Research articles for the 2021-05-17

Acquisitive Crimes, Time of Day, and Multiunit Housing in the City of Milwaukee
Scott W. Hegerty

According to "Social Disorganization" theory, criminal activity increases if the societal institutions that might be responsible for maintaining order are weakened. Do large apartment buildings, which often have fairly transient populations and low levels of community involvement, have disproportionately high rates of crime? Do these rates differ during the daytime or nighttime, depending when residents are present, or away from their property? This study examines four types of "acquisitive" crime in Milwaukee during 2014. Overall, nighttime crimes are shown to be more dispersed than daytime crimes. A spatial regression estimation finds that the density of multiunit housing is positively related to all types of crime except burglaries, but not for all times of day. Daytime robberies, in particular, increase as the density of multiunit housing increases.

Actuarial strategy for pricing Asian options under a mixed fractional Brownian motion with jumps
Foad Shokrollahi,Davood Ahmadian,Luca Vincenzo Ballestra

The mixed fractional Brownian motion ($mfBm$) has become quite popular in finance, since it allows one to model long-range dependence and self-similarity while remaining, for certain values of the Hurst parameter, arbitrage-free. In the present paper, we propose approximate closed-form solutions for pricing arithmetic Asian options on an underlying described by the $mfBm$. Specifically, we consider both arithmetic Asian options and arithmetic Asian power options, and we obtain analytical formulas for pricing them based on a convenient approximation of the strike price. Both the standard $mfBm$ and the $mfBm$ with Poisson log-normally distributed jumps are taken into account.

Are the Spatial Concentrations of Core-City and Suburban Poverty Converging in the Rust Belt?
Scott W. Hegerty

Decades of deindustrialization have led to economic decline and population loss throughout the U.S. Midwest, with the highest national poverty rates found in Detroit, Cleveland, and Buffalo. This poverty is often confined to core cities themselves, however, as many of their surrounding suburbs continue to prosper. Poverty can therefore be highly concentrated at the MSA level, but more evenly distributed within the borders of the city proper. One result of this disparity is that if suburbanites consider poverty to be confined to the central city, they might be less willing to devote resources to alleviate it. But due to recent increases in suburban poverty, particularly since the 2008 recession, such urban-suburban gaps might be shrinking. Using Census tract-level data, this study quantifies poverty concentrations for four "Rust Belt" MSAs, comparing core-city and suburban concentrations in 2000, 2010, and 2015. There is evidence of a large gap between core cities and outlying areas, which is closing in the three highest-poverty cities, but not in Milwaukee. A set of four comparison cities show a smaller, more stable city-suburban divide in the U.S. "Sunbelt," while Chicago resembles a "Rust Belt" metro.

Attention elasticities and invariant information costs
Dániel Csaba

We consider a generalization of rational inattention problems by measuring costs of information through the information radius (Sibson, 1969; Verd\'u, 2015) of statistical experiments. We introduce a notion of attention elasticity measuring the sensitivity of attention strategies with respect to changes in incentives. We show how the introduced class of cost functions controls attention elasticities while the Shannon model restricts attention elasticity to be unity. We explore further differences and similarities relative to the Shannon model in relation to invariance, posterior separability, consideration sets, and the ability to learn events with certainty. Lastly, we provide an efficient alternating minimization method -- analogous to the Blahut-Arimoto algorithm -- to obtain optimal attention strategies.

