# Research articles for the 2020-04-28

50 Shades of Green Part II: The Fallacy of Environmental Markets
Hache, Frederic
SSRN
Recent calls to action to address critical loss of biodiversity are both long overdue and very welcome, but a parallel debate on the â€˜howâ€™ is missing. Yet the â€˜howâ€™ is arguably as important as the headline objective. The â€˜howâ€™ is also in the process of changing drastically with the promotion of new financial markets on environmental destruction, and the mainstreaming of a new kind of sustainable finance. Offset markets on biodiversity and other ecosystem services have been shown to suffer from intractable conceptual issues, including measurement issues, incalculable additionality, highly uncertain valuations and an inexistent price signal. As a result, they will never be able to achieve their environmental and social objectives. Empirical evidence also suggests an appalling social and environmental track record for some existing markets. As importantly, the selective pricing of only some ecosystem services and the ignorance of ecosystem interdependencies mean that the resulting values cannot claim to represent biodiversity. Traditional environmental regulation would be far more effective, simpler and cheaper to address the critical loss of natural resources. They would not require the unrealistic assumptions and oversimplifications needed to create markets on biodiversity, and would accommodate infinitely better the high scientific uncertainty and our incomplete scientific knowledge. While putting a price on nature to save it is a catchy formula, it would therefore seem that regulating natureâ€™s destruction would be a far superior alternative. Sustainable finance should not foster the creation of such markets if it is to be truly sustainable.

Laby, Arthur B.
SSRN

Arbitrage Opportunity, Impossible Frontier, and Logical Circularity in CAPM Equilibrium
SSRN
The capital market for CAPM is incomplete and is a Hilbert space, we find out the analytic expression for the SDF mimicking payoff in this market. The CAPM formula holds under the partial equilibrium of purely risky assets, which is equivalent to the condition that the market portfolio is the tangency portfolio. Since the general solution to asset prices in CAPM has only one dimension, given all individual investor's endowments and mean-variance preferences, the condition of CAPM equilibrium turns out to be an equation of only one variable. With the closed-form solution to CAPM equilibrium, we see more clearly that the risk-return characteristics is a false impression from the partial equilibrium of purely risky assets. Thus it is illusory, for the assets are priced as a whole and the prices are endogenous, the return of market portfolio is not exogenous but endogenous. By way of numerical examples, we show that CAPM equilibrium may coexist with arbitrage opportunities, and that the crisis of impossible frontier is due to market disequilibrium. We point out the incorrect practice of beta pricing by presenting negative prices of European call options.

Are Lac Cooperative and Commercial Banks so Different in Their Management of Nonâ€Performing Loans?
SSRN
This paper assesses technical efficiency in the management of non‐performing loans (NPLs) in the Latin American and Caribbean (LAC) banking industry. To that end, Data Envelopment Analysis techniques are employed with data from the years 2013 to 2016 on a sample of 307 LAC cooperative and commercial banks. Our main contribution to existing literature is that differences of efficiency between cooperative banks and commercial banks are assessed as the result of the different capacities of their managers – managerial efficiency – and the so‐called programme efficiency, which represents differences in the technology used by these two categories of entities. Our principal result suggests that the technology used by cooperative banks in the management of NPLs is more efficient than the technology of commercial banks.

Avoiding zero probability events when computing Value at Risk contributions: a Malliavin calculus approach
Yuri F. Saporito,Rodrigo S. Targino
arXiv

This paper is concerned with the process of risk allocation for a generic multivariate model when the risk measure is chosen as the Value-at-Risk (VaR). Making use of Malliavin calculus, we recast the traditional Euler contributions from an expectation conditional to an event of zero probability to a ratio of conditional expectations, where both the numerator and the denominator's conditioning events have positive probability. For several different models we show empirically that the estimator using this novel representation has no perceivable bias and variance smaller than a standard estimator used in practice.

Board Governance: Does Ownership Matter?
HIDETO DATO, Muluneh,Hudon, Marek,Mersland, Roy
SSRN
Good governance is crucial to achieving an organization's mission. Nevertheless, little is known about how the structure of governance is influenced by the nonprofit (NPO) or for‐profit ownership (FPO) structure of an organization, partly because they tend to be active in different sectors. In this paper we overcome this challenge by using data from a global sample of 392 microfinance institutions. The results show that the average NPO has a larger board, more female directors, and a higher number of board meetings than the average FPO. Moreover, where there are larger boards and more frequent board meetings, this has a positive effect on the financial performance of NPOs. It is thus confirmed that ownership structures influence boards' characteristics and that some board mechanisms are more efficient in some ownership structures than in others. An effective board design should thus be based on a firm's ownership structure.

Born Out of Necessity: A Debt Standstill for COVID-19
Bolton, Patrick,Buchheit, Lee C.,Gourinchas, Pierre-Olivier,Gulati, G. Mitu,Hsieh, Chang-Tai,Panizza, Ugo,Weder di Mauro, Beatrice
SSRN
The global downturn caused by the Covid-19 pandemic has the potential to send more than half the nations around the globe into debt distress in the near future. As of this writing, nearly a hundred countries have approached the IMF for assistance. Many, perhaps most, of these countries will need to move scarce resources away from debt service and towards battling the novel coronavirus. In response, the G20 has called for a temporary standstill on bilateral official debt sector debt owed by 72 of the poorest nations. To be effective (and to be fair), however, this temporary debt relief provided by bilateral creditors must be complemented by an equivalent effort from private sector lenders. Our policy paper argues that a comprehensive suspension of debt obligations is justified on the grounds of necessity and lays out a simple mechanism by which the private sector participation can be implemented immediately.

COVID 19â€™s Impact on Crude Oil and Natural Gas S&p Gs Indexes
Aloui, Donia,Goutte, Stephane,Guesmi, Khaled,Hchaichi, Rafla
SSRN
On 12 March 2020, the sharp fell of U.S. crude oil price to 30 dollars was explained by the outspreads of coronavirus pandemic and the OPECâ€™s inability to reach a production quota agreement. We employ the structural VAR model with time-varying coefficients and stochastic volatility (TVP-SVAR model) developed by Primiceri (2005) to asses the impact of COVID-19 shocks on the energy futures markets, particularly on crude oil and natural gas S&P GS Indexes. The findings confirm that energy commodities S&P GS Indexes respond to COVID-19 shock that varying over time due to fundamentals factors as well as behavioral and psychological factors.

Continuous viscosity solutions to linear-quadratic stochastic control problems with singular terminal state constraint
Ulrich Horst,Xiaonyu Xia
arXiv

This paper establishes the existence of a unique nonnegative continuous viscosity solution to the HJB equation associated with a Markovian linear-quadratic control problems with singular terminal state constraint and possibly unbounded cost coefficients. The existence result is based on a novel comparison principle for semi-continuous viscosity sub- and supersolutions for PDEs with singular terminal value. Continuity of the viscosity solution is enough to carry out the verification argument.

Corporate Governance through Ownership Structure: Evidence from KSE-100 Index
Shabbir, Aqsa,Tahir, Dr. Safdar Husain,Aziz, Bilal
SSRN
This paper examined the association between ownership structure, firm performance and dividend policy with respect to Governance perspective of companies present in Karachi Stock Exchange (KSE). A sample of 45 Non-financial KSE-100 Index listed firms for a period of 2010 to 2013 has been taken for analysis of this study. Multiple Regression Models are applied on the panel data to measure the relationship between ownership structure, firm performance and dividend policy. The empirical results provide evidence that ownership structure significantly affects the dividend policy and firm performance in connection with family ownership concentration. The empirical results also exhibit a significant negative relation between Dividend payments and ownership concentration and thus support the Entrenchment Theory; it means that the major shareholders protect their own benefit at the cost of minor stakeholders. Furthermore, the results also showed a positive relation of firm performance with foreign holdings, which means better performance is an attractive sign for the foreign investment and financial health of the economy.

Coâ€Op Open Membership: Economic and Financial Effects
SSRN
This paper aims to analyze the objectives pursued by cooperatives upon opening doors to new members and how this affects business activity and financial indicators. Surprisingly, the results show that accepting new partners makes no positive impact on the return on assets, but it does make a variable impact on financial indicators according to the type of cooperative. Distinguishing between agricultural and worker co‐ops, we conduct a cross‐sectional study of a sample of Galician cooperatives to find whether they apply this principle the same way regardless of membership size. Our results corroborate that cooperatives apply the principle differently. This not only allows us to extract other relevant information from accounting for cooperatives, but it also permits other agents like financial entities to obtain indicators that reflect the true company image more adequately.

