Research articles for the 2021-07-19

A Classroom Experience to Introduce Behavioral Finance and the Endowment Effect
Itzkowitz, Jennifer,Itzkowitz, Jesse
SSRN
Despite Nobel recognition and far-reaching implications, behavioral finance is only beginning to make its way into finance curricula. As finance professors, we can do better. In this paper, we present a successfully implemented, hands-on exercise based on Richard Thalerâ€™s work which uses the studentâ€™s valuations of an item to demonstrate how they themselves behave in a predictably irrational way. This exercise can play a role in entry level finance classes to introduce behavioral finance and show some of the limitations of one of the fields most basic assumptions: rational choice theory. Additionally, this exercise can be used in a behavioral finance course to demonstrate the endowment effect.

A Data-driven Explainable Case-based Reasoning Approach for Financial Risk Detection
Wei Li,Florentina Paraschiv,Georgios Sermpinis
arXiv

The rapid development of artificial intelligence methods contributes to their wide applications for forecasting various financial risks in recent years. This study introduces a novel explainable case-based reasoning (CBR) approach without a requirement of rich expertise in financial risk. Compared with other black-box algorithms, the explainable CBR system allows a natural economic interpretation of results. Indeed, the empirical results emphasize the interpretability of the CBR system in predicting financial risk, which is essential for both financial companies and their customers. In addition, our results show that the proposed automatic design CBR system has a good prediction performance compared to other artificial intelligence methods, overcoming the main drawback of a standard CBR system of highly depending on prior domain knowledge about the corresponding field.

A DeFi Bank Run: Iron Finance, IRON Stablecoin, and the Fall of TITAN
Saengchote, Kanis
SSRN
Bank runs are a natural phenomenon for financial institutions that issue fixed value liabilities (e.g. money) that are backed by assets with uncertain value. I analyze Iron Finance, a decentralized finance (DeFi) protocol that issues stablecoin (a token with fixed nominal exchange rate: IRON) liabilities in exchange for a basket of other tokens (including a token issued by the protocol itself: TITAN). A combination of mathematical algorithms and incentive to arbitrage is used to maintain the exchange rate peg, but a shock to the protocol sent it into a downward spiral â€" much like a bank run. The incentives built into the protocol to defend the peg exacerbated its unravelling, raising the challenge of how DeFi protocols can address this vulnerability while remaining decentralized.

A Fast Evidential Approach for Stock Forecasting
Tianxiang Zhan,Fuyuan Xiao
arXiv

Within the framework of evidence theory, the confidence functions of different information can be combined into a combined confidence function to solve uncertain problems. The Dempster combination rule is a classic method of fusing different information. This paper proposes a similar confidence function for the time point in the time series. The Dempster combination rule can be used to fuse the growth rate of the last time point, and finally a relatively accurate forecast data can be obtained. Stock price forecasting is a concern of economics. The stock price data is large in volume, and more accurate forecasts are required at the same time. The classic methods of time series, such as ARIMA, cannot balance forecasting efficiency and forecasting accuracy at the same time. In this paper, the fusion method of evidence theory is applied to stock price prediction. Evidence theory deals with the uncertainty of stock price prediction and improves the accuracy of prediction. At the same time, the fusion method of evidence theory has low time complexity and fast prediction processing speed.

A New Attempt to Identify Long-term Precursors for Financial Crisis in the Market Correlation Structures
Anton J. Heckens,Thomas Guhr
arXiv

Prediction of events in financial markets is every investor's dream and, usually, wishful thinking. From a more general, economic and societal viewpoint, the identification of indicators for large events is highly desirable to assess systemic risks. Unfortunately, the very nature of financial markets, particularly the predominantly non-Markovian character as well as non-stationarity, make this challenge a formidable one, leaving little hope for fully fledged answers. Nevertheless, it is called for to collect pieces of evidence in a variety of observables to be assembled like the pieces of a puzzle that eventually might help to catch a glimpse of long-term indicators or precursors for large events - if at all in a statistical sense. Here, we present a new piece for this puzzle. We use the quasi-stationary market states which exist in the time evolution of the correlation structure in financial markets. Recently, we identified such market states relative to the collective motion of the market as a whole. We study their precursor properties in the US stock markets over 16 years, including two crises, the dot-com bubble burst and the pre-phase of the Lehman Brothers crash. We identify certain interesting features and critically discuss their suitability as indicators.

