# Research articles for the 2020-05-18

Ringo, Daniel
SSRN
Banks in the United States originate $100 billion in community development loans every year and hold a similar amount of community development investments on their balance sheets. A number of federal place-based policies encourage the provision of these loans and investments to promote growth, employment and the availability of affordable housing to disadvantaged communities. Research into the effectiveness of privately supplied community development financing has been hampered, however, by the lack of comprehensive data on banks' community development activities at a local level. Hand collected data from thousands of Community Reinvestment Act performance evaluations fill this gap. Using these data, the effect of the supply of community development funding on local economic outcomes is estimated. Endogeneity of community development financing to local demand factors is addressed, exploiting the fact that banks exhibit fixed tendencies to engage in community development financing across markets. Shifts in the share of local deposit markets toward banks with a greater tendency to supply community development loans are associated with subsequent expansion in total employment and wages paid. Estimates suggest$56,000 in community development lending is required to create one job, on net. There is no measurable effect on the supply of affordable housing or the growth of house prices. Counties experiencing a shift in local deposit market shares toward community development intensive banks were on similar pre-trends as the rest of the country in the years prior to the shift, as measured across a range of economic and credit market outcomes.

An analysis of Uniswap markets
Guillermo Angeris,Hsien-Tang Kao,Rei Chiang,Charlie Noyes,Tarun Chitra
arXiv

Uniswap---and other constant product markets---appear to work well in practice despite their simplicity. In this paper, we give a simple formal analysis of constant product markets and their generalizations, showing that, under some common conditions, these markets must closely track the reference market price. We also show that Uniswap satisfies many other desirable properties and numerically demonstrate, via a large-scale agent-based simulation, that Uniswap is stable under a wide range of market conditions.

Application of Nonlinear Autoregressive with Exogenous Input (NARX) neural network in macroeconomic forecasting, national goal setting and global competitiveness assessment
Liyang Tang
arXiv

This paper selects the NARX neural network as the method through literature review, and constructs specific NARX neural networks under application scenarios involving macroeconomic forecasting, national goal setting and global competitiveness assessment. Through case studies on China, US and Eurozone, this study explores how those limited & partial exogenous inputs or abundant & comprehensive exogenous inputs, a small set of most relevant exogenous inputs or a large set of exogenous inputs covering all major aspects of the macro economy, whole area related exogenous inputs or both whole area and subdivision area related exogenous inputs specifically affect the forecasting performance of NARX neural networks for specific macroeconomic indicators or indices. Through the case study on Russia this paper explores how the limited & most relevant exogenous inputs set or the abundant & comprehensive exogenous inputs set specifically influences the prediction performance of those specific NARX neural networks for national goal setting. Finally, comparative studies on the application of NARX neural networks for the forecasts of Global Competitiveness Indices (GCIs) of various economies are conducted, in order to explore whether the specific NARX neural network trained on the basis of the GCI related data of some economies can make sufficiently accurate predictions about GCIs of other economies, and whether the specific NARX neural network trained on the basis of the data of some type of economies can give more accurate predictions about GCIs of the same type of economies than those of different type of economies. Based on all of the above successful application, this paper provides policy recommendations on applying fully trained NARX neural networks that are assessed as qualified to assist or even replace the deductive and inductive abilities of the human brain in a variety of appropriate tasks.

Branching Networks and Geographic Contagion of Commodity Price Shocks
Wang, Teng
SSRN
This paper studies the role of banks' branching networks in propagating the oil shocks. Banks that were exposed to the oil shocks through their operations in oil-concentrated counties experienced a liquidity drainage in the form of a declining amount of demand deposit inflow as well as an increasing percentage of troubled loans. Banks were forced to sell liquid assets, and contracted lending to small businesses and mortgage borrowers in counties that were not directly affected by the oil shocks. The effect is magnified when banks do not have strong community ties, but is mitigated if banks' branching network is sufficiently dispersed. I also find the decline in local credit supply cannot be completely offset by healthy competing banks' increased lending, providing fresh evidence from the perspective of bank competition.

Buildingsâ€™ Energy Efficiency and the Probability of Mortgage Default: The Dutch Case
Billio, Monica,Costola, Michele,Pelizzon, Loriana,Riedel, Max
SSRN
We investigate the relation between buildingsâ€™ energy efficiency and the probability of mortgage default. To this end, we construct a novel panel dataset by combining Dutch loan-level mortgage information with provisional building energy ratings that are provided by the Netherlands Enterprise Agency. By employing the logistic regression and the extended Cox model, we find that buildingsâ€™ energy efficiency is associated with lower likelihood of mortgage default. We also show that energy efficiency provides a further mitigation of default risk for borrowers with a lower income potentially because of the savings coming from lower utility bills, which have a major impact on the borrower with less disposable income. The results hold for a battery of robustness checks.

Choice of Pension Management Fees and Effects on Pension Wealth.
Bernal, Noelia,Olivera, Javier
SSRN
To shed light on the effects of individual choice on pension wealth, we study a policy change to the management fees of pension funds implemented by Peru's government in 2013. The reform established a new balance fee as a default option; this fee is calculated as a percentage of the pension balance. Each individual had the initial option of keeping the previous management fee, a load factor fee calculated as a percentage of the individual's salary. We use administrative data to simulate pension balances based on the individual's choice of fee and the corresponding counterfactual. Our results indicate that the reform has been potentially adverse to 63.1 percent of individuals, of whom 41.4 percent were assigned to the default option and 21.7 percent voluntarily chose the load fee. These results reflect both the potentially negative unintended effects of the policy and an alarming lack of financial literacy among citizens. We also detect heterogeneity in the intensity of the losses and gains due to the reform, which caused greater losses than gains. In particular, younger and poorer individuals, as well as those automatically assigned to the balance fee, experienced higher losses. Moreover, the new fee scheme is also associated with increasing inequality between individuals' pension wealth.

Credit Ratings in the Age of Environmental, Social, and Governance (ESG)
Yang, Ruoke
SSRN
Environmental, social, and governance (ESG) issues of corporations have been the subject of much interest of late among many of their investors. Increasingly, these issues are being examined with a view towards managing financial risks. This paper studies the implications of this development for the credit ratings business. I find that a recent move by Standard and Poor's and Moody's towards incorporating ESG issues into their credit analysis was perceived by the market to have improved the quality of their ratings. However, despite this new recognition of ESG in the market for credit ratings, news about problems related to ESG appears to generally matter very little for these ratings.