Credit Union Member Group Domination Under High Interest Rate Environments
Mercer, Antonio,PÃ³voa, Angela,Piccoli, Pedro
SSRN
Theoretical models for credit unions advocate that such organizations should pursue a neutral orientation in order to accommodate the conflicting interests of borrower members, who seek lower interest rates, and saver members, who look for higher returns on their savings. However, there is a lack of empirical support for such neutrality in high interest rate environments. This is because under such conditions, credit unions could accomplish their social mission by providing microcredit at a lower interest rate to local communities, thus becoming more borrower‐dominated. This paper investigates the member group domination of credit unions in Brazil, a country known for its high interest rates, and finds that the majority of credit unions (78.34%) are borrower‐dominated. This behavior becomes more pronounced when local interest rates rise, contradicting the predictions of neutrality‐seeking models. A percentage increase in the interest rate, increases about 5 times the likelihood of a CU becoming extreme borrower‐dominated. Besides interest rates, age, lower size, capital and lower efficiency of the credit unions are the main determinants of borrower domination.

Current Developments in German Pension Schemes: What Are the Benefits of the New Target Pension?
Chen, An,Rach, Manuel
SSRN
We analyze the newly introduced German occupational pension scheme called target pension ("Zielrente"), which links the beneficiaries' benefits during the retirement phase to the mortality experienced among the pension beneficiaries and the performance of the financial market, from a pension beneficiary's perspective. We model the contract payoffs related to the target pension according to the new enhancement law on German occupational law. Specifically, we include two parameters in the plan design, one to control the surplus participation and one to control the loss participation. These parameters are chosen in such a way that the initial wealth of the retiree equals the initial value of the target pension. We find that the target pension provides a meaningful supplement to the first and third pillar. Further, we find some comparative advantages of the target pension over the traditional pure defined benefit and pure defined contribution plans from a policyholder's point of view.

Decreases in global CO$_2$ emissions due to COVID-19 pandemic
Zhu Liu,Zhu Deng,Philippe Ciais,Ruixue Lei,Sha Feng,Steven J. Davis,Yuan Wang,Xu Yue,Yadong Lei,Hao Zhou,Zhaonan Cai,Bo Zheng,Xinyu Dou,Duo Cui,Pan He,Biqing Zhu,Piyu Ke,Taochun Sun,Yuhui Wu,Runtao Guo,Tingxuan Han,Jinjun Xue,Yilong Wang,Frederic Chevallier,Qiang Zhang,Dabo Guan,Peng Gong,Daniel M. Kammen,Hans Joachim Schellnhuber
arXiv

Assessing the impacts of COVID-19 are of paramount importance for global sustainability. Using a coordinated set of high-resolution sectoral assessment tools, we report a decrease of 4.2% in global CO$_2$ emission in first quarter of 2020. Our emission estimates reflect near real time inventories of emissions from power generation, transportation, industry, international aviation and maritime sectors in 34 countries that account for >70% of world energy-related CO2 emissions in recent years. Regional variations in CO$_2$ emissions are significant, with a decrease in China (-9.3%), US (-3.0%), Europe (EU-27 & UK) (-3.3%) and India (-2.4%), respectively. The decline of short-lived gaseous pollutants, such as NO$_2$ concentration observed by Satellites (-25.73% for China, -4.76% for US) and ground observations (-23% for China) is consistent with the estimates based on energy activity (-23.94% for China, -3.52% for US), but the decline is not seen in satellite assessments of aerosol optical depth (AOD) or dry column CO$_2$ (XCO$_2$). With fast recovery and partial re-opening of national economies, our findings suggest that total annual emissions may drop far less than previously estimated (e.g., by 25% for China and more than 5% for the whole world). However, the longer-term effects on CO$_2$ emissions are unknown and should be carefully monitored using multiple measures.

Denise: Deep Learning based Robust PCA for Positive Semidefinite Matrices
Calypso Herrera,Florian Krach,Josef Teichmann
arXiv

We introduce Denise, a deep learning based algorithm for decomposing positive semidefinite matrices into the sum of a low rank plus a sparse matrix. The deep neural network is trained on a randomly generated dataset using the Cholesky factorization. This method, benchmarked on synthetic datasets as well as on some S&P500 stock returns covariance matrices, achieves comparable results to several state-of-the-art techniques, while outperforming all existing algorithms in terms of computational time. Finally, theoretical results concerning the convergence of the training are derived.

Designing a NISQ reservoir with maximal memory capacity for volatility forecasting
Samudra Dasgupta,Kathleen E. Hamilton,Arnab Banerjee
arXiv

Quantitative risk management, particularly volatility forecasting, is critically important to traders, portfolio managers as well as policy makers. In this paper, we applied quantum reservoir computing for forecasting VIX (the CBOE volatility index), a highly non-linear and memory intensive `real-life' signal that is driven by market dynamics and trader psychology and cannot be expressed by a deterministic equation. As a first step, we lay out the systematic design considerations for using a NISQ reservoir as a computing engine (which should be useful for practitioners). We then show how to experimentally evaluate the memory capacity of various reservoir topologies (using IBM-Q's Rochester device) to identify the configuration with maximum memory capacity. Once the optimal design is selected, the forecast is produced by a linear combination of the average spin of a 6-qubit quantum register trained using VIX and SPX data from year 1990 onwards. We test the forecast performance over the sub-prime mortgage crisis period (Dec 2007 - Jun 2009). Our results show a remarkable ability to predict the volatility during the Great Recession using today's NISQs.

Disagreement, Speculation and Management Forecasts
Dimitrov, Valentin,Palia, Darius,Xu, Zhiwei
SSRN
Prior research shows that disagreement leads to speculative trading and a speculative premium in stock prices. We examine how managers respond to this speculative premium. Using exogenous variation in speculative trading due to the reconstitution of the Russell 1000/2000 indices, we find that speculative trading reduces the frequency, likelihood, and precision of management forecasts. Consistent with theory, this relationship is significantly stronger when short sale constraints are more binding, and when managers have stronger equity-based incentives. We also find that managers sell equity to benefit from the speculative premium. In summary, our results suggest that managers issue forecasts opportunistically in response to speculative trading: they either keep silent, or issue fewer and more ambiguous forecasts to prolong disagreement among investors and the speculative premium.

Discrete Time Growth Optimal Investment With Costs
Iyengar, Garud
SSRN
In this work we ask how should an investor distribute wealth over various assets to maximize the growth rate of the cumulative wealth in a discrete time market with proportional transaction costs. We show that this sequential decision problem has a stationary optimal policy. In addition, we show that for all Îµ > 0 there exists a policy that guarantees a growth rate at most Îµ below optimal on almost every sample path. We also show the existence of an Îµ-optimal control- limit policies â€" control-limit policies correct the portfolio only it leaves a compact connected no-trade set. For the special case of two-asset markets, we establish that for all Îµ > 0 there exists a control-limit policy that is Îµ-optimal with probability 1.

Diversity in the C-Suite: The Dismal State of Diversity Among Fortune 100 Senior Executives
Larcker, David F.,Tayan, Brian
SSRN
There has been a broad push in recent years to increase diversity at the board and CEO levels of public corporations. Despite this effort, diversity on boards and in senior leadership positions has not reached the levels to which advocates aspire. We provide new insight into this topic by examining the size, structure, and demographic makeup of the C-suite (the CEO and the direct reports to the CEO) in each of the Fortune 100 companies. Demographic statistics by each functional role are provided. Organizational charts of the C-suites of each company as of February 2020 are provided by reference.We find that women (and, to a lesser extent, racially diverse executives) who directly report to the CEO are underrepresented in positions that directly feed into future CEO and board roles (such as CFO and P&L leaders) and have greater representation in positions that are less likely to lead to these appointments (such as general counsel or human resources). That is, diversity statistics in the C-suiteâ€"even though lowâ€"still overstate the likelihood of increased diversity among corporate leadership in coming years.We ask: â€¢ At what step along the way does the process of promoting diverse executives break down?â€¢ Should companies disclose diversity in greater detail by level or function?â€¢ What accounts for the fact that women have much higher representation in lower potential C-suite roles?â€¢ What accounts for the very low levels of racial diversity across C-suite roles?â€¢ When will company initiatives actually lead to tangible improvements in diversity?