A Peek into the Unobservable: Hidden States and Bayesian Inference for the Bitcoin and Ether Price Series
Constandina Koki,Stefanos Leonardos,Georgios Piliouras
arXiv

Conventional financial models fail to explain the economic and monetary properties of cryptocurrencies due to the latter's dual nature: their usage as financial assets on the one side and their tight connection to the underlying blockchain structure on the other. In an effort to examine both components via a unified approach, we apply a recently developed Non-Homogeneous Hidden Markov (NHHM) model with an extended set of financial and blockchain specific covariates on the Bitcoin (BTC) and Ether (ETH) price data. Based on the observable series, the NHHM model offers a novel perspective on the underlying microstructure of the cryptocurrency market and provides insight on unobservable parameters such as the behavior of investors, traders and miners. The algorithm identifies two alternating periods (hidden states) of inherently different activity -- fundamental versus uninformed or noise traders -- in the Bitcoin ecosystem and unveils differences in both the short/long run dynamics and in the financial characteristics of the two states, such as significant explanatory variables, extreme events and varying series autocorrelation. In a somewhat unexpected result, the Bitcoin and Ether markets are found to be influenced by markedly distinct indicators despite their perceived correlation. The current approach backs earlier findings that cryptocurrencies are unlike any conventional financial asset and makes a first step towards understanding cryptocurrency markets via a more comprehensive lens.

A Probit Estimation of Urban Bases of Environmental Awareness: Evidence from Sylhet City, Bangladesh
arXiv

This paper evaluates the significant factors contributing to environmental awareness among individuals living in the urban area of Sylhet, Bangladesh. Ordered Probit(OPM) estimation is applied on the value of ten measures of individual environmental concern. The estimated results of OPM reveal the dominance of higher education, higher income, and full-employment status on environmental concern and environmentally responsible behavior. Younger and more educated respondents tended to be more knowledgeable and concerned than older and less educated respondents. The marginal effect of household size, middle-income level income, and part-time employment status of the survey respondents played a less significant role in the degree of environmental awareness. Findings also validate the "age hypothesis" proposed by Van Liere and Dunlap (1980), and the gender effect reveals an insignificant role in determining the degree of environmental concern. Environmental awareness among urban individuals with higher income increased linearly with environmental awareness programs which may have significant policy importance, such as environmental awareness programs for old-aged and less-educated individuals, and may lead to increased taxation on higher income groups to mitigate city areas' pollution problems.

A characterisation of cross-impact kernels
Mathieu Rosenbaum,Mehdi Tomas
arXiv

Trading a financial asset pushes its price as well as the prices of other assets, a phenomenon known as cross-impact. We consider a general class of kernel-based cross-impact models and investigate suitable parameterisations for trading purposes. We focus on kernels that guarantee that prices are martingales and anticipate future order flow (martingale-admissible kernels) and those that ensure there is no possible price manipulation (no-statistical-arbitrage-admissible kernels). We determine the overlap between these two classes and provide formulas for calibration of cross-impact kernels on data. We illustrate our results using SP500 futures data.

A lender in need is a lender indeed: Role of fintech lending after natural disasters
Qi, Shusen,Li, Runliang,Sun, Hang
SSRN
Using earthquakes as exogenous demand shocks to the credit market, we explore whether fintech lending can complement traditional banks in face of surged credit demand under a continuous difference-in-differences framework. We find that fintech loans increases significantly after earthquakes, especially in the more severely affected regions. However, the acceptance ratio and the loan rate keep stable pre and post earthquakes, so as the borrower characteristics. Notably, the increase in fintech lending is lower in places where traditional banking networks are more intensive and concentrated, and where there is a larger share of local banks. Therefore, fintech lending is especially helpful in increases peopleâ€™s access to credit in areas where traditional banks are pulling back. Last, we find positive effects of fintech credit in job retention and creation after disasters.

