Research articles for the 2020-10-29

A deep neural network algorithm for semilinear elliptic PDEs with applications in insurance mathematics
Stefan Kremsner,Alexander Steinicke,Michaela Szölgyenyi

In insurance mathematics optimal control problems over an infinite time horizon arise when computing risk measures. Their solutions correspond to solutions of deterministic semilinear (degenerate) elliptic partial differential equations. In this paper we propose a deep neural network algorithm for solving such partial differential equations in high dimensions. The algorithm is based on the correspondence of elliptic partial differential equations to backward stochastic differential equations with random terminal time.

Anticipated impacts of Brexit scenarios on UK food prices and implications for policies on poverty and health: a structured expert judgement update
Martine J Barons,Willy Aspinall

Food insecurity is associated with increased risk for several health conditions and with increased national burden of chronic disease. Key determinants for household food insecurity are income and food costs. Forecasts show household disposable income for 2020 expected to fall and for 2021 to rise only slightly. Prices are forecast to rise. Thus, future increased food prices would be a significant driver of greater food insecurity. Structured expert judgement elicitation, a well-established method for quantifying uncertainty, using experts. In July 2020, each expert estimated the median, 5th percentile and 95th percentile quantiles of changes in price to April 2022 for ten food categories under three end-2020 settlement Brexit scenarios: A: full WTO terms; B: a moderately disruptive trade agreement (better than WTO); C: a minimally disruptive trade agreement. When combined in proportions for calculate Consumer Prices Index food basket costs, the median food price change under full WTO terms is expected to be +17.9% [90% credible interval:+5.2%, +35.1%]; with moderately disruptive trade agreement: +13.2% [+2.6%, +26.4%] and with a minimally disruptive trade agreement +9.3% [+0.8%, +21.9%]. The number of households experiencing food insecurity and its severity are likely to increase because of expected sizeable increases in median food prices in the months after Brexit, whereas low income group spending on food is unlikely to increase, and may be further eroded by other factors not considered here (e.g. COVID-19). Higher increases are more likely than lower rises and towards the upper limits, these would entail severe impacts. Research showing a low food budget leads to increasingly poor diet suggests that demand for health services in both the short and longer term is likely to increase due to the effects of food insecurity on the incidence and management of diet-sensitive conditions.

Are Superstar Directors Effective in Corporate Governance?
Cheng, Silu,Baran, Lindsay
In this paper, I hand-collected a sample of prestigious business award-winner directors based on the four types of awards discussed by Chen, Wu, and Zhivotova (2017) and use them to represent reputable board of directors. I examine how awardee directors would influence management monitoring effectiveness and corporate governance by testing with CEO compensation level, pay-performance sensitivity, risk-taking behavior, accounting conservatism, and turnover-performance sensitivity. The results show that with award-winner directors sitting in the boards, CEOs receive more incentive compensation, have higher risk-taking incentives, and the firm adopts higher level of accounting conservatism. The findings suggest that reputable directors are effective in performing monitoring and advising duties.

Bank Capital Forbearance and Serial Gambling
Martynova, Natalya,Perotti, Enrico C.,Suarez, Javier
We analyze the strategic interaction between undercapitalized banks and a supervisor who may intervene by preventive recapitalization. Supervisory forbearance emerges because political and fiscal costs undermine supervisors' commitment to intervene. When supervisors have lower credibility, banks' incentives to voluntary recapitalize are lower and supervisors may end up intervening more. Importantly, when intervention capacity is constrained (e.g. for fiscal reasons), private recapitalization decisions become strategic complements, producing equilibria with extremely high forbearance and high systemic costs. Anticipating forbearance in response to diffuse undercapitalization, banks may ex ante choose more correlated risks, a form of "serial gambling" undermining the supervisory response.