Do Accounting and Finance Masterâ€™s Students Apply Prospect Theory? (Â¿Aplican los estudiantes de maestrÃ­a en contabilidad y finanzas la teorÃ­a de la perspectiva?)
V. D. Alves, Maria Teresa
SSRN

Economics - 2020: What Happens When Everything Shuts Down Except the 'Money Printing Presses'
Murphy, Austin
SSRN
This short paper indicates how the massive fiscal deficits financed by creation of fiat money by central banks worldwide (undertaken in response to the 2020 coronavirus pandemic) may lead to an inflationary depression. In particular, the supply disruptions caused by the pandemic inhibit the production of real goods and services necessary to absorb the extensive money printing to fund the large amounts of government spending could lead to an increase in the prices of real goods and services that is comparable to that occurring during the hyperinflation in Germany in 1923 except on a broad international scale.

Econophysics Approach and Model on Mixed Economy
Ion Spanulescu,Anca Gheorghiu
arXiv

In this paper the general principles and categories of mixed economy that currently exist in almost all countries of the world are presented. The paper also presents an Advanced Model of Mixed Economy with Threshold (AMMET), which is characterized by a reduced value (approx. 10-15%) of the State and public sector participation in the national economy and proposes and analyzes an econophysics model for the mixed economy.

Embedded Leverage
Frazzini, Andrea,Pedersen, Lasse Heje
SSRN
Many financial instruments are designed with embedded leverage such as options and leveraged exchange traded funds (ETFs). Embedded leverage alleviates investorsâ€™ leverage constraints and, therefore, we hypothesize that embedded leverage lowers required returns. Consistent with this hypothesis, we find empirically that options and leveraged ETFs provide significant amounts of embedded leverage, this embedded leverage increases return volatility in proportion to the embedded leverage, and higher embedded leverage is associated with lower risk-adjusted returns. The results are statistically and economically significant, and we provide extensive robustness tests and discuss the broader implications of embedded leverage for financial economics.

Engineering Economics in the Conflux Network
Yuxi Cai,Fan Long,Andreas Park,Andreas Veneris
arXiv

Proof-of-work blockchains need to be carefully designed so as to create the proper incentives for miners to faithfully maintain the network in a sustainable way. This paper describes how the economic engineering of the Conflux Network, a high throughput proof-of-work blockchain, leads to sound economic incentives that support desirable and sustainable mining behavior. In detail, this paper parameterizes the level of income, and thus network security, that Conflux can generate, and it describes how this depends on user behavior and "policy variables'' such as block and interest inflation. It also discusses how the underlying economic engineering design makes the Conflux Network resilient against double spending and selfish mining attacks.

Estimating Full Lipschitz Constants of Deep Neural Networks
Calypso Herrera,Florian Krach,Josef Teichmann
arXiv

We estimate the Lipschitz constants of the gradient of a deep neural network and the network itself with respect to the full set of parameters. We first develop estimates for a deep feed-forward densely connected network and then, in a more general framework, for all neural networks that can be represented as solutions of controlled ordinary differential equations, where time appears as continuous depth. These estimates can be used to set the step size of stochastic gradient descent methods, which is illustrated for one example method.

Evidence on the Decision Usefulness of Fair Values in Business Combinations
Blann, Justin,Campbell, John L.,Shipman, Jonathan E.,Wiebe, Zac
SSRN
In 2001, SFAS 141 (ASC 805) required that identifiable assets and liabilities acquired in a business combination be initially recorded at fair value rather than pre-acquisition book value. The FASB argued that fair value measurement would provide more decision-useful information about future cash flows following business combinations. However, opponents argued that fair values are often difficult to estimate and may be too noisy to be useful. In this study, we examine whether fair value measurement for identifiable assets and liabilities provides incremental decision-useful information about post-acquisition cash flows and offer two main findings. First, we find that fair values have incremental predictive ability for post-deal cash flows (beyond pooled book values), but only in limited circumstances: (i) horizontal (i.e., same-industry) deals, (ii) deals that do not involve R&D-intensive targets, and (iii) deals in which managers have less incentive to over-allocate purchase price to goodwill. This suggests that fair value measurement in business combinations only enhances decision usefulness in transactions when fair values are more reliably estimable and/or less subject to manager incentives. Second, we find that analysts update their cash flow forecasts to reflect the information provided by fair value disclosures, but only in transactions where we find that fair values are decision useful. Overall, our results suggest that there are limits in the extent to which fair value measurement for acquired identifiable assets and liabilities provides decision-useful information about future cash flows, and that capital market participants appear to recognize those limits as reflected in their decision making.

Examination of Information Release on Return Volatility: A Market and Sectoral Analysis
SSRN
This paper examines the role of information release in explaining return volatility in Australian equities. The study utilised proxies of greater accuracy than have previously been used to examine the effect of private and public information on return volatility. Analyst price targets (PTR) and Morningstar stock star ratings (MSR) were proxies for private information and Australian Securities Exchange (ASX) announcements was a proxy for public information. Analysis was conducted at both the aggregate market level and the sectoral levels. Sectoral analysis is important because Australia operates as a â€˜two-speed economyâ€™ in which some sectors perform higher than others. The limited number of studies that highlight this distinction warranted the need to perform this study. Data was collected for ASX 200â€"listed firms for the period 2013 to 2017. The findings provide insights into how information disclosures instigate varied volatility within the entire market and across sectors. The results also suggest that PTR have the largest effect on return volatility at both the aggregate market and the sectoral levels, thereby further indicating that investors rely heavily on this information when undertaking investment decisions. In contrast, MSR had a negligible effect, which is likely due to the lower degree of informational content. Although investors rely on these information proxies, they do not realise the diverse effect that each private information proxy has on sectoral return volatility. Public information has a minor effect on return volatility at both the aggregate market and sectoral levels. These mixed results indicate that information flow varies depending on the information type (i.e. private or public) with each sector interpreting the same information differently, as highlighted by the varying levels of volatility. The research findings provide a valuable guide to investors regarding the appropriate information proxy to generate excess returns as well as to hedge against future losses.

Filling the Gap: Emergency Funding Programs and Asset-Based Finance in Times of Economic Crisis
Powell, David
SSRN
The value in 2018 of vehicles and equipment for consumer and business customers in Canada financed by the asset-based finance (ABF) industry was an estimated $416 billion. The ABF industry supports a broad network of dealers, manufacturers, distributors, vendors and brokers, and their customers throughout the country. ABF is offered by banks, credit unions, insurance companies, government financial institutions, manufacturer finance companies, and independent finance companies. Several of these entities are regulated with consequent access to existing Bank of Canada programs for emergency lending. This paper focuses on those entities â€" both regulated and unregulated â€" that may not have such access, and yet are critical to the functioning of the economy. ABF entities ran into deep trouble during the 2008-2009 global financial crisis and required an emergency liquidity program from the federal government that took months to devise and implement. The primary source of funding of the ABF sector was, and is, the asset-backed commercial paper and securitization markets, often with bank back-up or standby lines, purchased by private pools of investment capital â€" insurance companies, pension plans, hedge funds, banks and others. The 2008-2009 experience revealed that a complete loss of liquidity could occur within a few weeks, even days. Government was needed to step into the shoes of absent private-sector investors. Given the ABF industryâ€™s relative success and low delinquencies, this Commentary recommends that, during periods of extraordinary financial market turmoil, the federal government activate a large-scale securitization program that would fund ABF intermediaries who finance customers based on real assets. The government would purchase asset-backed securities backed by a pool of assets and their receivables, receiving the same protection and profit that a privatesector investor would receive. Once liquidity is restored and private investor confidence returned, the commercial markets would again resume their normal functioning and government could withdraw its scaled-up temporary emergency funding program. The 2009 Federal Budget established the Canadian Secured Credit Facility, a$12 billion fund administered by The Business Development Bank of Canada (BDC) to purchase term asset-based securities (ABS) backed by loans and leases on vehicles and equipment. Since then, under successor programs, the BDC has continued to purchase ABS albeit on a smaller scale. With more than 10 years of experience, the BDC understands the policies and rules for such funding. Existing BDC programs could, therefore, be scaled up in a severe downturn, with experienced people in place for effective, prudent and efficient funding. In a profoundly disrupted market, the policy objective should be to restore liquidity to allow the financial services sector to continue offering financing to credit-worthy consumers and businesses in support of the Canadian economy, and that must include the ABF industry.

