Research articles for the 2020-08-10

A Natural Disasters Index
Thilini V. Mahanama,Abootaleb Shirvani

Natural disasters, such as tornadoes, floods, and wildfire pose risks to life and property, requiring the intervention of insurance corporations. One of the most visible consequences of changing climate is an increase in the intensity and frequency of extreme weather events. The relative strengths of these disasters are far beyond the habitual seasonal maxima, often resulting in subsequent increases in property losses. Thus, insurance policies should be modified to endure increasingly volatile catastrophic weather events. We propose a Natural Disasters Index (NDI) for the property losses caused by natural disasters in the United States based on the "Storm Data" published by the National Oceanic and Atmospheric Administration. The proposed NDI is an attempt to construct a financial instrument for hedging the intrinsic risk. The NDI is intended to forecast the degree of future risk that could forewarn the insurers and corporations allowing them to transfer insurance risk to capital market investors. This index could also be modified to other regions and countries.

A New Uncertainty Measure - CAM
Klevak, Julia,Livnat, Joshua,Pei, Duo,Suslava, Kate
In contrast to past auditor opinions, which were largely unqualified and uniformly written, a new disclosure requirement expands auditors’ opinions to include a description of Critical Audit Matters (“CAMs”) and the audit steps necessary to form an opinion about them. The expanded disclosure provides substantially more information about the areas of financial reporting that auditors consider most uncertain. Using a comprehensive sample of initial CAM disclosures in the 10-K filings for the period of August 2019-May 2020, we find that a larger number of CAMs, a greater number of required auditing procedures and more wordy and extensive CAM discussions are negatively associated with stock returns immediately around the 10-K filings. We also document significantly more negative analyst earnings revisions for firms whose auditors report more CAMs and provide more verbose CAM disclosures.

Aggression in the workplace makes social distance difficult
Keisuke Kokubun

The spread of new coronavirus (COVID-19) infections continues to increase. The practice of social distance attracts attention as a measure to prevent the spread of infection, but it is difficult for some occupations. Therefore, in previous studies, the scale of factors that determine social distance has been developed. However, it was not clear how to select the items among them, and it seemed to be somewhat arbitrary. In response to this trend, this paper extracted eight scales by performing exploratory factor analysis based on certain rules while eliminating arbitrariness as much as possible. They were Adverse Conditions, Leadership, Information Processing, Response to Aggression, Mechanical Movement, Autonomy, Communication with the Outside, and Horizontal Teamwork. Of these, Adverse Conditions, Response to Aggression, and Horizontal Teamwork had a positive correlation with Physical Proximity, and Information Processing, Mechanical Movement, Autonomy, and Communication with the Outside had a negative correlation with Physical Proximity. Furthermore, as a result of multiple regression analysis, it was shown that Response to Aggression, not the mere teamwork assumed in previous studies, had the greatest influence on Physical Proximity.

Ai Human Impact: Toward a Model for Ethical Investing in Ai-Intensive Companies
Brusseau, James
Does AI conform to humans, or will we conform to AI? An ethical evaluation of AI-intensive companies will allow investors to knowledgeably participate in the decision. The evaluation is built from nine performance indicators that can be analyzed and scored to reflect a technology’s human-centering. When summed, the scores convert into objective investment guidance. The strategy of incorporating ethics into financial decisions will be recognizable to participants in environmental, social, and governance investing, however, this paper argues that conventional ESG frameworks are inadequate for AI-intensive companies. To fully account for contemporary technology, the following categories of evaluation will be developed and featured as vital investing criteria: autonomy, dignity, privacy, performance. With these priorities established, the larger goal is a model for humanitarian investing in AI-intensive companies that is intellectually robust, manageable for analysts, useful for portfolio managers, and credible for investors.

An Analysis of Connecticut's Public Employee Retirement Plans
Biggs, Andrew G.,Miller, Tracy
The state of Connecticut runs six defined benefit pension funds for its employees, which in the aggregate are among the most poorly funded retirement plans in the country and place increasing fiscal burdens on the state budget. We use a computer model to simulate the finances of these plans, demonstrating how sensitive the plans’ funded ratios and unfunded liabilities are to changes in assumed future investment returns. Future investment returns that are well within the reasonable distribution of outcomes could produce substantially greater unfunded liabilities than even those that currently are reported. This exercise demonstrates the need for greater attention to uncertain investment returns in government analyses and financial disclosures regarding public employee pensions plans.

