Research articles for the 2020-07-30

Caremark and ESG, Perfect Together: A Practical Approach to Implementing an Integrated, Efficient, and Effective Caremark and EESG Strategy
Strine, Leo,Smith, Kirby,Steel, Reilly
With increased calls from investors, legislators, and academics for corporations to consider employee, environmental, social, and governance factors (“EESG”) when making decisions, boards and managers are struggling to situate EESG within their existing reporting and organizational structures. Building on an emerging literature connecting EESG with corporate compliance, this Essay argues that EESG is best understood as an extension of the board’s duty to implement and monitor a compliance program under Caremark. If a company decides to do more than the legal minimum, it will simultaneously satisfy legitimate demands for strong EESG programs and promote compliance with the law. Building on that insight, we explain how boards can marry existing corporate compliance programs with budding EESG programs. By integrating compliance and EESG, corporations can meet growing societal demands in an effective and efficient manner that capitalizes on existing structures. Lastly, we address how EESG and corporate compliance responsibilities should be allocated at the board and senior management level. Instead of separating compliance and EESG oversight, this Essay suggests that boards embrace a functional approach, delegating similar compliance and EESG oversight to the same committee and managers. By situating EESG within the board’s existing fiduciary duties, this Essay provides academics, legislators, investors, and managers with a novel framework to conceptualize EESG while also offering a path forward for boards struggling to place the current EESG movement within their existing corporate structure.

ADHD Symptoms and Financial Distress
Liao, Chi
We examine the effect of attention-deficit/hyperactivity disorder (ADHD) on individual-level financial distress. ADHD is the most common mental disorder among children and is characterized by behaviors such as inattention, hyperactivity, and impulsiveness that interfere with school and home life. In a representative panel, we find that individuals with more severe ADHD symptoms during childhood have more difficulty paying bills and are more likely to be delinquent on bill payments in adulthood. Further, those with more severe symptoms are less likely to have precautionary savings and more likely to have to delay buying necessities. These effects exist across the full range of ADHD symptom scores, and are not driven by the most severe cases of ADHD; this is consistent with recent evidence that ADHD symptoms occur on a continuum. Preliminary evidence suggests that medication for behavioral issues may mitigate the effect of ADHD symptoms on financial distress.

Banks as Tanks: A Continuous-Time Model of Financial Clearing
Isaac M. Sonin,Konstantin Sonin

We present a simple continuous-time model of clearing in financial networks. Financial firms are represented as "tanks" filled with fluid (money), flowing in and out. Once "pipes" connecting "tanks" are open, the system reaches the clearing payment vector in finite time. This approach provides a simple recursive solution to a classical static model of financial clearing in bankruptcy, and suggests a practical payment mechanism. With sufficient resources, a system of mutual obligations can be restructured into an equivalent system that has a cascade structure: there is a group of banks that paid off their debts, another group that owes money only to banks in the first group, and so on. Technically, we use the machinery of Markov chains to analyze evolution of a deterministic dynamical system.

Bitcoin Transaction Networks: an overview of recent results
Nicolò Vallarano,Claudio Tessone,Tiziano Squartini

Cryptocurrencies are distributed systems that allow exchanges of native (and non-) tokens among participants. The complete historical bookkeeping and its wide availability opens up an unprecedented possibility, i.e. that of understanding the evolution of their network structure while gaining useful insight on the relationships between user' behaviour and cryptocurrency pricing in exchange markets. In this contribution we review some of the most recent results concerning the structural properties of Bitcoin Transaction Networks, a generic name referring to a set of different constructs: the Bitcoin Address Network, the Bitcoin User Network and the Bitcoin Lightning Network. The picture that emerges is that of system growing over time, which becomes increasingly sparse and whose mesoscopic structural organization is characterised by the presence of an increasingly significant core-periphery structure. Such a peculiar topology is matched by a highly uneven distribution of bitcoins, a result suggesting that Bitcoin is becoming an increasingly centralized system at different levels.