Finance, Distribution and the Economic Objective of Financial Cooperative Institutions
Khafagy, Amr
SSRN
This paper proposes a model where the structure rather than the size of the financial sector explains its influence on income distribution. Because of information asymmetries, a financial sector dominated solely by profit‐maximizing financial intermediaries will increase income and wealth inequality as it gives preferential access to credit for high‐income agents, whereas a diversified inclusive financial sector with alternative models of finance, like cooperatives, will reduce the inequality gap. No full convergence in income distribution can be realized through finance only and there is still a need for redistribution policies. Accordingly, an objective function for cooperative financial institutions should define a desired pricing behaviour that can increase the income of members at a rate higher than the average growth rate of the economy.

Financial Position and Performance in IFRS 17
Lindholm, Mathias,Lindskog, Filip,Palmborg, Lina
SSRN
The general principles for determining the financial performance of a company is that revenue is earned as goods are delivered or services provided, and that expenses in the period are made up of the costs associated with this earned revenue. To follow these principles in the insurance industry is a complex task.The premium payments are typically made upfront, and can provide coverage for several years, or be paid many years before the coverage period starts. The associated costs are often not fully know until many years later. Hence, complexity arises both in determining how a premium paid should be earned over time, and in valuing the costs associated with this earned premium. IFRS 17 attempts to align the insurance industry with these general accounting principles.We bring this new accounting standard into the realm of actuarial science, through a mathematical interpretation of the regulatory texts, and by defining the algorithm for profit or loss in accordance with the new standard. Furthermore, we suggest a computationally efficient risk-based method of valuing a portfolio of insurance contracts and an allocation of this value to sub-portfolios. Finally, we demonstrate the practicability of these methods and the algorithm for profit or loss in a large-scale numerical example.

Generalized Bounds on the Conditional Expected Excess Return on Individual Stocks
Chabi-Yo, Fousseni,Dim, Chukwuma,Vilkov, Grigory
SSRN
We derive generalized bounds on conditional expected excess returns on individual stocks. Bounds are developed in terms of observable risk-neutral quantities, and can be computed anytime using option prices for any available investment horizon. Accounting for all risk-neutral moments of individual stock returns, they outperform runner-up models for in- and out-of-sample return predictions. Calibrated to realized returns, bounds correspond to reasonable preference parameters at various horizons. Average conditional expected returns given by the generalized lower bounds significantly decrease on FOMC days and in the even weeks of the FOMC cycle; stocks with low sensitivity to FOMC news identified using high-order implied moments, beta, idiosyncratic volatility, momentum, among others, experience an increase in expected returns. Further asset pricing tests deliver a reasonable and positive unconditional market risk premium. We also derive bounds on the conditional expected excess log return for individual stocks and perform similar empirical exercises.

Government's Real Estate Interventions and the Stock Market
Akbari, Amir,Krystyniak, Karolina
SSRN
We study the investment choices of institutional investors in response to the governments' interventions in the real estate market. We find that mutual funds decreased their ownership in equities during the intervention months with no short-term reversal. This behavior is more observed among active mutual funds, especially those investing in the local assets. Interestingly, we find that these investors increased their ownership in the financial sector stocks without significant changes to their real estate equity holdings. Our results suggest that the interventions affecting the riskiness of the financial stocks were more effective than the ones focused on the real estate returns. Our results are based on a "quasi-natural experiment'' provided by a surprise announcement of foreign buyer tax and lending stress tests in Canada, which were introduced following the rapid increase in housing prices in major Canadian cities.

How do online consumers review negatively?
Menghan Sun,Jichang Zhao
arXiv

Negative reviews on e-commerce platforms, mainly in the form of texts, are posted by online consumers to express complaints about unsatisfactory experiences, providing a proxy of big data for sellers to consider improvements. However, the exact knowledge that lies beyond the negative reviewing still remains unknown. Aimed at a systemic understanding of how online consumers post negative reviews, using 1, 450, 000 negative reviews from JD.com, the largest B2C platform in China, the behavioral patterns from temporal, perceptional and emotional perspectives are comprehensively explored in the present study. Massive consumers behind these reviews across four sectors in the most recent 10 years are further split into five levels to reveal group discriminations at a fine resolution. Circadian rhythms of negative reviewing after making purchases were found, and the periodic intervals suggest stable habits in online consumption and that consumers tend to negatively review at the same hour of the purchase. Consumers from lower levels express more intensive negative feelings, especially on product pricing and seller attitudes, while those from upper levels demonstrate a stronger momentum of negative emotion. The value of negative reviews from higher-level consumers is thus unexpectedly highlighted because of less emotionalization and less biased narration, while the longer-lasting characteristic of these consumers' negative responses also stresses the need for more attention from sellers. Our results shed light on implementing distinguished proactive strategies in different buyer groups to help mitigate the negative impact due to negative reviews.

Humans in Charge of Trading Robots: The First Experiment
Asparouhova, Elena N.,Bossaerts, Peter,Rotaru, Kristian,Wang, Tingxuan,Yadav, Nitin,Yang, Wenhao
SSRN
We present results from an experiment where participants have access to a set of robots (automated trading algorithms), which they may deploy, launch, halt and replace at will, while still trading manually. We hypothesize that mispricing would be reduced. Yet, we observe equally large and frequent mispricing and, in early trading, significantly higher effective bid-ask spreads, and flash crashes/price surges. Nevertheless, participants who engage in both robot and manual trading perform better. Inspection of the types of robots deployed reveals a potentially disturbing source of bias in traditional field studies of algorithmic trading.

Income, Liquidity, and the Consumption Response to the 2020 Economic Stimulus Payments
Baker, Scott R.,Farrokhnia, R.,Meyer, Steffen,Pagel, Michaela,Yannelis, Constantine
SSRN
In response to the ongoing COVID-19 pandemic, the US government brought about a collection of fiscal stimulus measures: the 2020 CARES Act. Among other provisions, this Act directed cash payments to households. We analyze householdsâ€™ spending responses using high-frequency transaction data. We also explore heterogeneity by income levels, recent income declines, and liquidity. We find that households respond rapidly to receipt of stimulus payments, with spending increasing by $0.25-$0.35 per dollar of stimulus during the first 10 days. Households with lower incomes, greater income drops, and lower levels of liquidity display stronger responses. Liquidity plays the most important role, with no observed spending response for households with high levels of bank account balances. Relative to the effects of previous economic stimulus programs in 2001 and 2008, we see much smaller increases in durables spending and larger increases in spending on food, likely reflecting the impact of shelter-in-place orders and supply disruptions. In turn, we discuss the fiscal stimulus and multiplier effects that may result from these payments. We hope that our results inform the current debate about appropriate policy measures and next steps.

Incomeâ€Generating Activity: An Avenue to Improve the Sustainability of Shgs
Dhake, Saroj,NARKHEDE, Sameer P.
SSRN
Self‐help groups (SHGs) are formed to work for increased income through collective effort and use of banking facilities by initiating some income‐generating activities taking advantage of the financial strength of a group. Taking into consideration the significance of SHGs to economic growth, the present study analyzes and compares the management of the income‐generating activities of SHGs in rural and urban areas. It also explores the extent of resource mobilization through various income‐generating activities, and the constraints faced by the SHGs while undertaking these activities. It is an exploratory research in which a multi‐stage stratified cluster random sampling technique was used for the selection of SHGs. Data were collected at group level and member level through purposely developed interview schedules and focused group discussions. The study revealed that, because of various financial and marketing‐related problems occurring while initiating and conducting the activities, very few SHG members actually started new income‐generating activities. Testing of hypotheses indicated that SHGs do not fulfil all the requirements of income‐generating activities carried out by its members. An overall low to medium level of resource mobilization by a majority of the SHGs presented a poor picture of SHGs in generating resources for undertaking entrepreneurial activities.

Incomplete Contracts, Price, and Quality: Hedge Funds' Fees and Performance
Moszoro, Marian W.
SSRN
When sellers set the price for ex-ante unobservable and ex-post unenforceable quality, price signals credence quality. Hedge funds resemble incomplete long-term contracts for credence goods under buyer-determined auctions. I show that hedge funds' ability to solicit investments at higher management fees signals their capacity to generate higher net returns. This result is more pronounced during bust cycles and closer to financial hubs, i.e., when management quality signaling is more valuable.