Bitcoin Trading in Australian and Canadian Dollars, the Pound and Euro: Pre- and Post-COVID-19
Johnson, Jackie
Much of the research relating to the impact on Bitcoin, of the COVID-19 pandemic focuses on the United States (US) market using Bitcoin prices in US dollars, but this is a market not open to a large proportion of the world’s population who must trade Bitcoin in their local currency. The aim here is to compare Bitcoin trading behaviour pre- and post-COVID-19 in four currencies, the Australian dollar, the Canadian dollar, the UK pound and the European euro, to see if there is any consistency across currencies. The Bitcoin price may be universal but Bitcoin trading in local currencies can reflect local conditions. What becomes obvious is that when comparing across currencies, there is no consistent pattern. No two currencies are the same. The pre-COVID-19 period dominates in the Australian dollar market. The UK pound is similar except for transactions per day which is higher post-COVID-19. In the Canadian dollar and euro markets neither period dominates with each currency finding ‘not significantly different’ for a number of metrics. Surprisingly, there is not even any consensus with regard to the Bitcoin price which decreases in the Australian dollar and the UK pound markets in the post-COVID-19 period while this period sees an increase in the Bitcoin price in the Canadian dollar and euro markets. Consequently, observing Bitcoin trading behaviour in one currency does not indicate patterns of trade in another currency. This is particularly evident when comparing Bitcoin trading across countries with very different economic conditions, during a period of worldwide economic uncertainty as the COVID-19 pandemic continues to take a toll on local economies.

Black to Negative: Embedded optionalities in commodities markets
Richard J. Martin,Aldous Birchall

We address the modelling of commodities that are supposed to have positive price but, on account of a possible failure in the physical delivery mechanism, may turn out not to. This is done by explicitly incorporating a `delivery liability' option into the contract. As such it is a simple generalisation of the established Black model.

Casual Relationship and Volatility of BSE Index With Special Reference to Indian Stock Market
S, Baranidharan
As per the Central Statistics Organization and International Monetary Fund, India has emerged as the fastest growing major economy in the world and by its strong democracy and partnerships the Indian economy is expected to be one of the top three economic powers of the world over the next 10 â€" 15 years. Trade liberalization, financial liberalization, tax reforms and opening up to foreign investments were some of the important steps which also include share market, which helped the economy to gain momentum. The essential part of an Indian economy is the movement of shares in Stock exchange. Stock Exchange offers a ready market for buying and selling the securities. Share Bazaar is the business market with crores of rupees being put to stake. The Bombay Stock Exchange, the premier share market, registers dealings worth several hundred crore a day. The purpose of this study is to analyze the Casual Relationship and Volatility of BSE Index with special reference to Indian stock market through the data collected from the period of April 2010 to March 2018. Using SPSS software, the Descriptive statistics and Correlation developed which shows the relationship between share price & various factors affecting the same and also its casual relationship are very helpful for policy makers, Institutional investors, traders and all other stakeholders to take investment decision.

Constitutional Limits on Public Pension Reform: New Directions in Law and Legal Reasoning
Anenson, T. Leigh,Barkacs, Linda,Gershberg, Jennifer
Catastrophe cements a reputation, and the public pension crisis has been rapid and remarkable. Faced with alarming actuarial deficits, state and local legislatures are enacting comprehensive reforms to avoid insolvency. Government employees, however, are challenging these reforms under the Contract Clause. This Article collects the most important constitutional cases on public pension reform over the last six years. It adds a comprehensive study of recent state and federal court practice to the existing literature, including key U.S. Supreme Court decisions that have been missed. It takes stock of forty-eight decisions across twenty-two states, more than a dozen of which reached resolution in the highest courts. It offers a critical examination of key developments, an assessment of emerging challenges, and a new sustained account of the reforms that have succeeded and the grounds for that success. It also provides an appendix and various diagrams documenting our analysis and conclusions.The most surprising findings are that an overwhelming majority of barriers to pension reform are judge-made, meaning that changing case outcomes would not require a constitutional amendment. And that, in any event, reforms have generally been upheld even in those states in which existing doctrine is more protective of employee pensions. These results have practical implications by suggesting that governments can expand the scope of reforms. Clarifying the reasons and reasoning underlying these decisions also has jurisprudential significance. Courts in a number of jurisdictions have yet to rule on constitutional contract claims and, in those that have ruled, the decisional law is in flux and bordering on incoherence.

