Research articles for the 2021-01-27
arXiv
In chaotic modern society, there is an increasing demand for the realization of true 'fairness'. In Greek mythology, Themis, the 'goddess of justice', has a sword in her right hand to protect society from vices, and a 'balance of judgment' in her left hand that measures good and evil. In this study, we propose a fair distribution method 'utilising physics' for the profit in games of characteristic function form. Specifically, we show that the linear programming problem for calculating 'nucleolus' can be efficiently solved by considering it as a physical system in which gravity works. In addition to being able to significantly reduce computational complexity thereby, we believe that this system could have flexibility necessary to respond to real-time changes in the parameter.
SSRN
Risk represents a significant part of humans' interaction and has to be considered in various decision-making processes across diverse business and research areas. Furthermore, the disregard or non-awareness of certain risks may result in inappropriate decision-making processes and inadequate risk management practices which may negatively influence firms' performances. Thus, to the best of our knowledge, this paper is the first to develop an algorithmic-based and generally applicable framework that generates an extensive and integrated identification and categorization scheme of certain risks, using text mining and machine learning approaches. To demonstrate the applicability of our framework, we exemplarily apply our derived approach to the context of financial markets. Hence, we identify 193 financial market risks and categorize them into five categories by using common machine learning techniques. To evaluate the general applicability, we additionally apply the derived framework to the context of information systems. Finally, we give strong indications regarding robustness and superiority of our derived framework by benchmarking it against more manual risk identification techniques and other clustering approaches.
SSRN
In this study, I investigate the impact of heterogeneity in financial frictions across the Eurozone on bank balance sheet dynamics and the bank-lending channel of monetary policy. Using country-level bank balance sheet data, I estimate financial frictions in a two-country, monetary union New Keynesian model with banks. The results indicate that financial frictions in core countries are significantly smaller than peripheral countries in the Eurozone. Given this financial heterogeneity, my model predicts that (1) financial shocks cause more severe recessions in peripheral countries than in core countries, and (2) the bank-lending channel has a weaker stimulus effect in peripheral countries. In light of financial heterogeneities, these research findings have important policy implications for the single monetary authority in the Eurozone. By implementing simulations, I find that asset purchase policies, particularly region-specific asset purchases, can complement the bank-lending channel's unequal outcomes inside a region.
SSRN
Chains of the CME Group Time and Sales E-mini S&P 500 futures tick prices and their a-b-c-d-increments are studied. A discrete probability distribution based on the Hurwitz Zeta function and Dirichlet series is suggested for the price increments. The randomness of the ticks is discussed using the notions of typicalness, chaoticness, stochasticness introduced by Kolmogorov and Uspenskii, and developed by predecessors, them, and pupils. They define randomness in terms of the theory of algorithms.
SSRN
States are increasingly mandating financial literacy education as a high school graduation requirement. However, most states already include economics education as part of their curriculum, and it is unclear whether financial literacy education and economics education differ. We examine the returns to financial literacy education and compare the gains in financial knowledge to those acquired in economics courses. Using observational data (n=127) and difference-in-difference methodology we test for differences in returns across courses at the college level. We find that both financial literacy courses and economics courses increase financial knowledge. We also find no evidence that financial literacy courses increase understanding of financial literacy concepts at a higher rate than economics courses. We disaggregate financial knowledge into six areas of financial understanding as defined by the Test of Financial Literacy. We find the returns to financial literacy education are higher than economics courses in five categories, however these findings are driven mostly by observable differences between the financial literacy and economics students. We also find the returns to financial literacy education are higher for female students, even when controlling for observables. Female students experience a gain of 0.8 standard deviations in the Test of Financial Literacy, when enrolled in financial literacy courses relative to economics courses, providing evidence that financial literacy education is better at narrowing the gender financial literacy gap. Our results are important to policymakers introducing financial literacy education mandates and to school administrators determining implementation.
SSRN
We revisit the asymmetric timeliness of earnings as proposed by Basu (1997). For a large sample of US firm years from 1970-2019, we show that earnings are asymmetrically timely with respect to bad economic news, and that this is robust to the declining timeliness of good news, different time periods, changes in accounting standards and changes in sample firms. When we disaggregate earnings into its market, industry and firm idiosyncratic sources, it is apparent that asymmetrical timeliness is restricted to the idiosyncratic component. This result supports the argument in Watts (2003), that asymmetric timeliness is primarily a response to information asymmetry issues in contracts that rely on accounting information.
SSRN
With the pandemic caused by the novel coronavirus SARS-CoV-2 raging around the world, many countries’ economies are at a crucial juncture. The COVID-19 external shock to the economy has the potential to affect corporate governance profoundly. This article explores its possible impact on comparative corporate governance. For an economy to operate successfully, a society must first find a politically sustainable social equilibrium. In many countries, historical crises â€" such as the Great Depression and World War II â€" have resulted in a reconfiguration of corporate governance institutions that set the course for generations. While it is not yet clear whether COVID-19 will have a similar effect, it is possible that it will change patterns of what kind of firms are â€" from an evolutionary perspective â€" likely to survive, and which ones are not. We argue that to some extent, it will accelerate ongoing trends, whereas in other areas it put corporations on an entirely new course. We observe three trends, namely the need for resilience, a growth of nationalist policies in corporate law, and an increasing orientation toward ‘stakeholder’ interests. First, firms will have to become resilient to the crisis, and consequently long-term oriented. Corporations that are not operating merely on an arm’s length capital market basis but are integrated into a network, generated by core shareholders, state ownership or bank lending may be more likely to survive. In addition, firms are beginning to interact with their workforce differently in their attempts to maintain what could be called ‘healthy human capital.’ Second, we are likely to see a resurgence of nationalism in corporate governance to ensure that foreign ownership and interconnected supply chains do not put national security at risk. Third, the existing critiques of inequality but also climate change awareness will accelerate the trend toward a broadening of corporate purpose toward ‘stakeholderism’ and public policy issues. As in the past years, institutional investors acting as ‘universal owners’ will play a role in shaping this trend.