Deep Learning in Asset Pricing
Luyang Chen,Markus Pelger,Jason Zhu
arXiv

We use deep neural networks to estimate an asset pricing model for individual stock returns that takes advantage of the vast amount of conditioning information, while keeping a fully flexible form and accounting for time-variation. The key innovations are to use the fundamental no-arbitrage condition as criterion function, to construct the most informative test assets with an adversarial approach and to extract the states of the economy from many macroeconomic time series. Our asset pricing model outperforms out-of-sample all benchmark approaches in terms of Sharpe ratio, explained variation and pricing errors and identifies the key factors that drive asset prices.

Determinants of Profitability of Banks: Evidence from Islamic Banks of Bangladesh
Nusrat Jahan
arXiv

This empirical study is conducted on randomly selected six Islamic banks of Bangladesh. This study utilizes widely used Measures of banks profitability which are Return on Asset (ROA), Return on Equity (ROE) and Return on Deposit (ROD) and these are also commonly suggested tools by Bangladesh Bank to evaluate banks performance. In addition, this study examined the relationship of ROA with Asset Utilization (AU), Operational Efficiency (OE)and ROD. The result reveals that EXIM Bank Limited is performing very good in terms of all profitability measures ROA, ROE and ROD even though average asset size of Islami Bank Bangladesh Limited is found to be largest among all six Islamic Banks. The result of regression found the explanatory variable ROD is significantly associated with ROA but failed to establish any significant association with operational efficiency and asset utilization.

Disaster Resilience and Asset Prices
Marco Pagano,Christian Wagner,Josef Zechner
arXiv

This paper investigates whether security markets price the effect of social distancing on firms' operations. We document that firms that are more resilient to social distancing significantly outperformed those with lower resilience during the COVID-19 outbreak, even after controlling for the standard risk factors. Similar cross-sectional return differentials already emerged before the COVID-19 crisis: the 2014-19 cumulative return differential between more and less resilient firms is of similar size as during the outbreak, suggesting growing awareness of pandemic risk well in advance of its materialization. Finally, we use stock option prices to infer the market's return expectations after the onset of the pandemic: even at a two-year horizon, stocks of more pandemic-resilient firms are expected to yield significantly lower returns than less resilient ones, reflecting their lower exposure to disaster risk. Hence, going forward, markets appear to price exposure to a new risk factor, namely, pandemic risk.

Evaluation of Accounting and Market Performance: A Study on Listed Islamic Banks of Bangladesh
Nusrat Jahan,M. Ayub Islam
arXiv

This study compared accounting performance of Islamic banks with their market performance and also assessed the effect of firm-specific determinants and cross-sectional effect on accounting and market performance. This study selected all six listed Islamic banks of Chittagong Stock Exchange and the data were collected for the period of 2009 to 2013. This study reported that Social Islamic Bank Limited exhibits superior accounting performance whereas Islami Bank Bangladesh Limited holds better market performance. However, banks exhibiting superior accounting performance reported to have inferior market performance. Further, random-effect model for ROA reports that there exist significant entity or crosssectional effect on ROA; and operational efficiency and bank size are significantly negatively associated with ROA. However, random-effect model for Tobins Q failed to ascertain entity or cross-sectional effect on Tobins Q and also reveals that firm-specific determinants have no significant impact on Tobins Q.

Female Leadership and Bank Performance in Latin America
VÃ¤hÃ¤maa, Emilia,Baselga-Pascual, Laura
SSRN
This paper examines the relationship between gender diversity in corporate boards and executive positions and bank risk and performance in Latin America. Our sample covers 91 individual banks during 2000â€"2017. Our results suggest that banks with a higher proportion of female executives tend to have lower Z-scores than male-led banks. However, female-led banks are more profitable. Our results provide new information related to the debate on the relationship between gender-based behavioural differences and financial decisions by showing that Latin American banks with a higher proportion of female executives are riskier and more profitable than male-led banks. Given the impact of bank performance on the international economy, the global interconnection of financial institutions, and the lack of legal protection in this region, it is of interest for regulators and policy makers to analyse possible sources of better performance and governance in Latin American banks.

Financial Stability Committees and Basel III Macroprudential Capital Buffers
Edge, Rochelle M.,Liang, Nellie
SSRN
We evaluate how a countryâ€™s governance structure for macroprudential policy affects its implementation of Basel III macroprudential capital buffers. We find that the probabilities of using the countercyclical capital buffer (CCyB) are higher in countries that have financial stability committees (FSCs) with stronger governance mechanisms and fewer agencies, which reduces coordination problems. These higher probabilities are more sensitive to credit growth, consistent with the CCyB being used to mitigate systemic risk. A countryâ€™s probability of using the CCyB is even higher when the FSC or ministry of finance has direct authority to set the CCyB, perhaps because setting the CCyB involves establishing a new macro-financial analytical process to regularly assess systemic risks and allows these new entities to influence the process. These results are consistent with elected officials creating the FSCs with the strongest governance and fewer agencies for functional delegation reasons, but most FSCs are created for symbolic political reasons.

Foundations of System-Wide Financial Stress Testing with Heterogeneous Institutions
Farmer, J. Doyne,Kleinnijenhuis, Alissa M.,Nahai-Williamson, Paul,Wetzer, Thom
SSRN
We propose a structural framework for the development of system-wide financial stress tests with multiple interacting contagion, amplification channels and heterogeneous financial institutions. This framework conceptualises financial systems through the lens of five building blocks: financial institutions, contracts, markets, constraints, and behaviour. Using this framework, we implement a system-wide stress test for the European financial system. We obtain three key findings. First, the financial system may be stable or unstable for a given microprudential stress test outcome, depending on the systemâ€™s shock-amplifying tendency. Second, the â€˜usabilityâ€™ of banksâ€™ capital buffers (the willingness of banks to use buffers to absorb losses) is of great consequence to systemic resilience. Third, there is a risk that the size of capital buffers needed to limit systemic risk could be severely underestimated if calibrated in the absence of system-wide approaches.

