Research articles for the 2021-05-13

A Bayesian Long Short-Term Memory Model for Value at Risk and Expected Shortfall Joint Forecasting
Zhengkun Li,Minh-Ngoc Tran,Chao Wang,Richard Gerlach,Junbin Gao
arXiv

Value-at-Risk (VaR) and Expected Shortfall (ES) are widely used in the financial sector to measure the market risk and manage the extreme market movement. The recent link between the quantile score function and the Asymmetric Laplace density has led to a flexible likelihood-based framework for joint modelling of VaR and ES. It is of high interest in financial applications to be able to capture the underlying joint dynamics of these two quantities. We address this problem by developing a hybrid model that is based on the Asymmetric Laplace quasi-likelihood and employs the Long Short-Term Memory (LSTM) time series modelling technique from Machine Learning to capture efficiently the underlying dynamics of VaR and ES. We refer to this model as LSTM-AL. We adopt the adaptive Markov chain Monte Carlo (MCMC) algorithm for Bayesian inference in the LSTM-AL model. Empirical results show that the proposed LSTM-AL model can improve the VaR and ES forecasting accuracy over a range of well-established competing models.



A Reexamination of Factor Momentum:How Strong is It?
Fan, Minyou,Li, Youwei,Liao, Ming,Liu, Jiadong
SSRN
Recent studies have shown that most financial market anomalies exhibit a momentum effect. Based on a dataset covering 20 factors, we find that the factor momentum effect is weak in general. Six factors exhibit strong return continuation and dominate the factor momentum portfolio, while the remaining 14 factors do not. The choice of factors affects the ability of factor momentum to explain individual stock momentum. We uncover why the betting against beta factor exhibits the strongest factor momentum. This is because of its unique rank weighting scheme, whereas all the remaining factors are based on value-weighted portfolios.

Bitcoin Under Inflation-Hedging Scrutiny - The Extended Fisher Hypothesis in Crypto
Swiatkowski, Jan
SSRN
Improved access to the scarce, digital resource justifies analyzing Bitcoin from a macroeconomic perspective. Using ten years of historical monthly returns, this study examines Bitcoin’s hedging capabilities with respect to inflation measures following the Fisher hypothesis. Short-term interest rates are used to split the ex post ob- served inflation into an ex ante expected and unexpected part by apply- ing auto-regressive distributed lag models. Having 40 countries under scrutiny, the results show that Bitcoin has partial hedging capabilites against expected inflation in specific countries. In a cross-sectional view on expected inflation, rolling window regressions reveal a diminishing number of significant inflation betas over time.

Climate Risk is Investment Risk
Scanlan, Melissa K.
SSRN
In January of 2020, BlackRock, the world’s largest asset managerwith over seven trillion dollars under management at that time,announced it was placing environmental sustainability at the center ofits investment approach because it had concluded that climate risk wasinvestment risk. It warned of a very rapid movement of capital toward“sustainable” businesses. The coronavirus pandemic has intensifiedthe appeal of sustainable investing. There is a push in the United Statesand the European Union to rethink the purpose of investor-ownedcorporations in light of the unprecedented need to deeply decarbonizethe global economy and meet the Sustainable Development Goals on avery short timeframe. Without making substantive legal reforms, acommon ground in this debate appears to be to reduce risks bypromoting transparency and accountability. These values are aided byaccurate and thorough reporting of a corporation’s environmental andsocial impacts, which facilitates investors’ ability to manage risk, andcan inform broader public policy. Sustainability reporting also servesan internal purpose for boards of directors, alerting them about theeffect the business is having on the environment and society, systemicrisks, and ability of the company to achieve success in the long term.There is a growing awareness that a well-run company should havelong-term plans charting its way toward environmental, social, andeconomic sustainability: the triple bottom line. One step in thedirection of this call for transparency and accountability occurred in2017 when the EU Non-Financial Reporting Directive becameeffective. This new law requires EU publicly traded corporations andfinancial and insurance institutions with more than 500 employees toreport on environmental, social, and governance metrics. Strategicallyincreasing access to information holds promise because it movescorporate social responsibility out of the voluntary realm; but earlyresults already indicate areas where the law needs to be improved.This Article will explain how the climate crisis places a new focus onthe purpose of the corporation; private governance and voluntarysustainability reporting; and the new mandatory reporting approach inthe EU, its limitations and potential reforms, and possible replicationin the United States.

Creating Controversy in Proxy Voting Advice
Malenko, Andrey,Malenko, Nadya,Spatt, Chester S.
SSRN
The quality of proxy advisors' voting recommendations is important for policymakers and industry participants. We analyze the design of recommendations (available to all market participants) and research reports (available only to subscribers) by a proxy advisor, whose objective is to maximize its profits from selling information to shareholders. We show that even if all shareholders' interests are aligned and aim at maximizing firm value, the proxy advisor benefits from biasing its recommendations against the a priori more likely alternative. Such recommendations "create controversy" about the vote, increasing the probability that the outcome is close and raising each shareholder's willingness to pay for advice. In contrast, it serves the interest of the proxy advisor to make private research reports unbiased and precise. Our results help reinterpret empirical patterns of shareholders' voting behavior.