Bank Density, Population Density, and Economic Deprivation Across the United States
Scott W. Hegerty

Recent research on the geographic locations of bank branches in the United States has identified thresholds below which a given area can be considered to be a "banking desert." Thus far, most analyses of the country as a whole have tended to focus on minimum distances from geographic areas to the nearest bank, while a recent density-based analysis focused only on the city of Chicago. As such, there is not yet a nationwide study of bank densities for the entire United States. This study calculates banks per square mile for U.S. Census tracts over ten different ranges of population density. One main finding is that bank density is sensitive to the measurement radius used (for example, density in urban areas can be calculated as the number of banks within two miles, while some rural areas require a 20-mile radius). This study then compiles a set of lower 5- and 10-percent thresholds that might be used to identify "banking deserts" in various urban, suburban, and rural areas; these largely conform to the findings of previous analyses. Finally, adjusting for population density using regression residuals, this paper examines whether an index of economic deprivation is significantly higher in the five percent of "desert" tracts than in the remaining 95 percent. The differences are largest -- and highly significant -- in the densest tracts in large urban areas.

Denise: Deep Robust Principal Component Analysis for Positive Semidefinite Matrices
Calypso Herrera,Florian Krach,Anastasis Kratsios,Pierre Ruyssen,Josef Teichmann

The robust PCA of covariance matrices plays an essential role when isolating key explanatory features. The currently available methods for performing such a low-rank plus sparse decomposition are matrix specific, meaning, those algorithms must re-run for every new matrix. Since these algorithms are computationally expensive, it is preferable to learn and store a function that instantaneously performs this decomposition when evaluated. Therefore, we introduce Denise, a deep learning-based algorithm for robust PCA of covariance matrices, or more generally of symmetric positive semidefinite matrices, which learns precisely such a function. Theoretical guarantees for Denise are provided. These include a novel universal approximation theorem adapted to our geometric deep learning problem, convergence to an optimal solution of the learning problem and convergence of the training scheme. Our experiments show that Denise matches state-of-the-art performance in terms of decomposition quality, while being approximately 2000x faster than the state-of-the-art, PCP, and 200x faster than the current speed optimized method, fast PCP.

Derivation of wealth distributions from biased exchange of money
Fei Cao,Sebastien Motsch

In the manuscript, we are interested in using kinetic theory to better understand the time evolution of wealth distribution and their large scale behavior such as the evolution of inequality (e.g. Gini index). We investigate three type of dynamics denoted unbiased, poor-biased and rich-biased dynamics. At the particle level, one agent is picked randomly based on its wealth and one of its dollar is redistributed among the population. Proving the so-called propagation of chaos, we identify the limit of each dynamics as the number of individual approaches infinity using both coupling techniques [48] and martingale-based approach [36]. Equipped with the limit equation, we identify and prove the convergence to specific equilibrium for both the unbiased and poor-biased dynamics. In the rich-biased dynamics however, we observe a more complex behavior where a dispersive wave emerges. Although the dispersive wave is vanishing in time, its also accumulates all the wealth leading to a Gini approaching 1 (its maximum value). We characterize numerically the behavior of dispersive wave but further analytic investigation is needed to derive such dispersive wave directly from the dynamics.

ESG, Risk, and (tail) dependence
Karoline Bax,Özge Sahin,Claudia Czado,Sandra Paterlini

While environmental, social, and governance (ESG) trading activity has been a distinctive feature of financial markets, the debate if ESG scores can also convey information regarding a company's riskiness remains open. Regulatory authorities, such as the European Banking Authority (EBA), have acknowledged that ESG factors can contribute to risk. Therefore, it is important to model such risks and quantify what part of a company's riskiness can be attributed to the ESG ratings. This paper aims to question whether ESG scores can be used to provide information on (tail) riskiness. By analyzing the (tail) dependence structure of companies with a range of ESG scores, using high-dimensional vine copula modelling, we are able to show that risk can also depend on and be directly associated with a specific ESG rating class. Empirical findings on real-world data show positive not negligible dependencies between clusters determined by ESG scores, especially during the 2008 crisis.

Efficient Least Squares Monte-Carlo Technique for PFE/EE Calculations
Yuriy Krepkiy,Asif Lakhany,Amber Zhang

We describe a regression-based method, generally referred to as the Least Squares Monte Carlo (LSMC) method, to speed up exposure calculations of a portfolio. We assume that the portfolio contains several exotic derivatives that are priced using Monte-Carlo on each real world scenario and time step. Such a setting is often referred to as a Monte Carlo over a Monte Carlo or a Nested Monte Carlo method.