SSRN
We develop and present a new methodology to detect regime changes within a sequence of sparse networks that have overlapping and evolving community structure. The core of the methodology is a non-negative matrix factorization that maximizes a Poisson likelihood subject to a penalty that accounts for sparsity in the network. By fitting the factorization model over a rolling window with a fast numerical optimization algorithm, change detection is accomplished by statistical monitoring of the matrix factors' evolution. Using synthetic and real financial interbank lending networks, we demonstrate that the proposed methodology compares favorably with alternative techniques for on-the-go network change detection.
SSRN
We outline a framework in which accounting “valuation anchors" could be connected to expected stock returns. Under two general conditions, expected log returns is a log- linear function of a valuation (market value-to-accounting) multiple and the expected growth in the valuation anchor. We show that the framework can: 1) allow for expected enterprise returns, 2) correct for the use of stale accounting data in estimation, and 3) accommodate differences in information quality. This analytical formulation is tractable and flexible, and provides building blocks for further innovations in accounting valuation research.
SSRN
Different ETS allowance distribution method may vary the effeteness of the ETS on the regulated firm’s performance. This paper uses the Propensity Score Matching Difference-in-Differences method found that the China ETS could increase its regulated firm competitiveness from different aspects. Furthermore, we have tested the impact of the carbon price and its volatility on firm financial performance. Different from the traditional view on the impact of the carbon price, this paper has found that growing the carbon price would benefit regulated firm financial performance, but higher volatility is harmful to the performance.
arXiv
This paper describes a study designed to investigate the current and emergent impacts of Covid-19 and Brexit on UK horticultural businesses. Various characteristics of UK horticultural production, notably labour reliance and import dependence, make it an important sector for policymakers concerned to understand the effects of these disruptive events as we move from 2020 into 2021. The study design prioritised timeliness, using a rapid survey to gather information from a relatively small (n = 19) but indicative group of producers. The main novelty of the results is to suggest that a very substantial majority of producers either plan to scale back production in 2021 (47%) or have been unable to make plans for 2021 because of uncertainty (37%). The results also add to broader evidence that the sector has experienced profound labour supply challenges, with implications for labour cost and quality. The study discusses the implications of these insights from producers in terms of productivity and automation, as well as in terms of broader economic implications. Although automation is generally recognised as the long-term future for the industry (89%), it appeared in the study as the second most referred short-term option (32%) only after changes to labour schemes and policies (58%). Currently, automation plays a limited role in contributing to the UK's horticultural workforce shortage due to economic and socio-political uncertainties. The conclusion highlights policy recommendations and future investigative intentions, as well as suggesting methodological and other discussion points for the research community.
SSRN
We propose a new pseudo-Siamese Network for Asset Pricing (SNAP) model, based on deep learning approaches, for conditional asset pricing. Our model allows for the deep alpha, deep beta and deep factor risk premia conditional on high dimensional observable information of financial characteristics and macroeconomic states, while storing the long-term dependency of the informative features through long short-term memory network. We apply this method to monthly U.S. stock returns from 1970-2019 and find that our pseudo-SNAP model outperforms the benchmark approaches in terms of out-of-sample prediction and out-of-sample Sharpe ratio. In addition, we also apply our method to calculate deep mispricing errors which we use to construct an arbitrage portfolio K-Means clustering. We find that the arbitrage portfolio has significant alphas.
SSRN
This study investigates the corporate governance determinants of environmental investment in European firms. Using a sample of firms listed on the Bloomberg European Index 500 from 2001 to 2015, this study finds that firms with more independent directors, and female directors, are likely to invest more in the environment. It also finds that environmental investment is likely to be higher in firms with an environmental sub-committee of the board. Finally, this study documents that firms with CEO bonus plans linked to environmental compliance/performance are likely to incur higher environmental investment. The findings are robust to several alternative measures and methods. The findings of this study made a significant contribution to the environmental investment literature by adopting a quantifiable and non-biased monetary measure of environmental investment. Moreover, this study contributes to the literature by providing generalizable empirical evidence for a significantly positive association between a range of corporate governance characteristics and the level of environmental investment. Therefore, the findings of this study have practical implications to institutional investors.
SSRN
We document that equities indices spill over to currencies: cross-sectional momentum signals based on equities returns can help building investment strategies in the currencies space. Like momentum, this spillover effect tends to works better for short / mid term lookback periods, but spillover does not seem to be only a momentum phenomenon. Spillover is also robust to signals and portfolio construction modifications.
SSRN
Using individual level credit information, I estimate the impact of access to ride-sharing on student debt repayment and take-up. I find that following the introduction of ride-sharing services in a city, individuals decrease their student debt balance and probability of default. These results are primarily driven by former students, who are 0.4pp more likely to finish repaying their student loans and are 0.8pp less likely to default in their student debt in the three years after ride-sharing arrives. This effect is absent for current students. For potential students, I find that access to ride-sharing increases the likelihood of getting a first student loan by 0.5pp. This suggests that there is a willingness to attend higher education that is not met given the structure of the current labor market, and that having access to the gig-economy is allowing individuals that would otherwise chosen not to enroll to do so. Taken together, results suggest that access to the flexible work improves student loan repayment rates, while simultaneously fostering enrollment.