Cómo evitar otra crisis de derivados: Manejo de riesgos para mercados emergentes (How To Avoid Another Derivative Crisis: Risk Management for Emerging Markets)
Al Janabi, Mazin A. M.
SSRN
Spanish Abstract: Las pérdidas reportadas por empresas e instituciones financieras generaron mucha alarma y preocupación en la sociedad, así como debate y confusión sobre el uso apropiado de los instrumentos derivados. ¿Fueron los derivados responsables de estas pérdidas o simplemente su mal manejo? Lo cierto es que los valores derivados pueden controlar y cubrir eficazmente los riesgos financieros, pero su uso incontrolado puede ser muy peligroso. En el capítulo “Derivative Products in Emerging Markets and Prudential Regulations”, incluido en la monografía Emerging Markets: Recent Developments, Challenges and Future Prospects (Nova, 2018), examino los cambios observados en años recientes en las transacciones de derivados en mercados emergentes como México. Desde mi experiencia como gestor e investigador en gestión de riesgos y productos derivados, analizo los principales obstáculos para el uso adecuado de estos instrumentos, así como recomendaciones prácticas con el fin de utilizar plataformas operativas eficientes, regulaciones rigurosas y vigilancia efectiva para desalentar la morosidad y las operaciones ilegales dentro de la industria de servicios financieros.English Abstract: The losses reported by companies and financial institutions caused enormous alarm and concern in society, as well as debate and confusion on the appropriate use of derivatives instruments. Were derivatives responsible for these losses or was it simply their poor management? The fact is that while derivatives securities can effectively control and hedge financial risks, their uncontrolled use can be very dangerous. The chapter “Derivative Products in Emerging Markets and Prudential Regulations”, included in the monography Emerging Markets: Recent Developments, Challenges and Future Prospects (Nova Science Publishers, Inc., New York, 2018), examined the recent changes observed in derivatives trading in emerging markets, such as Mexico. In my experience as a practitioner and researcher of risk management and derivative products, I analyze the main obstacles to the adequate use of these instruments and offer practical recommendations for the use of efficient operational platforms, rigorous regulations and effective surveillance to discourage delinquencies and rogue trading within the financial service industry.

Determinants of Nonperforming Loans: A Review of Empirical Evidence
Syed, Aamir
SSRN
[enter Abstract Body]Purpose: The main purpose of this chapter is to thoroughly investigate the diverse literature available concerning nonperforming loans (NPLs) and its determinants by studying and analyzing the empirical studies from 1985 to 2019.Design/Methodology: A qualitative approach is being incorporated, and by using content analysis, various previous studies are reviewed and impor- tant issues like the objectives, methodology, key findings, and variables are reported.Findings: The study tries to compile the main findings from the various studies done concerning NPLs and its determinants. The study shows how various determinants both bank-specific and macroeconomic affect the banking structure and thus the NPLs, in different countries and at different periods of time. The study also highlights how countries’ bank- ing structure got affected by various economic phenomena like recession, contagious effect of the financial crisis, banking Basel norms, and NPL management strategies. Further major issues like data acquisition, lack of data reporting, countries specific banking conditions, methodologies used in the analysis, scarce resources, and disclosure hindrance which are faced by previous studies were also reported.Originality/Value: As there are very few studies that provide a detailed viewpoint on NPLs and its determinants in this area, this research will provide a concise and detailed framework for the researchers to analyses the diverse literature on NPLs and its determinates.

Do City Borders Constrain Ethnic Diversity?
Scott W. Hegerty
arXiv

U.S. metropolitan areas, particularly in the industrial Midwest and Northeast, are well-known for high levels of racial segregation. This is especially true where core cities end and suburbs begin; often crossing the street can lead to physically similar, but much less ethnically diverse, suburban neighborhood. While these differences are often visually or "intuitively" apparent, this study seeks to quantify them using Geographic Information Systems and a variety of statistical methods. 2016 Census block group data are used to calculate an ethnic Herfindahl index for a set of two dozen large U.S. cities and their contiguous suburbs. Then, a mathematical method is developed to calculate a block-group-level "Border Disparity Index" (BDI), which is shown to vary by MSA and by specific suburbs. Its values can be compared across the sample to examine which cities are more likely to have borders that separate more-diverse block groups from less-diverse ones. The index can also be used to see which core cities are relatively more or less diverse than their suburbs, and which individual suburbs have the largest disparities vis-\`a-vis their core city. Atlanta and Detroit have particularly diverse suburbs, while Milwaukee's are not. Regression analysis shows that income differences and suburban shares of Black residents play significant roles in explaining variation across suburbs.



Do insiders use audit findings? Evidence from the expanded audit report in the United Kingdom
Gutierrez, Elizabeth F.,Korczak, Adriana,Vulcheva, Maria
SSRN
In this paper, we examine the association between the contents of the expanded audit report, which was adopted in 2013, and insider trading in the United Kingdom. Pre/post analyses indicate that following adoption of the expanded report, the likelihood and volume of insider trading in the period between an earnings announcement and publication of the audit report do not change. In cross-sectional tests of the post-adoption period only, we find that insiders trade based on auditors’ materiality disclosures both before and after the expanded report is published, but the association between insider trading and the number of risks of material misstatement is significant only in the period after the report’s publication. We attribute our findings to the availability and ease of interpretation of audit disclosures and insiders’ desire to minimize their legal and reputational risks. Our findings speak to the usefulness of the mandated information in the expanded audit report and the importance of timing for audit report publication.

Equity Returns, Bond Spreads, and Economic Activity in Emerging Countries
Horvath, Jaroslav,Yang, Guanyi
SSRN
While simultaneously accounting for the effects of sovereign and corporate bond spreads, we document that emerging market economy (EME) equity returns have a strong predictive power for future output growth and account for a significant fraction of output fluctuations in these countries. Our results are based on the environment of Caballero, Fernandez, and Park (2019), who show that corporate bond spreads are a better driver of EME economic activity than sovereign bond spreads. We find that equity returns, a proxy of domestic and external financial conditions, play a more important role for EME output growth than both types of bond spreads. We attribute this difference to the effectiveness of equity returns in transmitting global financial risk shocks to EMEs and to the role of equity issuance in international capital flows in EMEs.