Hedging Goals
Thomas Krabichler,Marcus Wunsch

Goal-based investing is concerned with reaching a monetary investment goal by a given deadline, which differs from mean-variance optimization in modern portfolio theory. In this article, we expand the close connection between goal-based investing and option hedging that was originally discovered in [Bro99b] by allowing for varying degrees of investor risk aversion using lower partial moments of different orders. Moreover, we show that maximizing the probability of reaching the goal (quantile hedging, cf. [FL99]) and minimizing the expected shortfall (efficient hedging, cf. [FL00]) yield, in fact, the same optimal investment policy. Finally, we develop an innovative approach to goal-based investing using methods of reinforcement learning, demonstrating its flexibility vis-\`a-vis general market dynamics incorporating transaction costs.

How Costly is Noise? Data and Disparities in Consumer Credit
Laura Blattner,Scott Nelson

We show that lenders face more uncertainty when assessing default risk of historically under-served groups in US credit markets and that this information disparity is a quantitatively important driver of inefficient and unequal credit market outcomes. We first document that widely used credit scores are statistically noisier indicators of default risk for historically under-served groups. This noise emerges primarily through the explanatory power of the underlying credit report data (e.g., thin credit files), not through issues with model fit (e.g., the inability to include protected class in the scoring model). Estimating a structural model of lending with heterogeneity in information, we quantify the gains from addressing these information disparities for the US mortgage market. We find that equalizing the precision of credit scores can reduce disparities in approval rates and in credit misallocation for disadvantaged groups by approximately half.

Lender Liability and Fault for Deepening Insolvency: A Comparative Analysis
Omar, Paul,Gant, Jennifer L. L.
The issue of how companies in a financially difficult position are to be financed is an important but delicate one. The approach to insolvency will undoubtedly require the directors to consider whether an extension to existing finance or new finance is an option. This consideration is fraught with danger, given that many of the responses directors might take, including asset disposals, payment of the most pressing demands, enhancing existing or granting further security in favor of creditors as well as entering into further funding obligations that may invite creditors to impose higher/greater than usual terms as a measure of the heightened risk of lending at the insolvency threshold, may well attract the use of transactional avoidance measures known to most insolvency systems. As an added peril, to continue trading while within sight of the moment of formal insolvency may also attract the application of wrongful or insolvent trading rules, also a feature of many developed legal systems. General misfeasance, of which the above may be particular illustrations, may also attract liability. The justification for the rules dealing with the avoidance of transactions, wrongful trading and misfeasance (more generally) is that continued trading and transacting may have a disadvantageous impact on the position of creditors overall. Thus, directors are to be encouraged to seek help at the earliest opportunity, by engaging turnaround, pre-insolvency and insolvency measures, whichever may be appropriate. Thus, they can avoid exposure to liability and the chances of litigation being brought by an insolvency office-holder keen to ensure that the estate is restored to the position it ought to have been in had these transactions not taken place.It is the intention in this article to look at two contrasting approaches to creditor liability, that in France, where a generalized principle exists, albeit attenuated by insolvency law reforms in the mid-2000s, and that in the United Kingdom, where contractual freedom and a robust lending culture have given less room for the development of creditor liability rules except in very limited and carefully crafted instances.

Managerial and financial barriers to the net-zero transition
De Haas, Ralph,Martin, Ralf,Muûls, Mirabelle,Schweiger, Helena
We use data on 11,233 firms across 22 emerging markets to analyze how credit constraints and low-quality firm management inhibit corporate investment in green technologies. For identification we exploit quasi-exogenous variation in local credit conditions and in exposure to weather shocks. Our results suggest that both financial frictions and managerial constraints slow down firm investment in more energy efficient and less polluting technologies. Complementary analysis of data from the European Pollutant Release and Transfer Register (E-PRTR) corroborates some of this evidence by revealing that in areas where banks deleveraged more after the global financial crisis, industrial facilities reduced their carbon emissions by less. On aggregate this kept local emissions 15% above the level they would have been in the absence of financial frictions.