SSRN
This paper examines earnings management around the reduction in the corporate tax rate from 35% to 21% as enacted by the ‘Tax Cuts and Jobs Act’ (TCJA) of 2017. Building on a theoretical model that considers a higher level of book-tax conformity of ‘real earnings management’ (REM) in relation to ‘accrual-based earnings management’ (AEM), we hypothesize that firms concertedly use these manipulation techniques for different purposes. Specifically, we predict and find that firms engage in REM to shift income from the high-tax period prior to the TCJA to the low-tax period after of the TCJA to realize tax benefits. In contrast, we predict and find that firms use AEM, which has a lower degree of book-tax conformity, to simultaneously increase book income. Consistent with intertemporal income shifting, we also find that these effects reverse in 2018. Overall, our results document a potential unintended consequence of the TCJA on firm behavior that should be useful to policymakers, regulators, and researchers to evaluate the largest tax reform since 1986.
SSRN
We study how the involvement of families in ownership and governance positions affects the stock-market and accounting performance of Italian listed firms during the COVID-19 pandemic. We find that firms with controlling family shareholders fared significantly better than other firms throughout the pandemic period. This effect is particularly pronounced for firms in which a family is both the controlling shareholder and holds the CEO position. Delving into the mechanisms, we further show that family firms primarily outperformed in labor-intensive industries. Collectively, our results expand a growing research on the organizational response to adverse events.
SSRN
This chapter is to provide an overview of financial literacy in Asia, describe financial literacy education in Asian countries, and propose recommendations for policy makers. The chapter demonstrates that: 1) Financial literacy is an important factor contributing to consumer financial capability and wellbeing in Asia; 2) Financial literacy national strategies and education programs in Asian countries are beneficial for consumer wellbeing and economic developments; and 3) Public policies promoting financial literacy education can be compatible with the socio-economic development goals of Asian countries.
SSRN
This study investigates whether and how financial technologies (FinTech) influence the effectiveness of monetary policy transmission. We examine regional-level FinTech adoption and use an interacted panel vector autoregression model to explore how the effects of monetary policy shocks change with FinTech adoption. The results indicate that FinTech adoption generally enhances monetary policy transmission to real GDP, bank loans, and housing prices, while the evidence of transmission to consumer prices is mixed. A subcategorical analysis shows that the enhanced effectiveness is the most pronounced in the adoption of FinTech payment, compared to that of insurance and credit.
arXiv
Scale-up is the process of growing a venture in size. The paper identifies modularity and speed as keys to successful scale-up. On that basis four types of scale-up are identified: Smart, dumb, forced, and fumbled. Smart scale-up combines modularity and speed. Dumb scale-up is bespoke and slow, and very common. The paper presents examples of each type of scale-up, explaining why they were successful or not. Whether you are a small startup or Elon Musk trying to grow Tesla and SpaceX or Jeff Bezos scaling up Amazon - or you are the US, UK, Chinese, or other government trying to increase power production, expand your infrastructure, or make your health, education, and social services work better - modularity and speed are the answer to effective delivery, or so the paper argues. How well you deal with modularity and speed decides whether your efforts succeed or fail. Most ventures, existing or planned, are neither fully smart nor fully dumb, but have elements of both. Successful organizations work to tip the balance towards smart by (a) introducing elements of smart scale-up into existing ventures and (b) starting new, fully smart-scaled ventures, to make themselves less dumb and ever smarter.
arXiv
The transfer of tasks with sometimes far-reaching moral implications to autonomous systems raises a number of ethical questions. In addition to fundamental questions about the moral agency of these systems, behavioral issues arise. This article focuses on the responsibility of agents who decide on our behalf. We investigate the empirically accessible question of whether the production of moral outcomes by an agent is systematically judged differently when the agent is artificial and not human. The results of a laboratory experiment suggest that decision-makers can actually rid themselves of guilt more easily by delegating to machines than by delegating to other people. Our results imply that the availability of artificial agents could provide stronger incentives for decision makers to delegate morally sensitive decisions.
SSRN
The disposition effect has been widely studied in academia, while the reverse disposition effect observed in mutual funds has gained relatively little attention. This study examines the reverse disposition effect in detail by using policy-level data from a Finnish life insurer with a considerable sample size. The results show that the Finnish savings policies with a positive return have a surrender rate that is over 30 percent lower than that of policies with a negative return. Tax incentives and expected future returns do not seem to cause this reverse disposition effect directly. Salient information strengthens the reverse disposition effect, and higher policyholder age and surrender fees weaken it. These empirical findings deepen the understanding of the reverse disposition effect.
SSRN
Recent changes in Australian legislation that limit the value of how artworks that can be considered as assets in retirement funds have had an impact on the Australian Aboriginal Art market. In this paper we estimate the impact of these changes on the price index based on prices paid for 15,845 works by over 200 artists at art auctions from 1986 to 2019.Using an OLS and a quantile regression approach, we estimate hedonic price models for various segments of the Australian Aboriginal art market. These models are used to estimate price indices in order to investigate if the changes in Australian laws concerning the sale and use of art assets has influenced the potential returns for different segments of the market.