Bond vs Bank Finance and the Great Recession
Martins, Manuel M. F.,Verona, Fabio
The typical increase of the corporate bond-to-bank ratio during downturns is known to mitigate business cycle recessions. In the three longest and deepest post-war U.S. recessions this ratio didn't increase from their outsets. In this paper we focus on the timing of the corporate bank-to-bond substitution in the Great Recession, simulating counterfactual paths for output growth under plausible notional behaviors of the bond-to-bank ratio. We find that the Great Recession would have been milder and the recovery much stronger if the bank-to-bond substitution had started since the outset of the recession and evolved thereafter as in most U.S. recessions.

Combining distributed 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.

Connecting actuarial judgment to probabilistic learning techniques with graph theory
Roland R. Ramsahai

Graphical models have been widely used in applications ranging from medical expert systems to natural language processing. Their popularity partly arises since they are intuitive representations of complex inter-dependencies among variables with efficient algorithms for performing computationally intensive inference in high-dimensional models. It is argued that the formalism is very useful for applications in the modelling of non-life insurance claims data. It is also shown that actuarial models in current practice can be expressed graphically to exploit the advantages of the approach. More general models are proposed within the framework to demonstrate the potential use of graphical models for probabilistic learning with telematics and other dynamic actuarial data. The discussion also demonstrates throughout that the intuitive nature of the models allows the inclusion of qualitative knowledge or actuarial judgment in analyses.

Corporate Governance and the Pricing of Initial Public Offerings: Evidence from Global Board Reforms
Chen, Yangyang,Goyal, Abhinav,Zolotoy, Leon
We study the impact of global board reforms on the pricing of IPOs. We document that board reforms are associated with a significant reduction in IPO first-day returns. The effect is amplified for IPOs with greater agency problems and mitigated for IPOs certified by reputable intermediaries, IPOs with greater disclosure specificity, and IPOs in countries with better shareholder protection and stringent financial reporting regulations. Further evidence suggests that board reforms have led to an improvement in the long-term market performance of IPOs. Our findings suggest that board reforms improve board oversight and enhance financial transparency, leading to less under-priced IPOs.

Correlating L\'evy processes with Self-Decomposability: Applications to Energy Markets
Matteo Gardini,Piergiacomo Sabino,Emanuela Sasso

Based on the concept of self-decomposability, we extend some recent multivariate L\'evy models built using multivariate subordination with the aim of capturing situations in which a sudden event in one market is propagated onto related markets after a certain stochastic time delay. Consequently, we study the properties of such processes, derive closed form expressions for the characteristic function and detail how a Monte Carlo scheme can be easily implemented. We illustrate the applicability of our approach in the context of gas and power Energy markets focusing on the calibration and on the pricing of spread options written on different underlying assets using simulations techniques.

Deep Hedging of Long-Term Financial Derivatives
Alexandre Carbonneau

This study presents a deep reinforcement learning approach for global hedging of long-term financial derivatives. A similar setup as in Coleman et al. (2007) is considered with the risk management of lookback options embedded in guarantees of variable annuities with ratchet features. The deep hedging algorithm of Buehler et al. (2019a) is applied to optimize neural networks representing global hedging policies with both quadratic and non-quadratic penalties. To the best of the author's knowledge, this is the first paper that presents an extensive benchmarking of global policies for long-term contingent claims with the use of various hedging instruments (e.g. underlying and standard options) and with the presence of jump risk for equity. Monte Carlo experiments demonstrate the vast superiority of non-quadratic global hedging as it results simultaneously in downside risk metrics two to three times smaller than best benchmarks and in significant hedging gains. Analyses show that the neural networks are able to effectively adapt their hedging decisions to different penalties and stylized facts of risky asset dynamics only by experiencing simulations of the financial market exhibiting these features. Numerical results also indicate that non-quadratic global policies are significantly more geared towards being long equity risk which entails earning the equity risk premium.