Managing mental & psychological wellbeing amidst COVID-19 pandemic: Positive psychology interventions
M.T. Paul V,N.U. Devi

COVID-19 pandemic has shaken the roots of healthcare facilities worldwide, with the US being one of the most affected countries irrespective of being a superpower. Along with the current pandemic, COVID-19 can cause a secondary crisis of mental health pandemic if left unignored. Various studies from past epidemics, financial turmoil and pandemic, especially SARS and MERS, have shown a steep increase in mental and psychological issues like depression, low quality of life, self-harm and suicidal tendencies among general populations. The most venerable being the individuals infected and cured due to social discrimination. The government is taking steps to contain and prevent further infections of COVID-19. However, the mental and psychological wellbeing of people is still left ignored in developing countries like India. There is a significant gap in India concerning mental and psychological health still being stigmatized and considered 'non-existent'. This study's effort is to highlight the importance of mental and psychological health and to suggest interventions based on positive psychology literature. These interventions can support the wellbeing of people acting as a psychological first aid. Keywords: COVID-19, Coronavirus, Pandemic, Mental wellbeing, Psychological Wellbeing, Positive Psychology Interventions.

On the Efficiency of Meme Stocks
Aloosh, Arash,Choi, Hyung-Eun,Ouzan, Samuel
Meme stocks have received a lot of attention in the media from both investors and regulators in recent months, particularly following the GameStop episode. The power of the crowd, coupled with unprecedented coordination, raises obvious questions about the impact of these social media traders on market efficiency. We construct two meme stock indices based on stocks whose purchase the Robinhood app restricted during the GameStop episode. We provide evidence of meme stocks’ market efficiency, and particularly during the COVID-19 crisis. Our result indicates, perhaps contrary to some early speculation, that this new influx of highly connected retail investors improves efficiency.

Optimal Reinsurance and Investment under Common Shock Dependence Between Financial and Actuarial Markets
Claudia Ceci,Katia Colaneri,Alessandra Cretarola

We study optimal proportional reinsurance and investment strategies for an insurance company which experiences both ordinary and catastrophic claims and wishes to maximize the expected exponential utility of its terminal wealth. We propose a model where the insurance framework is affected by environmental factors, and aggregate claims and stock prices are subject to common shocks, i.e. drastic events such as earthquakes, extreme weather conditions, or even pandemics, that have an immediate impact on the financial market and simultaneously induce insurance claims. Using the classical stochastic control approach based on the Hamilton-Jacobi-Bellman equation, we provide a verification result for the value function via classical solutions to two backward partial differential equations and characterize the optimal reinsurance and investment strategies. Finally, we make a comparison analysis to discuss the effect of common shock dependence.

Path Dependent Obstacles to Cross-Border Insolvency: A Social Darwinian Perspective
Gant, Jennifer L. L.
There are complex factors that exist within the legal, political, cultural, social and economic histories of each Member State that contribute to the diversity of aims of legal regulation. These unique historical experiences influence the developmental path of individual legal systems. While insolvency laws are influenced by a myriad of historical, social, economic and political characteristics, the focus of this treatise will be the path dependent influence of social policy and regulation on the legal development of insolvency law and the aims that individual jurisdictions ascribe to it. This will provide a snapshot of a far more complex framework that can explain how along just a single thread of historical development, a whole area of law can be fundamentally affected and differentiated from parallel developments in another legal system. There is a complexity of diverse legal development in the social policies and regulation of Member States, which has an effect on the aims of insolvency law in the relative weight of protection given to creditors and employees. By way of example, the United Kingdom13 and France will be used as comparators.