How much is your Strangle worth? On the relative value of the $\delta-$Symmetric Strangle under the Black-Scholes model
Ben Boukai
arXiv

Trading option strangles is a highly popular strategy often used by market participants to mitigate volatility risks in their portfolios. In this paper we propose a measure of the relative value of a delta-Symmetric Strangle and compute it under the standard Black-Scholes option pricing model. This new measure accounts for the price of the strangle, relative to the Present Value of the spread between the two strikes, all expressed, after a natural re-parameterization, in terms of delta and a volatility parameter. We show that under the standard BS option pricing model, this measure of relative value is bounded by a simple function of delta only and is independent of the time to expiry, the price of the underlying security or the prevailing volatility used in the pricing model. We demonstrate how this bound can be used as a quick {\it benchmark} to assess, regardless the market volatility, the duration of the contract or the price of the underlying security, the market (relative) value of the $\delta-$strangle in comparison to its BS (relative) price. In fact, the explicit and simple expression for this measure and bound allows us to also study in detail the strangle's exit strategy and the corresponding {\it optimal} choice for a value of delta.

How sustainable environments have reduced the diffusion of coronavirus disease 2019: the interaction between spread of COVID-19 infection, polluting industrialization, wind (renewable) energy
Mario Coccia
arXiv

This study endeavors to explain the relation between air pollution and particulate compounds emissions, wind resources and energy, and the diffusion of COVID-19 infection to provide insights of sustainable policy to prevent future epidemics. The statistical analysis here focuses on case study of Italy, one of the countries to experience a rapid increase in confirmed cases and deaths. Results reveal two main findings: 1) cities in regions with high wind speed and a high wind energy production in MW have a lower number of infected individuals of COVID-19 infection and total deaths; 2) cities located in hinterland zones (mostly those bordering large urban conurbations) with high polluting industrialization, low wind speed and less cleaner production have a greater number of infected individuals and total deaths. Hence, cities with pollution industrialization and low renewable energy have also to consider low wind speed and other climatological factors that can increase stagnation of the air in the atmosphere with potential problems for public health in the presence of viral agents. Results here suggest that current pandemic of Coronavirus disease and future epidemics similar to COVID-19 infection cannot be solved only with research and practice of medicine, immunology and microbiology but also with a proactive strategy directed to interventions for a sustainable development. Overall, then, this study has to conclude that a strategy to prevent future epidemics similar to COVID-19 infection must also be based on sustainability science to support a higher level of renewable energy and cleaner production to reduce polluting industrialization and, as result, the factors determining the spread of coronavirus disease and other infections in society.

How to manage the post pandemic opening? A Pontryagin Maximum Principle approach
R. Mansilla
arXiv

The COVID-19 pandemic has completely disrupted the operation of our societies. Its elusive transmission process, characterized by an unusually long incubation period, as well as a high contagion capacity, has forced many countries to take quarantine and social isolation measures that conspire against the performance of national economies. This situation confronts decision makers in different countries with the alternative of reopening the economies, thus facing the unpredictable cost of a rebound of the infection. This work tries to offer an initial theoretical framework to handle this alternative.

Implementing stakeholder participation as "egalitarian bidding" – The test of the Kantian pudding is in the institutionalized eating
Alberti, Federica,Güth, Werner,Kliemt, Hartmut,Tsutsui, Kei
RePEC
Stakeholder conceptions of corporate governance tend to address managers and owners of companies as benevolent despots who follow ethical appeals to respect all stakeholders equally. Avoiding the benevolent despot assumption we axiomatically specify how "stakeholder participation as 'egalitarian bidding' " could conceivably be used to implement the values underlying stakeholder conceptions as procedures of corporate governance. We do not claim that stakeholder theorists have to concur with our proposed operationalization of their ideals. Yet those who do not accept participatory 'egalitarian bidding' should come up with some alternative operationalization of "equal (Kantian) respect" or admit that their theories are non-operational.

In the Eye of the Beholder: Regulatory Versus Industry Risk Perception
Burns, Meghan,Kenett, Dror Y.,Sokobin, Jonathan S.
SSRN
Is the perception of risk, as outlined and defined by the regulatory and supervisory community, shared by private financial institutions? In this paper we assess a representative sample of recent publicly available risk perspectives and outlooks, and study similarities and differences. We find that for established (traditional) risk themes there is relatively greater consensus between regulators and industry participants. However, for emerging risk themes, we find a divergence in perspectives between industry and regulators and, at times, even within each group. We discuss this spectrum of risk perspectives, as well as approaches to mitigate the resulting â€œrisk-gapâ€ between the regulators and the industry.

Inference on Achieved Signal Noise Ratio
Steven E. Pav
arXiv

We describe a procedure to perform approximate inference on the achieved signal-noise ratio of the Markowitz Portfolio under Gaussian i.i.d. returns. The procedure relies on a statistic similar to the Sharpe Ratio Information Criterion. Testing indicates the procedure is somewhat conservative, but otherwise works well for reasonable values of sample and asset universe sizes. We adapt the procedure to deal with generalizations of the portfolio optimization problem.

Innovative Activity, Growth Options and the Heterogeneous Return Performance of Cross-border vs. Domestic M&A Firms
Del Viva, Luca,Ragozzino, Roberto,Trigeorgis, Lenos
SSRN
M&A deals in the US are done mostly at the domestic level. We examine the M&A performance of US acquirers during 1991-2014 based on the enhanced innovative capacity afforded by cross-border deals. We find that US firms engaging in cross-border M&A have superior innovative capacity, which results in lower short-term returns and downside risk. In contrast, long-run returns following cross-border acquisition are higher.

Institutional Diversity in Domestic Banking Sectors and Bank Stability: A Cross-Country Study
Baum, Christopher F.,Forti Grazzini, Caterina,Schaefer, Dorothea
SSRN
This paper analyzes the causal relationship between institutional diversity in domestic banking sectors and bank stability. We use a large bank- and country-level unbalanced panel data set covering the EU member statesâ€™ banking sectors between 1998 and 2014. Constructing two distinct indicators for measuring institutional diversity, we ï¬nd that a high degree of institutional diversity in the domestic banking sector positively affects bank stability. The positive relationship between domestic institutional diversity and bank stability is stronger in times of crisis, providing evidence that diversity can help to absorb both ï¬nancial and real shocks. In particular, greater institutional diversity smooths bank earnings risk in times of crisis. Our results are economically meaningful and offer important insights to the ongoing economic policy debate on how to reshape the architecture of the banking sector.