Combining distributive ethics and causal Inference to make trade-offs between austerity and population health
Adel Daoud,Anders Herlitz,SV Subramanian

The International Monetary Fund (IMF) provides financial assistance to its member-countries in economic turmoil, but requires at the same time that these countries reform their public policies. In several contexts, these reforms are at odds with population health. While researchers have empirically analyzed the consequences of these reforms on health, no analysis exist on identifying fair tradeoffs between consequences on population health and economic outcomes. Our article analyzes and identifies the principles governing these tradeoffs. First, this article reviews existing policy-evaluation studies, which show, on balance, that IMF policies frequently cause adverse effects on child health and material standards in the pursuit of macroeconmic improvement. Second, this article discusses four theories in distributive ethics (maximization, egalitarianianism, prioritarianiasm, and sufficientarianism) to identify which is the most compatible with the core mission of the IMF, that is, improved macroeconomics (Articles of Agreement) while at the same time balancing consequences on health. Using a distributive-ethics analyses of IMF polices, we argue that sufficientarianism is the most compatible theory. Third, this article offer a qualitative rearticulation of the Articles of Agreement, and formalize sufficientarian principles in the language of causal inference. We also offer a framework on how to empirically measure, from observational data, the extent that IMF policies trade off fairly between population health and economic outcomes. We conclude with policy recommendations and suggestions for future research.

Corporate Governance and Firms Financial Performance in the United Kingdom
Martin Kyere,Marcel Ausloos

The objective of this study is to examine empirically the impact of good corporate governance on financial performance of United Kingdom non-financial listed firms. Agency theory and stewardship theory serve as the bases of a conceptual model. Five corporate governance mechanisms are examined on two financial performance indicators, return on assets (ROA) and Tobin's Q, employing cross-sectional regression methodology. The conclusion drawn from empirical test so performed on 252 firms listed on London Stock Exchange for the year 2014 indicates a positive or a negative relationship, but also sometimes no effect, of corporate governance mechanisms impact on financial performance. The implications are discussed. Thereby, so distinguishing effects due to causes, we present a proof that, when the right corporate governance mechanisms are chosen, the finances of a firm can be improved. The results of this research should have some implication on academia and policy makers thoughts.

Creating Strategic Value: Applying Value Investing Principles to Corporate Management (Introduction)
Calandro, Jr., Joseph
The principles of value investing have resonated with savvy practitioners in the world of finance for a long time. Creating Strategic Value explores how the core ideas and methods of value investing can be profitably applied to corporate strategy and management. The book builds from an analysis of traditional value investing concepts to their strategic applications. It surveys value investing’s past, present, and future, drawing on influential texts, from Graham and Dodd’s time-tested works to more recent studies, to reveal potent managerial lessons. It explains the theoretical aspects of value investing-consistent approaches to corporate strategy and management and details how they can be successfully employed through practical case studies that demonstrate value realization in action. Creating Strategic Value analyzes the applicability of key ideas such as the margin-of-safety principle to corporate strategy in a wide range of areas beyond stocks and bonds. It highlights the importance of an “information advantage”â€"knowing something that a firm’s competitors either do not know or choose to ignoreâ€"and explains how corporate managers can apply this key value investing differentiator. Offering numerous insights into the use of time-tested value investing principles in new fields, Creating Strategic Value was written for corporate strategy and management practitioners at all levels as well as for students and researchers. [Note: The downloadable document is the book’s Introduction without its Appendix.]

Credit Bubbles in Arbitrage Markets: The Geometric Arbitrage Approach to Credit Risk
Simone Farinelli,Hideyuki Takada

We apply Geometric Arbitrage Theory to obtain results in mathematical finance for credit markets, which do not need stochastic differential geometry in their formulation. We obtain closed form equations involving default intensities and loss given defaults characterizing the no-free-lunch-with-vanishing-risk condition for corporate bonds, as well as the generic dynamics for credit market allowing for arbitrage possibilities. Moreover, arbitrage credit bubbles for both base credit assets and credit derivatives are explicitly computed for the market dynamics minimizing the arbitrage.