Random Fixed Points, Limits and Systemic risk
Veeraruna Kavitha,Indrajit Saha,Sandeep Juneja

We consider vector fixed point (FP) equations in large dimensional spaces involving random variables, and study their realization-wise solutions. We have an underlying directed random graph, that defines the connections between various components of the FP equations. Existence of an edge between nodes i, j implies the i th FP equation depends on the j th component. We consider a special case where any component of the FP equation depends upon an appropriate aggregate of that of the random neighbor components. We obtain finite dimensional limit FP equations (in a much smaller dimensional space), whose solutions approximate the solution of the random FP equations for almost all realizations, in the asymptotic limit (number of components increase). Our techniques are different from the traditional mean-field methods, which deal with stochastic FP equations in the space of distributions to describe the stationary distributions of the systems. In contrast our focus is on realization-wise FP solutions. We apply the results to study systemic risk in a large financial heterogeneous network with many small institutions and one big institution, and demonstrate some interesting phenomenon.

Spatial Measures of Socioeconomic Deprivation: An Application to Four Midwestern Industrial Cities
Scott W. Hegerty

Decades of economic decline have led to areas of increased deprivation in a number of U.S. inner cities, which can be linked to adverse health and other outcomes. Yet the calculation of a single "deprivation" index, which has received wide application in Britain and elsewhere in the world, involves a choice of variables and methods that have not been directly compared in the American context. This study creates four related measures--using two sets of variables and two weighting schemes--to create such indices for block groups in Buffalo, Cleveland, Detroit, and Milwaukee. After examining the indices' similarities, we then map concentrations of high deprivation in each city and analyze their relationships to income, racial makeup, and transportation usage. Overall, we find certain measures to have higher correlations than others, but that all show deprivation to be linked with lower incomes and a higher nonwhite population.

Stationary Discounted and Ergodic Mean Field Games of Singular Control
Haoyang Cao,Jodi Dianetti,Giorgio Ferrari

We study stationary mean field games with singular controls in which the representative player interacts with a long-time weighted average of the population through a discounted and an ergodic performance criterion. This class of games finds natural applications in the context of optimal productivity expansion in dynamic oligopolies. We prove existence and uniqueness of the mean field equilibria, which are completely characterized through nonlinear equations. Furthermore, we relate the mean field equilibria for the discounted and the ergodic games by showing the validity of an Abelian limit. The latter allows also to approximate Nash equilibria of - so far unexplored - symmetric N-player ergodic singular control games through the mean field equilibrium of the discounted game. Numerical examples finally illustrate in a case study the dependency of the mean field equilibria with respect to the parameters of the games.

Stock Price Behavior: A Survey of Literature (With Special Emphasis on the Random Walk Theory)
Sree Rama Murthy, Y.
This study is a review of literature on the topic of stock price behavior in the pre-1980 period. The focus of the review of literature is on the "Random Walk Hypothesis".

Studying the association of online brand importance with museum visitors: An application of the semantic brand score
A. Fronzetti Colladon,F. Grippa,R. Innarella

This paper explores the association between brand importance and growth in museum visitors. We analyzed 10 years of online forum discussions and applied the Semantic Brand Score (SBS) to assess the brand importance of five European Museums. Our Naive Bayes and regression models indicate that variations in the combined dimensions of the SBS (prevalence, diversity and connectivity) are aligned with changes in museum visitors. Results suggest that, in order to attract more visitors, museum brand managers should focus on increasing the volume of online posting and the richness of information generated by users around the brand, rather than controlling for the posts' overall positivity or negativity.