Explainable Machine Learning-driven Strategy for Automated Trading Pattern Extraction
Artur Sokolovsky,Luca Arnaboldi,Jaume Bacardit,Thomas Gross
arXiv

Financial markets are a source of non-stationary multidimensional time series which has been drawing attention for decades. Each financial instrument has its specific changing over time properties, making their analysis a complex task. Improvement of understanding and development of methods for financial time series analysis is essential for successful operation on financial markets. In this study we propose a volume-based data pre-processing method for making financial time series more suitable for machine learning pipelines. We use a statistical approach for assessing the performance of the method. Namely, we formally state the hypotheses, set up associated classification tasks, compute effect sizes with confidence intervals, and run statistical tests to validate the hypotheses. We additionally assess the trading performance of the proposed method on historical data and compare it to a previously published approach. Our analysis shows that the proposed volume-based method allows successful classification of the financial time series patterns, and also leads to better classification performance than a price action-based method, excelling specifically on more liquid financial instruments. Finally, we propose an approach for obtaining feature interactions directly from tree-based models on example of CatBoost estimator, as well as formally assess the relatedness of the proposed approach and SHAP feature interactions with a positive outcome.



First Come, First Served: The Timing of Government Support and Its Impact on Firms
Denes, Matthew,Lagaras, Spyridon,Tsoutsoura, Margarita
SSRN
We study the effects of deploying government capital to firms during crises. Using exogenous variation in the timing of disbursements in the Paycheck Protection Program (PPP), we find that firms receiving PPP loans later become more financially distressed and face reductions in credit supply. These effects are amplified for firms with heightened financial constraints. We also show that firms receiving loans later have lower economic activity using in-store activity and shutdowns. The results are consistent with a direct channel on firm operations and a financing channel. Overall, our findings highlight the role of timely and uninterrupted fiscal support during crises.

How Unique is Milwaukee's 53206? An Examination of Disaggregated Socioeconomic Characteristics Across the City and Beyond
Scott W. Hegerty
arXiv

Milwaukee's 53206 ZIP code, located on the city's near North Side, has drawn considerable attention for its poverty and incarceration rates, as well as for its large proportion of vacant properties. As a result, it has benefited from targeted policies at the city level. Keeping in mind that ZIP codes are often not the most effective unit of geographic analysis, this study investigates Milwaukee's socioeconomic conditions at the block group level. These smaller areas' statistics are then compared with those of their corresponding ZIP codes. The 53206 ZIP code is compared against others in Milwaukee for eight socioeconomic variables and is found to be near the extreme end of most rankings. This ZIP code would also be among Chicago's most extreme areas, but would lie near the middle of the rankings if located in Detroit. Parts of other ZIP codes, which are often adjacent, are statistically similar to 53206, however--suggesting that a focus solely on ZIP codes, while a convenient shorthand, might overlook neighborhoods that have similar need for investment. A multivariate index created for this study performs similarly to a standard multivariate index of economic deprivation if spatial correlation is taken into account, confirming that poverty and other socioeconomic stresses are clustered, both in the 53206 ZIP code and across Milwaukee.



How the 'Auction Cube' Supports the Selection of Auction Designs in Industrial Procurement
Gregor Berz,Florian Rupp,Brian Sieben
arXiv

It is well known that rightly applied reverse auctions offer big commercial potential to procurement departments. However, the sheer number of auction types often overwhelms users in practice. And since the implications of a wrongly chosen auction type are equally well known, the overall usage of reverse auctions lacks its potential significantly. In this paper, a novel method is being proposed that guides the user in selecting the right combination of basic auction forms for single lot events, considering both market-, as well as supplier-related, bijective criteria.



If He's Still in, I'm Still in! How Reddit Posts Affect Gamestop Retail Trading
Betzer, André,Harries, Jan Philipp
SSRN
In January 2021, the stock price of NASDAQ-listed GameStop Corporation surged more than thirty-fold following frenzied discussions on a Reddit forum. While Social Media-organized retail trading is not a new phenomenon, the magnitude of the resulting swings in GameStop's share price in combination with a short- and/or gamma squeeze scenario is unprecedented. Using financial data as well as an extensive dataset of Reddit posts, we show that Reddit posts lead to increased retail trading activity in GameStop shares and introduce a new option-based measure for retail trading proportion which could help academics, regulators and investors to track and analyze similar developments in the future.

Internet Search, Fund Flows, and Fund Performance
Chen, Hong-Yi,Chen, Hsuan-Chi,Lai, Christine W.
SSRN
This study uses the Google search volume index as a direct measure of investor attention to explore the connection between attention-grabbing information and fund flows, future performance, and the survivorship of newly issued funds. We find that investors often engage in attention-driven purchases of new funds that have captured their attention online. However, fund investors who conduct internet searches and make attention-driven purchases are less sophisticated and fail to allocate their capital for earning abnormal returns. We also find that attention-induced inflows can help sustain new funds in competitive fund markets via potential mitigation of mergers and liquidations. Our robustness checks show similar results for old funds, but attention-driven fund flows do not enhance the survival of old funds.

