# Research articles for the 2020-10-14

Accuracy of Deep Learning in Calibrating HJM Forward Curves
Fred Espen Benth,Nils Detering,Silvia Lavagnini
arXiv

We price European-style options written on forward contracts in a commodity market, which we model with an infinite-dimensional Heath-Jarrow-Morton (HJM) approach. For this purpose we introduce a new class of state-dependent volatility operators that map the square integrable noise into the Filipovi{\'{c}} space of forward curves. For calibration, we specify a fully parametrized version of our model and train a neural network to approximate the true option price as a function of the model parameters. This neural network can then be used to calibrate the HJM parameters based on observed option prices. We conduct a numerical case study based on artificially generated option prices in a deterministic volatility setting. In this setting we derive closed pricing formulas, allowing us to benchmark the neural network based calibration approach. We also study calibration in illiquid markets with a large bid-ask spread. The experiments reveal a high degree of accuracy in recovering the prices after calibration, even if the original meaning of the model parameters is partly lost in the approximation step.

Acquisitions and Social Capital
Hossain, Ashrafee T,Jha, Anand
SSRN
We find that when an acquirer is headquartered in a high social capital state in the US, it has a higher cumulative abnormal return (CAR) around an acquisition announcement. A one standard deviation increase in social capital is associated with a 3.63% increase in the standard deviation of the announcement period CAR, which is comparable to the effect of corporate governance in Masulis et al. (2007). This effect is robust and incremental to the effect of corporate social responsibility. Acquirers in high social capital states are also more likely to buy private targets with equity, less likely to acquire firms in unrelated industries, and less likely to be a serial acquirer. Further, we find that the effect of social capital on the CAR is much stronger when monitoring is weak. We conclude that social capital reduces the agency cost that is associated with an acquisition.

An Analysis of Cryptocurrency and Their Functioning
Soni, Neha
SSRN
Cryptocurrency is a digital currency which acquires cryptography to secure the transactions. It is designed to make payments anonymously and in more secured way. In this paper, I first explain the detailed meaning of cryptocurrency. Then some features of trade in cryptocurrency are discussed such as the technique include the zero involvement of any governmental authority and allowing users to store and trade anonymously. Next, I demonstrate the facts and functioning of blockchain technology. It is believed that block chain technique has potential to disrupt many industries such as finance, law, banking or accounting. For the explanation of this, I state some critic point of views for the use of cryptocurrencies. It also faces criticism for vulnerabilities of the infrastructure and volatility of exchange rates. Being the nature of anonymous, cryptocurrency becomes a host for money laundering, tax evasion and other illicit activities. After this, I bring to discuss the types of cryptocurrency. Today there are thousands of cryptocurrencies with various functions and specifications. Some of the very first and famous cryptocurrencies are studied in the paper such as Bitcoin, Ethereum and XRP. The timeline of global market growth of cryptographic currencies are covered next. The idea of digital currency is not new. From 1998, Wei Daiâ€™s â€˜B-moneyâ€™ concept to first ever functioning cryptocurrency â€˜Bitcoinâ€™ in 2008, many digital currencies introduced. For that some basic terminologies are bought to discuss in the paper. And lastly the journey of cryptocurrency in India is described.

An Application of Dirac's Interaction Picture to Option Pricing
Mauricio Contreras G
arXiv

In this paper, the Dirac's quantum mechanical interaction picture is applied to option pricing to obtain a solution of the Black-Scholes equation in the presence of a time-dependent arbitrage bubble. In particular, for the case of a call perturbed by a square bubble, an approximate solution (valid up third order in a perturbation series) is given in terms of the three first Greeks: Delta, Gamma, and Speed. Then an exact solution is constructed in terms of all higher order $S$-derivatives of the Black-Scholes formula. It is also shown that the interacting Black-Scholes equation is invariant under a discrete transformation that interchanges the interest rate with the mean of the underlying asset and vice versa. This implies that the interacting Black-Scholes equation can be written in a 'low energy' and a 'high energy' form, in such a way that the high-interaction limit of the low energy form corresponds to the weak-interaction limit of the high energy form. One can apply a perturbative analysis to the high energy form to study the high-interaction limit of the low energy form.