Lost in Translation? Analystsâ€™ Forecasts of Cross-Listed Firms
Cho, Hyunkwon,Muslu, Volkan,Koo, Minjae
SSRN
The level of difficulty for U.S. analysts in the native language of a cross-listed firm increases their forecast errors. The association is decreased by analyst experience and analyst fluency in the language of the cross-listed firms. The association is also decreased for countries using IFRS and those with higher financial reporting quality. Investors react more strongly to forecasts for firms that present greater language difficulty to analysts. Overall, our findings suggest that the language difficulty of cross-listed firms is associated with poor information environment and capital-market-related costs.

Monetary Policy Uncertainty and Monetary Policy Surprises
De Pooter, Michiel,Favara, Giovanni,Modugno, Michele,Wu, Jason
SSRN
Monetary policy uncertainty affects the transmission of monetary policy shocks to longer-term nominal and real yields. For a given monetary policy shock, the reaction of yields is more pronounced when the level of monetary policy uncertainty is low. Primary dealers and other investors adjust their interest rate positions more when monetary policy uncertainty is low than when uncertainty is high. These portfolio adjustments likely explain the larger pass-through of a monetary policy shock to bond yields when uncertainty is low. These findings shed new light on the role that monetary policy uncertainty plays in the transmission of monetary policy to financial markets.

Galanis, Spyros
SSRN

Nonparametric Expected Shortfall Forecasting Incorporating Weighted Quantiles
Giuseppe Storti,Chao Wang
arXiv

A new semi-parametric Expected Shortfall (ES) estimation and forecasting framework is proposed. The proposed approach is based on a two step estimation procedure. The first step involves the estimation of Value-at-Risk (VaR) at different levels through a set of quantile time series regressions. Then, the ES is computed as a weighted average of the estimated quantiles. The quantiles weighting structure is parsimoniously parameterized by means of a Beta function whose coefficients are optimized by minimizing a joint VaR and ES loss function of the Fissler-Ziegel class. The properties of the proposed approach are first evaluated with an extensive simulation study using various data generating processes. Two forecasting studies with different out-of-sample sizes are conducted, one of which focuses on the 2008 Global Financial Crisis (GFC) period. The proposed models are applied to 7 stock market indices and their forecasting performances are compared to those of a range of parametric, non-parametric and semi-parametric models, including GARCH, Conditional AutoRegressive Expectile (CARE, Taylor 2008), joint VaR and ES quantile regression models (Taylor, 2019) and simple average of quantiles. The results of the forecasting experiments provide clear evidence in support of the proposed models.

On unbalanced data and common shock models in stochastic loss reserving
Benjamin Avanzi,Gregory Clive Taylor,Phuong Anh Vu,Bernard Wong
arXiv

Introducing common shocks is a popular dependence modelling approach, with some recent applications in loss reserving. The main advantage of this approach is the ability to capture structural dependence coming from known relationships. In addition, it helps with the parsimonious construction of correlation matrices of large dimensions. However, complications arise in the presence of "unbalanced data", that is, when (expected) magnitude of observations over a single triangle, or between triangles, can vary substantially. Specifically, if a single common shock is applied to all of these cells, it can contribute insignificantly to the larger values and/or swamp the smaller ones, unless careful adjustments are made. This problem is further complicated in applications involving negative claim amounts. In this paper, we address this problem in the loss reserving context using a common shock Tweedie approach for unbalanced data. We show that the solution not only provides a much better balance of the common shock proportions relative to the unbalanced data, but it is also parsimonious. Finally, the common shock Tweedie model also provides distributional tractability.

Optimal execution strategy with an uncertain volume target
Julien Vaes,Raphael Hauser
arXiv

In the seminal paper on optimal execution of portfolio transactions, Almgren and Chriss (2001) define the optimal trading strategy to liquidate a fixed volume of a single security under price uncertainty. Yet there exist situations, such as in the power market, in which the volume to be traded can only be estimated and becomes more accurate when approaching a specified delivery time. During the course of execution, a trader should then constantly adapt their trading strategy to meet their fluctuating volume target. In this paper, we develop a model that accounts for volume uncertainty and we show that a risk-averse trader has benefit in delaying their trades. More precisely, we argue that the optimal strategy is a trade-off between early and late trades in order to balance risk associated with both price and volume. By incorporating a risk term related to the volume to trade, the static optimal strategies suggested by our model avoid the explosion in the algorithmic complexity usually associated with dynamic programming solutions, all the while yielding competitive performance.

Parameter estimation of default portfolios using the Merton model and Phase transition
arXiv

We discuss the parameter estimation of the probability of default (PD), the correlation between the obligors, and a phase transition. In our previous work, we studied the problem using the beta-binomial distribution. A non-equilibrium phase transition with an order parameter occurs when the temporal correlation decays by power law. In this article, we adopt the Merton model, which uses an asset correlation as the default correlation, and find that a phase transition occurs when the temporal correlation decays by power law. When the power index is less than one, the PD estimator converges slowly. Thus, it is difficult to estimate PD with limited historical data. Conversely, when the power index is greater than one, the convergence speed is inversely proportional to the number of samples. We investigate the empirical default data history of several rating agencies. The estimated power index is in the slow convergence range when we use long history data. This suggests that PD could have a long memory and that it is difficult to estimate parameters due to slow convergence.

Parameters of Profitability: Evidence From Conventional and Islamic Banks of Bangladesh
K.M. Golam Muhiuddin,Nusrat Jahan
arXiv

This paper evaluates the commercial banks of Bangladesh in terms of profitability dimension of performance and also examines the impact of selected determinants and banking system on this dimension of performance. Evaluation of trend in profitability of listed commercial banks of Bangladesh reveals that, on an average, profitability is exhibiting a decreasing trend over the selected period; however, the profitability performance of Islamic banks remained rather high compared to Conventional banks. Profitability measured by Return on Asset is found to be significantly affected by the bank-specific factors, industry-specific factor and the banking system. However, macro-economic factors evidently have no significant impact on profitability of commercial banks of Bangladesh.