Introducing “Focused Firms”: Implications from REIT Prime Operating Revenue
Feng, Zifeng,Liu, Peng
SSRN
We examine the relationship between a firm’s main business focus and its risk and performance, using the unique settings of U.S. equity real estate investment trusts (REITs). In this paper, a REIT’s prime operating revenue ratio (POR) is measured as the ratio of rental revenue to total revenue. The empirical results show that REITs that earn more revenue from their prime businessâ€"property rentalsâ€"are less apt to take on risk but also achieve higher operational performance in the cross-section and over the medium term. The magnitudes of these results in a market crisis period are even stronger than in normal times. We also find evidence that REITs with higher POR are associated with less information asymmetry, higher operational efficiency, and higher market value. We also use three alternative REIT business focus measures based on their assets, expenses, and income. The results are qualitatively and quantitatively similar. To investigate why some REITs focus to a greater extent on non-prime businesses, the paper provides evidence that REIT executives receive, on average, higher pay when their firms engage more extensively in other businesses, and larger REITs are more likely to explore non-rental-revenue businesses. Lastly, we use the coronavirus pandemic as a quasi-experimental setting and provide evidence that REITs that have earned higher POR in recent years generally achieve better operational performance and reduce risk during the first three quarters of 2020. In sum, the results suggest that a REIT’s focus on its prime business generally leads to greater profitability and lower risk.

Labour Regulation and Historical Socio-Economic Context: The UK and France
Gant, Jennifer L. L.
SSRN
Labour regulation is a complex and ever changing area of the law fed by social and economic policy, politics, external and internal pressures, and cultural influences. In isolation, labour regulation is particular to the country in which it is found. However, in a world growing smaller due to a global marketplace, the differences in labour regulation between jurisdictions can become an issue in cross border business transactions and may even affect a multi-national company’s choice of investment or divestment. The flexibility or inflexibility of labour regulation affects the attractiveness of a jurisdiction, as evidenced by the outsourcing of labour intensive sectors of many corporations to developing countries which lack the expense of protective labour regulation and benefit from a cheaper labour force. Law among the Member States of the EU has been in a process of slow convergence since the 1950s. However, if one deconstructs and reconstructs legal systems with a view to determining their core similarities, some exhibit areas of convergence while other aspects remain quite different. Even when one compares those systems which are significantly similar, there remain distinctive characteristics which distinguish one from another. There are differences that seem irreconcilable even within legal groups such as those common law or civil law systems. While certain rules and solutions may seem alike, legal cultures and traditions can differ significantly, leading to fundamental differences in approach to regulation and policy initiatives. These differences in approach are influenced by aspects of culture and history which cannot easily be separated from the legislative process. Convergence therefore becomes more difficult with culture bound areas of the law, such as labour and employment. EU social policy initiatives have aimed to harmonise standards based initially on a minimum floor of rights to a level which is more reflective of what is present in more socially progressive countries, such as France. However, lack of concrete EU wide definitions have made any coordination in social policy difficult. Though similar terms to describe elements of procedure may be used, the ideologies and policies informing the objectives of those procedures result in an asynchronous meaning, creating a barrier to mutual understanding and an obstacle to coordinated action. The question remains then as to how it may be possible to find a means of coordinating the law in order to create a more balanced environment for cross border business. In discovering the influences on the aims of socially oriented regulation, it may be possible to identify areas where coordination and perhaps convergence may be realistically attempted and to work around those areas in which the different social aims make such convergence impossible or at least improbable in the near future. In order to even attempt an alignment of labour systems in the EU, which of itself is a potentially unrealistic suggestion, at least in the current political climate, an understanding of the fundamental values which have influenced a country’s approach labour law is vital. Any EU level coordination would require diplomacy and compromise, a full knowledge and understanding of the elements of the systems being the most important tool to guide any such process. To this end, an analysis of the historical context of labour regulation and the working classes will reveal much about the fundamental values upon which labour systems and employment regulation are based and the differences between them. A typically top down technical analysis would only expose a positivist view of the law, isolated from its constituent parts without which it would not exist in its current form. The comparative perspective such as will be presented is not only useful for the importation of solutions but also for the discovery of other questions which may help find alternatives. This unique methodology could then be relied upon as a means finding a path to greater coordination by attempting to align systemic values. For the purpose of this paper, the UK and France will be compared in order to establish a baseline of differences. The UK and France provide examples of two extremes of current systems of labour law, but are also two of the most powerful and influential countries within the EU, thus providing a sound starting point from which to draw further comparisons in later research.

Machine Learning Classification of Price Extrema Based on Market Microstructure Features: A Case Study of S&P500 E-mini Futures
Artur Sokolovsky,Luca Arnaboldi
arXiv

The study introduces an automated trading system for S\&P500 E-mini futures (ES) based on state-of-the-art machine learning. Concretely: we extract a set of scenarios from the tick market data to train the model and further use the predictions to model trading. We define the scenarios from the local extrema of the price action. Price extrema is a commonly traded pattern, however, to the best of our knowledge, there is no study presenting a pipeline for automated classification and profitability evaluation. Our study is filling this gap by presenting a broad evaluation of the approach showing the resulting average Sharpe ratio of 6.32. However, we do not take into account order execution queues, which of course affect the result in the live-trading setting. The obtained performance results give us confidence that this approach is worthwhile.