Anatomy of Corporate Credit Spreads: The Great Recession vs. Covid-19
Ebsim, Mahdi,Faria-e-Castro, Miguel,Kozlowski, Julian
SSRN
We compare the evolution of corporate credit spreads during the Great Recession and the COVID-19 pandemic. The two crises featured increases of similar magnitudes in the median and cross-sectional dispersion of credit spreads, but the pandemic was short-lived and different sectors were affected. The micro-data reveal larger differences between the two episodes: the Great Recession featured an increase in the across-firm dispersion, and leverage was an important predictor of credit spreads. Differently, the COVID-19 crisis displayed a larger increase in within-firm dispersion, and funding liquidity was a more important predictor of movements in spreads. These findings suggest that, at the corporate level, the Great Recession was primarily a solvency crisis, while COVID-19 was a liquidity crisis.

Bureaucratic Discretion and Contracting Outcomes
Boland, Matthew,Godsell, David
SSRN
We find that federal bureaucrats award more, larger, and less risky contracts to politically connected firms when they have greater discretion over contracting outcomes. Using a sample of 4.3 million federal government contract actions obligating $2.47 trillion between 2000 and 2015, we show that this result varies predictably across contract and agency characteristics, over time, and in placebo tests, and is robust to a comprehensive fixed effect structure and seven alternate measures of political connectedness. Our evidence illustrates the overlooked role of the bureaucrat in facilitating political bias in federal contracting outcomes. Business Portfolio, Market Share and Trend of Nepalese Non-Life Insurance Market Ghimire, Rabindra SSRN The aim of the paper is to observe the trend and growth of market share of seven different non-life insurance policies in Nepal and examine business performance of Nepalese non-life insurers in terms of premium written during the study period. Secondary data of twenty companies for FY 2015 to 2019 have been analyzed with descriptive statistic. It has been found that market share of fire and aviation business decreased with fluctuation, marine business remain constant, motor and agriculture insurance fluctuated and increased, engineering insurance increased, and miscellaneous insurance fluctuated and remained constant during five years period. Non-life insurance market experienced slow growth during the study period. Among the seven different segments of business, motor insurance occupied highest share while agriculture occupied lowest share. The growth of aviation market is very slow while agriculture is very high. Out of 17 old companies, Shikhar, Sagarmatha and Neco insurers stood at first, second and third rank in terms of premium written during 2019. The potentiality of non-life insurance market is high but due to the lack of extra efforts of insurers, the market growth is not found impressive. COVID-19 and the Potency of Disruption on the Islamic Banking Performance (Indonesia Cases) Nugroho, Lucky,Utami, Wiwik,harnovinsah, harnovinsah,Doktoralina, Caturida Meiwanto SSRN The indicators commonly used in conducting simulations are economic growth and the US Dollar exchange rate. The purpose of this study is to conduct a stress test on the impact of macroeconomic changes on key financial indicators of the three largest Islamic banks in Indonesia, which are subsidiaries of state-owned banks. The banks are Bank Mandiri Syariah (BSM), BNI Syariah (BNIS), and BRI Syariah (BRIS). The stress test method in this study uses three scenarios, namely: mild, moderate, and worst. Furthermore, the key financial indicators used in this research are assets, net profit, return on assets (ROA), and non-performing financing (NPF). The stress test results state that the mild scenario and moderate scenario of the Islamic banking industry can still endure. However, inthe worst-case scenario, NPF of the Islamic banking industry has a significant increase. Also, during the current COVID-19 pandemic, banks must mitigate risk early by strengthening liquidation, restructuring, and changing strategic initiatives. Also, there is an alternative to merge of Islamic Bank that subsidiaries from its state bank. Furthermore, the government and all stakeholders must collaborate to overcome the negative effects of the COVID-19 pandemic outbreak to avoid major losses to both the lives of the people and the nation's economy. Catastrophic health expenditure and inequalities -- a district level study of West Bengal Pijush Kanti Das arXiv In this study, I aimed to estimate the incidence of catastrophic health expenditure and analyze the extent of inequalities in out-of-pocket health expenditure and its decomposition according to gender, sector, religion and social groups of the households across Districts of West Bengal. I analysed health spending in West Bengal, using National Sample Survey 71st round pooled data suitably represented to estimate up to district level. We measured CHE at different thresholds when OOP in health expenditure. Gini Coefficients and its decomposition techniques were applied to assess the degree of inequality in OOP health expenditures and between different socio geographic factors across districts. The incidence of catastrophic payments varies considerably across districts. Only 14.1 percent population of West Bengal was covered under health coverage in 2014. The inequality in OOP health expenditure for West Bengal has been observed with gini coefficient of 0.67. Based on the findings from this analysis, more attention is needed on effective financial protection for people of West Bengal to promote fairness, with special focus on the districts with higher inequality. This study