Prediction defaults for networked-guarantee loans
Dawei Cheng,Zhibin Niu,Yi Tu,Liqing Zhang
arXiv

Networked-guarantee loans may cause the systemic risk related concern of the government and banks in China. The prediction of default of enterprise loans is a typical extremely imbalanced prediction problem, and the networked-guarantee make this problem more difficult to solve. Since the guaranteed loan is a debt obligation promise, if one enterprise in the guarantee network falls into a financial crisis, the debt risk may spread like a virus across the guarantee network, even lead to a systemic financial crisis. In this paper, we propose an imbalanced network risk diffusion model to forecast the enterprise default risk in a short future. Positive weighted k-nearest neighbors (p-wkNN) algorithm is developed for the stand-alone case -- when there is no default contagious; then a data-driven default diffusion model is integrated to further improve the prediction accuracy. We perform the empirical study on a real-world three-years loan record from a major commercial bank. The results show that our proposed method outperforms conventional credit risk methods in terms of AUC. In summary, our quantitative risk evaluation model shows promising prediction performance on real-world data, which could be useful to both regulators and stakeholders.

Presentation Slides for 'Decision Fatigue and Heuristic Analyst Forecasts'
Hirshleifer, David A.,Levi, Yaron,Lourie, Ben,Teoh, Siew Hong
SSRN
Psychological evidence indicates that decision quality declines after an extensive session of decision-making, a phenomenon known as decision fatigue. We study whether decision fatigue affects analystsâ€™ judgments. Analysts cover multiple firms and often issue several forecasts in a single day. We find that forecast accuracy declines over the course of a day as the number of forecasts the analyst has already issued increases. Also consistent with decision fatigue, we find that the more forecasts an analyst issues, the higher the likelihood the analyst resorts to more heuristic decisions by herding more closely with the consensus forecast, self-herding (i.e., reissuing their own previous outstanding forecasts), and issuing a rounded forecast. Finally, we find that the stock market understands these effects and discounts for analyst decision fatigue.

Presentation Slides for Key Performance Indicators as Supplements to Earnings: Incremental informativeness, Demand Factors, Measurement Issues, and Properties of Their Forecasts
Givoly, Dan,Li, Yifan,Lourie, Ben,Nekrasov, Alexander
SSRN
The documented decline in the information content of earnings numbers has paralleled the emergence of disclosures, mostly voluntary, of industry-specific key performance indicators (KPIs). We find that the incremental information content conveyed by KPI news is significant for many KPIs, yet it is diminished when details about the computation of the KPI are absent or when the computation of the KPI changes over time. Consistent with analysts responding to investor information demand, we find that analysts are more likely to produce forecasts for a KPI when that KPI has more information content and when earnings are less informative. We also analyze the properties of analystsâ€™ KPI forecasts, and we find that KPI forecasts are more accurate than mechanical forecasts, and their accuracy exceeds that of earnings forecasts. Our study contributes to the literature on the information content of KPIs and increases our understanding of the factors that affect this content. We provide evidence pertinent to the debate on whether and how to regulate KPI disclosures. This study further contributes to research on the properties of analystsâ€™ forecasts.Link to the SSRN version: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2990730

Quality is Our Asset: The International Transmission of Liquidity Regulation
Reinhardt, Dennis,Reynolds, Stephen,Sowerbutts, Rhiannon,van Hombeeck, Carlos
SSRN
We examine how banksâ€™ cross-border lending reacts to changes in liquidity regulation using a new dataset on Individual Liquidity Guidance (ILG), which was enacted in the UK from 2000 to 2015 and is similar to the Basel III Liquidity Coverage Ratio. A one percentage point increase in liquidity requirements to total assets reduces UK resident banksâ€™ cross-border lending growth by around 0.6 percentage points and both bank and non-bank lending are affected. But quality matters: an increase in the holdings of High Quality Liquid Asset (HQLA) qualifying sovereign debt offsets some of the reduction in total cross-border lending growth. Furthermore, the strongest reduction is driven by foreign subsidiaries from countries where sovereigns do not issue HQLA; in contrast subsidiaries from countries issuing HQLA are able to protect their lending to unrelated entities and cut their intragroup lending instead. Banks with a higher deposit share as a consequence of established retail operations, such as those headquartered in the UK, are also able to offset the effects of increases of liquidity requirement on cross-border lending.

Reactive Global Minimum Variance Portfolios with $k-$BAHC covariance cleaning
Christian Bongiorno,Damien Challet
arXiv

We introduce a $k$-fold boosted version of our Boostrapped Average Hierarchical Clustering cleaning procedure for correlation and covariance matrices. We then apply this method to global minimum variance portfolios for various values of $k$ and compare their performance with other state-of-the-art methods. Generally, we find that our method yields better Sharpe ratios after transaction costs than competing filtering methods, despite requiring a larger turnover.

Relative Net Utility and the Saint Petersburg Paradox
Daniel Muller,Tshilidzi Marwala
arXiv

The famous Saint Petersburg Paradox (St. Petersburg Paradox) shows that the theory of expected value does not capture the real-world economics of decision-making problems. Over the years, many economic theories were developed to resolve the paradox and explain gaps in the economic value theory in the evaluation of economic decisions, the subjective utility of the expected outcomes, and risk aversion as observed in the game of the St. Petersburg Paradox. In this paper, we use the concept of the relative net utility to resolve the St. Petersburg Paradox. Because the net utility concept is able to explain both behavioral economics and the St. Petersburg Paradox, it is deemed to be a universal approach to handling utility. This paper shows how the information content of the notion of net utility value allows us to capture a broader context of the impact of a decision's possible achievements. It discusses the necessary conditions that the utility function has to conform to avoid the paradox. Combining these necessary conditions allows us to define the theorem of indifference in the evaluation of economic decisions and to present the role of the relative net utility and net utility polarity in a value rational decision-making process.

