role played by financial flexibility. We also find that firms with greater ownership by short-term investors or active investors experience worse stock returns during the COVID-19 shock, suggesting that a base of shareholders with long-term orientation and commitment helps firms to weather the effect of market-wide shocks.

The Value of Green Energy under Regulation Uncertainty
Detemple, Jerome,Kitapbayev, Yerkin
SSRN
We examine investments in power generation projects under policy uncertainty, when the investor has the choice between two alternative technologies, a gas-fired plant and a wind plant. Increased risk of subsidy withdrawal reduces the payoff from and postpones investments in the wind technology. Simultaneously, it accelerates investments in gas, thereby eliminating or further postponing investments in wind capacity. We show that this substitution phenomenon can be of first order importance: it can have a significant impact on the timing of investment, the wind premium, and the probability of investing in the wind technology. Our results provide new insights about the scope and impact of green energy regulation.

The equivalent constant-elasticity-of-variance (CEV) volatility of the stochastic-alpha-beta-rho (SABR) model
Jaehyuk Choi,Lixin Wu
arXiv

This study presents new analytic approximations of the stochastic-alpha-beta-rho (SABR) model. Unlike existing studies that focus on the equivalent Black-Scholes (BS) volatility, we instead derive the equivalent constant-elasticity-of-variance (CEV) volatility. Our approach effectively reduces the approximation error in a way similar to the control variate method because the CEV model is the zero vol-of-vol limit of the SABR model. Moreover, the use of CEV volatility has the effect of imposing an absorbing boundary condition at the origin and thus provides small-time asymptotics for the mass at zero. The numerical results compare favorably with the BS volatility approximations in terms of the approximation accuracy and no-arbitrage region.

Trump vs. Paris: The Impact of Climate Policy on U.S. Listed Oil and Gas Firm Returns and Volatility
Diaz-Rainey, Ivan,Gehricke, Sebastian,Roberts, Helen,Zhang, Renzhu
SSRN
We explore the stock market and option implied volatility response of the oil and gas industry to four policy events associated with the Paris Agreement and the election of Donald Trump. Our results show that the signing of the Paris Agreement had a large negative impact for the Oil and Gas sector (CAAR -8.4%), with Exploration and Production (CAAR -12.2%) and Drilling (CAAR -10.5%) most severely affected. This is further supported by an increase in implied volatility and by a structural break in option trader sentiment around the signing of the agreement. In general, the Paris Agreement had a much stronger impact on firms that had primarily U.S.-focused operations. Contrary to expectations, the election of Donald Trump and the announced withdrawal of the U.S. from the Paris Agreement negatively affected some sub-sectors (transport and integrated) and the sector overall. We attribute this to (1) Trumpâ€™s policies supporting domestic production (benefitting unlisted independent producers at the expense of listed competitors with import and international assets), and (2) on â€œWe Are Still Inâ€ efforts by U.S. states, cities and companies to continue to meet Paris Agreement goals. Overall, our results indicated that investors are pricing current policies when examining climate risk and that, in this respect, the Paris agreement trumped Trump.

Uncertainty Resolution Before Earnings Announcements
Gao, Chao,Hu, Grace Xing,Zhang, Xiaoyan
SSRN
We show that 71% of the earnings announcement premium takes place before, rather than after, earning releases. We attribute this pattern to uncertainty resolution before earnings announcement, and provide compelling evidence that high uncertainty stocks experience more uncertainty resolution and therefore have larger pre-announcement return before earnings releases. This effect is stronger when the aggregate market uncertainty is high and when earnings announcements carry more systematic uncertainty. Both the systematic and idiosyncratic components of a firmâ€™s uncertainty can predict its pre-announcement return. Uncertainty resolution could happen via two distinct channels: information acquisition by investors and information supply by analysts.

Value Creation Principles: PowerPoint Presentation