only provides the extent of CHE and inequality across Districts of West Bengal but the causality may be taken in future scope of study. China's 2060 carbon neutrality goal will require up to 2.5 GtCO2/year of negative emissions technology deployment Jay Fuhrman,Andres F. Clarens,Haewon McJeon,Pralit Patel,Scott C. Doney,William M. Shobe,Shreekar Pradhan arXiv China's pledge to reach carbon neutrality by 2060 is ambitious and could provide the world with much-needed leadership on how to achieve a +1.5 degC warming target above pre-industrial levels by the end of the century. But the pathways that would achieve net zero by 2060 are still unclear including the dependence on negative emissions technologies. Here, we use the Global Change Analysis Model (GCAM 5.3), a dynamic-recursive, technology-rich integrated assessment model, to simulate how negative emissions technologies, in general, and direct air capture (DAC), in particular, will contribute to China's meeting this target. Our results show that, for China to be net-zero in 2060, it would need to deploy negative emissions technologies (NETs) at very large scales, on the order of 2.5 GtCO2 negative emissions per year with up to 1.5 GtCO2 per year of that coming from DAC. DAC, like other forms of negative emissions, such as bioenergy with carbon capture and storage and afforestation is an emerging technology that has not been demonstrated at a commercial scale. Deploying NETs at this scale will have widespread impacts on financial systems and resources availability such as water, land, and energy in China and beyond. Common Ownership, Competition, and Top Management Incentives Anton, Miguel,Ederer, Florian,Gine, Mireia,Schmalz, Martin C. SSRN When one firmâ€™s strategy affects other firmsâ€™ value, optimal executive incentives depend on whether shareholders have interests in only one or in multiple firms. Performance-sensitive contracts induce managerial effort to reduce costs, and lower costs induce higher output. Hence, greater managerial effort can lead to lower product prices and industry profits Therefore, steep managerial incentives can be optimal for a single firm and at the same time violate the interests of common owners of several firms in the same industry. Empirically, managerial wealth is more sensitive to performance when a firmâ€™s largest shareholders do not own large stakes in competitors. Corporate Lending in January-July 2020 Zubov, Sergey SSRN On the back of the implementation of containment measures due to the spread of the coronavirus infection, the Central Bank of Russia took a host of regulatory measures aimed at reducing banksâ€™ expenses on creation of loan loss provisions and stimulating soft lending. From the point of view of liquidity and capital provisions, the CB actions coupled with the banking system resilience allowed to avoid repetition of the credit shocks of 2008 and 2014 and ramp up volumes of corporate lending. Debt Financing of Small OTC Firms Reporting to the SEC Cole, Rebel A.,Liang, Claire Y.C.,Zhang, Rengong SSRN We examine the usage of debt by small firms trading on the over-the-counter (OTC) market and filing annual reports with the SEC. Similar to firms included in the Survey of Small Business Finance, the small OTC firms in our sample are more dependent on debt financing than firms listed on the NYSE and NASDAQ, despite having high R&D intensity and being smaller, younger and less profitable than NYSE/NASDAQ firms. We find that debt usage increases and debt composition changes as these small OTC firms develop. Specifically, positive sales and positive cash flows mark two milestones of debt financing: Positive sales broaden their access to various segments of the debt market, while positive cash flows deepen their relationships with conventional lenders, such as banks. Our study indicates that debt capital, with its diversified sources and flexible features, supplements equity to finance the development of small firms, even for non-profitable research-intensive ventures. Dynamic Programming with State-Dependent Discounting John Stachurski,Junnan Zhang arXiv This paper extends the core results of discrete time infinite horizon dynamic programming to the case of state-dependent discounting. We obtain a condition on the discount factor process under which all of the standard optimality results can be recovered. We also show that the condition cannot be significantly weakened. Our framework is general enough to handle complications such as recursive preferences and unbounded rewards. Economic and financial applications are discussed. Financial Constraints and Propagation of Shocks in Production Networks Pakel, Banu Demir,Javorcik, Beata Smarzynska,Michalski, Tomasz Kamil,Ors, Evren SSRN This study finds that even small unexpected supply shocks propagate downstream through production networks and are amplified by firms with short-term financial constraints. The unexpected 2011 increase in the tax on imports purchased with foreign-sourced trade credit is examined using data capturing almost all Turkish supplier-customer links. The identification strategy exploits the heterogeneous impact of the shock on importers. The results indicate that this relatively minor, non-localized shock had a non-trivial economic impact on exposed firms and propagated downstream through affected suppliers. Additional empirical tests, motivated by a simple theory, demonstrate that low-liquidity firms amplified its transmission. Firm Performance Pay as Insurance against Promotion Risk Chen, Alvin SSRN The prevalence of pay based on risky firm outcomes for non-executive workers presents a puzzling departure from conventional contract theory, which predicts insurance provision by the firm. I revisit this puzzle in a framework with