Equilibrium Oil Market Share under the COVID-19 Pandemic
Xiaojun Chen,Yun Shi,Xiaozhou Wang

Equilibrium models for energy markets under uncertain demand and supply have attracted considerable attentions. This paper focuses on modelling crude oil market share under the COVID-19 pandemic using two-stage stochastic equilibrium. We describe the uncertainties in the demand and supply by random variables and provide two types of production decisions (here-and-now and wait-and-see). The here-and-now decision in the first stage does not depend on the outcome of random events to be revealed in the future and the wait-and-see decision in the second stage is allowed to depend on the random events in the future and adjust the feasibility of the here-and-now decision in rare unexpected scenarios such as those observed during the COVID-19 pandemic. We develop a fast algorithm to find a solution of the two-stage stochastic equilibrium. We show the robustness of the two-stage stochastic equilibrium model for forecasting the oil market share using the real market data from January 2019 to May 2020.

Modelling time-varying interactions in complex systems: the Score Driven Kinetic Ising Model
Carlo Campajola,Domenico Di Gangi,Fabrizio Lillo,Daniele Tantari

We introduce a generalization of the Kinetic Ising Model using the score-driven approach, which allows the efficient estimation and filtering of time-varying parameters from time series data. We show that this approach allows to overcome systematic errors in the parameter estimation, and is useful to study complex systems of interacting variables where the strength of the interactions is not constant in time: in particular we propose to quantify the amount of noise in the data and the reliability of forecasts, as well as to discriminate between periods of higher or lower endogeneity in the observed dynamics, namely when interactions are more or less relevant in determining the realization of the observations. We apply our methodology to three different financial settings to showcase some realistic applications, focusing on forecasting high-frequency volatility of stocks, measuring its endogenous component during extreme events in the market, and analysing the strategic behaviour of traders around news releases. We find interesting results on financial systems and, given the widespread use of Ising models in multiple fields, we believe our approach can be efficiently adapted to a variety of settings, ranging from neuroscience to social sciences and machine learning.

Money flow network among firms' accounts in a regional bank of Japan
Yoshi Fujiwara,Hiroyasu Inoue,Takayuki Yamaguchi,Hideaki Aoyama,Takuma Tanaka

In this study, we investigate the flow of money among bank accounts possessed by firms in a region by employing an exhaustive list of all the bank transfers in a regional bank in Japan, to clarify how the network of money flow is related to the economic activities of the firms. The network statistics and structures are examined and shown to be similar to those of a nationwide production network. Specifically, the bowtie analysis indicates what we refer to as a "walnut" structure with core and upstream/downstream components. To quantify the location of an individual account in the network, we used the Hodge decomposition method and found that the Hodge potential of the account has a significant correlation to its position in the bowtie structure as well as to its net flow of incoming and outgoing money and links, namely the net demand/supply of individual accounts. In addition, we used non-negative matrix factorization to identify important factors underlying the entire flow of money; it can be interpreted that these factors are associated with regional economic activities.One factor has a feature whereby the remittance source is localized to the largest city in the region, while the destination is scattered. The other factors correspond to the economic activities specific to different local places.This study serves as a basis for further investigation on the relationship between money flow and economic activities of firms.

Notes for Empirical Finance (Presentation Slides)
Dai, Rui
From experience in research, teaching, and support to research community, I realize there may be a knowledge gap in between financial economic theories and their empirical implementations, resulting inefficient research designs and less reproducible outputs especially among the researchers in their early career. This slide deck is created to partially fill this gap in a practical way. Through four empirical case studies, essential knowledge of major financial databases, CRSP, Compustat, I/B/E/S, and Refinitive Ownership is introduced with a concise SAS execution of widely used applications, Fama and French Factors, Event Studies, Post-earning Announcement Drift and DGTW adjusted returns. Various data details, obscures, and errors documented in literature are also discussed within a context of design and implementation of real research applications.