Integrated Design of Unmanned Aerial Mobility Network: A Data-Driven Risk-Averse Approach
Wenjuan Hou,Tao Fang,Zhi Pei,Qiao-Chu He
arXiv

The real challenge in drone-logistics is to develop an economically-feasible Unmanned Aerial Mobility Network (UAMN). In this paper, we propose an integrated airport location (strategic decision) and routes planning (operational decision) optimization framework to minimize the total cost of the network, while guaranteeing flow constraints, capacity constraints, and electricity constraints. To facility expensive long-term infrastructure planning facing demand uncertainty, we develop a data-driven risk-averse two-stage stochastic optimization model based on the Wasserstein distance. We develop a reformulation technique which simplifies the worst-case expectation term in the original model, and obtain a fractable Min-Max solution procedure correspondingly. Using Lagrange multipliers, we successfully decompose decision variables and reduce the complexity of computation. To provide managerial insights, we design specific numerical examples. For example, we find that the optimal network configuration is affected by the "pooling effects" in channel capacities. A nice feature of our DRO framework is that the optimal network design is relatively robust under demand uncertainty. Interestingly, a candidate node without historical demand records can be chosen to locate an airport. We demonstrate the application of our model for a real medical resources transportation problem with our industry partner, collecting donated blood to a blood bank in Hangzhou, China.

Intellectual Capital, Bank Size, Bank Market Share, and Efficiency of Conventional Banks in Indonesia (Capital intelectual, tamaÃ±o del banco, participaciÃ³n en el mercado bancario y eficiencia de los bancos convencionales en Indonesia)
S.IP.,M.H, Rahmat
SSRN
English Abstract: This study aims to empirically examine the effect of intellectual capital, bank size, and market share on the efficiency of commercial banks in Indonesia from 2013 to 2017. The results of a panel data analysis of two models show that intellectual capital (calculated simultaneously or individually per component), bank size, and market share have a significant effect on bank efficiency, as confirmed by a fixed-effect regression model. Said model indicates that the year-to-year effect of the independent variables is influenced by individual bank differences. In other words, dissimilar characteristics of banksâ€™ intellectual capital and its components determine the effect of said variables on bank efficiency. Likewise, the asset ownership and market share of banks also distinguish their behavior in terms of bank efficiency.Spanish Abstract: Este trabajo tiene como objetivo estudiar empÃ­ricamente el efecto que el capital intelectual, el tamaÃ±o del banco y la participaciÃ³n en el mercado tuvieron sobre la eficiencia de los bancos comerciales en Indonesia entre 2013 y 2017. Los resultados de un anÃ¡lisis de datos de panel de dos modelos muestran que el capital intelectual (calculado de forma simultÃ¡nea o individual por componente), el tamaÃ±o del banco y la participaciÃ³n en el mercado tienen un efecto significativo en la eficiencia bancaria, lo cual confirmÃ³ un modelo (regresiÃ³n) de efectos fijos. Dicho modelo indica que la diferencia anual de las variables independientes estÃ¡ influenciada por las caracterÃ­sticas particulares de las instituciones bancarias. En otras palabras, las diferentes caracterÃ­sticas del capital intelectual de los bancos y sus componentes determinan el efecto de dichas variables en la eficiencia bancaria. Asimismo, los activos y participaciÃ³n en el mercado de los bancos distinguen su comportamiento en tÃ©rminos de eficiencia bancaria.

Is There Too Much Benchmarking in Asset Management?
Kashyap, Anil K.,Kovrijnykh, Natalia,Li, Jian,Pavlova, Anna
SSRN
We propose a model of asset management in which benchmarking arises endogenously, and analyze its unintended welfare consequences. Fund managers' portfolios are unobservable and they incur private costs in running them. Conditioning managers' compensation on a benchmark portfolio's performance partially protects them from risk, and thus gives them incentives to generate higher abnormal returns. In general equilibrium, these compensation contracts create an externality through their effect on asset prices. Benchmarking inflates asset prices and gives rise to crowded trades, thereby reducing the effectiveness of incentive contracts for others. Contracts chosen by fund investors diverge from socially optimal ones. A social planner, recognizing the crowding, opts for less benchmarking and less incentive provision. We also show that asset management costs are lower with socially optimal contracts, and the planner's benchmark-portfolio weights differ from the privately optimal ones.

Joint Modelling and Calibration of SPX and VIX by Optimal Transport
Guo, Ivan,Loeper, Gregoire,ObÅ‚Ã³j, Jan,Wang, Shiyi
SSRN
This paper addresses the joint calibration problem of SPX options and VIX options or futures. We show that the problem can be formulated as a semimartingale optimal transport problem under a finite number of discrete constraints, in the spirit of [arXiv:1906.06478]. We introduce a PDE formulation along with its dual counterpart. The optimal processes can then be represented via the solutions of Hamiltonâ€"Jacobiâ€"Bellman equations arising from the dual formulation. A numerical example shows that the model can be accurately calibrated to the SPX European options and the VIX futures simultaneously.

Language Sentiment in Fundamental and Noise Trading: Evidence from Crude Oil
Alfano, Simon,Feuerriegel, Stefan,Neumann, Dirk
SSRN
Recent research has found the language sentiment in financial news to be a substantial driver of prices in financial markets, though there are two diametrically opposed interpretations for this: either markets perceive news sentiment as fundamental information (thus leading to changes in the valuation of assets) or news sentiment conveys a noise signal (thus contributing to the stochastic component of prices). The opposite roles are resolved in the context of crude oil prices by decomposing price movements into two components referring to fundamental and noise trading. Contrary to theoretical arguments in prior literature, we find empirical results supporting both interpretations.

Mapping Coupled Time-series Onto Complex Network
Jamshid Ardalankia,Jafar Askari,Somaye Sheykhali,Emmanuel Haven,G. Reza Jafari
arXiv

For the sake of extracting hidden mutual and coupled information from possibly uncoupled time-series, we explored the profound measures of network science on time-series. Alongside common methods in time-series analysis of coupling between financial and economic markets, mapping coupled time-series onto networks is an outstanding measure to provide insight into hidden aspects embedded in couplings intrinsically. In this manner, we discretize the amplitude of coupled time-series and investigate relative simultaneous locations of the corresponding amplitudes (nodes). The transmissions between simultaneous amplitudes are clarified by edges in the network. In this sense, by segmenting magnitudes, the scaling features, volatilities' size and also the direction of the coupled amplitudes can be described. The frequency of occurrences of the coupled amplitudes is illustrated by the weighted edges, that is to say, some coupled amplitudes in the time-series can be identified as communities in the network. The results show that despite apparently uncoupled joint probabilities, the couplings possess some aspects which diverge from random Gaussian noise. Thereby, with the aid of the network's topological and statistical measurements, we distinguished basic structures of coupling of cross-market networks. Meanwhile, it was discovered that even two possibly known uncoupled markets may possess coupled patterns with each other. Thereby, those markets should be examined as coupled and weakly coupled markets!

Market Reactions to the Arrival and Containment of COVID-19: An Event Study
Heyden, Kim J.,Heyden, Thomas
SSRN
We study the short-term market reactions of US and European stocks during the beginning of the COVID-19 pandemic. Employing an event study, we document that stocks react significantly negative to the announcement of the first death in a given country. While our results suggest that the announcements of country-specific fiscal policy measures negatively affect stock returns, monetary policy measures have the potential to calm markets. These reactions are either intensified or lessened by firm-specific characteristics such as tangible assets, liquidity, and institutional holdings.

Non-Differentiable Learning of Quantum Circuit Born Machine with Genetic Algorithm
Kondratyev, Alexei
SSRN
The Quantum Circuit Born Machine (QCBM) is a generative quantum machine learning model that can be efficiently trained and run on the NISQ era quantum processors. QCBM has greater expressive power than comparable classical neural networks such as Restricted Boltzmann Machine (RBM) and, therefore, has potential to demonstrate quantum advantage by generating high quality samples from the learned empirical distribution while using less computational resources than its classical counterpart. However, efficient training of QCBM remains a challenging problem. Traditional differentiable learning approach may not work well when the loss function is highly non-smooth. In such cases it may be more efficient to use the non-differentiable learning methods. This paper proposes a non-differentiable learning approach to the training of QCBM based on Genetic Algorithm (GA). The paper also presents results of the numerical experiments which compare performance of QCBM trained with GA against performance of the equivalent classical RBM and investigates the question of GA convergence as a function of QCBM architecture and the choice of algorithmâ€™s hyperparameters.