Crowd, Lending, Machine, and Bias
Runshan Fu,Yan Huang,Param Vir Singh

Big data and machine learning (ML) algorithms are key drivers of many fintech innovations. While it may be obvious that replacing humans with machine would increase efficiency, it is not clear whether and where machines can make better decisions than humans. We answer this question in the context of crowd lending, where decisions are traditionally made by a crowd of investors. Using data from, we show that a reasonably sophisticated ML algorithm predicts listing default probability more accurately than crowd investors. The dominance of the machine over the crowd is more pronounced for highly risky listings. We then use the machine to make investment decisions, and find that the machine benefits not only the lenders but also the borrowers. When machine prediction is used to select loans, it leads to a higher rate of return for investors and more funding opportunities for borrowers with few alternative funding options. We also find suggestive evidence that the machine is biased in gender and race even when it does not use gender and race information as input. We propose a general and effective "debasing" method that can be applied to any prediction focused ML applications, and demonstrate its use in our context. We show that the debiased ML algorithm, which suffers from lower prediction accuracy, still leads to better investment decisions compared with the crowd. These results indicate that ML can help crowd lending platforms better fulfill the promise of providing access to financial resources to otherwise underserved individuals and ensure fairness in the allocation of these resources.

Deciphering the Fed’s Motivations Behind Corporate Bond Purchases after COVID-19
Flanagan, Thomas,Purnanandam, Amiyatosh
The Federal Reserve Bank and the U.S. Treasury bought several individual corporate bonds in response to COVID-19. We show that the program did not target bonds issued by firms that were hit harder by the pandemic or firms with a large employee base. It primarily purchased bonds that served as collateral in the repo market, and if they became information-sensitive due to the crisis. On the policy announcement days, credit spreads on all corporate bonds came down significantly, and the effect was stronger for the purchased bonds. Further, primary dealers from whom large amounts of bonds were bought experienced significantly higher equity returns around these events. Overall, these findings suggest that the program relaxed the funding constraints of intermediaries.

Delaware Corporate Law and the 'End of History' in Creditor Protection
Ellias, Jared A.,Stark, Robert
In this Chapter, we briefly survey the common law’s adventures with creditor protection over the course of American history with a special focus on Delaware, the most important jurisdiction for corporate law. We examine the evolution of the equitable doctrines that judges have used to answer a question that arises time and again: What help, if any, should the common law be to creditors that suffer losses due to the purported carelessness or disloyalty of corporate directors and officers? Judges have struggled to answer that question, first deploying Judge Story’s “trust fund doctrine” and then molding fiduciary duty law to fashion a remedy for creditors. In Delaware, the appetite of corporate law judges to protect creditors reached a high point in the early 2000s as judges flirted with recognizing a “deepening insolvency” tort cause of action. Suddenly, though, a new course was set, and Delaware’s judges effectively abandoned this project in a series of important decisions around the time of the financial crisis. In this “third generation” of jurisprudence, Delaware’s corporate law judges told creditors to look to other areas of law to protect themselves from opportunistic misconduct, such as bankruptcy law, fraudulent transfer law, and their loan contracts. However, as this Chapter illustrates, the same question of whether the common law ought to protect creditors has arisen time and again and today’s “settled” law is unlikely to represent the end of history in creditor protection.

Digitalisation of Financial Supervision with Supervisory Technology (SupTech)
Zeranski, Stefan,Sancak, Ibrahim Ethem
IIn this article, we discuss and analyse the main components of a digital financial supervisory system with supervisory technology (SupTech). This work offers a new SupTech definition and configures the digital pillars of a financial supervisory system. We contribute to the TECHs in Finance (FinTech, RegTech, SupTech) literature with two new concepts: “prudential supervisory disclosure” and “sustainable finance technology”, or SuFTech. This work also touches on real TECHs in Finance cases from several countries. We find that the May 6, 2010 market crash at the U.S. financial markets, one of the biggest FinTech crises, addresses the importance of having a well-functioning SupTech system. The case also points out that even a leading technology-producing country or a developed country faces unprecedented FinTech crashes or crises unless the country’s financial supervisors keep pace with technology and develop a well-functioning SupTech system.