workers who prefer early resolution of uncertainty. When workers at the same firm compete against each other for promotions, the optimal contract features pay based on firm outcomes as insurance against unfavorable promotion prospects. The modelâ€™s predictions are consistent with observed phenomena such as option-like payoffs, performance-based vesting, and over-valuation of equity pay by non-executive workers. It also generates novel predictions linking organizational structure to firm performance pay. Global SARS-CoV-2 Pandemic: The Impact on Libraries Abulude, Ifeoluwa Ayodeji,Gbotoso , Arinola,Abulude, Francis Olawale SSRN The library is one of the sections in an educational sector that contributes to knowledge. Most of the libraries worldwide operate on a 24-hr basis, but a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic came and ravaged many countries of the world and turned their libraries into â€˜ghostâ€˜ arenas for about eight months. To protect the stakeholders (students, lecturers, staff, and visitors) from the infection of the virus, the management of each institution and associations ordered the partial or total closure of the libraries until the official announcement of the reduction of the risk from SARS-CoV-2. To ensure continuous contacts to the library, many libraries have resulted in the use of virtual methods where they provide e-books, e-journals, e-magazines, and many others to those who require the services. The objective of this work is to present a systematic review of the effects the pandemic has on the libraries and the stakeholders and the preparations for re-opening partially or fully How Different Is Real Estate? A Story of Factors Peng , Liang SSRN How different is real estate from stocks and bonds? This paper sheds light on this question with new data and new methods. Analyzing 10,848 commercial properties from 1977 to 2017, we find that propertiesâ€™ risk premiums contain systematic components that are orthogonal to a comprehensive list of stock and bond factors. We call these components real estate factors. We also find that properties in each region and property type have their own factors. The real estate factors have substantial incremental explanatory power for individual propertiesâ€™ risk premiums, and propertiesâ€™ attributes are related to their loadings of the real estate factors. How do Taxes Affect the Trading Behavior of Private Investors? Evidence from Individual Portfolio Data Buhlmann, Florian,Doerrenberg, Philipp,Voget, Johannes,Loos, Benjamin SSRN We exploit a large reform of capital-gains taxation in Germany combined with portfolio-level daily panel data to study the causal eï¬€ect of taxes on individual stock-trading behavior and the disposition eï¬€ect. We ï¬nd substantial spikes in selling probabilities around an intertemporal tax discontinuity, and no such spikes after the abolishment of the discontinuity. Using diï¬€erence-in-bunching methods, nonparametric regressions and eï¬€ective tax rates, we quantify the tax eï¬€ect and identify interesting patterns of heterogeneity. We further ï¬nd evidence that the wellestablished disposition eï¬€ect is strongly aï¬€ected by the tax discontinuity through tax motivated selling of both gains and losses. Incomplete Financial Markets and the Over-Development of the Chinese Housing Sector Bayoumi, Tamim,Zhao, Yunhui SSRN Housing is by far the most important asset in Chinese householdsâ€™ balance sheets. However, despite forceful and frequent government interventions, the rise in Chinese housing prices has not been contained as much as intended, a trend that has not been reversed by the COVID-19 shock. In this paper, we highlight the impact of a â€œslow-movingâ€ structural factorâ€"financial market incompletenessâ€"on Chinaâ€™s housing prices using a stylized DSGE model with heterogeneous households that encompasses both demand and supply channels. The model implies that to eradicate the root causes of the rising housing price, policymakers need to go beyond the housing market itself; instead, it would be desirable to deepen financial markets because these markets would help channel financial resources to productive sectors rather than to housing speculation. This is particularly important in the context of fighting the COVID crisis because without addressing this structural vulnerability, the government stimulus may fuel the housing bubble and sow seeds for a future crisis. The paper can also shed light on the housing markets in other economies that face similar vulnerabilities or policy trade-offs. Innovative Entrepreneurship as a Collaborative Effort: An Institutional Framework Elert, Niklas,Henrekson, Magnus SSRN We demonstrate how successful entrepreneurship depends on a collaborative innovation bloc (CIB), a system of innovation that evolves spontaneously and within which activity takes place through time. A CIB consists of six pools of economic skills from which people are drawn or recruited to form part of a collaborative team, which is necessary for innovation-based venturing to flourish. The six pools include entrepreneurs, inventors, early- and later-stage financiers, key personnel, and customers. We show how the application of the CIB perspective can help make institutional and evolutionary economics more concrete, relevant, and persuasive, especially regarding institutional prescriptions. Generally, we envision an institutional framework that improves the antifragility of CIBs and the economic system as a whole, thus enabling individual CIBs and the broader economic system to thrive when faced with adversity. Investment and Asset Pricing with ESG Disagreement Avramov, Doron,Cheng, Si,Lioui, Abraham,Tarelli, Andrea SSRN This paper analyzes the equilibrium implications of ESG rating disagreement