Design Diversity for Improving Efficiency and Reducing Risk in Oil and Gas Well Stimulation under Uncertain Reservoir Conditions
Cheng Cheng

Hydraulic fracturing stimulates fracture swarm in reservoir formation though pressurized injection fluid. However restricted by the availability of formation data, the variability embraced by reservoir keeps uncertain, driving unstable gas recovery along with low resource efficiency, being responsible for resource scarcity, contaminated water, and injection-induced earthquake. Resource efficiency is qualified though new determined energy efficiency, a scale of recovery and associated environmental footprint. To maximize energy efficiency while minimize its' variation, we issue picked designs at reservoir conditions dependent optimal probabilities, assembling high efficiency portfolios and low risk portfolios for portfolio combination, which balance the variation and efficiency at optimal by adjusting the proportion of each portfolio. Relative to regular design for one well, the optimal portfolio combination applied in multiple wells receive remarkable variation reduction meanwhile substantial energy efficiency increase, in response to the call of more recovery per unit investment and less environment cost per unit nature gas extracted.

Discrete-time portfolio optimization under maximum drawdown constraint with partial information and deep learning resolution
Carmine De Franco,Johann Nicolle,Huyên Pham

We study a discrete-time portfolio selection problem with partial information and maxi\-mum drawdown constraint. Drift uncertainty in the multidimensional framework is modeled by a prior probability distribution. In this Bayesian framework, we derive the dynamic programming equation using an appropriate change of measure, and obtain semi-explicit results in the Gaussian case. The latter case, with a CRRA utility function is completely solved numerically using recent deep learning techniques for stochastic optimal control problems. We emphasize the informative value of the learning strategy versus the non-learning one by providing empirical performance and sensitivity analysis with respect to the uncertainty of the drift. Furthermore, we show numerical evidence of the close relationship between the non-learning strategy and a no short-sale constrained Merton problem, by illustrating the convergence of the former towards the latter as the maximum drawdown constraint vanishes.

Dynamic Default Contagion in Interbank Systems
Zachary Feinstein,Andreas Sojmark

In this work we provide a simple setting that connects the structural modelling approach of Gai-Kapadia interbank networks with the mean-field approach to default contagion. To accomplish this we make two key contributions. First, we propose a dynamic default contagion model with endogenous early defaults for a finite set of banks, generalising the Gai-Kapadia framework. Second, we reformulate this system as a stochastic particle system leading to a limiting mean-field problem. We study the existence of these clearing systems and, for the mean-field problem, the continuity of the system response.

Event-Driven Learning of Systematic Behaviours in Stock Markets
Xianchao Wu

It is reported that financial news, especially financial events expressed in news, provide information to investors' long/short decisions and influence the movements of stock markets. Motivated by this, we leverage financial event streams to train a classification neural network that detects latent event-stock linkages and stock markets' systematic behaviours in the U.S. stock market. Our proposed pipeline includes (1) a combined event extraction method that utilizes Open Information Extraction and neural co-reference resolution, (2) a BERT/ALBERT enhanced representation of events, and (3) an extended hierarchical attention network that includes attentions on event, news and temporal levels. Our pipeline achieves significantly better accuracies and higher simulated annualized returns than state-of-the-art models when being applied to predicting Standard\&Poor 500, Dow Jones, Nasdaq indices and 10 individual stocks.

Extreme Climate Events and Financial Values: Empirical Evidence From the Stock Market
Ravina, Alessandro,D'Arcangelis, Anna Maria,Rotundo, Giulia
This paper answers the research question of the impact of extreme climate events on stock returns. The article makes four contributions. Firstly, a method that permits the transposition of country-level climate related GDP losses into firm- level climate related fixed assets losses is put forward. Secondly, an economically significant factor that proxies for the risk factor in stock returns related to extreme climate events, LME, is proposed and tested in a Fama and French framework. Thirdly, the sensitivities of stock portfolios to the LME factor are found to be statistically highly significant. Fourthly, a climate stress test based upon the LME factor is presented. The climate stress test is able to show the impact of plausible but more severe extreme climate phenomena on stock returns.