SHIFT: A Highly Realistic Financial Market Simulation Platform
Thiago W. Alves,Ionut Florescu,George Calhoun,Dragos Bozdog
arXiv

This paper presents a new financial market simulator that may be used as a tool in both industry and academia for research in market microstructure. It allows multiple automated traders and/or researchers to simultaneously connect to an exchange-like environment, where they are able to asynchronously trade several financial assets at the same time. In its current iteration, this order-driven market implements the basic rules of U.S. equity markets, supporting both market and limit orders, and executing them in a first-in-first-out fashion. We overview the system architecture and we present possible use cases. We demonstrate how a set of automated agents is capable of producing a price process with characteristics similar to the statistics of real price from financial markets. Finally, we detail a market stress scenario and we draw, what we believe to be, interesting conclusions about crash events.

Social Inequality Measures: The Kolkata index in comparison with other measures
Suchismita Banerjee,Bikas K. Chakrabarti,Manipushpak Mitra,Suresh Mutuswami
arXiv

We provide a survey of the Kolkata index of social inequality, focusing in particular on income inequality. We look at both continuous and discrete income distributions. We also compare the Kolkata index to some other measures like the Gini coefficient, Hirsch index and the Pietra index. Lastly, we provide some empirical studies which illustrate the differences between the Kolkata index and the Gini coefficient.

Sowing the Seeds of Financial Imbalances: The Role of Macroeconomic Performance
Afanasyeva, Elena,Jerow, Sam,Lee, Seung Jung,Modugno, Michele
SSRN
The seeds of financial imbalances are sown in times of buoyant economic growth. We study the link between macroeconomic performance and financial imbalances, focusing on the experience of the United States since the 1960s. We first follow a narrative approach to review historical episodes of significant financial imbalances and find that the onset of financial disturbances typically occurs when the economy is running hot. We then look for evidence of a statistical link between measures of macroeconomic conditions and financial imbalances. In our in-sample analysis, we find that strong economic growth is followed by a build-up of financial imbalances across all dimensions of the National Financial Conditions Index. In our out-of-sample analysis, we find that the link between strong economic performance and increases in nonfinancial leverage is particularly strong and robust. Using a structural VAR identified with narrative sign restrictions, we also demonstrate that business cycle shocks are important drivers of non financial leverage.

Sustaining the economy under partial lockdown: A pandemic centric approach
Saket Saurabh,Ayush Trivedi,Nithilaksh P. Lokesh,Bhagyashree Gaikwad
arXiv

As the world fights to contain and control the spread of the Novel Coronavirus, countries are imposing severe measures from restrictions on travel and social gatherings to complete lockdowns. Lockdowns, though effective in controlling the virus spread, leaves a massive economic impact. In a country like India with 21.9 % of its population below the poverty line, lockdowns have a direct impact on the livelihood of a large part of the population. Our approach conforms to healthcare and state practices of reducing human to human contact, by optimizing the lockdown strategy. We propose resuming economic activities while keeping healthcare facilities from being overwhelmed. We model the coronavirus pandemic as SEIR dynamic model for a set of states as nodes with certain population and analyze the model output before and after complete lockdown. Social distancing that people would willingly follow, in the no lockdown situation is modeled as being influenced with the knowledge of the current number of infection by imitating Granovetter threshold model. We then provide optimal lockdown policy solutions for the duration of ten weeks using NSGA-II optimization algorithm. While there are many studies that focus on modelling the transmission of COVID-19, ours is one of the few attempts to strike a balance between number of infections and economic operations.

Taxation of a GMWB Variable Annuity in a Stochastic Interest Rate Model
Andrea Molent
arXiv

Modeling taxation of Variable Annuities has been frequently neglected but accounting for it can significantly improve the explanation of the withdrawal dynamics and lead to a better modeling of the financial cost of these insurance products. The importance of including a model for taxation has first been observed by Moenig and Bauer (2016) while considering a GMWB Variable Annuity. In particular, they consider the simple Black-Scholes dynamics to describe the underlying security. Nevertheless, GMWB are long term products and thus accounting for stochastic interest rate has relevant effects on both the financial evaluation and the policy holder behavior, as observed by Gouden\ege et al. (2018). In this paper we investigate the outcomes of these two elements together on GMWB evaluation. To this aim, we develop a numerical framework which allows one to efficiently compute the fair value of a policy. Numerical results show that accounting for both taxation and stochastic interest rate has a determinant impact on the withdrawal strategy and on the cost of GMWB contracts. In addition, it can explain why these products are so popular with people looking for a protected form of investment for retirement.

Taxes and IPO Pricing: Evidence from U.S. Tax Reform
Edwards, Alexander,Hutchens, Michelle
SSRN
This study examines when and how tax reform impacts the pricing of IPOs. Using the Tax Cuts and Jobs Act of 2017 (TCJA), we examine IPO pricing during the periods of anticipated and post-tax reform. First, we document that firms completing an IPO following the passage of the TCJA experience an increase in valuation. The increase in valuation is significantly lower for firms with net deferred tax assets and U.S. based multinational firms, consistent with those firms benefiting less from the reform. Second, we fail to document an increase in valuation for firms completing their IPO during the period of anticipated tax reform. We further observe that firms did not experience an increased probability of an upward pricing revision during the book-building process during this period, suggesting that the IPO market was unwilling to impound the benefits of anticipated tax reform into offer prices until enactment. This result contrasts with research on the pricing of tax reform for existing publicly traded stock, where prices impound the anticipated benefits from tax reform, far in advance of enactment.

Technological Innovation and Discrimination in Household Finance
SSRN
Technology has changed how discrimination manifests itself in financial services. Replacing human discretion with algorithms in decision-making roles reduces taste-based discrimination, and new modeling techniques have expanded access to financial services to households who were previously excluded from these markets. However, algorithms can exhibit bias from human involvement in the development process, and their opacity and complexity can facilitate statistical discrimination inconsistent with antidiscrimination laws in several aspects of financial services provision, including advertising, pricing, and credit-risk assessment. In this chapter, we provide a new amalgamation and analysis of these developments, identifying five gateways whereby technology induces discrimination to creep into financial services. We also consider how these technological changes in finance intersect with existing discrimination and data privacy laws, leading to our contribution of four frontlines of regulation. Our analysis concludes that the net effect of innovation in technological finance on discrimination is ambiguous and depends on the future choices made by policymakers, the courts, and firms.