Does Environmental and Social Disclosure Affect Firm-Level Innovation? Evidence from Around the World
Gibbons, Brian
I document the effects of environmental and social (E&S) disclosure on firm-level innovation using the staggered adoption of mandatory disclosure regulations around the world. Although transparency mitigates information asymmetry, it is also accompanied by costs that make the effect of disclosure ambiguous, ex-ante. I demonstrate that E&S disclosure increases innovative activity. Following a shock to disclosure, firms raise R&D expenditures, apply for more new patents, and receive more patent citations. Consistent with a reduction in financing frictions arising from information asymmetry, I show that firms issue more external equity after improving E&S disclosure and that the increase in innovation is stronger for equity-dependent firms. Further supporting the information asymmetry channel, I find that E&S disclosure leads to lower adverse selection costs between equity market participants and ameliorates moral hazard problems between managers and shareholders through the increased adoption of executive compensation contracts linked to E&S outcomes.

Epidemic Disease and Financial Development
An, Jiafu,Hou, Wenxuan,Lin, Chen
We study the impact of the epidemic disease on modern financial development by exploiting the geographical variation in pre-colonial survival conditions of TseTse fly, which transmits an epidemic disease harmful to humans and lethal to livestock in Africa. Using the newly georeferenced firm data across the world, we discover that firms in regions with more exposure to the epidemic disease environment have less access to external finance for firms and households today. Further tests suggest that trust, information sharing, and the tendency to adopt new technologies are potential economic channels. People are less likely to trust financial institutions and others, to share credit information, and to learn and adopt new financial technologies in historically infested regions.

Insider Ownership and Dividend Payout Policy: The Role of Business Cycle
Asmar Aliyeva

We investigate how the relationship between managerial stock incentives and the dividend payout policy is impacted by the business cycle by using the data of S&P 1500 companies during 2000-2018. We find a strong negative relationship between managerial stock options and annual dividend payouts of companies for the full sample. Although the direction of the relationship is also negative for the recession period, the coefficient is found to be insignificant. We also find that the mentioned relationship may vary during the recession depending on the size of the company. The impact of stock options on the dividend payout is negative for medium-sized companies and the coefficient is both economically and statistically significant. The direction of impact changes for large-cap companies indicating to deterioration of the CEO voting power in those companies and less agency problem. We also determine that the percentage of shares held by the CEO has a positive impact on annual dividends distributed for large-cap companies, whereas this relationship changes in times of recession.

Insider Trading in Rumored Takeover Targets
Davis, Frederick James,Khadivar, Hamed,Pukthuanthong, Kuntara,Walker, Thomas John
We examine insider trading surrounding takeover rumors in a sample of 1,642 publicly traded U.S. firms. Using difference-in-differences regressions, we find that insider net purchases increase within the year prior to the first publication of a takeover rumor, particularly when rumor articles are either accurate (lead to a takeover announcement) or informative (provide substantial justification for the rumor’s publication). Moreover, we find abnormal insider trading to be a significant predictor of takeover announcements occurring within the following year. Finally, passive net purchasing (i.e., selling less rather than buying more) is more pronounced among managing insiders than among non-managing insiders.

Log-Modulated Rough Stochastic Volatility Models
Bayer, Christian,Harang, Fabian,Pigato, Paolo
We propose a new class of rough stochastic volatility models obtained by modulating the power-law kernel defining the fractional Brownian motion (fBm) by a logarithmic term, such that the kernel retains square integrability even in the limit case of vanishing Hurst index H. The so-obtained log-modulated fractional Brownian motion (log-fBm) is a continuous Gaussian process even for H = 0. As a consequence, the resulting super-rough stochastic volatility models can be analysed over the whole range 0 <= H < 1/2 without the need of further normalization. We obtain skew asymptotics of the form log(1/T)^(-p)T^(H-1/2) as T -> 0, H >= 0, so no flattening of the skew occurs as H -> 0.

Market's Pricing and Risk-Return Trade-Offs Associated with Covenant-Lite Issues
Isin, Adnan Anil,Jacob, Martin,McMeeking, Kevin,Tharyan, Rajesh
We examine risk-return trade-offs associated with “covlite” deals which lack systematic covenant compliance requirements. While lenders charge spread premiums for covlite deals over non-covlite deals, we document increasingly borrower-accommodating covlite deal pricing patterns with smaller than anticipated emphasis on issuer-level financial leverage and credit quality. These results suggest strong risk taking incentives in leveraged loan markets. Finally, equity markets factor in both benefits and risks associated with covlite deals for “low-risk” vs. “high-risk” issuers in setting post-issue-period firm-specific risk premiums. Our analysis presents the most holistic view as to risk-benefit profile of covlite deals, from both investors’ and issuers’ perspective, to date.