Non-Performing Loans and Systemic Risk of Indian Banks
Dash, Mihir
SSRN
This study examines the role of non-performing loans in systemic risk for Indian banks using a fixed-effects panel regression model, with bank fixed effects and year fixed effects. The moderator variables considered for the study include bank size, capital adequacy, leverage, deposits, loans & advances, and investments. The study contributes to the literature by proposing the concept of maximum level of non-performing loans for neutral systemic risk, which is the level of net non-performing loans to net advances for which the systemic risk is non-positive. The results of the study indicate that bank size, capital adequacy, and loans & advances have a significant impact on the maximum level of non-performing loans for neutral systemic risk. Further, the results of the study suggest that the role of non-performing loans in systemic impact was different for public sector and private sector banks. The study suggests that the model can be used to set maximum levels of non-performing loans for individual banks with estimates or projections of the bankâ€™s characteristics.

Old and New Methods of Risk Measurements for Financial Stability Amid the Great Outbreak
SSRN
Increasing financial and political turmoil in the 1970s and 1980s coupled with oil shock prompted Governors of the G-10 countries to engage in cooperation and financial collaboration that eventually paved the road for the establishment of the Basel Committee on Banking Supervision in 1974. After over a decade of relentless work, the Basel Committee released Basel I Accord in July 1988 which had the primary objective of â€œInternational Convergence of Capital Measurement and Capital Standardsâ€. In the U.S., the savings and loan (S&L) crisis in the 1980s and the stock market crash of 1987 (Black Monday) resulted in the emergence of VaR model in risk management. The homegrown Asian crisis of 1997-98 forced the Basel Committee to introduce a Revised Framework commonly known as Basel II and prompted the International Monetary Fund and the World Bank to launch a joint Financial Sector Assessment Program (FSAP), the goal of which was â€œto gauge the stability and soundness of the financial sector and to assess its potential contribution to growth and developmentâ€. Stress testing became the mainstay when the Basel Committee required banks to use VaR and stress testing while calculating capital adequacy. With the subprime crisis and the ensuing unprecedented global financial crisis in 2007-08 gave birth to the use of macro stress testing as a crisis management tool. Farfetched implications of the GFC also triggered overhauling of Basel I and II, and overly hyped Basel III with higher capital and tighter liquidity regulation promised to strengthen the resilience of the global financial system as a whole. Unfortunately, none of these measures has made the global financial system any more stable; on the contrary, these reactionary steps have inflicted more instability. As the world is hit by the coronavirus pandemic, many are curiously waiting to see what measures and aid packages governments (the U.S. in particular) will rush to announce; however, as antecedents, just promising to give trillions of dollars to restore confidence will only make the rich get richer, but the unresolved issues (i.e. capitalism and dollar as its weapon) will cause even greater pandemics as well as economic and financial crises in the near future.

On the statistics of scaling exponents and the Multiscaling Value at Risk
Giuseppe Brandi,T. Di Matteo
arXiv

Scaling and multiscaling financial time series have been widely studied in the literature. The research on this topic is vast and still flourishing. One way to analyse the scaling properties of time series is through the estimation of scaling exponents. These exponents are recognized as being valuable measures to discriminate between random, persistent, and anti-persistent behaviours in time series. In the literature, several methods have been proposed to study the multiscaling property and in this paper we use the generalized Hurst exponent (GHE). On the base of this methodology, we propose a novel statistical procedure to robustly estimate and test the multiscaling property and we name it RNSGHE. This methodology, together with a combination of t-tests and F-tests to discriminated between real and spurious scaling. Moreover, we also introduce a new methodology to estimate the optimal aggregation time used in our methodology. We numerically validate our procedure on simulated time series using the Multifractal Random Walk (MRW) and then apply it to real financial data. We also present results for times series with and without anomalies and we compute the bias that such anomalies introduce in the measurement of the scaling exponents. Finally, we show how the use of proper scaling and multiscaling can ameliorate the estimation of risk measures such as Value at Risk (VaR). We also propose a methodology based on Monte Carlo simulation, that we name Multiscaling Value at Risk (MSVaR), which takes into account the statical properties of multiscaling time series. We show that by using this statistical procedure in combination with the robustly estimated multiscaling exponents, the one year forecasted MSVaR mimics the VaR on the annual data for the majority of the stocks analysed.

Optimal insurance contract with benefits in kind under adverse selection
Clémence Alasseur,Corinne Chaton,Emma Hubert
arXiv

An income loss can have a negative impact on households, forcing them to reduce their consumption of some staple goods. This can lead to health issues and, consequently, generate significant costs for society. We suggest that consumers can, to prevent these negative consequences, buy insurance to secure sufficient consumption of a staple good if they lose part of their income. We develop a two-period/two-good principal-agent problem with adverse selection and endogenous reservation utility to model insurance with in-kind benefits. This model allows us to obtain semi-explicit solutions for the insurance contract and is applied to the context of fuel poverty. For this application, our model allows to conclude that, even in the least efficient scenario from the households point of view, i.e., when the insurance is provided by a monopoly, this mechanism improves significantly the living conditions of the riskiest households by ensuring them a sufficient consumption of energy.

Optimal valuation of American callable credit default swaps under drawdown of L\'evy insurance risk process
Zbigniew Palmowski,Budhi Surya
arXiv

This paper discusses the valuation of credit default swaps, where default is announced when the reference asset price has gone below certain level from the last record maximum, also known as the high-water mark or drawdown. We assume that the protection buyer pays premium at fixed rate when the asset price is above a pre-specified level and continuously pays whenever the price increases. This payment scheme is in favour of the buyer as she only pays the premium when the market is in good condition for the protection against financial downturn. Under this framework, we look at an embedded option which gives the issuer an opportunity to call back the contract to a new one with reduced premium payment rate and slightly lower default coverage subject to paying a certain cost. We assume that the buyer is risk neutral investor trying to maximize the expected monetary value of the option over a class of stopping time. We discuss optimal solution to the stopping problem when the source of uncertainty of the asset price is modelled by L\'evy process with only downward jumps. Using recent development in excursion theory of L\'evy process, the results are given explicitly in terms of scale function of the L\'evy process. Furthermore, the value function of the stopping problem is shown to satisfy continuous and smooth pasting conditions regardless of regularity of the sample paths of the L\'evy process. Optimality and uniqueness of the solution are established using martingale approach for drawdown process and convexity of the scale function under Esscher transform of measure. Some numerical examples are discussed to illustrate the main results.

Order Book Dynamics in the Presence of Liquidity Fluctuations
Rojas, Helder,Yambartsev, Anatoly
SSRN
We propose a stochastic model for a limit order book with liquidity fluctuations. Our model shows how severe intermittencies in the liquidity can affect the order book dynamics. The law of large numbers (LLN), central limit theorem (CLT) and large deviations (LD) are proved for our model. Our results allow us to satisfactorily explain the volatility and local trends in the prices, relevant empirical characteristics that are observed in this type of markets. Furthermore, it shows us how these local trends and volatility are determined by the typical values of the bid-ask spread. In addition, we use our model to show how large deviations occur in the spread as a direct result of severe liquidity fluctuations.

Performance Ratios for Selecting International Portfolios: A Comparative Analysis Using Stock Market Indices in the Euro Area
SSRN
This paper compares the ability of alternate performance measures to support investment selection in ten euro area stock markets. The performance ratios used in the paper are grouped in two main categories. One category comprises the performance ratios using risk measures which do not separate systematic and non-systematic risk. The performance measures of this group are Sharpe ratio, Sortino ratio, Rachev ratio and STARR ratio. The other category comprises performance ratios based exclusively on systematic risk given by asset pricing models.The performance ratios of this category are the standard Treynor ratio based on CAPM betas, and two innovations of this ratio, mentioned in the paper by Treynord and Treynoru, based on the betas given by an asset pricing model, highlighted in this paper as Downside-Upside Risk Model (DURM), which estimates separate betas for downside and upside market returns. The empirical part of the paper consists of recursive portfolio selection based on each of the performance ratios mentioned above. The comparison of the ex post returns of the different portfolios shows that portfolios based on Sharpe, Sortino and STARR ratios offer better protection against losses in low return periods in the financial markets of the euro area , while Rachev ratio and Treynor, Treynord and Treynoru ratios are more able to take advantage from high return periods.