The Impact of COVID-19 on Stock Return in Asian Stock Markets Evidences from Developed, Emerging and Frontier Asian Markets
Kumarapperuma, Oshini,Deyshappriya, N.P. Ravindra,Rajapakshe, Maheshi
The study focuses on the impact of COVID-19 on stock market in Asian region highlighting the impact on stock returns of 15 Asian stock markets while observing the relationship between confirmed COVID-19 cases and stock return. In this regard, daily closing price indices during the period of 1st January 2019 and 30th June 2020 were collected. The impact of COVID-19 on stock returns were analysed using Event Study method by comparing the calculated abnormal return before and after the event day (20th of January, 2020) under two evet windows such as (0,10) and (10, 20). Apart from that, OLS based panel regression analysis was carried out to observe the impact of the number of COVID-19 confirmed cases on stock return in selected stock markets. The empirical analysis reveals that abnormal returns after the event day were negative and therefore it is apparent that the COVID-19 outbreak has drastically affected the stock returns of selected stock markets of the Asian region. Specifically, two event windows indicates that COVID-19 has an immediate negative impact on all selected stock markets while long term negative impact has limited to emerging and frontier markets. Moreover, it is observed that COVID-19 confirmed cases negatively affect the stock return of all selected stock markets in Asian region. Hence, the current study recommends the importance of recovering from the pandemic and sustaining appropriate environment for the development and smooth running of stock markets.

The Road to Recovery: A Comparative Analysis of the Impact of the Financial Crisis on the Rights of Workers in Greece, Portugal, France and the United Kingdom and their Insolvency Legal Systems
Gant, Jennifer L. L. ,Kastrinou, Alexandra
The financial crisis and the sovereign debt crisis that followed it have been attributed to a number of causes. Whether these are economic, social, cultural or legal, they are all by and large also political. The aim of this paper is not to delve into the myriad of heated political arguments that continue to dominate the scene, but to assess the impact of the financial crisis on workers’ rights in Greece, Portugal, France and the United Kingdom and to examine its impact on their corporate rescue regimes with a view to understanding what the legislative and social changes may mean for the future of these individual nations, their people and businesses, and perhaps for the EU and Eurozone as a whole. In light of the crisis, the rights of the workforce have been severely compromised in order to alleviate pressures on troubled companies and to afford them a greater potential for recovery. In response to the crisis, all four jurisdictions have introduced reforms to their labor codes and corporate rescue mechanisms in order to minimize the catastrophic impact on their economies and societies.As a project, this is only the beginning. This paper will only offer a snap shot of those important changes that have occurred since the crisis began, the effects as understood at the current level of research, and an initial assessment as to whether or not the reforms of the pre-insolvency regimes in particular have operated as an effective embankment for the protection of social and economic welfare, the former of these being already significantly reduced throughout the EU. While France and the UK have had their fair share of economic hardships, Greece and Portugal were forced to go to the International Monetary Fund, European Commission and the European Central Bank3 for assistance in order to avoid defaulting on sovereign loans, an outcome that would have had a severe effect on financial markets throughout the EU. This assistance was granted in exchange for their agreement to the terms of Memoranda of Understanding4 that set out measures to be taken to improve their economic viability and market flexibility. The austerity measures implemented in response to the MoUs have caused great hardship and social turmoil in both Greece and Portugal.

What shapes climate change perceptions in Africa? A random forest approach
Juan B Gonzalez,Alfonso Sanchez

Climate change perceptions are fundamental for adaptation and environmental policy support. Although Africa is one of the most vulnerable regions to climate change, little research has focused on how climate change is perceived in the continent. Using random forest methodology, we analyse Afrobarometer data (N = 45,732), joint with climatic data, to explore what shapes climate change perceptions in Africa. We include 5 different dimensions of climate change perceptions: awareness, belief in its human cause, risk perception, need to stop it and self-efficacy. Results indicate that perceived agriculture conditions are crucial for perceiving climate change. Country-level factors and long-term changes in local weather conditions are among the most important predictors. Moreover, education level, access to information, poverty, authoritarian values, and trust in institutions shape individual climate change perceptions. Demographic effects -- including religion -- seem negligible. These findings suggest policymakers and environmental communicators how to frame climate change in Africa to raise awareness, gather public support and induce adaptation.