The Digital Transformation of Payment Systems - Libras Impact on the Global Economy
Mesanovic, Enzo
SSRN
This master thesis examines the conceptual and technical specifications of Facebook's Libra project, which provides a comprehensive understanding of the fiat-backed digital currency, the payment system and financial infrastructures for billions of people to be launched in the first half of 2020. The results demonstrate that Libra could potentially accelerate financial inclusion and improve services within the network, but current drawbacks such as the permissioned blockchain and centralized network limit user participation, and resistance from governments, regulators and legislators underlines the disruptive nature of the project, which, if accepted globally, could have a significant impact on the global economy.

The Distributional Short-Term Impact of the COVID-19 Crisis on Wages in the United States
Yonatan Berman
arXiv

This paper uses Bureau of Labor Statistics employment and wage data to study the distributional impact of the COVID-19 crisis on wages in the United States by mid-April. It answers whether wages of lower-wage workers decreased more than others', and to what extent. We find that the COVID-19 outbreak exacerbates existing inequalities. Workers at the bottom quintile in mid-March were three times more likely to be laid off by mid-April compared to higher-wage workers. Weekly wages of workers at the bottom quintile decreased by 6% on average between mid-February and mid-March and by 26% between mid-March and mid-April. The average decrease for higher quintiles was less than 1% between mid-February and mid-March and about 10% between mid-March and mid-April. We also find that workers aged 16-24 were hit much harder than older workers. Hispanic workers were also hurt more than other racial groups. Their wages decreased by 2-3 percentage points more than other workers' between mid-March and mid-April.

The Effect of Bank Monitoring on Loan Repayment
Branzoli, Nicola,Fringuellotti, Fulvia
SSRN
Monitoring is one of the main activities explaining the existence of banks, yet empirical evidence about its effect on loan outcomes is scant. Using granular loan-level information from the Italian Credit Register, we build a novel measure of bank monitoring based on banksâ€™ requests for information on their existing borrowers and we investigate the effect of bank monitoring on loan repayment. We perform a causal analysis exploiting changes in the regional corporate tax rate as a source of exogenous variation in bank monitoring. Our identification strategy is supported by a theoretical model predicting that a decrease in the tax rate improves bank incentives to monitor borrowers by increasing returns from lending. We find that bank monitoring reduces the probability of a delinquency in a substantial way and that the effect is stronger for the types of loans that benefit most from bank oversight, such as term loans.

The Effect of Common Ownership on Investment Decisions under Uncertainty
Baek, In Gyun,Kwon, Sewon,Lynch, Dan
SSRN
This paper examines the effects of firm-level common ownership on the level and efficiency of investment when firms face uncertainty. There is a current debate about the costs and benefits of common ownership, whereby a firm owns large stakes in multiple companies in the same industry. Critics of common ownership argue that it reduces competition and leads to a deadweight loss for the economy through decreased investment. Proponents of common ownership suggest that it allows firms to increase investment due to a reduced threat of involuntary knowledge spillover to rivals. This study contributes to this debate by examining the effects of uncertainty on these relationships. We find that common ownership allows firms to enjoy the value of waiting in the presence of uncertainty resulting in decreased investment that is more efficient. In contrast, common ownership increases investment when uncertainty is low, but these investments are less efficient. These results indicate that common ownership provides benefits to firms in the face of high uncertainty, but also allows firms to engage in value-destroying activities when uncertainty is low. These findings are important to regulators as they debate regulations that could limit common ownership.

The Improvement in Life Expectancy: Systematic Literature Review of Retirement Saving
Jantan, Mohd Sedek
SSRN
The motivations of this study are to analyse issues in the retirement-pension system and to overcome issues in retirement saving faced by households. The systematic literature review on retirement savings is able to provide clear insight, aiming to identify the implication from increased life expectancy on the household retirement savings from the individual's viewpoint and of the other stakeholders, next of kin, government and financial institutions. The literature review will be based on the studies published between 1975 to early 2019 in major database namely Scopus and Web of Science (WoS). The SLR uses the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol. The concern about retirement savings has increased since the year 2000. This concern brought a number of researchers to study the relatedness and impact of life expectancy and retirement. From the 134 shortlisted articles, only four were published before 1990. The retirement issues focused on these systematic literature reviews are divided into two areas; the longevity risk of retirement plan and adequacy retirement saving.

The Interbank Market Puzzle
Allen, Franklin,Covi, Giovanni,Gu, Xian,Kowalewski, Oskar,Montagna, Mattia
SSRN
This study documents significant differences in the interbank market lending and borrowing levels across countries. We argue that the existing differences in interbank market usage can be explained by the trust of the market participants in the stability of the countryâ€™s banking sector and counterparties, proxied by the history of banking crises and failures. Specifically, banks originating from a country that has lower level of trust tend to have lower interbank borrowing. Using a proprietary dataset on bilateral exposures, we investigate the Euro Area interbank network and find the effect of trust relies on the network structure of interbank markets. Core banks acting as interbank intermediaries in the network are more significantly influenced by trust in obtaining interbank funding, while being more exposed in a community can mitigate the negative effect of low trust. Country-level institutional factors might partially substitute for the limited trust and enhance interbank activity.

The Natural Capital Indicator Framework (NCIF): A framework of indicators for national natural capital reporting
Alison Fairbrass,Georgina Mace,Paul Ekins,Ben Milligan
arXiv

It is now widely recognised that components of the environment play the role of economic assets, termed natural capital, that are a foundation of social and economic development. National governments monitor the state and trends of natural capital through a range of activities including natural capital accounting, national ecosystem assessments, ecosystem service valuation, and economic and environmental analyses. Indicators play an integral role in these activities as they facilitate the reporting of complex natural capital information. One factor that hinders the success of these activities and their comparability across countries is the absence of a coherent framework of indicators concerning natural capital (and its benefits) that can aid decision-making. Here we present an integrated Natural Capital Indicator Framework (NCIF) alongside example indicators, which provides an illustrative structure for countries to select and organise indicators to assess their use of and dependence on natural capital. The NCIF sits within a wider context of indicators related to natural, human, social and manufactured capital, and associated flows of benefits. The framework provides decision-makers with a structured approach to selecting natural capital indicators with which to make decisions about economic development that take into account national natural capital and associated flows of benefits.