Medir el riesgo de liquidez para evitar otra crisis financiera (Liquidity Risk Management in the Avoidance of Another Financial Crisis)
Al Janabi, Mazin A. M.
SSRN
Spanish Abstract: La crisis financiera global puso en evidencia la necesidad de una adecuada identificación y evaluación del riesgo de liquidez implícito en las carteras de inversión. Es indudable que algunos colapsos de entidades financierasâ€" tanto en los mercados desarrollados como emergentes â€", así como las consiguientes turbulencias financieras, fueron causadas, hasta cierto punto, por el impacto del riesgo de liquidez en carteras de acciones estructuradas. Para evaluar los riesgos involucrados en sus operaciones comerciales, las principales instituciones financieras están adoptando cada vez más las técnicas y modelos de Valor en Riesgo (Value at Risk - VaR). También los adaptan a sus rasgos individuales. No existe una manera correcta o incorrecta de medir y gestionar el riesgo de liquidez. Todo depende de los objetivos de cada entidad, las líneas de negocio, el apetito por el riesgo y la disponibilidad de fondos para la inversión en proyectos de gestión del riesgo. Los resultados de este estudio sugieren la inevitabilidad de combinar evaluaciones L-VaR con otros métodos, tales como el análisis de escenarios y pruebas de estrés para captar una visión completa de otros riesgos restantes. En contraste con otros modelos de liquidez comúnmente utilizados, el enfoque que se aplica en este trabajo es más apropiado, ya que considera la liquidación diaria de pequeñas fracciones de los activos tanto de venta corta como posiciones de inversión de largo plazo.English Abstract: The global financial crisis showed us that there is a need for appropriate identification and evaluation of implicit liquidity trading risks in investment portfolios. It is undeniable that many of the financial institution collapses, both in developed and emerging markets, as well as the subsequent financial turbulence, were, to a certain extent, caused by the impact of liquidity trading risk on structured stocks portfolios. In order to evaluate the risks involved in their trading operations, main financial institutions are increasingly adopting Value at Risk [VaR] techniques and models. They are also adapting each of their individual features. There is no right or wrong way to measure or manage liquidity risk. It all depends on the individual objectives of each institution, their lines of business, their risk appetite and the funds available to invest in risk management projects. The results of this study suggest that there is an inevitability of combining L-VaR evaluations with other methods, such as scenario analysis and stress testing to obtain a full view of other existing risks. In contrast to other liquidity models commonly used, the strategy implemented in this study is more suitable, as it takes into consideration the daily liquidation of small fractions of the investment assets from short-selling and long-only trading positions.

Modeling Managerial Search Behavior based on Simon's Concept of Satisficing
Friederike Wall
arXiv

Computational models of managerial search often build on backward-looking search based on hill-climbing algorithms. Regardless of its prevalence, there is some evidence that this family of algorithms does not universally represent managers' search behavior. Against this background, the paper proposes an alternative algorithm that captures key elements of Simon's concept of satisficing which received considerable support in behavioral experiments. The paper contrasts the satisficing-based algorithm to two variants of hill-climbing search in an agent-based model of a simple decision-making organization. The model builds on the framework of NK fitness landscapes which allows controlling for the complexity of the decision problem to be solved. The results suggest that the model's behavior may remarkably differ depending on whether satisficing or hill-climbing serves as an algorithmic representation for decision-makers' search. Moreover, with the satisficing algorithm, results indicate oscillating aspiration levels, even to the negative, and intense - and potentially destabilizing - search activities when intra-organizational complexity increases. Findings may shed some new light on prior computational models of decision-making in organizations and point to avenues for future research.



Modernizing ESG Disclosure
Harper Ho, Virginia E.
SSRN
Nearly a decade ago, the U.S. Securities and Exchange Commission (SEC) began a comprehensive effort to “modernize and simplify” the disclosure rules that apply to U.S. public companies. In that period, investor demand for the SEC to standardize how companies disclose climate-related risk and other “environmental, social, and governance” (ESG) information has risen, and private standard setters, international organizations, and financial regulators outside the U.S. have already introduced ESG reporting frameworks. While the SEC has sought guidance from market participants on possible paths forward, it has previously resisted calls to standardize how material ESG information reaches investors in the face of controversy over the rationale for ESG disclosure reform, its potential costs and benefits, and the precise form any new reporting rules should take. The SEC, and indeed, the U.S. capital markets themselves, are now at a crossroads. As the Biden administration has prioritized a coordinated response to climate change and committed to a climate finance plan, the SEC and Congress must now engage with difficult policy questions as they consider how to implement corporate ESG disclosure reform and whether to pursue a sustainable finance transition.This Article presents a roadmap for modernizing ESG disclosure that can be undertaken directly by the SEC, as well as more ambitious proposals that are a necessary foundation for sustainable finance reform and that could proceed with Congressional authorization. While there is growing consensus about the core goals of both of these paths, this Article is the first to address the key issues that must be resolved in order to transform how ESG information reaches the capital markets. Going beyond prior proposals, this Article advocates a multi-dimensional, tiered approach that will promote greater transparency and comparability of ESG information and also better align the regulatory framework for ESG reporting under the federal securities laws with emerging international standards.

Optimal Algorithmic Monetary Policy
Luyao Zhang,Yulin Liu
arXiv

Centralized monetary policy, leading to persistent inflation, is often inconsistent, untrustworthy, and unpredictable. Algorithmic stable coins enabled by blockchain technology are promising in solving this problem. Algorithmic stable coins utilize a monetary policy that is entirely rule-based. However, there is little understanding about how to optimize the rule. We propose a model that trade-offs between the price and supply stability. We further study the comparative statistics by varying several design features. Finally, we discuss the empirical implications and further research for industry applications.