Mean-variance-utility portfolio selection with time and state dependent risk aversion
Ben-Zhang Yang,Xin-Jiang He,Song-Ping Zhu

Under mean-variance-utility framework, we propose a new portfolio selection model, which allows wealth and time both have influences on risk aversion in the process of investment. We solved the model under a game theoretic framework and analytically derived the equilibrium investment (consumption) policy. The results conform with the facts that optimal investment strategy heavily depends on the investor's wealth and future income-consumption balance as well as the continuous optimally consumption process is highly dependent on the consumption preference of the investor.

Monetization Matters: Active Tail Risk Management and The Great Virus Crisis
Bhansali, Vineer,Chang, Linda,Holdom, Jeremie,Rappaport, Marcy
We discuss monetization strategies for both “Left” and “Right” tail risk hedging to illustrate potential benefits of active management of hedges. In particular, by including actual data from the sharp COVID-19 pandemic related market correction and subsequent rebound of 2020 we quantify how monetization strategies have the ability to improve the performance of portfolio hedges. This extends previous work on active tail risk hedging published in this journal. We conclude that active management of tail hedging can result in significant increases in the efficacy of tail hedging.

Obamacare and a Fix for the IRS Iteration
Samuel J. Ferguson

We model the quantities appearing in Internal Revenue Service (IRS) tax guidance for calculating the health insurance premium tax credit created by the Patient Protection and Affordable Care Act, also called Obamacare. We ask the question of whether there is a procedure, computable by hand, which can calculate the appropriate premium tax credit for any household with self-employment income. We motivate current IRS tax guidance, which has had self-employed taxpayers use a fixed point iteration to calculate their premium tax credits since 2014. Then, we give an example showing that the IRS iteration can lead to a divergent sequence of iterates. As a consequence, IRS guidance does not calculate appropriate premium tax credits for tax returns in certain income intervals, adversely affecting eligible beneficiaries. A bisection procedure for calculating premium tax credits is proposed. We prove that this procedure calculates appropriate premium tax credits for a model of simple tax returns. This is generalized to the case where premium tax credits are received in advance, which is the most common one in applications. We outline the problem of calculating appropriate premium tax credits for models of general tax returns. While the bisection procedure will work with the tax code in its current configuration, it could fail, eg, in states which have not expanded Medicaid, if a new deduction with certain properties were to arise.

Pension Information and Women's Awareness
Angelici, Marta,Boca, Daniela Del,Oggero, Noemi,Profeta, Paola,Rossi, Mariacristina,Villosio, Claudia
We explore the role of financial and pension information in increasing women's knowledge and awareness of their future pension status, and consequently, in reducing the gender pension gap. A representative sample of 1249 Italian working women were interviewed to assess their knowledge about pensions and financial issues and about their own savings and personal wealth planned for retirement. The responses showed that their knowledge and awareness of retirement planning was limited. We then ran a randomized experiment to evaluate the effect of increased information regarding pensions on women's awareness, knowledge, and behaviors. Women in the treated group were provided information in the form of three short online tutorials. A follow-up survey shows that these women became more interested and aware of pension schemes and retirement options after completing the tutorials and were more likely to be better informed and keen to obtain further information. When looking at changes in behavior, we find that treated women who are closer to retirement are more likely to believe that they would make different work-life decisions if they received specific pension information in a timely fashion. They are also more likely to have a supplementary pension fund if they are concerned about their standard of living after retirement.