The Savings Banks in the Context of Corporate Social Responsibility (Las Cajas de Ahorros en el Ã¡mbito de la responsabilidad social corporativa)
QuintÃ¡s-Seoane, Juan-RamÃ³n
SSRN
English Abstract: For many people, besides generating value for shareholders, the modern company has responsibilities towards groups with an interest in its management (stakeholders). This view of corporate social responsibility is especially important in financial institutions owing to the quasi public nature of the services they provide and to their importance for economic development. The author contends that the Spanish savings banks have been genuine pioneers of this new conception, which is inscribed in their founding principles, and examines in depth the four areas in which CSR is embodied in the savings banks: good government, social and environmental dimen- sion of internal and external relations, the social approach to financial activity, and the social works characteristics of these institutions.Spanish Abstract: Para muchos, la empresa moderna, ademÃ¡s de la generaciÃ³n de valor para los accionistas, tiene responsabilidades respecto a grupos interesados en su gestiÃ³n (stakeholders). Esa visiÃ³n de la responsabilidad social corporativa de la empresa es especialmente importante en las entidades financieras por la naturaleza cuasi pÃºblica de los servicios que producen y por su significado para el desarrollo econÃ³mico. El autor sostiene que las cajas de ahorros espaÃ±olas han sido verdaderas pioneras de esa nueva concepciÃ³n, que estÃ¡ inscrita en sus principios fundacionales, y analiza con detenimiento los cuatro Ã¡mbitos en que la RSC se concreta en la caja de ahorros: buen gobierno, dimensiÃ³n social y medioambiental de las relaciones internas y externas, el enfoque social de la actividad financiera y la obra social caracterÃ­stica de estas instituciones.

The socio-economic determinants of the coronavirus disease (COVID-19) pandemic
Viktor Stojkoski,Zoran Utkovski,Petar Jolakoski,Dragan Tevdovski,Ljupco Kocarev
arXiv

The magnitude of the coronavirus disease (COVID-19) pandemic has an enormous impact on the social life and the economic activities in almost every country in the world. Besides the biological and epidemiological factors, a multitude of social and economic criteria also govern the extent of the coronavirus disease spread in the population. Consequently, there is an active debate regarding the critical socio-economic determinants that contribute to the resulting pandemic. In this paper, we contribute towards the resolution of the debate by leveraging Bayesian model averaging techniques and country level data to investigate the potential of 29 determinants, describing a diverse set of socio-economic characteristics, in explaining the coronavirus pandemic outcome. We show that the true empirical model behind the coronavirus outcome is constituted only of few determinants, but the extent to which each determinant is able to provide a credible explanation varies between countries due to their heterogeneous socio-economic characteristics. To understand the relationship between the potential determinants in the specification of the true model, we develop the coronavirus determinants Jointness space. In this space, two determinants are connected with each other if they are able to jointly explain the coronavirus outcome. As constructed, the obtained map acts as a bridge between theoretical investigations and empirical observations, and offers an alternate view for the joint importance of the socio-economic determinants when used for developing policies aimed at preventing future epidemic crises.

Unappropriated Dollars: The Fed's Ad Hoc Lending Facilities and the Rules That Govern Them
Menand, Lev
SSRN
In response to the spread of COVID-19, the Federal Reserve has established fourteen ad hoc facilities to lend to financial firms, foreign central banks, nonfinancial businesses, and state and local governments. This Article reviews these facilities, explains what they are for, and examines the statutory rules that govern them. It distinguishes between seven liquidity facilities designed to backstop deposit substitutes issued by shadow banks and seven credit facilities designed to invest directly in the real economy. Ten of these facilities â€" three of the liquidity facilities and all seven of the credit facilities â€" are contemplated by the CARES Act, which appropriates money for the Treasury Secretary to invest in them. But all ten are inconsistent with at least one of the following three provisions of existing law, none of which the CARES Act explicitly amends: (1) section 13(3)(B)(i) of the Federal Reserve Act, which requires the Fed to ensure that 13(3) lending is â€œfor the purpose of providing liquidity to the financial systemâ€; (2) section 13(3)(A), which requires the Fed to â€œobtain evidenceâ€ that participants are â€œunable to secure adequate credit accommodationsâ€ from other banks; and (3) section 10(a) of the Gold Reserve Act, codified at 31 U.S.C. Â§ 5302, which limits the Treasury Secretary to using the Exchange Stabilization Fund to â€œdealâ€ in â€œsecuritiesâ€ consistent with â€œa stable system of exchange rates.â€ Of the four liquidity facilities not contemplated by the CARES Act, two are inconsistent with any reasonable interpretation of section 14(2)(b) of the Federal Reserve Act, which authorizes the Fed to buy and sell government debt only â€œin the open market,â€ and one is inconsistent with a similar requirement in section 14(1) regarding foreign currency. (Although these facilities are permitted by sections 13(13) and 13(3) respectively.) Hence thirteen of the Fedâ€™s fourteen facilities as currently constituted are in tension with either the Federal Reserve Act, the Gold Reserve Act, or both. Three conclusions follow. First, most of the Fedâ€™s current, critical lending activities are an exception to the baseline statutory framework, permissible only in conjunction with the CARES Act. Second, Congressâ€™s failure to amend that framework is obscuring the fact that it is asking the Fed to take on substantial new responsibilities â€" ones for which it was not designed and which it may struggle to discharge. Third, Congress should update our money and banking laws to clarify the rules governing Fed lending, reduce the need for monetary backstops, and improve the governmentâ€™s ability to respond quickly and effectively to fiscal emergencies in the future.â€ƒ

Yield Curve Quantization and Simulation with Neural Networks
Benedetti, Giuseppe
SSRN
We present a method for simulating yield curve dynamics by learning the curve distribution from historical data using Artificial Neural Networks (ANN) in a two step procedure. The first step involves an autoencoder which performs a quantization of curve moves, generating a set of representative curve shapes. The second step learns a probability distribution over the quantized shapes, conditional on the current curve and the shift of a single pivot tenor point. This allows to simulate the curve by first drawing the the pivot tenor shift and then the shape of the curve move from its dynamic distribution. A suitable choice of regularizers allows to keep the simulation statistics close to the original data.