A risk not worth taking - The corporate bond liquidity factor
Dienemann, Fabian
SSRN
This study documents properties of market-wide corporate bond liquidity and tests if liquidity risk is priced. In market downturns, when many investors want to liquidate corporate bonds, transaction costs rise for sellers and fall for buyers. The negative relation between buyer and seller liquidity motivates a new across-measure liquidity factor that incorporates an asymmetric liquidity component. Aggregate liquidity measures are persistent, driven by common systematic components, and predict returns. Shocks to market liquidity drive return variation in the time series. However, this risk exposure is not priced as corporate bonds do not earn a positive cross-sectional liquidity risk premium.

Automatic Fatou Property of Law-invariant Risk Measures
Shengzhong Chen,Niushan Gao,Denny Leung,Lei Li
arXiv

In this paper, we show that, on classical model spaces including Orlicz spaces, every real-valued, law-invariant, coherent risk measure automatically has the Fatou property at every point whose negative part has a thin tail.

Behavioral Economics and Financial Decision Making
Lyons, Angela,Kass-Hanna, Josephine
SSRN
Behavioral economics provides insights into how people process information and make decisions. It also helps to explain why and how people tend to make decisions that are not in their best interest, as opposed to what rational choice theory would suggest. This chapter provides an introduction to behavioral economics and highlights its relevance to understanding and influencing financial decision-making. The chapter explores major cognitive biases that commonly lead to mistakes in financial decisions, such as confirmation bias, overconfidence bias, loss aversion, the endowment effect, and status quo bias. The chapter also highlights the challenges brought about by choice overload, that is the multiplicity of options that overwhelms people and undermines their ability to make appropriate financial decisions. The chapter then discusses how choice architecture and nudges can be used to address the limitations resulting from cognitive biases and choice overload. In particular, we examine default choices, pre-commitment mechanisms, framing, and priming approaches and discuss how these can foster positive financial behaviors. This chapter thus represents a useful starting point for researchers and practitioners interested in developing and applying behavioral economics principles and tools to prompt financial decisions that lead to long-run financial security.

Choosing an Insurer
Kumar, Sonjai
SSRN
This paper is about how customers can choose an insurance company for taking insurance policies based on its financial position. In some market such as in India, the ranking of the insurance companies are based on new business but this paper also gives other variables to select.

Competitive equilibrium always exists for combinatorial auctions with graphical pricing schemes
Marie-Charlotte Brandenburg,Christian Haase,Ngoc Mai Tran
arXiv

We show that a competitive equilibrium always exists in combinatorial auctions with anonymous graphical valuations and pricing, using discrete geometry. This is an intuitive and easy-to-construct class of valuations that can model both complementarity and substitutes, and to our knowledge, it is the first class besides gross substitutes that have guaranteed competitive equilibrium. We prove through counter-examples that our result is tight, and we give explicit algorithms for constructive competitive pricing vectors. We also give extensions to multi-unit combinatorial auctions (also known as product-mix auctions). Combined with theorems on graphical valuations and pricing equilibrium of Candogan, Ozdagar and Parillo, our results indicate that quadratic pricing is a highly practical method to run combinatorial auctions.

Corporate Governance: Literature Review on Agency Costs and Pieces of Evidence on Different Perspectives
Agarwal, Shubhi
SSRN
This article intends to review different pieces of literature that try to establish a link between the tools of corporate governance and agency costs. Tools of corporate governance play a key role in reducing agency costs. This article focuses on reviewing the literature on ownership structure, firm structure, board structure, and remuneration structure extensively. This paper reviews many aspects of ownership structure as well as firm structure i.e. institutional ownership, non-institutional ownership, managerial ownership, firm age, and firm size respectively. The works of literature have cited many way outs as strong institutional ownership, managerial ownership, the board size, frequency of board meetings, board independence, board composition, board ownership, remuneration structure, and firm age as well as the size can be beneficial in eliminating agency costs. This article uses a descriptive research design. A lottery system of random sampling is used while selecting different kinds of literature reviews of ownership as well as remuneration structure. This article takes the 2004-2019-time period for reviewing of literature. The period is selected based on convenience sampling. This extensive review of literature will enlighten the research scholars as well as academicians in understanding the problem of agency and how tools of corporate governance will help in reducing agency costs.