Rates Factors and Global Asset Allocation
Kothe, Joshua,Lohre, Harald,Rother, Carsten
Style factors that are prominent in other asset classes, such as carry, value, momentum, and defensive, do extend to the fixed income domain as well. We investigate factor investing across global government bonds and the use of such rates factors for a multi-asset investor. These rates factors significantly improve the investment opportunity set of investors, representing valuable tail hedges and offering diversification potential. Furthermore, complementing conservative multi-asset strategies by rates factors can enhance returns and reduce the likelihood and severity of downturns not only in-sample, but also in out-of-sample portfolio simulations

Text-based crude oil price forecasting
Yun Bai,Xixi Li,Hao Yu,Suling Jia

Crude oil price forecasting has attracted substantial attention in the field of forecasting. Recently, the research on text-based crude oil price forecasting has advanced. To improve accuracy, some studies have added as many covariates as possible, such as textual and nontextual factors, to their models, leading to unnecessary human intervention and computational costs. Moreover, some methods are only designed for crude oil forecasting and cannot be well transferred to the forecasting of other similar futures commodities. In contrast, this article proposes a text-based forecasting framework for futures commodities that uses only future news headlines obtained from to forecast crude oil prices. Two marketing indexes, the sentiment index and the topic intensity index, are extracted from these news headlines. Considering that the public's sentiment changes over time, the time factor is innovatively applied to the construction of the sentiment index. Taking the nature of the short news headlines into consideration, a short text topic model called SeaNMF is used to calculate the topic intensity of the futures market more accurately. Two methods, VAR and RFE, are used for lag order judgment and feature selection, respectively, at the model construction stage. The experimental results show that the Ada-text model outperforms the Adaboost.RT baseline model and the other benchmarks.

The Curious Case of Italian Interlocking Directorates
Ghezzi, Federico Cesare Guido,Picciau, Chiara
In this paper, we provide an overview of the Italian legislation on interlocking directorates and its enforcement in the last decade. Italy is the only EU Member State to have introduced a specific anti-interlocking provision aimed at promoting competition in the banking, insurance, and financial sectors. After explaining why, without any regulation, these personal ties may facilitate or reinforce the achievement of a collusive or quiet life equilibrium among competitors, we attempt to evaluate the effectiveness and limits of the Italian interlocking ban at reducing interlocking directorates among competing firms. Using the banking sector as a case study, we gathered data on the number of interlocking directorates that persist among Italian banks and banking groups at the end of 2019. The result of our study is that interlocking directorates among major Italian banks seem to have completely disappeared. We then consider some empirical studies that, consistently with our finding, show that in the period following the entry into force of the interlocking ban, bank lending rates have fallen, indicating more vigorous competition in the banking sector. We conclude our paper questioning whether the 2011 Italian interlocking ban has had any effect on the ownership structure of the relevant market players, for instance contributing to the disposal of minority and cross-shareholdings held by competing companies, and on the composition of their governing bodies.

The Financial Position of the Workers Most Affected by the Pandemic: An Analysis Drawing on the Spanish Survey of Household Finances
Alvargonzález, Pilar,Pidkuyko, Myroslav,Villanueva, Ernesto
In the European economies, employment in the retail sector, in accommodation and food services and in the arts and recreation activities has been hit especially hard by the pandemic, so it is important to ascertain the financial resources that the individuals working in these sectors have available to withstand a possible fall in their income. This article draws on the Banco de España’s Survey of Household Finances (EFF, by its Spanish abbreviation) to characterise the financial position of the workers most affected by the present crisis. In 2017, these sectors employed approximately half of all women and the under-35s, two population groups with relatively lower labour income levels. In many cases, these workers lived in households that included higher income earners, which may partially mitigate the incidence of possible job losses. Even so, in 2017, 28% of those employed in the sectors affected lived in households whose financial assets amounted to less than one month’s income, and one in 12 lived in households for which debt repayments amounted to more than 40% of their pre-tax income. Among the workers in the sectors most affected by the pandemic, the financial position of those who were less able to work from home and those employed in the accommodation and food services and arts and recreation sectors was relatively more vulnerable.