Prudential Supervisory Disclosure (PSD) with Supervisory Technology (SupTech): Lessons from a FinTech Crisis
Zeranski, Stefan,Sancak, Ibrahim Ethem
The U.S. financial markets faced an unprecedented rapid decline and recovery on May 6, 2010, known as the May 6 flash crash. Roughly one trillion $ market value in less than thirty minutes vanished with the biggest one-day point decline in the history of the DJIA at the time.Since the market events took place in electronic markets, and algorithmic trading (AT) and high-frequency trading (HFT), parts of FinTech, played significant roles, we handle the May 6 flash crash from the FinTech, SupTech, and financial supervision perspectives.With the flashback method, we analyzed the reactions of market participants, media, and two financial supervisors, the SEC, and the CFTC, to the market crash. We find that the technological imbalance between financial markets or institutions and their supervisors drove the markets in uncertainty, hence in a fear and panic environment. Since the imbalance has not diminished yet, the same risks still exist. As a remedy, we introduce a new concept and model with a well-functioning SupTech system to cope with the May 6 type FinTech crises.

Public Debt and Economic Recovery Following the COVID-19 Pandemic
Prohorovs, Anatolijs
One of the main sources of funding for economic recovery in countries after the COVID-19 pandemic is the increase in public debt. But as a result of the COVID-19 pandemic and the strengthening of new trends in the development of the global economy, the level of uncertainty has greatly increased. As a result, countries that significantly increase their amount of public debt will reduce their level of macroeconomic stability considerably.The article analyses the risks that can have a negative impact on the macroeconomic stability of countries and the possibility of reducing the size of public debt during the period of economic growth after the economic recovery from the COVID-19 pandemic. The article also shows that one of the factors in deciding to increase public debt is a country's ability to significantly reduce public debt during a period of economic growth and examines the methods of financing economic recovery which will allow countries to increase their level of macroeconomic stability and international competitiveness in the medium and long term.

Quantum Computation for Pricing the Collateral Debt Obligations
Hao Tang,Anurag Pal,Lu-Feng Qiao,Tian-Yu Wang,Jun Gao,Xian-Min Jin

Collateral debt obligation (CDO) has been one of the most commonly used structured financial products and is intensively studied in quantitative finance. By setting the asset pool into different tranches, it effectively works out and redistributes credit risks and returns to meet the risk preferences for different tranche investors. The copula models of various kinds are normally used for pricing CDOs, and the Monte Carlo simulations are required to get their numerical solution. Here we implement two typical CDO models, the single-factor Gaussian copula model and Normal Inverse Gaussian copula model, and by applying the conditional independence approach, we manage to load each model of distribution in quantum circuits. We then apply quantum amplitude estimation as an alternative to Monte Carlo simulation for CDO pricing. We demonstrate the quantum computation results using IBM Qiskit. Our work addresses a useful task in finance instrument pricing, significantly broadening the application scope for quantum computing in finance.

Radner equilibrium and systems of quadratic BSDEs with discontinuous generators
Luis Escauriaza,Daniel C. Schwarz,Hao Xing

Motivated by an equilibrium problem, we establish the existence of a solution for a family of Markovian backward stochastic differential equations with quadratic nonlinearity and discontinuity in $Z$. Using unique continuation and backward uniqueness, we show that the set of discontinuity has measure zero. In a continuous-time stochastic model of an endowment economy, we prove the existence of an incomplete Radner equilibrium with nondegenerate endogenous volatility.

Risk and the Returns to Skew and Volatility Trading Around Earnings Announcements
Neururer, Thaddeus,Papadakis, George
In this study, we examine negative skew and volatility risk premiums in the option equity markets around earnings announcements. We use the realized returns to delta-neutral risk reversals and straddles option spread trades as proxies for the two types of risk premiums. We find that both strategies earn economically and statistically significant returns around earnings announcements, the returns to each strategy are elevated on earnings dates compared to non-earnings dates, the returns to the two strategies load on different option-implied risks, and the returns to each strategy hold conditional to the other strategy. We additionally present evidence that both strategies earn higher returns for firms with higher CAPM beta. However, we find evidence that firms with higher return correlations with market returns have elevated skew premia while volatility premiums are associated with firms’ total and idiosyncratic return variances. Finally, we find that these relationships do not generally hold on non-earnings announcement dates. Collectively, we find that traditional risk measures differentially associate with the returns to skewness and volatility trading on earnings announcement dates.