SSRN
According to the Bank Lending Survey, during 2020 Q4, both in Spain and in the euro area there was a slight contraction in the credit supply, linked to banks’ higher risk perceptions, against a background of a worsening economic outlook, which was also reflected in lower demand for loans. These trends were recorded in most of the segments analysed. In a similar vein, according to the banks responding, the NPL ratio contributed in both areas to a slight tightening of credit standards in loans to firms and consumer credit and other lending to households. In 2020 H1, credit standards and the terms and conditions on loans with government guarantees eased considerably in both areas, while a contraction was observed in the supply of loans without guarantees in the same period. Furthermore, applications for loans with guarantees rose robustly between January and June, both in Spain and in the euro area, owing to firms’ higher liquidity needs in those months and the need to build up precautionary liquidity buffers, while the demand for loans without guarantees dropped significantly.
SSRN
We exploit the unexpected and sizeable corporate credit line drawdowns in the early phase of the COVID-19 pandemic as a bank balance sheet shock and examine the impact on banks’ lending decisions. We show that banks with larger ex-ante credit line portfolios---and hence higher risk of drawdowns---reported tightening lending standards on new C&I loans to small and large firms, curtailed the supply of large syndicated loans, and reduced the number and volume of small business loans since March 2020. Exposed banks were also less likely to participate in and grant loans through government credit-subsidy programs such as the Paycheck Protection Program and the Main Street Lending Program. We document that the main mechanism by which the risk of credit line drawdowns likely affected banks' lending decisions was a reduction of risk tolerance rather than balance sheet constraints. Our findings suggest that tension may arise between banks providing liquidity insurance to firms through pre-committed credit lines while at the same time sustaining loan supply to the broader economy during crises, with important implications for monetary policy and financial stability policies.
SSRN
We study whether firm managers’ physical appearance affects their decisions on corporate philanthropy. Examining a large sample of corporate donations matched with managers’ attractiveness data, we find that male managers’ motivations for philanthropic giving are driven by their physical attractiveness. In contrast to managers with average looks, attractive managers do not engage more actively in corporate philanthropy; however, unattractive managers are more inclined to participate in charitable giving and contribute a greater amount. Further, the impact of managers’ unattractiveness on their philanthropic decisions is stronger in firms with lower market capitalization, lower managerial compensation, and weaker corporate governance. Inspired by the research in psychology, we propose two psychological channels through which physical attractiveness may influence a manager’s philanthropic decisions. First, corporate executives with undesirable looks may perceive themselves as belonging to a relatively lower social class, which is associated with a greater motivation for conducting philanthropy. Second, because altruistic behaviors may characteristically aggrandize individuals and concretely enhance their performance evaluations, unattractive managers are motivated to contribute to charity to assail the sense of inferiority due to their undesirable appearance. Together, out findings demonstrate a significant link between individuals’ attractiveness features and philanthropic motivations as well as agency problems behind managers’ ostensibly prosocial behaviors that satisfy their self-interest and personal needs.
SSRN
This paper develops a dynamic model to study optimal liquidity regulations for multiple assets that differ in liquidity. I show that optimal macroprudential policies are affected by asset liquidity and the multi-asset structure. Lower asset liquidity amplifies declines in asset prices and tightens the collateral constraint during financial crises, raising macroprudential taxes on debt. With multiple assets, the marginal benefit of investing in one asset is affected by cross-price elasticities of all assets, depending on trading positions and the collateral constraint's tightness. The optimal policy in the multi-asset model can differ from those in standard one-asset models in size and sign. Quantitatively, optimal macroprudential policies favor liquid assets and reduce borrowing. The policy reduces the probability of financial crises from 8% to zero and increases welfare by 1.2%. Finally, I analyze and quantify the current Basel III reform, which increases agents' liquid holdings and decreases the probability of crises. However, the policy reduces welfare, as agents overborrow and overinvest in liquid assets.
arXiv
Surrender poses one of the major risks to life insurance and a sound modeling of its true probability has direct implication on the risk capital demanded by the Solvency II directive. We add to the existing literature by performing extensive experiments that present highly practical results for various modeling approaches, including XGBoost and neural networks. Further, we detect shortcomings of prevalent model assessments, which are in essence based on a confusion matrix. Our results indicate that accurate label predictions and a sound modeling of the true probability can be opposing objectives. We illustrate this with the example of resampling. While resampling is capable of improving label prediction in rare event settings, such as surrender, and thus is commonly applied, we show theoretically and numerically that models trained on resampled data predict significantly biased event probabilities. Following a probabilistic perspective on surrender, we further propose time-dependent confidence bands on predicted mean surrender rates as a complementary assessment and demonstrate its benefit. This evaluation takes a very practical, going concern perspective, which respects that the composition of a portfolio might change over time.
arXiv
This paper studies pure bundling. Specifically, I show that, under some conditions, a firm optimally chooses to sell only the full bundle of a given set of products if and only if the optimal sales volume of the full bundle is weakly larger than the optimal sales volume for any smaller bundle. I argue that this characterization can be interpreted as follows: pure bundling is sub-optimal when there is considerable variation across consumers in how complementary they find disjoint sub-bundles, and/or when this variation correlates negatively with their price sensitivity. I then demonstrate--using simulated data and a random-coefficient discrete choice demand model--that capturing these two variations is indeed crucial for model selection in the empirical analysis of bundling decisions.
SSRN
Insurers and pension funds face the challenges of historically low interest rates and volatility in equity markets, that have been accentuated due to the COVID-19 pandemic. Recent advances in equity portfolio management with a target volatility have been shown to deliver improved on average risk adjusted return, after transaction costs. This paper studies these targeted volatility portfolios in applications to equity, balanced and target-date funds with varying constraints on leverage. Conservative leverage constraints are particularly relevant to pension funds and insurance companies, with more aggressive leverage levels appropriate for alternative investments. We show substantial improvements in fund performance for differing leverage levels and that the return per unit of risk is not significantly impacted by the leverage constraint. Of most interest to insurers and pensions funds, we show that the highest return per unit of risk is in targeted volatility balanced portfolios with equity and bond allocations. Furthermore, we demonstrate the outperformance of targeted volatility portfolios during major stock market crashes, including the crash from the COVID-19 pandemic.