Optimal Monetary and Macroprudential Policies
Schroth, Josef
SSRN
This paper studies monetary policy in an economy where banks make risky loans to firms and provide liquidity services in the form of deposits to households. For given bank equity, market discipline implies that banks can take more deposits when assets are safer or more profitable. Banks respond to loan losses by making their balance sheets safer\textemdash i.e., they reduce risky lending sharply and accumulate more safe bonds. In contrast, a social planner would respond by making banks temporarily more profitable such that a riskier balance sheet can be maintained. A planner would temporarily reduce the expansiveness of monetary policy to avoid bonds becoming too liquid in support of the liquidity premium banks earn via deposits. Specifically, when bank equity is low, then optimal monetary policy stabilizes output by supporting bank lending rather than employment.

Optimiza tu cartera de inversión en mercados bajistas (Optimize your Investment Portfolio in Bearish Markets)
Al Janabi, Mazin A. M.
SSRN
Spanish Abstract: Desde la crisis financiera global de 2008-2009, las técnicas de VaR (Value-at-Risk - VaR, por sus siglas en inglés) se han convertido en herramientas críticas para monitorear y pronosticar el riesgo de mercado y liquidez de los activos financieros. Estas técnicas de modelación del riesgo financiero, que han sido reconocidas por el Bank for International Settlements (BIS) o el Comité de Basilea sobre suficiencia de capital y regulaciones bancarias, miden y previenen pérdidas potenciales que surgen, no sólo de los cambios en el precio de los valores y de la interdependencia entre diferentes tipos de activos (acciones, divisas, tasas de interés o commodities), sino también de comovimientos negativos de las coberturas de cola (riesgo de evento colateral) en condiciones bajistas del mercado. En la eventualidad de una crisis financiera o una desaceleración del mercado, conviene que exista una modelización adecuada del riesgo de liquidez. Precisamente, la principal ventaja de los modelos VaR es su enfoque en el riesgo a la baja (es decir, el impacto de los resultados de rentabilidad negativa) y su interpretación directa en términos monetarios. Sin embargo, especialmente en tiempos de turbulencias financieras, los modelos VaR tradicionales no toman en cuenta adecuadamente la dependencia no lineal entre los activos de una cartera y se vuelven ineficientes en escenarios de mercado ilíquidos. A pesar de los avances en los modelos de medición, obtener estimaciones precisas del riesgo de liquidez del mercado y su aplicación para optimizar las carteras siguen siendo un desafío para las entidades financieras.English Abstract: Since the 2008-2009 global financial crisis, VaR (Value-at-Risk) techniques have become critical tools for monitoring and predicting the market risk and liquidity of financial assets. These financial risk modeling techniques, which have been recognized by the Bank for International Settlements (BIS) or the Basel Committee on capital adequacy and bank regulations, measure and prevent any potential losses that arise, not only from securities’ price changes and the interdependence between the different types of assets (stocks, currencies, interest rates or commodities), but also from their negative tail co-movements in bearish market conditions. In the event of a financial crisis or market downturn, adequate liquidity risk modeling is advisable. In fact, the main advantage of VaR models is their focus on downside risk (i.e., the impact of the results of negative tails) and their direct interpretation in monetary terms. Nevertheless, particularly in times of financial turbulence, traditional VaR models do not properly consider nonlinear dependence between portfolio assets and become inefficient in illiquid market scenarios. Despite the advances in measurement models, obtaining precise market liquidity risk estimations and applying them to optimize portfolios continues to be a challenge for financial institutions.

Performance and Factor Structure of Green, Grey and Red Securities
Kottas, Ferdinantos
SSRN
The purpose of this research is to determine the factors that are important in explaining the Green (eco-friendly), Grey (neutral), and Red (eco-enemy) EU securities returns. This study investigates the factors that influence performance over time, before and after the crisis (breakpoint, 2009) â€" the analysis is divided into two parts. In the first part, we study the factor structure of our specific universe stocks in each category, and in the second part, we distinguish the financial performance between Green and Red stock. We define Green stocks, those in the primary business that are relatively beneficial to the environment, and Red as, harmful to the environment. Our analysis applies the asset pricing models from the Fama-French Model (3-factor model and 5-factor model) and the Carhart Model (4-factor model) and two-step regression for the comparison models. The research findings show that our asset class underperforms relative to the applied signals from the market index and the other macro-factors. Moreover, the exposures from the global factors are changing from period to period, which shows the depression affected the asset class's sensitivity. However, we observed that the Grey and Red assets were affected more than the Green ones after the slump. Lastly, our firm evidence shows that the Red securities initiate a superior performance compared to Green securities.

Political Risk and Toxic Releases
Chu, Yongqiang,Guo, Savannah (Yuanyuan),Zhao, Daxuan,Zheng, Michael
SSRN
Studying the environmental impact of political risk, we find that firms more exposed to political risk decrease the releases of toxic chemicals and close polluting plants. We also find that the effect is not driven by decreases in production activities and that non-political risk does not have a similar impact. Further analyses reveal that firms more exposed to political risk incur higher environmental regulatory costs and invest more in green technology. Exploiting plausibly exogenous variations in political risk generated by the congressional redistricting following the 2010 decennial census, we show that the effect is likely to be causal. The result suggests that political risk exposure causes firms to reduce toxic releases to mitigate environmental regulatory actions.

Profit or Policy? Cross-Border Syndicated Lending by Chinese State-Owned Banks
Ahonon, Borel,Lin, Luca X.
SSRN
Chinese banks, particularly the state-owned "Big Four" commercial banks, have significantly increased their presence in overseas syndicated loan markets over the past two decades. The Big Four are of great systemic importance as they are also the four largest banks globally by assets as in 2019. Previous evidence has heavily associated state ownership with bank inefficiency. Using borrower-time fixed effect to isolate demand-side factors, we show that foreign syndicated loans involving the Big Four have higher spreads than otherwise identical loans to the same borrowers during the same period, particularly in advanced economies. We find the opposite result in loans to Middle Eastern, Central Asian, and African Countries. Further analyses suggest that higher premia demanded by the Big Four are more likely to be explained by their increased profit sensitivity, with partial privatization and domestic banking market reform achieving success at least to some extent. Our evidence indicates that these megabanks could be becoming more efficient over time.