Extreme Climate Phenomena and Bond Returns
D'Arcangelis, Anna Maria,Ravina, Alessandro,Rotundo, Giulia
This paper answers the research question of the impact of extreme climate phenomena on bond returns. The question in answered by means of a factor model. Particularly, we add a climate factor to the classical bond market factors. The climate factor is constructed leveraging a novel methodology that permits the transposition of country-level climate related GDP losses into firm-level climate related fixed assets losses. The climatic factor proxies for the risk factor in bond returns related to extreme climate phenomena. The sensitivities of bond portfolios to the climatic factor are found to be statistically highly significant in most cases. We supplement the analysis with a climate stress test able to show the impact of plausible but more severe extreme climate phenomena on bond returns.

Fear and Volatility in Digital Assets
Faizaan Pervaiz,Christopher Goh,Ashley Pennington,Samuel Holt,James West,Shaun Ng

We show Bitcoin implied volatility on a 5 minute time horizon is modestly predictable from price, volatility momentum and alternative data including sentiment and engagement. Lagged Bitcoin index price and volatility movements contribute to the model alongside Google Trends with markets responding often several hours later. The code and datasets used in this paper can be found at

Financial Profiles of Workers Most Vulnerable to Coronavirus-Related Earnings Loss in the Spring of 2020
Helppie-McFall, Brooke,Hsu, Joanne W.
In spring 2020, the COVID-19 pandemic and related shutdowns had huge effects on unemployment. Using data from the Survey of Consumer Finances, we describe the financial profiles of US families whose workers were most vulnerable to coronavirus-related earnings losses in the spring of 2020, based on whether a particular worker was deemed “essential” and whether a worker’s job could be conducted remotely. We use descriptive analytic techniques to examine how families’ baseline financial situations would allow them to weather COVID-shutdown-related earnings losses. We find that families with non-teleworkable workers who were most vulnerable to layoff also had both demographic and financial profiles that are associated with greater vulnerability to income shocks: non-teleworkable families were more likely to be people of color and single wage-earners, and also to have less savings. The median non-teleworkable family, whether in non-essential or essential occupations, held only three weeks of income in savings, underscoring the importance of policy measures to blunt the financial effect of the COVID crisis.

Globally Consistent Creditor Protection, Reallocation, and Productivity
Bian, Bo
This paper documents that resource reallocation across firms is an important mechanism through which creditor rights affect real outcomes. I exploit the staggered adoption of an international convention that provides globally consistent strong creditor protection for aircraft finance. After this reform, country-level productivity in the aviation sector increases by 12%, driven mostly by across-firm reallocation. Productive airlines borrow more, expand, and adopt new technology at the expense of unproductive ones. Such reallocation is facilitated by (i) easier and quicker asset redeployment; and (ii) the influx of foreign financiers offering innovative financial products to improve credit allocative efficiency. I further document an increase in competition and an improvement in the breadth and the quality of products available to consumers.

In the Nick of Time: Performance-Based Compensation and Proactive Responses to the Tax Cuts and Jobs Act
Durrant, Jon,Gong, James Jianxin,Howard, Jennifer
The Tax Cuts and Jobs Act of 2017 (TCJA) introduced two major changes that may influence the structure of executive compensation: (1) reducing corporate tax rates from 35 to 21 percent and (2) eliminating the performance-based pay exception in Section 162(m). These changes provide incentives to maximize deductible compensation expense in 2017, before the TCJA goes into effect. Therefore, we predict performance-based compensation to increase more in 2017 relative to prior years. Consistent with our expectation, we find that the increase in CEO bonus and stock option compensation is significantly greater in 2017. Our difference-in-difference results are consistent with the tax rate reduction driving the bonus increase and the repeal of the performance-based exception leading to the increase in CEO stock options. The TCJA also changed the definition of covered employees to include the CFO. We find weak evidence for abnormal increases in CFO performance-based compensation. Additional analyses indicate firms facing stronger tax incentives drive our results. Overall, our findings suggest that firms’ responded to the TCJA in the period before it was effective.