SSRN
We examine the effect of auditor conservatism on corporate innovation. We hypothesize that, because conservative auditors constrain income-increasing accounting discretion, managers may sacrifice long-term investments in innovation to boost current earnings and meet short-term performance targets. Exploiting state-level auditor legal liability shocks as a means of identification, we find evidence consistent with this hypothesis. Cross-sectional analyses reveal that the negative effect of increased auditor conservatism on corporate innovation is more pronounced when the client firms are under greater equity- and debt-market pressures, when the client firms are exposed to greater litigation risk, and when the client firms are audited by large auditors. Our study highlights how auditors, as external monitors, can affect not only the financial reporting quality of their clients but may also induce alterations in their real operations.
SSRN
Previous research has found that high-frequency traders will vary the bid or offer price rapidly over periods of milliseconds. This is a benefit to fast traders who can time their trades with microsecond precision, however it is a cost to the average market participant due to increased trade execution price uncertainty. In this analysis we attempt to construct real-time methods for determining whether the liquidity of a security is being altered rapidly. We find a four-state Markov switching model identifies a state where liquidity is being rapidly varied about a mean value. This state can be used to generate a signal to delay market participant orders until the price volatility subsides. Over our sample, the signal would delay orders, in aggregate, over 0 to 10% of the trading day. Each individual delay would only last tens of milliseconds, and so would not be noticable by the average market participant.
arXiv
This paper proposes the sample path generation method for the stochastic volatility version of CGMY process. We present the Monte-Carlo method for European and American option pricing with the sample path generation and calibrate model parameters to the American style S\&P 100 index options market, using the least square regression method. Moreover, we discuss path-dependent options such as Asian and Barrier options.
arXiv
A market consisting of a generator with thermal and renewable generation capability, a set of non-preemptive loads (i.e., loads which cannot be interrupted once started), and an independent system operator (ISO) is considered. Loads are characterized by durations, power demand rates and utility for receiving service, as well as disutility functions giving preferences for time slots in which service is preferred. Given this information, along with the generator's thermal generation cost function and forecast renewable generation, the social planner solves a mixed integer program to determine a load activation schedule which maximizes social welfare. Assuming price taking behavior, we develop a competitive equilibrium concept based on a relaxed version of the social planner's problem which includes prices for consumption and incentives for flexibility, and allows for probabilistic allocation of power to loads. Considering each load as representative of a population of identical loads with scaled characteristics, we demonstrate that the relaxed social planner's problem gives an exact solution to the original mixed integer problem in the large population limit, and give a market mechanism for implementing the competitive equilibrium. Finally, we evaluate via case study the benefit of incorporating load flexibility information into power consumption and generation scheduling in terms of proportion of loads served and overall social welfare.
SSRN
Economic theory suggests that the presence of uninsurable and unavoidable background risks influences household portfolio choices. Households face significant location-specific background risks due to sea level rise (SLR). Using detailed local variation in SLR exposure and disaggregated geographic information on households in the United States, I show that SLR exposed homeowners are less likely to participate in the stock market and invest a smaller share of their financial wealth in risky assets, compared to unexposed homeowners in the same neighborhood. Differences in risk preferences and endogenous location choices are unable to explain this effect. Using plausibly exogenous variation stemming from the adoption of state-level climate change adaptation plans that reduced households' SLR risks, I provide causal evidence of the effect of SLR risks on portfolio allocation decisions. Following the adoption of such climate adaptation plans, SLR exposed households increase their stock market participation and hold a larger risky share in their financial wealth.
RePEC
Consider a Örm owned by shareholders with heterogeneous beliefs and discount rates who delegate to a manager the choice of a production plan. The shareholders and the manager can trade contingent claims in a complete asset market. Shareholders cannot observe the chosen production plan and design a compensation scheme so that at equilibrium the manager chooses the plan they prefer and reveals it truthfully. We show that at equilibrium i) proÖt is maximized, ii) the manager gets a constant share of production, iii) she has no incentive to trade. We then show that such equilibrium exists if and only if the manager has the same belief and discount rate as the representative shareholder. This allows us to characterize the required characteristics of the manager as a function of shareholdersí characteristics.
SSRN
Purpose â€" The purpose of this paper is to assess perception of the stakeholders about Islamic banking and find out approaches to make it closer to the Shari’ah. Methodology â€" The paper adopts direct survey approach to find out perception of stakeholders about the Islamic banking. The survey results have been evaluated using Ordinary Least Square method. Findings â€" The paper reveals that respondents have negative perception about the present form of Islamic banking due to multiple similarities in conventional and Islamic banking products and operations. The respondents supported the idea of different model of Islamic banking. Research limitations â€" The study relies solely on the opinion of limited number of respondents, living in few major cities of Pakistan. It does not provide any empirical evidence for the proposed model of Islamic banking. Practical Implications â€" Riba is significantly condemned and prohibited in Islam. Therefore, avoiding riba in all business transactions is very important for our faith. Islamic world has started practicing banking under the branding of Islam which has approval of a large group of Islamic scholars but still there is no consensus. This paper helps in addressing perception issues and suggests a future direction of Islamic banking for the regulators. Originality â€" Many researchers have questioned the Shariah compliance and perception issues of Islamic Banking but most of them have suggested only awareness programs. This research proposes a new model for Islamic banking which has not been witnessed in any other research.