Corporate Leverage and Monetary Policy Effectiveness in the Euro Area
Auer, Simone,Bernardini, Marco,Cecioni, Martina
SSRN
We study the relationship between corporate leverage and the sensitivity of industrial production to monetary policy shocks within the euro-area manufacturing sector. Using polynomial state-dependent local projections, we document a non-linear association. When leverage is low, more indebted industries adjust their production more strongly in response to a monetary policy shock, consistently with a financial accelerator framework. At higher leverage ratios, this positive relationship weakens until it reaches a point where additional leverage is associated with a decrease in sensitivity to monetary policy. We show that this weakening effect is particularly intense within the short-term horizon and in recessions. Our results are consistent with recent studies analyzing the role of default risk in dampening the financial accelerator mechanism.

Day-ahead electricity price prediction applying hybrid models of LSTM-based deep learning methods and feature selection algorithms under consideration of market coupling
Wei Li,Denis Mike Becker
arXiv

The availability of accurate day-ahead electricity price forecasts is pivotal for electricity market participants. In the context of trade liberalisation and market harmonisation in the European markets, accurate price forecasting becomes difficult for electricity market participants to obtain because electricity forecasting requires the consideration of features from ever-growing coupling markets. This study provides a method of exploring the influence of market coupling on electricity price prediction. We apply state-of-the-art long short-term memory (LSTM) deep neural networks combined with feature selection algorithms for electricity price prediction under the consideration of market coupling. LSTM models have a good performance in handling nonlinear and complex problems and processing time series data. In our empirical study of the Nordic market, the proposed models obtain considerably accurate results. The results show that feature selection is essential to achieving accurate prediction, and features from integrated markets have an impact on prediction. The feature importance analysis implies that the German market has a salient role in the price generation of Nord Pool.

Debt Capacity, Cash Holdings, and Financial Constraints
Chen, Hsuan-Chi,Chou, Robin K.,Lin, Chih-Yung,Lu, Chien-Lin
SSRN
This research seeks to clarify the relationship among cash holdings, debt capacity, and financial constraints. Compared with other firms, financially constrained firms show relatively smaller decreases in debt capacity when they hold more cash. Cash holdings also help financially constrained firms receive more bank loans, across different types of debts. Heterogeneous beliefs in loan contracts help explain this relationship. Whereas some predictions indicate that cash can act as a financing source, substituting for debt capacity, this study reveals that cash holdings also can complement debt capacity when a firm is financially constrained.

Decomposing Momentum: Eliminating its Crash Component
SSRN
We propose a purely cross-sectional momentum strategy that avoids crash risk and does not depend on the state of the market. To do so, we simply split up the standard momentum return over months t-12 to t-2 at the highest stock price within this formation period. Both resulting momentum return components predict subsequent returns on a stand-alone basis. However, the long-short returns associated with the first component completely avoid negative skewness since momentum crashes are entirely driven by the second component.

Do Financial Advisors Exploit Responsible Investment Preferences?
Laudi, Marten,Smeets, Paul,Weitzel, Utz
SSRN
An unprecedented number of investors are giving their financial advisors a mandate for socially responsible investing (SRI). Yet, the impact of SRI mandates on consumers is unclear. In a pre-registered lab-in-the-field experiment with 345 professional advisors, we find that advisors charge a premium to SRI clients that cannot be justified by higher effort, skill, or costs. This suggests that advisors exploit the SRI preferences of their clients (who accept these higher fees). In an independent survey, financial regulators predict higher SRI fees but do not predict exploitation. Regulators confirm that our findings are externally valid and require attention from policymakers.

Do good deeds earn chits? Evidence from SEC enforcement against the financial restatements of socially responsible firms
Gao, Ru,Wang, Yujie,Xiang, Yi
SSRN
Focus on a comprehensive set of financial restatements during the 2000-2015 time period, we examine whether the prior investment in CSR biases SECâ€™s decision in picking potential targets for investigation and subsequently influences the likelihood of a firm receiving an SEC's Accounting and Auditing Enforcement Releases (AAERs). Based on a novel database on all SEC formal investigations, our results show that when financial restatement does occur, high CSR firms are less likely to be selected by SEC to start the formal investigation. Subsequently, their prior investment in CSR reduces the likelihood of a firm receiving an Accounting and Auditing Enforcement Releases (AAERs) issued by the SEC and is also negatively associated with the value of monetary penalties levied against the firm. Our results are robust when controlling for the severity of the restatements, the level of firmsâ€™ cooperation with SEC investigation, and firmsâ€™ donation to political campaigns. Moreover, our results are more pronounced when firmsâ€™ headquarters are located in geographical proximity to SEC offices and when restatements are the result of innocent mistakes. Collectively, our results suggest that CSR activity leads to positive ascriptions from SEC, who then temper its potentially negative reactions toward firms after occurrences of restatements.