Kemajuan Perekonomian Indonesia Setelah 50 Tahun Kerja-Sama: Perspektif Adb (Indonesia’s Economic Progress After 50 Years of Cooperation: Adb’s Perspective)
Sari, Dyana,McCawley, Peter
Indonesian abstract: Buku ini terinspirasi dari presentasi dalam Forum Kajian Pembangunan tanggal 5 Maret 2020 di FE UI. Karena terbatasnya waktu, presentasi itu tentunya sangat singkat sehingga diperlukan uraian yang lebih detil hingga terbitlah buku ini. Tujuan membuat buku ini adalah untuk memberi wawasan dan pencerahan terutama bagi generasi muda Indonesia, bahwa peristiwa â€" peristiwa masa lalu, telah membawa perbaikan dalam perekonomian Indonesia. Kami tidak hendak membahas dari sudut politik, tetapi kami akan menguraikannya sesuai dengan kapasitas kami sebagai ilmuwan, sehingga setiap uraian yang kami tulis, adalah merujuk kepada pembahasan yang tidak lepas dari kaidah-kaidah ilmu Ekonomi. Jikalau ada hal-hal yang bersinggungan dengan sikap politik pemimpin, makahal itu adalah sekedar suatu pandangan (‘one view’) berdasar dari kenyataan yang ada, tanpa ada tendensi untuk tujuan apapun. Kami sadari bahwa tulisan ini jauh dari sempurna, namun diharapkan buku ini akan menjadi masukan bagi generasi penerus bangsa, untuk dapat memetik pelajaran dari pengalaman masa lalu, agar membawa perekonomian Indonesia yang lebih baik lagi di masa mendatangEnglish abstract: This book was inspired by a presentation at the Development Study Forum on March 5, 2020 at FE UI. Due to limited time, the presentation was of course very short, so a more detailed description was needed until the publication of this book. The purpose of this book is to provide insight and enlightenment, especially for the younger generation of Indonesia, that past events have brought improvements in the Indonesian economy. We don't want to discuss it from a political point of view, but we will describe it according to our capacity as scientists, so that every description we write refers to a discussion that cannot be separated from the principles of Economics. If there are things that intersect with the political attitude of the leader, then that is just a 'one view' based on existing facts, without any tendency for any purpose. We realize that this paper is far from perfect, but it is hoped that this book will be an input for the nation's future generations, to be able to learn lessons from past experiences, in order to bring a better Indonesian economy in the future.

Linkages and Volatility Effect of Finance Companies Stock Price on BSE Finance Index
S, Baranidharan,Sathish, A.
n India, Finance sector act as a booster to boost up the Indian economy. The main purpose of the analytical work is to scrutinize the mobility of stock price in BSE Indices and the selected Finance companies. The current work has made by observing the data from the period of 2nd April 2014 to 30 August 2019 and employed the statistical tools such as Augmented Dickey Fuller test, GRACH Model and Johansen Co integration Rank Test from the sources such as The present research work selected the sample as Bombay stock exchange SENSEX and Bombay stock exchange FINANCE and the companies of financial sector such as AB CAPITAL LTD, BAJAJ FINSERV LTD, CAPRI GLOBAL CAPITAL LTD, IIFL FINANCE LTD, JSW HOLDINGS LTD and JM FINANCE LTD. The study revealed that there were significant changes in the stock returns of BSE SENSEX and BSE FINANCE reflected on the stock prices of selected companies of the finance industry. Thus the research work helps the institutional investors to aware about identify the volatility of stocks shock, existence in long run association of stocks, and also control the overwhelmed speculation in the stock market. The current work also supports and the motive of policy makers or regulators such as SEBI, RBI provide guidelines and to create aware the policies in order to the individual investors investment. The study also supports and aids to the investors to do further research regarding the change or movement of financial companies stock price in Indian stock market.