SSRN
How does social capital affect trust? Evidence from a Chinese peer-to-peer lending platform shows regional social capital affects the trustee’s trustworthiness and the trustor’s trust propensity. Ceteris paribus, borrowers from higher social capital regions receive larger bid from individual lenders, have higher funding success, larger loan size, and lower default rates, especially for low-quality borrowers. Lenders from higher social capital regions take higher risks and have higher default rates, especially for inexperienced lenders. Cross-regional transactions are most (least) likely to be realized between parties from high (low) social capital regions.
SSRN
This study examines the impact of staggered boards, poison pills, and unequal voting rights on corporate innovation intensity using a sample of listed firms in six Asian countries from 2010-2017. We analyze the differential effects of antitakeover provisions using the high order fixed effects panel data model that controls for firm fixed effects, industry-year fixed effects, and country-year fixed effects. The propensity score-matched sample is used to deal with possible endogeneity issues. This paper shows that adopting staggered boards impede R&D investments while unequal voting rights and poison pills pose no influence on long term R&D investments. We also find that a combination of staggered boards and poison pill provisions discourage innovation. We find that the effect of staggered boards on R&D investment is more pronounced in old firms, large firms, firms with poor corporate governance, opaque firms, less indebted firms, and firms with more cash holdings. Our study evidence supports that poison pill provisions have no effect on their own, but a combination of a staggered board and a poison pill provision contributes to managerial entrenchment.
SSRN
We examine the impact of CEO-related sexual misconduct on U.S. firms’ stock market value in the #MeToo era. Our findings suggest that investors react negatively to corporate sexual misconduct, meaning that misbehaving CEOs cause significant damage to their shareholders’ wealth. On average, firms lose $2.23 billion when sexual misconduct is uncovered, which corresponds to a total value loss of $42.42 billion in equity market value. CEO-related sexual misconduct is more likely to occur in firms with lower profitability than their direct competitors. Additionally, firms that are larger and have more debt than their industry average are more inclined to employ misbehaving CEOs. Furthermore, CEOs who are accused of sexual misconduct are employed for a shorter period of time.
SSRN
We examine the evolution and factors of systemic risk in the Chinese banking sector over the last decade from the perspective of international investors. We apply the SRISK measure of systemic risk to a representative sample of listed Chinese institutions that captures 50-60% of total banking assets and utilize the Granger-causality network-based approach to demonstrate interlinkages among Chinese banks beyond the largest financial institutions. Firstly, we show a dramatic increase in systemic risk after 2011 and the increased contribution of small- and medium-sized banks. Then, we identify causality relationships from housing prices, economic policy uncertainty and shadow banking towards systemic risk and causality from shadow banking to housing prices. According to our results, international concerns about the stability of the Chinese banking system are well justified and a systemic event with international impact could be caused by distress in a Chinese financial institution outside of the group of the largest banks.
arXiv
We study a forward rate model in the presence of volatility uncertainty. The forward rate is modeled as a diffusion process in the spirit of Heath, Jarrow, and Morton [Econometrica 60 (1), 77-105]. The uncertainty about the volatility is represented by a G-Brownian motion, being the driver of the forward rate dynamics. Within this framework, we derive a sufficient condition for the absence of arbitrage, known as the drift condition. In contrast to the traditional model, the drift condition consists of several equations and several market prices, termed market price of risk and market prices of uncertainty, respectively. The drift condition is still consistent with the classical one if there is no volatility uncertainty. Similar to the traditional model, the risk-neutral dynamics of the forward rate are completely determined by its diffusion term. Furthermore, we obtain robust versions of classical term structure models as examples in this framework.
SSRN
This paper reexamines the empirical evidence on the cash flow sensitivity of cash presented by Almeida, Campello, and Weisbach (2004). The original paper introduces a model in which financially constrained firms choose to save cash out of incremental cash flows but financially unconstrained do not. The authors find evidence consistent with this hypothesis on a sample of U.S. public firms between 1971 and 2000. This paper extends that analysis in a number of ways. In particular, it uses a larger sample covering the 1971â€"2019 window, considers a number of alternative definitions of financial constraints, and incorporates new methods and tests suggested by Welch (2020), Almeida, Campello, and Galvao (2010), and Grieser and Hadlock (2019). The original empirical findings are robust to these alternative specifications.
SSRN
In this paper, we examine the influence of bank regulation, concentration, and financial and institutional development on commercial bank margins and profitability across a broad selection of Middle East and North Africa (MENA) countries. The empirical results suggest that bank-specific characteristics, in particular bank capitalization and credit risk, have a positive and significant impact on banks' net interest margin, cost efficiency, and profitability. Also we find that macroeconomic and financial development indicators have no significant impact on net interest margins, except for inflation. Regulatory and institutional variables seem to have an impact on bank performance.
SSRN
We identify a component of monetary policy news that is extracted from high-frequency changes in risky asset prices. These surprises, which we call “risk shiftsâ€, are uncorrelated, and therefore complementary, to risk-free rate surprises. We show that (i) risk shifts capture the lion’s share of stock price movements around FOMC announcements; (ii) that they are accompanied by significant investor fund flows, suggesting that investors react heterogeneously to monetary policy news; and (iii) that price pressure amplifies the stock market response to monetary policy news. Our results imply that central bank information effects are overshadowed by short-term dynamics stemming from investor rebalancing activities and are likely to be more difficult to identify than previously thought.