for investment decisions and asset pricing. Rating disagreement leads to higher effective risk aversion and market premium as well as lower demand for stocks, either brown or green. In addition, disagreement tilts the negative ESG-CAPM alpha relationship and affects the systematic risk exposure. Combining ESG ratings from six major rating agencies, we provide supporting evidence for the model predictions. Our findings help reconcile the mixed evidence on the cross-sectional return predictability of ESG ratings and reinforce the notion that the lack of consistency in ESG ratings considerably hurts investment opportunities and economic welfare. Long term dynamics of poverty transitions in India Anand Sahasranaman arXiv We model the dynamics of poverty using a stochastic model of Geometric Brownian Motion with reallocation (RGBM) and explore both transient and persistent poverty over 1952-2006. We find that annual transitions in and out of poverty are common and show a rising trend, with the rise largely being driven by transitions out of poverty. Despite this promising trend, even toward the end of the time frame, there is a non-trivial proportion of individuals still transitioning annually into poverty, indicative of the economic fragility of those near the poverty line. We also find that there is still a marked persistence of poverty over time, though the probability of poverty persistence is slowly declining. Particularly concerning in this context are the poverty trajectories of those at the very bottom of the income distribution. The choice of poverty line appears to impact the dynamics, with higher poverty lines corresponding to lower transitions and higher persistence probabilities. The distinct nature of emergent transient and persistence dynamics suggests that the approaches to counter these phenomena need to be different, possibly incorporating both missing financial markets and state action. Markov Decision Processes with Recursive Risk Measures Nicole Bäuerle,Alexander Glauner arXiv In this paper, we consider risk-sensitive Markov Decision Processes (MDPs) with Borel state and action spaces and unbounded cost under both finite and infinite planning horizons. Our optimality criterion is based on the recursive application of static risk measures. This is motivated by recursive utilities in the economic literature, has been studied before for the entropic risk measure and is extended here to an axiomatic characterization of suitable risk measures. We derive a Bellman equation and prove the existence of Markovian optimal policies. For an infinite planning horizon, the model is shown to be contractive and the optimal policy to be stationary. Moreover, we establish a connection to distributionally robust MDPs, which provides a global interpretation of the recursively defined objective function. Monotone models are studied in particular. Mental Accounting, Loss Aversion, and Tax Evasion: Theory and Evidence Dhami, Sanjit,Hajimoladarvish, Narges SSRN The evidence shows source-dependent entitlement to income sources and individuals are reluctant to part with income they feel more entitled to, e.g., earned labor income. Taxpayers may also be more reluctant to part with tax payments (evade more) from income sources they feel more entitled to- a form of mental accounting. We embed two main hypotheses within a rigorous theoretical model based on prospect theory. From incomes sources they feel more entitled to, taxpayers experience (i) greater loss aversion from paying taxes, and (ii) lower moral costs of evasion. We confirm the predictions of our model through MTurk experiments. Evasion is increasing in the tax rate and decreasing in the audit penalty. Moral costs influence taxpayers decisions. Loss aversion, measured â€œdirectlyâ€ for the first time for each individual in an evasion experiment, reduces evasion, as predicted by our theory. Loss aversion, risk aversion, and their interaction, are critical determinants of evasion. Modeling and analysis of the effect of COVID-19 on the stock price: V and L-shape recovery Ajit Mahata,Anish rai,Om Prakash,Md Nurujjaman arXiv The emergence of the COVID-19 pandemic, a new and novel risk factor, leads to the stock price crash due to the investors' rapid and synchronous sell-off. However, within a short period, the quality sectors start recovering from the bottom. A stock price model has been developed during such crises based on the net-fund-flow ($\Psi_t$) due to institutional investors, and financial antifragility ($\phi$) of a company. We assume that during the crash, the stock price fall is independent of the$\phi$. We study the effects of shock lengths and$\phi$on the stock price during the crises period using the$\Psi_t$obtained from synthetic and real fund flow data. We observed that the possibility of recovery of stock with$\phi>0$, termed as quality stock, decreases with an increase in shock-length beyond a specific period. A quality stock with higher$\phi$shows V-shape recovery and outperform others. The shock length and recovery period of quality stock are almost equal that is seen in the Indian market. Financially stressed stocks, i.e., the stocks with$\phi<0$, show L-shape recovery during the pandemic. The stock data and model analysis shows that the investors, in the uncertainty like COVID-19, invest in the quality stocks to restructure their portfolio to reduce the risk. The study may help the investors to make the right investment decision during a crisis. Monitoring War Destruction from Space: A Machine Learning Approach Hannes Mueller,Andre Groger,Jonathan Hersh,Andrea Matranga,Joan Serrat arXiv Existing data on building destruction in conflict zones rely on eyewitness reports or manual detection, which makes it generally scarce, incomplete