Political Connections of Russian Corporations: Blessing or Curse?
Trifonov, Dmitri
SSRN
This paper provides comprehensive empirical evidence on political connections of Russian corporations based on a sample of companies for the period 2011 â€" 2015, divided into subsamples before and after the events in Ukraine. Specifically, the study (1) evaluates how common political connections are for Russian corporate environment, and (2) investigates the impact of political connections on firm value through an event study. The research shows that 27% of Russian corporations from the sample had the top officials of Russia as directors, and 43% of corporations were found to be politically connected on the basis of either state ownership or directorship. Political connections are unevenly distributed among industries, and regulated industries are more heavily politicized. Aviation, oil & gas, and banking were the most politically connected sectors of the Russian economy. The event study analysis showed that political connections have a value-destructive total effect which is statistically significant and robust. Generally, the stock market responds to announcements of political connections with a drop in share prices by 1.34% on average within 5 trading days. Different groups of stakeholders exert different impacts on firm value. The most negative influence on firm valuation is that of politically connected owners. The stock market reacts to announcements of new politically connected owners with a drop in stock prices by 1.82% within 5 trading days, and with a drop in stock prices by 4.3% when the politically connected owners were individuals. The negative value effect of political connections strengthened after the events in Ukraine.

Predicting Cryptocurrency Returns Based on Economic Policy Uncertainty: A Multicountry Analysis Using Linear and Quantile-Based Models
SSRN
In this paper, we examine whether the economic policy uncertainty (EPU) index can predict the cryptocurrency returns for countries with the highest number of Bitcoin nodes, which include U.S., Germany, France, Netherlands, Singapore, Canada, the UK, China, Russia, and Japan. To the extent cryptocurrencies are a speculative asset, we expect that an increase in EPU drives the prices of cryptocurrencies below fundamental values due to the flight to quality and that they subsequently correct. Therefore, we hypothesis that EPU is a positive predictor of cryptocurrency returns. Furthermore, we expect that the positive predictability of EPU is stronger in the long run than the short run since mis-pricing takes time to correct. Using ordinary least squares, multivariate augmented regression, and quantile regression, we find that EPU positively predicts cryptocurrency returns in the short run for subsequent one-month returns. Moreover, we find stronger predictability of EPU for the subsequent returns over a longer horizon of 6- and 12-month than 1-month, which is again consistent with our hypothesis. Thus, cryptocurrencies cannot act as a hedge or safe haven against other financial assets during uncertain times.

RM-CVaR: Regularized Multiple $\beta$-CVaR Portfolio
Kei Nakagawa,Shuhei Noma,Masaya Abe
arXiv

The problem of finding the optimal portfolio for investors is called the portfolio optimization problem. Such problem mainly concerns the expectation and variability of return (i.e., mean and variance). Although the variance would be the most fundamental risk measure to be minimized, it has several drawbacks. Conditional Value-at-Risk (CVaR) is a relatively new risk measure that addresses some of the shortcomings of well-known variance-related risk measures, and because of its computational efficiencies, it has gained popularity. CVaR is defined as the expected value of the loss that occurs beyond a certain probability level ($\beta$). However, portfolio optimization problems that use CVaR as a risk measure are formulated with a single $\beta$ and may output significantly different portfolios depending on how the $\beta$ is selected. We confirm even small changes in $\beta$ can result in huge changes in the whole portfolio structure. In order to improve this problem, we propose RM-CVaR: Regularized Multiple $\beta$-CVaR Portfolio. We perform experiments on well-known benchmarks to evaluate the proposed portfolio. Compared with various portfolios, RM-CVaR demonstrates a superior performance of having both higher risk-adjusted returns and lower maximum drawdown.

Risk Appetite and Intermediation by Swap Dealers
Mixon, Scott,Onur, Esen
SSRN
We find that intermediary risk appetite plays an important role in the availability of dealer hedging services provided to real economy firms. We show that dealers intermediate the swap exposures of different clienteles and hedge some residual risk in the futures market. Using novel data on WTI crude oil swaps and futures positions of individual dealers, we present evidence that dealers hedgebespoke contracts with standard, liquid instruments and face basis risk. We conclude that the equilibrium quantity of basis risk taken, and therefore the amount of inter-mediation service available at a given price, is correlated with risk appetite.

Risk Disclosure and Cost of Equity: A Bayesian Approach (DivulgaciÃ³n de informaciÃ³n sobre riesgos y coste de los recursos propios: un enfoque bayesiano)
SSRN
English Abstract: This paper aims to analyze the relationship between risk information disclosure and the cost of equity of companies in the Spanish capital market. This study uses a set of 71 firms listed on Madrid stock exchange between 2010 and 2015; all of them are non-financial listed companies for which profit forecasts existed. The problem was analyzed using a Bayesian linear regression approach. The results show that cost of equity and disclosed risk information are not related if a global view of the latter is adopted. However, a positive relationship between financial risks and the cost of equity occurs when risk information is divided into financial and non-financial risks.Spanish Abstract: El objetivo de este artÃ­culo es analizar la relaciÃ³n entre la divulgaciÃ³n de informaciÃ³n sobre riesgo y el coste de capital de los recursos propios de empresas que cotizan en el mercado de capitales espaÃ±ol. Este estudio utiliza un conjunto de 71 empresas que cotizaron en la Bolsa de Madrid entre 2010 y 2015; todas son empresas no financieras de las que habÃ­a previsiones de beneficios. El problema se ha analizado bajo un enfoque de regresiÃ³n lineal Bayesiana. Los resultados del estudio muestran que el coste de capital de los recursos propios y la informaciÃ³n de riesgo divulgada no estÃ¡n relacionados cuando se toma la informaciÃ³n de riesgos de manera global. Sin embargo, cuando la informaciÃ³n de riesgo se divide en riesgos financieros y no financieros, se encuentra una relaciÃ³n positiva entre los riesgos financieros y el coste de capital de los recursos propios.

Ruin probability in a two-dimensional model with correlated Brownian motions
Peter Grandits,Maike Klein
arXiv

We consider two insurance companies with endowment processes given by Brownian motions with drift. The firms can collaborate by transfer payments in order to maximize the probability that none of them goes bankrupt. We show that pushing maximally the company with less endowment is the optimal strategy for the collaboration if the Brownian motions are correlated and the transfer rate can exceed the drift rates. Moreover, we obtain an explicit formula for the minimal ruin probability in case of perfectly positively correlated Brownian motions where we also allow for different diffusion coefficients.

The AI Economist: Improving Equality and Productivity with AI-Driven Tax Policies
Stephan Zheng,Alexander Trott,Sunil Srinivasa,Nikhil Naik,Melvin Gruesbeck,David C. Parkes,Richard Socher
arXiv

Tackling real-world socio-economic challenges requires designing and testing economic policies. However, this is hard in practice, due to a lack of appropriate (micro-level) economic data and limited opportunity to experiment. In this work, we train social planners that discover tax policies in dynamic economies that can effectively trade-off economic equality and productivity. We propose a two-level deep reinforcement learning approach to learn dynamic tax policies, based on economic simulations in which both agents and a government learn and adapt. Our data-driven approach does not make use of economic modeling assumptions, and learns from observational data alone. We make four main contributions. First, we present an economic simulation environment that features competitive pressures and market dynamics. We validate the simulation by showing that baseline tax systems perform in a way that is consistent with economic theory, including in regard to learned agent behaviors and specializations. Second, we show that AI-driven tax policies improve the trade-off between equality and productivity by 16% over baseline policies, including the prominent Saez tax framework. Third, we showcase several emergent features: AI-driven tax policies are qualitatively different from baselines, setting a higher top tax rate and higher net subsidies for low incomes. Moreover, AI-driven tax policies perform strongly in the face of emergent tax-gaming strategies learned by AI agents. Lastly, AI-driven tax policies are also effective when used in experiments with human participants. In experiments conducted on MTurk, an AI tax policy provides an equality-productivity trade-off that is similar to that provided by the Saez framework along with higher inverse-income weighted social welfare.

The Convergence of Sovereign ESG Ratings
SSRN
This paper studies sovereign ESG ratings from both qualitative and quantitative angles. First, we introduce the landscape for sovereign ESG ratings. Second, we provide a comparison with the history of credit ratings, factoring in that ESG ratings are in an early development stage. The third section reviews different actors, key issues, including taxonomy, models and data from different providers. Sovereign ESG ratings exhibit cross-sectional correlation. A noticeable contribution to the literature is that ESG scores contribute to explain credit default swap (CDS) spreads, as an additional variable to the average credit ratings. Finally, we provide a new factor attribution method, that maps all providers' ratings into a common taxonomy defined by the United Nations-supported Principles for Responsible Investment (UNPRI). The fourth section concludes.