SSRN
This paper examines the effect of the political network of Chinese municipal leaders on the pricing of municipal corporate bonds. Using municipal leaders' working experience to measure the political network, we find that this network improves the credit ratings of the issuer, local government financing vehicles (LGFVs), reducing their issuance yield spreads. The relationship between political networks and issuance yield spreads is strengthened in areas where financial markets and legal systems are less developed.
arXiv
We study the Hull-White model for the term structure of interest rates in the presence of volatility uncertainty. The uncertainty about the volatility is represented by a set of beliefs, which naturally leads to a sublinear expectation and a G-Brownian motion. The main question in this setting is how to find an arbitrage-free term structure. This question is crucial, since we can show that the classical approach, martingale modeling, does not work in the presence of volatility uncertainty. Therefore, we need to adjust the model in order to find an arbitrage-free term structure. The resulting term structure is affine with respect to the short rate and the adjustment factor. Although the adjustment changes the structure of the model, it is still consistent with the traditional Hull-White model after fitting the yield curve. In addition, we extend the model and the results to a multifactor version, driven by multiple risk factors.
arXiv
Policy makers worldwide draft privacy laws that require trading-off between safeguarding consumer privacy and preventing economic damage to companies that use consumer data. However, little empirical knowledge exists as to how privacy laws affect companies' performance. Accordingly, this paper empirically quantifies the effects of the enforcement of the EU's General Data Protection Regulation (GDPR) on online user behavior over time, analyzing data from 6,286 websites spanning 24 industries, during the 10 months before and 18 months after the GDPR's enforcement in 2018. A difference-in-differences analysis, with a synthetic control group approach, enables the short- and long-term effects of the GDPR on user behavior to be reliably isolated. The results show that, on average, the GDPR's effects on user quantity and usage intensity were negative; e.g., 3 months (18 months) post-GDPR, the numbers of unique visitors and total visits to a website decreased by 0.8% (6.6%) and 4.9% (10%), respectively. These effects could translate into average revenue losses of 7 million USD for e-commerce websites and almost 2.5 million USD for ad-based websites 18 months after GDPR. The GDPR's effects vary across websites, with some industries even benefiting from it; moreover, more-popular websites suffered less damage, suggesting that the GDPR increased market concentration.
arXiv
The opioid epidemic began with prescription pain relievers. In 2010 Purdue Pharma reformulated OxyContin to make it more difficult to abuse. OxyContin misuse fell dramatically, and concurrently heroin deaths began to rise. Previous research overlooked generic oxycodone and argued that the reformulation induced OxyContin users to switch directly to heroin. Using a novel and fine-grained source of all oxycodone sales from 2006-2014, we show that the reformulation led users to substitute from OxyContin to generic oxycodone, and the reformulation had no overall impact on opioid or heroin mortality. In fact, generic oxycodone, instead of OxyContin, was the driving factor in the transition to heroin. Finally, we show that by omitting generic oxycodone we recover the results of the literature. These findings highlight the important role generic oxycodone played in the opioid epidemic and the limited effectiveness of a partial supply-side intervention.
SSRN
In this paper we investigate the relationship between past trading volume and variance risk premiums (VRPs) around earnings announcement dates (EADs). Theoretical models suggest opposing relationships between trading volume and VRPs. Using a large sample of straddle returns, we find higher VRPs for firms around EADs with higher trading volume. This relationship holds conditional to other factors suggested to predict VRPs and appears specific to the EAD period. Further tests reveal that the result is driven by excess options trading and options trading continues to predict straddle returns conditional on excess stock trading, option open interest, analyst dispersion, and realized earnings surprises. Our main results suggest a one-standard deviation increase in abnormal log options trading is associated with a 170 to 190 basis point drop in realized straddle returns around EADs. Finally, we find excess option trading is a stronger predictor of EAD VRPs for smaller firms and firms with tighter equity bid-ask spreads.
SSRN
Spanish Abstract: La taxonomÃa de actividades económicas sostenibles de la Unión Europea (UE) se ha creado con el objetivo de que se convierta en una normativa transversal para todas las regulaciones europeas actuales y futuras de finanzas sostenibles. Tras haberse propuesto en 2018, en junio de 2020 se publicó finalmente el reglamento que contiene sus principios básicos y sus fundamentos. En este documento se describen las caracterÃsticas fundamentales de la taxonomÃa, su funcionamiento, su influencia sobre el futuro estándar de bono verde europeo y su previsible desarrollo futuro. Además, se reflexiona sobre su importancia para los bancos centrales desde el punto de vista de sus inversiones y sobre su relevancia para la UE y para la financiación sostenible, y se apuntan las ventajas que supone, pero también los retos a los que se enfrenta, para que pueda ser utilizada por empresas e inversores. En última instancia, la aplicación exitosa de la taxonomÃa europea es clave para que Europa logre sus ambiciosos objetivos climáticos y medioambientales, y para que las generaciones futuras disfruten de un mundo más habitable y sostenible.English Abstract: The EU Taxonomy for sustainable activities was created with the goal of becoming a crosssectional law for all current and future EU regulations on sustainable finance. The initial proposal for an EU Taxonomy was in 2018, and the final regulation, containing its basic principles and foundations, was released in June 2020. In this article I describe the main characteristics of the taxonomy: how it works, its influence on the future EU Green Bond Standard and its foreseeable future development. I also reflect on the importance of the EU Taxonomy for Central Banks from the standpoint of their investments, the relevance of the Taxonomy for the EU and sustainable finance, and the benefits it entails and the challenges it poses if companies and investors are to use it. Ultimately, a successful implementation of the Taxonomy will be key to Europe achieving its ambitious climate and environmental objectives and to future generations enjoying a more sustainable and habitable world.