and potentially biased. This lack of reliable data imposes severe limitations for media reporting, humanitarian relief efforts, human rights monitoring, reconstruction initiatives, and academic studies of violent conflict. This article introduces an automated method of measuring destruction in high-resolution satellite images using deep learning techniques combined with data augmentation to expand training samples. We apply this method to the Syrian civil war and reconstruct the evolution of damage in major cities across the country. The approach allows generating destruction data with unprecedented scope, resolution, and frequency - only limited by the available satellite imagery - which can alleviate data limitations decisively. Multiple yield curve modelling with CBI processes Claudio Fontana,Alessandro Gnoatto,Guillaume Szulda arXiv We develop a modelling framework for multiple yield curves driven by continuous-state branching processes with immigration (CBI processes). Exploiting the self-exciting behavior of CBI jump processes, this approach can reproduce the relevant empirical features of spreads between different interbank rates. In particular, we introduce multi-curve models driven by a flow of tempered alpha-stable CBI processes. Such models are especially parsimonious and tractable, and can generate contagion effects among different spreads. We provide a complete analytical framework, including a detailed study of discounted exponential moments of CBI processes. The proposed approach allows for explicit valuation formulae for all linear interest rate derivatives and semi-closed formulae for non-linear derivatives via Fourier techniques and quantization. We show that a simple specification of the model can be successfully calibrated to market data. Municipal Bond Sectoral Risk and Information Intermediation in Uncertain Times: Evidence from the COVID-19 Pandemic Yang, Lang Kate,Winecoff, Ruth SSRN The municipal bond market is not homogeneous but consists of varying credits supporting different governmental activities. The literature lacks a formal framework to understand sectoral risk in the market. In this paper we discuss how sectors are formed and how they are differentially subject to market risks, using the COVID-19 pandemic as a case study. The pandemic has brought unprecedented challenges to financial markets, and particularly to some municipal bond sectors supported by non-general obligation credits, such as health care, higher education, and recreation. We empirically examine how government issuers, faced with elevated risk, conduct their issuance to mitigate information asymmetry in this uncertain time. We find an increased use of negotiated underwriting and bond insurance but not credit ratings. However, the uses of negotiated underwriting and bond insurance are not associated with larger reductions in offering yield in the high-risk sectors than the low-risk sectors. The yield difference between unrated and rated bonds expands more in the high-risk sectors. Primary market data from California suggest that bond insurance may be associated with more borrowing cost savings for the high-risk sectors when the spread of COVIDis high. On the Shareholder- versus Stakeholder-Firm Debate Bejan, Camelia SSRN When externalities are present, is the inclusion of the affected stakeholders in the firm's decision process a better solution than government regulation? Magill, Quinzii, and Rochet (2015) argue that it is, and propose an objective for the stakeholder corporation as well as a market mechanism to implement it. This paper shows that: (1) within the framework of Magill, Quinzii, and Rochet's (2015) model, the shareholder-oriented firm and the government can implement the same outcome even when the government does not know the firm's costs; (2) outside that framework, the proposed stakeholder objective fails to address the inefficiency. The results help garner more insight into the difficulties and limitations of embedding the stakeholder corporation into a general equilibrium model. Political Booms, Currency Crises and Economic Growth Sever, Can SSRN This paper finds evidence that political booms, defined as the rise in governmentsâ€˜ popularity, are a good predictor of currency crises, suggesting that currency crises are often â€œpolitical booms gone bustâ€ events. The result is robust to controlling for other potential predictors of crises and contagion across countries, and not likely to be driven by banking crises preceding currency crises. It also shows that political booms are associated with lower GDP in the long-term upwards of 10 years, possibly through their effect on the occurrence of crises. Powering Work from Home Cicala, Steve SSRN This paper documents an increase in residential electricity consumption while industrial and commercial consumption has fallen during the COVID-19 pandemic in the United States. Hourly smart meter data from Texas reveals how daily routines changed during the pandemic, with usage during weekdays closely resembling those of weekends. The 16% residential increase during work hours oï¬€sets the declines from commercial and industrial customers. Using monthly data from electric utilities nationwide, I find a 10% increase in residential consumption, and a 12% and 14% reduction in commercial and industrial usage, respectively, during the second quarter of 2020. This contrasts with the financial crisis of 2008, which also witnessed a rapid decline in industrial electricity consumption, but left residential usage unaffected. The increase in residential consumption is found to be positively associated with the share of the labor force that may work from home. From April through July of 2020, total excess expenditure on residential electricity was nearly$6B.