The Impact of Banking Risk on Regional Development Banks in Indonesia
Karamoy, Herman,Tulung, Joy Elly
Financial performance of a bank represents its financial condition for a certain period of time, either in relation to fund raising or fund allocation, which is usually observed for several indicators, such as capital adequacy, liquidity, and bank profitability. In banking industries, profitability is the most accurate indicator to measure bank performance. Instruments used to measure profitability are Return on Equity (ROE) and Return on Assets (ROA). In this study, the impact of banking risk is analyzed using the ratio of Non-Performing Loans (NPL), Net Interest Margin (NIM), the Loan-to- Deposit ratio (LDR), and the ratio of Operational Cost to Operational Income (OCOI/ BOPO) on financial performance of regional development banks in Indonesia. The data used in this study were obtained from the annual reports disseminated on the website of each bank. The number of samples includes 26 Indonesian regional development banks for 2013â€"2015. The study includes 4 hypotheses for testing. The results show that simultaneously, NPL, NIM, LDR, and OBOI/BOPO are significant to ROA; while NPLs are significant and negatively affect ROA, NIM is significant and positively affects ROA, LDR is not significant and negatively affects ROA, and OCOI/BOPO is significant and negatively affects ROA. This means the banks should minimize the ratio of NPLs, LDR, and BOPO, as they have a negative influence on ROA. Conversely, banks should maximize the ratio of NIM since the latter has a positive effect on ROA.

The Impact of COVID-19 on Price Volatility of Crude Oil and Natural Gas Listed on Multi Commodity Exchange of India
Meher, Bharat Kumar,Hawaldar, Iqbal Thonse ,Mohapatra, Latasha,Sarea, Adel
The impact of COVID-19, due to the wide-spread demand and supply destruction and downward movement of crude oil prices is of concern for all those connected with the oil and gas industry. In this study, an attempt has been made to estimate the price volatility of crude oil and natural gas listed on multi commodity exchange of India (MCX). We measured the leverage effect of COVID-19 on price volatility of crude oil and natural gas by using the daily prices of crude oil and natural gas from May 01, 2017 to April 30, 2020. The findings of the study reveal that there is a presence of leverage effect of COVID-19 on the price volatility of crude oil. However, this leverage effect is not present on the price volatility of natural gas. The findings of the study will help investors to develop investment strategies and to the policymakers to formulate appropriate policies to overcome or minimise the impact of COVID-19. The forecasting graphs of crude oil prices indicate that there is a possibility that price volatility will be higher in the future. However, it is difficult to forecast the expected price volatility of natural gas for the future because the price volatility graph is extremely fluctuating.

Uniqueness in Cauchy problems for diffusive real-valued strict local martingales
Umut Cetin,Kasper Larsen

For a real-valued one dimensional diffusive strict local martingale, we provide a set of smooth functions in which the Cauchy problem has a unique classical solution. We exemplify our results using the inverse 2D Bessel process and quadratic normal volatility models.

What Do Outside CEOs Really Do? A Look Inside the Black Box With Plant-Level Data
Bai, John (Jianqiu),Mkrtchyan, Anahit
Using rich plant-level data, we analyze the relative performance of inside and outside CEOs and provide the first empirical evidence on what CEOs actually do to improve performance. Contrary to conventional wisdom, we show that outsiders achieve higher growth in productivity in both low- and high-performing firms. Efficiency gains arise from divesting low-performing, non-core, and low-tech plants. Additionally, outsiders improve productivity of the remaining plants by cutting costs, consolidating product offering, adopting newer technology, and shifting to more capital-intensive production that increases labor productivity. Overall, our results suggest that, compared to insiders, outsiders are more effective in correcting pre-turnover inefficiencies.

Willingness to Pay for Multi-Peril Hazard Insurance
Landry, Craig E.,Anderson, Sarah,Krasovskaia, Elena,Turner, Dylan
Increasing the number of insured assets in high risk areas can help reduce the need for federal disaster aid and help communities rebuild quicker following a disaster event. Offering a bundled multi-peril homeowners insurance product may be one way to do this. Using individual level survey data, we assess demand for a hypothetical multi-peril insurance product and estimate a mean annual willingness to pay of \$4396.93. Both quantitative and qualitative analysis point to cost being the primary concern for adoption, however, reducing cognitive burden and uncertainty in the claims filing process appear to be important factors that appeal to homeowners.