Quantile Risk-Return Trade-Off
Aslanidis, Nektarios,Christiansen, Charlotte,Savva, Christos S.
SSRN
We investigate the risk-return trade-off on the US and European stock markets. We investigate the non-linear risk-return trade-off with a special eye to the tails of the stock returns using quantile regressions. We first consider the US stock market portfolio. We find that the risk-return trade-off is significantly positive at the upper tail (0.9 quantile), where the upper tail is large positive excess returns. The positive trade-off is as expected from asset pricing models. For the lower tail (0.1 quantile), that is for large negative stock returns, the trade-off is significantly negative. And for the median (0.5 quantile), the risk-return trade-off is insignificant. These results are recovered for the US industry portfolios as well as for Eurozone stock market portfolios.

Revisiting the Implied Remaining Variance framework of Carr and Sun (2014): Locally consistent dynamics and sandwiched martingales
Claude Martini,Iacopo Raffaelli
arXiv

Implied volatility is at the very core of modern finance, notwithstanding standard option pricing models continue to derive option prices starting from the joint dynamics of the underlying asset price and the spot volatility. These models often cause difficulties: no closed formulas for prices, demanding calibration techniques, unclear maps between spot and implied volatility. Inspired by the practice of using implied volatility as quoting system for option prices, models for the joint dynamics of the underlying asset price and the implied volatility have been proposed to replace standard option pricing models. Starting from Carr and Sun (2014), we develop a framework based on the Implied Remaining Variance where minimal conditions for absence of arbitrage are identified, and smile bubbles are dealt with. The key concepts arising from the new IRV framework are those of locally consistent dynamics and sandwiched martingale. Within the new IRV framework, the results of Schweizer and Wissel (2008b) are reformulated, while those of El Amrani, Jacquier and Martini (2021) are independently derived.



Subjective Cash Flow and Discount Rate Expectations
De la O, Ricardo,Myers, Sean
SSRN
Why do stock prices vary? Using survey forecasts, we find that cash flow growth expectations explain most movements in the S&P 500 price-dividend and price-earnings ratios, accounting for at least 93% and 63% of their variation. These expectations comove strongly with price ratios, even when price ratios do not predict future cash flow growth. In comparison, return expectations have low volatility and small comovement with price ratios. Short-term, rather than long-term, expectations account for most price ratio variation. We propose an asset pricing model with beliefs about earnings growth reversal that accurately replicates these cash flow growth expectations and dynamics.

Subjective Cash Flow and Discount Rate Expectations
De la O, Ricardo,Myers, Sean
SSRN
Why do stock prices vary? Using survey forecasts, we find that cash flow growth expectations explain most movements in the S&P 500 price-dividend and price-earnings ratios, accounting for at least 93% and 63% of their variation. These expectations comove strongly with price ratios, even when price ratios do not predict future cash flow growth. In comparison, return expectations have low volatility and small comovement with price ratios. Short-term, rather than long-term, expectations account for most price ratio variation. We propose an asset pricing model with beliefs about earnings growth reversal that accurately replicates these cash flow growth expectations and dynamics.

The Capital Asset Pricing Model
Chen, James Ming
SSRN
The capital asset pricing model (CAPM) is the dominant paradigm in financial risk management. It formalizes mean-variance optimization of a risky portfolio given the presence of a risk-free investment such as short-term government bonds. The CAPM defines the price of financial assets according to the premium demanded by investors for bearing risk in excess of the risk-free return.

The Impact of Social Policy on Cross Border Insolvency
Gant, Jennifer L. L.
SSRN
Cross-border insolvency can often be impeded by the lack of legal coordination between jurisdictions, both in terms of differences in insolvency systems and in other more fundamental differences in legal approach to regulation generally. The European Insolvency Regulation (“EIR”) is one attempt to increase cross-border coordination in an area that is important to business related market activities. While the EIR aims to coordinate insolvency proceedings within the EU, gaps remain between Member state insolvency procedures as well as in other regulations linked to insolvency. The content and even the fundamental aims of regulation differ throughout the EU, exemplified through a comparison between the UK and France below. One legal area that can be a particular obstacle to effective cross-border business coordination is social policy regulation which impacts corporate rescue success.

Time-Varying Relative Risk Aversion: Mechanisms and Evidence
Liu, Xuan,Liu, Haiyong,Cai, Zongwu
SSRN
This paper explores theoretically and empirically the issue of time-varying relative risk aversion. We analytically solve a parsimonious life-cycle portfolio choice model with the preferences given by Greenwood, Hercowitz and Huffman (1988, GHH). Our analytical solution identifies four partial equilibrium effects in our model with GHH preferences on risky shares through two channels, and two net effects whose signs hinge on the value of a key structural parameter. With household-level micro data, our mean and quantile regression results show that wealth negatively affects risky shares and the estimated effects are statistically significant and robust. This finding provides strong evidence to support our theoretical prediction. Thus, we show successfully that our portfolio choice model with GHH preferences provides a plausible underlying mechanism in understanding the wealth effect on risky shares in the microdata. Furthermore, we conclude that such a mechanism alone is not sufficient in explaining how risky shares respond to labor income and labor income risks in the microdata.