SSRN
Whether the conflict that was started on November 3, 2020, in Northern Ethiopia will be short-lived or a protracted one that turns itself into a stalemate, guerrilla warfare and draws the Greater Horn of Africa region into larger conflict is unclear. The spark of November 3, 2020, was a result of the simmering tensions that were allowed to build up within the once invincible ethnic coalition that ruled Ethiopia for 27 years. TThe cleavages cut through all state institutions, including in the defense and security establishments. In this short paper, I attempt to provide a rejoinder to show that “the Tigray conflict†has as much to do with resource control as it is with politics. De-escalation of the conflict requires the understanding of the stakes for the parties to the conflict. The ownership and management of party-affiliated endowment companies are one of the economic dimensions of the conflict. The paper outlines the pros and cons of various reform options.
SSRN
In this paper we study the performance of several machine learning (ML) models for credit default prediction. We do so by using a unique and anonymized database from a major Spanish bank. We compare the statistical performance of a simple and traditionally used model like the Logistic Regression (Logit), with more advanced ones like Lasso penalized logistic regression, Classification And Regression Tree (CART), Random Forest, XGBoost and Deep Neural Networks. Following the process deployed for the supervisory validation of Internal Rating-Based (IRB) systems, we examine the benefits of using ML in terms of predictive power, both in classification and calibration. Running a simulation exercise for different sample sizes and number of features we are able to isolate the information advantage associated to the access to big amounts of data, and measure the ML model advantage. Despite the fact that ML models outperforms Logit both in classification and in calibration, more complex ML algorithms do not necessarily predict better. We then translate this statistical performance into economic impact. We do so by estimating the savings in regulatory capital when using ML models instead of a simpler model like Lasso to compute the risk-weighted assets. Our benchmark results show that implementing XGBoost could yield savings from 12.4% to 17% in terms of regulatory capital requirements under the IRB approach. This leads us to conclude that the potential benefits in economic terms for the institutions would be significant and this justify further research to better understand all the risks embedded in ML models.
arXiv
Using network analysis, this paper develops a multidimensional methodological framework for understanding the uneven (cross-country) spread of COVID-19 in the context of the global interconnected economy. The globally interconnected system of tourism mobility is modeled as a complex network, where two main stages in the temporal spread of COVID-19 are revealed and defined by the cutting-point of the 44th day from Wuhan. The first stage describes the outbreak in Asia and North America, the second one in Europe, South America, and Africa, while the outbreak in Oceania is spread along both stages. The analysis shows that highly connected nodes in the global tourism network (GTN) are infected early by the pandemic, while nodes of lower connectivity are late infected. Moreover, countries with the same network centrality as China were early infected on average by COVID-19. The paper also finds that network interconnectedness, economic openness, and transport integration are key determinants in the early global spread of the pandemic, and it reveals that the spatio-temporal patterns of the worldwide spread of COVID-19 are more a matter of network interconnectivity than of spatial proximity.
SSRN
Despite blockchain based digital assets trading since 2009, there has been a functional gap between (1) on-chain transactions and (2) trust based centralized exchanges. This is now bridged with the success of Uniswap, a decentralized exchange. Uniswap's constant product automated market maker enables the trading of blockchain token pairs without relying on market makers, bids or asks. This overturns centuries of practice in financial markets, and constitutes a potential building block of a new decentralized financial system. We apply ARDL and VAR methodologies to a dataset of 999 hours of Uniswap trading, and conclude that its simplicity enables liquidty providers and arbitrageurs to ensure the ratio of reserves match the trading pair price. We find that changes in Ether reserves Granger causes changes in USDT reserves.
SSRN
The paper examines the combination of Google Trends search engine tools and the Decision Making Helper decision support system, taking into account the possibility of solving scientific problems in the compliance organization. The object of research is the compliance organization in the field of funded pension provision. One of the most problematic areas is the lack of research to assess the level of interest of users of the search engine Google Trends in the topic of compliance and the degree of its spread. This hinders the practice of identifying trends and current trends in the development of modern scientific, social and professional thought in the organization of compliance. The research used the tools of the Google Trends search engine based on the frequency of requests for this definition in Ukrainian, Russian and English. According to the frequency of search queries of users, trend models for the considered concepts of "compliance" have been built, having a satisfactory (0.859 and 0.7507) value of the approximation reliability. These two trend models are recommended for predicting the level of user interest in the compliance topic. So, it is modeled the process of assessing the level of interest of users of the Google Trends search engine by the “compliance†concept. This provides the advantage of being able to predict the interest of Google Trends users on the topic. The positive effect of the conducted research is to identify trends and current trends in the development of modern scientific, social and professional thought on compliance.Obtained, using the Decision Making Helper decision support system, an assessment of alternatives for the key components of the organization's compliance in the area of funded pension provision. This is due to the fact that the proposed approach to decision-making has a number of features, including organizational, methodological and process aspects. In particular, the priority of the organizational aspect is determined, it has the characteristics of the most positive decision. This provides benefits such as automating decisions and the ability to prioritize those decisions.
SSRN
In this study we explore market power in 13 EU banking sectors for the years 2007 to 2019 by estimating a structural model with demand and supply equations, where the mark-up of price over marginal cost is parameterized as a measure of banks’ conduct that depends on selected factors. Our evidence indicates that EU banks enjoy a significant degree of market power, which shows a decreasing trend over time and some difference across countries. More competition is associated with higher bank density, lower bank capitalization, more efficient and stable banking systems, and better macroeconomic conditions. Finally, a clear convergence pattern emerges in the behaviour of EU banks.