Supervised Machine Learning Techniques: An Overview with Applications to Banking
Linwei Hu,Jie Chen,Joel Vaughan,Hanyu Yang,Kelly Wang,Agus Sudjianto,Vijayan N. Nair

This article provides an overview of Supervised Machine Learning (SML) with a focus on applications to banking. The SML techniques covered include Bagging (Random Forest or RF), Boosting (Gradient Boosting Machine or GBM) and Neural Networks (NNs). We begin with an introduction to ML tasks and techniques. This is followed by a description of: i) tree-based ensemble algorithms including Bagging with RF and Boosting with GBMs, ii) Feedforward NNs, iii) a discussion of hyper-parameter optimization techniques, and iv) machine learning interpretability. The paper concludes with a comparison of the features of different ML algorithms. Examples taken from credit risk modeling in banking are used throughout the paper to illustrate the techniques and interpret the results of the algorithms.

The Dangerous Utopia of the ECB's Cancellation of Public Debts
Pichet, Eric
The main result of the quick reactions of the Federal Reserve (the Fed) and the European Central Bank (ECB) to the Covid-19 crisis are that more than 20% of their public debt is now held by these central banks and that the balance sheet of the ECB is now near 50% of GDP (33% for the Fed). Two questions arise from this situation. Is this new ECB policy of quantitative easing a monetisation policy forbidden by the EU treaty? According to the ECB this policy being exceptional and temporary isn’t. The second is more radical because some politicians call for pure cancellation of part or all of the public debts held by the ECB knowing that the capital of the bank is ultimately held by the 19 states of the Eurozone. We explain why such a policy would be clearly a breach of the UE treaty and would bring strong long term disadvantages.

The Hansen Ratio in Mean-Variance Portfolio Theory
Černý, Aleš
It is shown that the ratio between the mean and the L2-norm leads to a particularly parsimonious description of the mean-variance efficient frontier and the dual pricing kernel restrictions known as the Hansen-Jagannathan (HJ) bounds. Because this ratio has not appeared in economic theory previously, it seems appropriate to name it the Hansen ratio. The initial treatment of the mean-variance theory via the Hansen ratio is extended in two directions, to monotone mean-variance preferences and to arbitrary Hilbert space setting. A multi-period example with IID returns is also discussed.

The Inverted Parabola World of Classical Quantitative Finance: Non-Equilibrium and Non-Perturbative Finance Perspective
Igor Halperin

Classical quantitative finance models such as the Geometric Brownian Motion or its later extensions such as local or stochastic volatility models do not make sense when seen from a physics-based perspective, as they are all equivalent to a negative mass oscillator with a noise. This paper presents an alternative formulation based on insights from physics.

The Matthew Effect and Modern Finance: On the Nexus between Wealth Inequality, Financial Development and Financial Technology
Frost, Jon,Gambacorta, Leonardo,Gambacorta, Romina
This paper analyses the role of financial development and financial technology in driving inequality in (returns to) wealth. Using micro data from the Survey on Household Income and Wealth (SHIW) conducted by the Bank of Italy for the period 1991-2016, we find evidence of the "Matthew effect" - a capacity of wealthy households to achieve higher returns than other households. With an instrumental variable approach, we find that financial development (number of bank branches) and financial technology (use of remote banking) both have a positive association with households' financial wealth and financial returns. While households of all wealth deciles benefit from the effects of financial development and financial technology, these benefits are larger when moving towards the top of the wealth distribution. Still, the economic significance of this gap fell in the last part of the sample period, as remote banking became more widespread.

Transparency versus Performance in Financial Markets: The Role of CSR Communications
Rajiv Kashyap,Mohamed Menisy,Peter Caiazzo,Jim Samuel

Although companies are exhorted to provide more information to the financial community, it is evident that they choose different paths based upon their strategic emphasis and competitive environments. Our investigation explores the empirical boundary conditions under which firms choose to disclose versus withhold information from investors based upon their strategic emphasis. We found significant differences in terms of voluntary information disclosures between firms that consistently delivered positive earnings surprises versus those that delivered negative earnings surprises. We investigated this effect in a more granular fashion by separately examining differences in environmental, social, and governance disclosures between the two pools of firms. We found that in essence, the differences remained consistent and positive earnings firms were significantly more likely to disclose information about their ESG activities than their counterparts. Interestingly, none of the measures of financial performance were instrumental in distinguishing between the two pools of firms. However, our measures of reach -- as measured by the number of -- negative news stories lends credence to our findings. From a fund manager-s perspective, this finding should raise an immediate red flag firms that are likely to underperform are likely to be less transparent than overperformers.