Using Machine Learning to Create an Early Warning System for Welfare Recipients
Dario Sansone,Anna Zhu
arXiv

Using high-quality nation-wide social security data combined with machine learning tools, we develop predictive models of income support receipt intensities for any payment enrolee in the Australian social security system between 2014 and 2018. We show that off-the-shelf machine learning algorithms can significantly improve predictive accuracy compared to simpler heuristic models or early warning systems currently in use. Specifically, the former predicts the proportion of time individuals are on income support in the subsequent four years with greater accuracy, by a magnitude of at least 22% (14 percentage points increase in the R2), compared to the latter. This gain can be achieved at no extra cost to practitioners since the algorithms use administrative data currently available to caseworkers. Consequently, our machine learning algorithms can improve the detection of long-term income support recipients, which can potentially provide governments with large savings in accrued welfare costs.



Volatility Spillover and Contagion Effects Between Eurodollar Future and Zero Coupons Markets: Evidence From Italy
Tsiaras, Konstantinos
SSRN
Τhis paper investigates the potential volatility spillover and contagion effects of the Eurodollar futures market and the zero coupons of Banca Fideuram. We consider the zero coupons of Banca Fideuram ending from 2018 to 2033. By employing a bivariate DCC-GARCH model, we show significant volatility spillover effects. Moreover, we use the definition of contagion as suggested by Forbes and Rigobon. They defined contagion as a significant increase in cross-market linkages after a shock. Dynamic conditional correlations reveal contagion effects in sub-periods between the Eurodollar futures market and all the zero coupons of Banca Fideuram.

Willingness to Pay and Attitudinal Preferences of Indian Consumers for Electric Vehicles
Prateek Bansal,Rajeev Ranjan Kumar,Alok Raj,Subodh Dubey,Daniel J. Graham
arXiv

Consumer preference elicitation is critical to devise effective policies for the diffusion of electric vehicles (EVs) in India. This study contributes to the EV demand literature in the Indian context by (a) analysing the EV attributes and attitudinal factors of Indian car buyers that determine consumers' preferences for EVs, (b) estimating Indian consumers' willingness to pay (WTP) to buy EVs with improved attributes, and c) quantifying how the reference dependence affects the WTP estimates. We adopt a hybrid choice modelling approach for the above analysis. The results indicate that accounting for reference dependence provides more realistic WTP estimates than the standard utility estimation approach. Our results suggest that Indian consumers are willing to pay an additional USD 10-34 in the purchase price to reduce the fast charging time by 1 minute, USD 7-40 to add a kilometre to the driving range of EVs at 200 kilometres, and USD 104-692 to save USD 1 per 100 kilometres in operating cost. These estimates and the effect of attitudes on the likelihood to adopt EVs provide insights about EV design, marketing strategies, and pro-EV policies (e.g., specialised lanes and reserved parking for EVs) to expedite the adoption of EVs in India.



¿Mercados bajistas?, así puedes optimizar tu cartera de inversión (How to Optimize your Investment Portfolio in Bearish Markets)
Al Janabi, Mazin A. M.
SSRN
Spanish Abstract: Desde la crisis financiera global de 2008-2009, las técnicas de VaR (Value-at-Risk - VaR, por sus siglas en inglés) se han convertido en herramientas críticas para monitorear y pronosticar el riesgo de mercado y liquidez de los activos financieros. Estas técnicas de modelación del riesgo financiero, que han sido reconocidas por el Bank for International Settlements (BIS) o el Comité de Basilea sobre suficiencia de capital y regulaciones bancarias, miden y previenen pérdidas potenciales que surgen, no sólo de los cambios en el precio de los valores y de la interdependencia entre diferentes tipos de activos (acciones, divisas, tasas de interés o commodities), sino también de comovimientos negativos de las coberturas de cola (riesgo de evento colateral) en condiciones bajistas del mercado. En la eventualidad de una crisis financiera o una desaceleración del mercado, conviene que exista una modelización adecuada del riesgo de liquidez. Precisamente, la principal ventaja de los modelos VaR es su enfoque en el riesgo a la baja (es decir, el impacto de los resultados de rentabilidad negativa) y su interpretación directa en términos monetarios. Sin embargo, especialmente en tiempos de turbulencias financieras, los modelos VaR tradicionales no toman en cuenta adecuadamente la dependencia no lineal entre los activos de una cartera y se vuelven ineficientes en escenarios de mercado ilíquidos. A pesar de los avances en los modelos de medición, obtener estimaciones precisas del riesgo de liquidez del mercado y su aplicación para optimizar las carteras siguen siendo un desafío para las entidades financieras.English Abstract: Since the 2008-2009 global financial crisis, VaR (Value-at-Risk) techniques have become critical tools for monitoring and predicting the market risk and liquidity of financial assets. These financial risk modeling techniques, which have been recognized by the Bank for International Settlements (BIS) or the Basel Committee on capital adequacy and bank regulations, measure and prevent any potential losses that arise, not only from securities’ price changes and the interdependence between the different types of assets (stocks, currencies, interest rates or commodities), but also from their negative tail co-movements in bearish market conditions. In the event of a financial crisis or market downturn, adequate liquidity risk modeling is advisable. In fact, the main advantage of VaR models is their focus on downside risk (i.e., the impact of the results of negative tails) and their direct interpretation in monetary terms. Nevertheless, particularly in times of financial turbulence, traditional VaR models do not properly consider nonlinear dependence between portfolio assets and become inefficient in illiquid market scenarios. Despite the advances in measurement models, obtaining precise market liquidity risk estimations and applying them to optimize portfolios continues to be a challenge for financial institutions.