Rise of the â€œQuantsâ€ in Financial Services: Regulation and Crowding Out of Routine Jobs
Makridis, Christos,Rossi, Alberto G.
SSRN
We document three recent trends in employment in financial services: (a) the share of science, technology, engineering, and math (STEM) workers grew by 30 percent between 2011 and 2017; (b) while the earnings premium of working in finance has grown, the STEM premium in finance has declined since 2011; and (c) regulatory restrictions in financial services have grown faster than in other sectors. We investigate three economic mechanisms underlying these patterns: (a) capital-skill complementarity, (b) relabeling of non-STEM degree programs as STEM degree programs, and (c) regulation. We show that only the rise in regulation can explain our observations.

Should the Ransomware be Paid?
Rui Fang,Maochao Xu,Peng Zhao
arXiv

Ransomware has emerged as one of the most concerned cyber risks in recent years, which has caused millions of dollars monetary loss over the world. It typically demands a certain amount of ransom payment within a limited timeframe to decrypt the encrypted victim's files. This paper explores whether the ransomware should be paid in a novel game-theoretic model from the perspective of Bayesian game. In particular, the new model analyzes the ransom payment strategies within the framework of incomplete information for both hacker and victim. Our results show that there exist pure and randomized Bayesian Nash equilibria under some mild conditions for the hacker and victim. The sufficient conditions that when the ransom should be paid are presented when an organization is compromised by the ransomware attack. We further study how the costs and probabilities of cracking or recovering affect the expected payoffs of the hacker and the victim in the equilibria. In particular, it is found that the backup option for computer files is not always beneficial, which actually depends on the related cost. Moreover, it is discovered that fake ransomware may be more than expected because of the potential high payoffs. Numerical examples are also presented for illustration.

The (Unobservable) Value of Central Bank's Refinancing Operations
Albertazzi, Ugo,Burlon, Lorenzo,Pavanini, Nicola,Jankauskas, Tomas
SSRN
We quantify the impact that central bank refinancing operations and funding facilities had at reducing the banking sectorâ€™s intrinsic fragility in the euro area in 2014-2019. We do so by constructing, estimating and calibrating a micro-structural model of imperfect competition in the banking sector that allows for runs in the form of multiple equilibria, in the spirit of Diamond & Dybvig (1983), banksâ€™ default and contagion, and central bank funding. Our framework incorporates demand and supply for insured and uninsured deposits, and for loans to firms and households, as well as borrowersâ€™ default. The estimation and the calibration are based on confidential granular data for the euro area banking sector, including information on the amount of deposits covered by the deposit guarantee scheme and the borrowing from the European Central Bank (ECB). We document that the quantitative relevance of non-fundamental risk is potentially large in the euro area banking sector, as witnessed by the presence of alternative equilibria with run-type features, but also that central bank interventions exerted a crucial role in containing fundamental as well as non-fundamental risk. Our counterfactuals show that 1 percentage point reduction (increase) in the ECB lending rate of its refinancing operations reduces (increases) the median of banksâ€™ default risk across equilibria by around 50%, with substantial heterogeneity of this pass-through across time, banks and countries.