Do retail investors value environmental impact? A lab-in-the-field experiment with crowdfunders
Siemroth, Christoph,Hornuf, Lars
SSRN
Are investors willing to give up a higher return if the investment generates positive environmental impact? We investigate this question with a decision experiment among crowdfunders, where they choose between a higher return or environmental impact. Overall, 65% of investors choose environmental impact at the expense of a higher return for sufficiently large impact, 14% choose impact independent of the magnitude of impact, while 21% choose the higher return independent of impact. Combining the experimental data with historical investments, we find that investors allocate a larger share of funds to green projects if they value environmental impact more, and if they expect green projects to be more profitable. These findings suggest that investors have a preference for positive environmental impact, and satisfy it by investing in green projects. We further show that the preference for environmental impact is distinct from a preference for positive social impact. Finally, we introduce new survey measures of impact for future use, which are experimentally validated and predict field behavior.

Does CEO Power Affect The Association Between CEO Compensation and Tangible Assets Impairments?
Lee, Kinâ€Wai,Lee, Cheng-Few,Yeo, Gillian H. H.
SSRN
This paper examines the association between CEO compensation and tangible long-lived assets impairment. We find that the level of CEO compensation is negatively associated with the tangible long-lived assets impairment charges. We also document that in firms with CEOs who have more decision-making power, the negative association between CEO compensation and tangible long-lived assets impairment charges is mitigated. Specifically, the negative association between CEO compensation and tangible long-lived assets impairment charges is less pronounced (1) when CEO chairs the board, (2) when CEO is the founder of the firm, (3) when the CEO is involved in the director selection process, and (4) when overall board independence is low.

Empirical evidence on the Euler equation for investment in the US
Guido Ascari,Qazi Haque,Leandro M. Magnusson,Sophocles Mavroeidis
arXiv

The Euler equation model for investment with adjustment costs and variable capital utilization is estimated using aggregate US post-war data with econometric methods that are robust to weak instruments and exploit information in possible structural changes. Various alternative identification assumptions are considered, including external instruments, and instruments obtained from Dynamic Stochastic General Equilibrium models. Results show that the elasticity of capital utilization and investment adjustment cost parameters are very weakly identified. This is because investment appears to be unresponsive to changes in capital utilization and the real interest rate.

Estimation of State Financial Support for Non-Priority Territorial Units Using the Example of Bridge Constructions
Levchenko, Iaroslava,Britchenko, Igor
SSRN
The article discloses the problem of distributing state financial support based on an integrated approach. The study has proved the urgency and necessity of state support for the lowest priority territorial units (regions). It answers the research question of what components need to be included in the methodology for determining state financial support. A comprehensive method for estimating the share of public funds is proposed, taking into account the investment attractiveness of a region (oblast) and the risk of the corresponding region (oblast). To achieve this goal, the following general scientific and special methods and research techniques were used in the work, such as comparative analysis of scientific literature and information sources based on methods of comparison, systematization, and generalization; generalization of the analysis results, as well as logical generation of conclusions and integral assessment.

Faster than Flying: High-Speed Rail, Investors, and Firms
Autore, Don M.,Jiang, Danling,Qin, Lu,Zhu, Hongquan
SSRN
We study the effects of a direct high-speed rail (HSR) service between two cities on investors and firms in China. We find that, after an HSR introduction, investors make more cross-city searches and block purchases of firms in connected cities. An HSR introduction also leads to less co-movement among local stocks and more co-movement between stocks in connected cities. Firms located in more central cities in the HSR network enjoy higher firm valuation, lower cost of equity, and better liquidity, in part through the channel of increased investor recognition. The HSR effects on valuation, cost of equity, and liquidity are more pronounced among small firms and when the connected city-pair distance is below 1,500 km, for which HSR is faster than flying.