The Effects of Targeting Predictors in a Random Forest Regression Model
Borup, Daniel,Christensen, Bent Jesper,MÃ¼hlbach, Nicolaj,Nielsen, Mikkel Slot
SSRN
The random forest regression (RF) has become an extremely popular tool to analyze high-dimensional data. Nonetheless, it has been argued that its benefits are lessened in sparse high-dimensional settings due to the presence of weak predictors and an initial dimension reduction (targeting) step prior to estimation is required. We show theoretically that, in high-dimensional settings with limited signal, proper targeting is an important complement to RFâ€™s feature sampling by controlling the probability of placing splits along strong predictors. This is supported by simulations with re-presentable finite samples. Moreover, we quantify the immediate gain from targeting in terms of increased strength of individual trees. Our conclusions are elaborated by a broad set of applications within macroeconomics and finance. These show that the inherent bias-variance trade-off implied by targeting, due to increased tree correlation, is balanced at a medium level, selecting the best 10â€"30% of commonly applied predictors. The applications consolidate that improvements from the targeted RF over the ordinary RF can be significant, particularly in long-horizon forecasting, and both in expansions and recessions.

The Efficiency of Stock Exchange Self-Regulation: Evidence from Stock Market Liquidity and Transparency
Kim, Jeong-Bon,Ma, Mark (Shuai),Yan, Wenjia
SSRN
This study examines whether and how stock exchange self-regulation affects stock market liquidity and corporate transparency. Using a large sample of firms from 46 stock exchanges from 2001 to 2015, we find significant and robust evidence that firms listed in self-regulated stock exchange are associated with fewer zero-return days, lower daily stock price variation, higher stock trading volume, smaller analyst forecast errors, lower discretionary accruals and less earnings management. These findings are more pronounced when the stock exchange has a strong self-regulation model rather than a limited self-regulation model. Also, our results are robust in different-in-difference tests based on the Australian Securities Exchangeâ€™s change from strong self-regulation model to a government regulation model. Further, when a firm from a country with a government-regulated stock exchange is cross-listed in a self-regulated stock exchange, the firm has higher liquidity and transparency than the matched firms. In addition, we find that self-regulated exchanges set more detailed insider trading and disclosure rules and are more transparent with their rules and rule enforcement. Overall, our study suggests that stock exchange self-regulation improves the efficiency of stock market regulation.

The Paradox of Startup Acquisitions: Eliminating Competition and Creating New Competitors
Kim, J. Daniel
SSRN
Existing research shows that incumbent firms frequently acquire high-tech startups in order to eliminate nascent competition, raising policy concerns around the anti-competitive effects of startup acquisitions. In this study, I document that high-tech startup acquisitions paradoxically lead to the creation of new competition. Leveraging employee-employer matched data from the US Census, I find that acquisitions significantly increase the target startupâ€™s rate of employee entrepreneurship, leading to the spawning of new competitors. Surprisingly, even in cases of withdrawn acquisitions, the mere announcement of an acquisition leads to an increase in employee entrepreneurship, though it is ultimately cancelled. To reconcile these empirical patterns, I explore a set of theoretical mechanisms by drawing on both the technology M&A and entrepreneurship literature. In particular, I find support for a novel mechanism to explain the link between acquisitions and employee entrepreneurship: workersâ€™ resentment towards their young employers â€œselling outâ€ to a bigger rival. Taken together, these results demonstrate that acquiring a high-tech startup can generate new competition by spurring the target employees to pursue their own ventures in the same space.

The Story of the Open Pension Funds and the Employee Capital Plans in Poland. Will It Succeed This Time?
Blaszczyk, Barbara
SSRN
Polandâ€™s new Employee Capital Plans (PPK) scheme, which is mandatory for employers, started to be implemented in July 2019. The article looks at the systemic solutions applied in the programme from the perspective of the concept of the simultaneous reconstruction of the retirement pension system. The aim is to present arguments for and against the project from the point of view of various actors, and to assess the chances of success for the new system. The article offers a detailed study of legal solutions, an analysis of the literature on the subject, and reports of institutions that supervise pension funds. The results of this analysis point to the lack of cohesion between certain solutions of the 1999 pension reform and expose a lack of consistency in how the reform was carried out, which led to the eventual removal of the capital part of the pension system. The study shows that additional saving for old age is advisable in the countryâ€™s current demographic situation and necessary for both economic and social reasons. However, the systemic solutions offered by the government appear to be chiefly designated to serve short-term state interests and do not create sufficient incentives for pension plan participants to join the programme.

Unveil stock correlation via a new tensor-based decomposition method
Giuseppe Brandi,Ruggero Gramatica,Tiziana Di Matteo
arXiv

Portfolio allocation and risk management make use of correlation matrices and heavily rely on the choice of a proper correlation matrix to be used. In this regard, one important question is related to the choice of the proper sample period to be used to estimate a stable correlation matrix. This paper addresses this question and proposes a new methodology to estimate the correlation matrix which doesn't depend on the chosen sample period. This new methodology is based on tensor factorization techniques. In particular, combining and normalizing factor components, we build a correlation matrix which shows emerging structural dependency properties not affected by the sample period. To retrieve the factor components, we propose a new tensor decomposition (which we name Slice-Diagonal Tensor (SDT) factorization) and compare it to the two most used tensor decompositions, the Tucker and the PARAFAC. We have that the new factorization is more parsimonious than the Tucker decomposition and more flexible than the PARAFAC. Moreover, this methodology applied to both simulated and empirical data shows results which are robust to two non-parametric tests, namely Kruskal-Wallis and Kolmogorov-Smirnov tests. Since the resulting correlation matrix features stability and emerging structural dependency properties, it can be used as alternative to other correlation matrices type of measures, including the Person correlation.

Venture Capital and Corporate Social Responsibility
Cheng, Cheng,Chu, Yongqiang,deng, zijie,Huang, Bo
SSRN
We examine the impact on venture capital (VC) involvement and monitoring on their portfolio companies' corporate social responsibility (CSR) performance. Exploiting the timing of VC exit, we find that CSR performance of VC-backed companies improves after the exit of VC. Using the age of VC funds as an instrument for VC exit, we find that the effect is likely to be causal. We also find that portfolio firms' CSR performance declines after the introduction of direct high speed rail services between VC firms and their portfolio companies. Further analyses suggest that the effect is largely driven by inexperienced, bad performing, and less reputable VCs.

Wealth distribution under the spread of infectious diseases
G. Dimarco,L. Pareschi,G. Toscani,M. Zanella
arXiv

We develop a mathematical framework to study the economic impact of infectious diseases by integrating epidemiological dynamics with a kinetic model of wealth exchange. The multi-agent description leads to study the evolution over time of a system of kinetic equations for the wealth densities of susceptible, infectious and recovered individuals, whose proportions are driven by a classical compartmental model in epidemiology. Explicit calculations show that the spread of the disease seriously affects the distribution of wealth, which, unlike the situation in the absence of epidemics, can converge towards a stationary state with a bimodal form. Furthermore, simulations confirm the ability of the model to describe different phenomena characteristics of economic trends in situations compromised by the rapid spread of an epidemic, such as the unequal impact on the various wealth classes and the risk of a shrinking middle class.

Women on Bank Boards and Risk-Taking: A Cross-Countries Analysis on the Moderating Role of Masculinity
Gallucci, Carmen,Santulli, Rosalia,Tipaldi, Riccardo
SSRN
This study examines the effects of board gender diversity on a bankâ€™s risk by applying a moderate multiple regression analysis on a dataset covering the years 2008-2017 and comprising 110 banks from Germany, Italy, Spain, and Switzerland. Masculinity, a country-level cultural dimension incorporating the behavioural expectations surrounding men and women in a society, is used as a moderator. Results suggest that high country-level masculinity stresses the risk-aversion of a bankâ€™s women directors, therefore compromising financial performance. To mitigate the negative effects of high country-level masculinity, this paper provides several suggestions. First, banks should change their stereotypical depiction of the â€œideal workerâ€. Second, banks should question the cultural motives underpinning the entrance of women directors in the â€œboyâ€™s clubâ€. Last, banks should create a more egalitarian workplace where the distribution of rewards does not strengthen the privileges of the established elites.