The Calendar Effects of the Idiosyncratic-Volatility Puzzle: A Tale of Two Days?
Cao, Jie,Chordia, Tarun,Zhan, Xintong
SSRN
The idiosyncratic volatility (IVOL) anomaly exhibits strong calendar effects. The negative relation between IVOL and the next month return obtains mainly in the third week of the month. The IVOL-return relation is generally negative on Mondays and positive on Fridays. However, the positive impact is absent on the third Friday due to selling pressure from stocks delivered at option expiration. This imbalance between the negative and positive returns during the third week of the month has a large impact on the IVOL-return relation. Removing the third Friday and subsequent Monday return reduces the monthly IVOL effect by at least 40%.

The Conduits of Price Discovery: A Machine Learning Approach
Kwan, Amy,Philip, Richard,Shkilko, Andriy
SSRN
Theory models suggest that market conditions could have substantial effects on order submission strategies and price discovery. Empirical analyses of such conditional effects are methodologically challenging and therefore uncommon. We bypass these challenges using a machine learning technique that allows for multiple conditioning variables in the presence of non-linearities. The analysis confirms theory predictions in that price discovery is affected, and often dominated, by such conditions as the state of the limit order book and prior order history. Furthermore, the technique allows us to rank the importance of conduits through which information flows into prices. The current state of the limit order book stands out as the primary conduit.

The Dynamics of Daily, Intraday and Overnight Betas
Insana, Alessandra
SSRN
We investigate on the dynamics of intraday and overnight systematic risk through beta estimation. In order to understand if beta shows a different behavior overnight, we divide the total daily return into intraday and overnight return and evaluate daily, intraday and overnight betas. We estimate our betas starting from the Capital Asset Pricing Model (CAPM) assuming a constant systematic risk. Afterwards, we consider a non-parametric method for timevarying conditional betas that was proposed by Ang and Kristensen (2012) and Li and Yang (2011). We conduct our analysis on the universe of US stocks, evaluating our three kinds of beta considering single stocks and also aggregating them into portfolios by market capitalization. Empirical evidence shows substantial differences between intraday and overnight betas. In particular we find higher values for intraday betas that imply an higher intraday systematic risk.

The Global Factor Structure of Exchange Rates
Korsaye, Sofonias A.,Trojani, Fabio,Vedolin, Andrea
SSRN
We provide a model-free framework to study the global factor structure of exchange rates. To this end, we propose a new methodology to estimate international stochastic discount factors (SDFs) that jointly price cross-sections of international assets, such as stocks, bonds, and currencies, in the presence of frictions. We theoretically establish a two-factor representation for the cross-section of international SDFs, consisting of one global and one local factor, which is independent of the currency denomination. We show that our two-factor specification prices a large cross-section of international asset returns, not just in- but also out-of-sample with R2s of up to 80%.

The Underlying Economic Components of Acquired Goodwill
Linsmeier, Thomas,Wangerin, Daniel,Wheeler, Erika
SSRN
In this study, we investigate what makes up acquired goodwill and find that it consists of at least three distinct components: expected synergies from combining the assets of the target and acquirer, the going concern value of the target firm, and overpayment. We identify these components empirically through a factor analysis on target, acquirer, and acquisition characteristics. We then document that acquired goodwill is positively associated with the synergy value, going concern value, and residual components. Further, we predict and find that going concern value and expected synergies are associated with a lower risk of future goodwill impairment, but that synergies reduce the risk of goodwill impairment more than the going concern value component. We also find that overpayment is associated with a greater risk of future goodwill impairment. The evidence we provide on the nature of acquired goodwill is important to understand how to account for goodwill subsequent to the acquisition, as each of these components have a different effect on the future cash inflows to the entity. Our findings suggest that a one-size-fits-all subsequent accounting alternative for goodwill may be difficult to apply due to heterogeneity in the economic components of goodwill.