Mass Flow Analysis of SARS-CoV-2 for quantified COVID-19 Risk Analysis
Gjalt Huppes,Ruben Huele

How may exposure risks to SARS-CoV-2 be assessed quantitatively? The material metabolism approach of Industrial Ecology can be applied to the mass flows of these virions by their numbers, as a key step in the analysis of the current pandemic. Several transmission routes of SARS-2 from emission by a person to exposure of another person have been modelled and quantified. Start is a COVID-19 illness progression model specifying rising emissions by an infected person: the human virion factory. The first route covers closed spaces, with an emission, concentration, and decay model quantifying exposure. A next set of routes covers person-to-person contacts mostly in open spaces, modelling the spatial distribution of exhales towards inhalation. These models also cover incidental exposures, like coughs and sneezes, and exposure through objects. Routes through animal contacts, excrements, and food, have not been quantified. Potential exposures differ by six orders of magnitude. Closed rooms, even with reasonably (VR 2) to good (VR 5) ventilation, constitute the major exposure risks. Close person-to-person contacts of longer duration create two orders of magnitude lower exposure risks. Open spaces may create risks an order of magnitude lower again. Burst of larger droplets may cause a common cold but not viral pneumonia as the virions in such droplets cannot reach the alveoli. Fomites have not shown viable viruses in hospitals, let alone infections. Infection by animals might be possible, as by cats and ferrets kept as pets. These results indicate priority domains for individual and collective measures. The wide divergence in outcomes indicates robustness to most modelling and data improvements, hardly leading to major changes in relative exposure potentials. However, models and data can substantially be improved.

Measuring and Hedging Geopolitical Risk
Engle, Robert F.,Campos-Martins, Susana
Geopolitical events can impact volatilities of all assets, asset classes, sectors and countries. It is shown that innovations to volatilities are correlated across assets and therefore can be used to measure and hedge geopolitical risk. We introduce a definition of geopolitical risk which is based on volatility shocks to a wide range of financial market prices. To measure geopolitical risk, we propose a statistical model for the magnitude of the common volatility shocks. Accordingly, a test and estimation methods are developed and studied using both empirical and simulated data. We provide a novel explanation for why idiosyncratic volatilities comove based on a new way to formulate multiplicative factors. Finally, we propose a new criterion for portfolio optimality which is intended to reduce the exposure to geopolitical risk.

Modelling and simulation of dependence structures in nonlife insurance with Bernstein copulas
Dietmar Pfeifer,Doreen Strassburger,Joerg Philipps

In this paper we review Bernstein and grid-type copulas for arbitrary dimensions and general grid resolutions in connection with discrete random vectors possessing uniform margins. We further suggest a pragmatic way to fit the dependence structure of multivariate data to Bernstein copulas via grid-type copulas and empirical contingency tables. Finally, we discuss a Monte Carlo study for the simulation and PML estimation for aggregate dependent losses form observed windstorm and flooding data.

Multi-State Health Transition Modeling Using Neural Networks
Wang, Qiqi,Hanewald, Katja,Wang, Xiaojun
This article proposes a new model that combines a neural network with a generalized linear model (GLM) to estimate and predict health transition intensities. The model allows for socioeconomic and lifestyle factors to impact the health transition processes, and captures linear and nonlinear relationships. A key innovation is that the model features transfer learning between different transition rates. It autonomously finds the relationships between factors and the links between the transition processes. We apply the model to individual-level data from the Chinese Longitudinal Healthy Longevity Survey from 1998â€"2018. The results show that our model performs better in estimation and prediction than standalone GLM and neural network models. We thus provide new estimates of the life expectancies for a range of population subgroups. The model can be easily applied to other datasets, and our results confirm that machine learning techniques are promising tools to model insurance risks.

Multiscale characteristics of the emerging global cryptocurrency market
Marcin Wątorek,Stanisław Drożdż,Jarosław Kwapień,Ludovico Minati,Paweł Oświęcimka,Marek Stanuszek

The review introduces the history of cryptocurrencies, offering a description of the blockchain technology behind them. Differences between cryptocurrencies and the exchanges on which they are traded have been shown. The central part surveys the analysis of cryptocurrency price changes on various platforms. The statistical properties of the fluctuations in the cryptocurrency market have been compared to the traditional markets. With the help of the latest statistical physics methods the non-linear correlations and multiscale characteristics of the cryptocurrency market are analyzed. In the last part the co-evolution of the correlation structure among the 100 cryptocurrencies having the largest capitalization is retraced. The detailed topology of cryptocurrency network on the Binance platform from bitcoin perspective is also considered. Finally, an interesting observation on the Covid-19 pandemic impact on the cryptocurrency market is presented and discussed: recently we have witnessed a "phase transition" of the cryptocurrencies from being a hedge opportunity for the investors fleeing the traditional markets to become a part of the global market that is substantially coupled to the traditional financial instruments like the currencies, stocks, and commodities.

The main contribution is an extensive demonstration that structural self-organization in the cryptocurrency markets has caused the same to attain complexity characteristics that are nearly indistinguishable from the Forex market at the level of individual time-series. However, the cross-correlations between the exchange rates on cryptocurrency platforms differ from it. The cryptocurrency market is less synchronized and the information flows more slowly, which results in more frequent arbitrage opportunities. The methodology used in the review allows the latter to be detected, and lead-lag relationships to be discovered.

Optimal Dividend Strategy for an Insurance Group with Contagious Default Risk
Zhuo Jin,Huafu Liao,Yue Yang,Xiang Yu

This paper studies the optimal dividend for a multi-line insurance group, in which each subsidiary runs a product line and is exposed to some external credit risk. The default contagion is considered such that one default event may increase the default probabilities of all surviving subsidiaries. The total dividend problem for the insurance group is investigated and we find that the optimal dividend strategy is still of the barrier type. Furthermore, we show that the optimal barrier of each subsidiary is modulated by the default state. That is, how many and which subsidiaries have defaulted will determine the dividend threshold of each surviving subsidiary. These conclusions are based on the analysis of the associated recursive system of Hamilton-Jacobi-Bellman variational inequalities (HJBVIs). The existence of the classical solution is established and the verification theorem is proved. In the case of two subsidiaries, the value function and optimal barriers are given in analytical forms, allowing us to conclude that the optimal barrier of one subsidiary decreases if the other subsidiary defaults.

Preventing COVID-19 Fatalities: State versus Federal Policies
Jean-Paul Renne,Guillaume Roussellet,Gustavo Schwenkler

Are policies implemented in individual states to prevent pandemic deaths effective when there is no policy coordination by the federal government? We answer this question by developing a stochastic extension of a SIRD epidemiological model for a country composed of multiple states. Our model allows for interstate mobility. We consider three policies: mask mandates, stay-at-home orders, and interstate travel bans. We fit our model to daily U.S. state-level COVID-19 death counts and exploit our estimates to produce various policy counterfactuals. While the restrictions imposed by some states inhibited a significant number of virus deaths, we find that more than two-thirds of U.S. COVID-19 deaths could have been prevented by late September 2020 had the federal government imposed federal mandates as early as some of the earliest states did. Our results highlight the need for a coordination-aimed approach by a federal government for the successful containment of a pandemic.

Retail Banking Operations in January-August 2020
Zubov, Sergey
Growth rates of the credit portfolio have notably decreased compared to the prepandemic period. This is due to a decline in demand for credits from the population and more stringent bank requirements to the borrowers. In the meantime, despite a reduction in the interest rates and imposition of a tax on bank deposits interest, banks have failed to ramp up retail deposits volumes. This was mainly due to the return of the part of population to the savings behavior pattern during the pandemic.

Sovereign Risk and Bank Fragility
Anand, Kartik,Mankart, Jochen
We develop a model of bank risk-taking with strategic sovereign default risk. Domestic banks invest in real projects and purchase government bonds. While an increase in bond purchases crowds out profitable investments, it improves the government's incentives to repay and therefore lowers its borrowing costs. For low levels of government debt, banks influence their default risks through purchases of bonds. But, for high debt levels, this influence is lost since bank and government default are perfectly correlated. Banks fail to account for how their bond purchases influence the government's default incentives. This leads to socially inefficient levels of bond holdings.

Subnational Old-Age Mortality Modeling: Accounting for Underreporting in a Bayesian Framework
Lu, Qian,Hanewald, Katja,Villegas, Andres,Wang, Xiaojun
Accurate old-age mortality projections for subnational areas are important for assessing health outcomes and valuing pension liabilities. However, subnational mortality data often face small sample sizes at older ages. In some countries, the underreporting of deaths and population numbers poses additional problems. We propose a new Bayesian framework for old-age mortality that allows for deaths underreporting by introducing a reporting probability, which is defined as the ratio of reported deaths to real deaths and uses informative priors derived from demographic death distribution methods. We show that the proposed modeling framework works well for province-level old-age mortality data (ages 60â€"99) in China over 1982â€"2010. Compared to a more conventional framework that assumes the reported data are accurate and uses reported mortality data directly, the proposed framework provides a better fit, with a lower deviance information criterion. The proposed framework generates a reasonable mortality curvature and coherent forecasts for subpopulations with sparse or incomplete mortality data.

The Market Loves a Layoff
Mace, Chris
This paper examines whether layoffs damage or create firm value. Using a large sample of firm-matched layoff events, I show that layoffs increase firm value with abnormal returns increasing in the days and months following layoff announcements. Using a synthetic controls methodology, I also show that layoffs also continue to result in higher returns in the years following the layoff event. Using changes in minimum wage laws as a natural experiment, I show that layoffs often target low-skill workers, suggesting that layoffs do not necessarily destroy knowledge capital.

The Rise of State-Owned Investors: Sovereign Wealth Funds and Public Pension Funds
Megginson, William L.,López, Diego,Malik, Asif
State-owned investors (SOIs), including sovereign wealth funds and public pension funds, have $27 trillion in assets under management in 2020, making these funds the third largest group of asset owners globally. SOIs have become the largest and most important private equity investors and are key investors in other alternative asset investments such as real estate, infrastructure and hedge funds. SOIs are also leaders in promoting environmental, social and governance (ESG) and corporate social responsibility in investee companies. We document the rise of SOIs, assess their current investment policies, and describe how their state ownership both constrains and enhances their investment opportunity sets. We survey the most impactful recent academic research on sovereign wealth funds (SWFs), public pension funds (PPFs), and their closest financial analogs, private pension funds. We also introduce a new Governance-Sustainability-Resilience (GSR) Scoreboard for SOIs and survey research examining their role in promoting good corporate governance.

The public debt multiplier
Alice Albonico,Guido Ascari,Alessandro Gobbi

We study the effects on economic activity of a pure temporary change in government debt and the relationship between the debt multiplier and the level of debt in an overlapping generations framework. The debt multiplier is positive but quite small during normal times while it is much larger during crises. Moreover, it increases with the steady state level of debt. Hence, the call for fiscal consolidation during recessions seems ill-advised. Finally, a rise in the steady state debt-to-GDP level increases the steady state real interest rate providing more room for manoeuvre to monetary policy to fight deflationary shocks.

Video: Pioneers in Finance: An Interview with Michael C. Jensen - Part 1 Video 1
Jensen, Michael C.,Walkling, Ralph A.
This interview is Part 1 Video 2 of a two-part series (contained in 4 videos) in which Professor Ralph Walkling, the Stratakis Chair in Corporate Governance and Executive Director of the Center for Corporate Governance at Drexel University, interviews Professor Michael C. Jensen, Jesse Isidor Straus Professor of Business Administration, Emeritus, of the Harvard Business School, on topics ranging from his early work to current research.