Financial Literacy in For-Profit vs Pro-Social Peer-to-Peer Lending
Gonzalez, Laura
SSRN
Fintech applications enable convenient direct access to online lending opportunities and highlight the need for financial literacy. This study examines heuristics and behavioral decisions in for-profit vs. pro-social online Peer-to-Peer (P2P) lending. The goal is to support financial literacy towards borrower inclusion and lender success in P2P platforms. More specifically, this experimental study examines 1,347 lending decisions by 449 finance students. Each participant was asked to make three lending decisions. Testimonials were used to condition participants towards either for-profit or pro-social decision making. The loan applications were identical except for a female or male headshot (vs.an icon) and reports of half the loan being raised in either 3 or 11 days (vs. 7). Data analysis shows that pro-social lenders pursue returns on investment and state a lower trust in P2P borrowers than for-profit lenders. However, compared to for-profit ones, pro-social investors underestimate the risk in P2P lending and overestimate their financial literacy. Second, pro-social investors are more confident than for-profit investors when lending to borrowers highly trusted by other lenders, especially if the popular loan applicant is female. Third, pro-social conditioning increases lending to male applicants who are less trusted by other lenders. Forth, pro-social investors who have experienced financial trauma have greater confidence in bad loan recovery. The findings assist P2P platforms and regulators by highlighting the need for balanced testimonials and transparent comprehensive data analytics on P2P sites.

Form 10-Q Itemization
Yanci Zhang,Tianming Du,Yujie Sun,Lawrence Donohue,Rui Dai
arXiv

The quarterly financial statement, or Form 10-Q, is one of the most frequently required filings for US public companies to disclose financial and other important business information. Due to the massive volume of 10-Q filings and the enormous variations in the reporting format, it has been a long-standing challenge to retrieve item-specific information from 10-Q filings that lack machine-readable hierarchy. This paper presents a solution for itemizing 10-Q files by complementing a rule-based algorithm with a Convolutional Neural Network (CNN) image classifier. This solution demonstrates a pipeline that can be generalized to a rapid data retrieval solution among a large volume of textual data using only typographic items. The extracted textual data can be used as unlabeled content-specific data to train transformer models (e.g., BERT) or fit into various field-focus natural language processing (NLP) applications.

Generalized Feynman-Kac Formula under volatility uncertainty
Bahar Akhtari,Francesca Biagini,Andrea Mazzon,Katharina Oberpriller
arXiv

In this paper we provide a generalization of the Feynmac-Kac formula under volatility uncertainty in presence of discounting. We state our result under different hypothesis with respect to the derivation given by Hu, Ji, Peng and Song (Comparison theorem, Feynman-Kac formula and Girsanov transformation for BSDEs driven by G-Brownian motion, Stochastic Processes and their Application, 124 (2)), where the Lipschitz continuity of some functionals is assumed which is not necessarily satisfied in our setting. In particular, we obtain the $G$-conditional expectation of a discounted payoff as the limit of $C^{1,2}$ solutions of some regularized PDEs, for different kinds of convergence. In applications, this permits to approximate such a sublinear expectation in a computationally efficient way.

Global Gridded Daily CO2 Emissions
Xinyu Dou,Yilong Wang,Philippe Ciais,Frédéric Chevallier,Steven J. Davis,Monica Crippa,Greet Janssens-Maenhout,Diego Guizzardi,Efisio Solazzo,Feifan Yan,Da Huo,Zheng Bo,Zhu Deng,Biqing Zhu,Hengqi Wang,Qiang Zhang,Pierre Gentine,Zhu Liu
arXiv

Precise and high-resolution carbon dioxide (CO2) emission data is of great importance of achieving the carbon neutrality around the world. Here we present for the first time the near-real-time Global Gridded Daily CO2 Emission Datasets (called GRACED) from fossil fuel and cement production with a global spatial-resolution of 0.1{\deg} by 0.1{\deg} and a temporal-resolution of 1-day. Gridded fossil emissions are computed for different sectors based on the daily national CO2 emissions from near real time dataset (Carbon Monitor), the spatial patterns of point source emission dataset Global Carbon Grid (GID), Emission Database for Global Atmospheric Research (EDGAR) and spatiotemporal patters of satellite nitrogen dioxide (NO2) retrievals. Our study on the global CO2 emissions responds to the growing and urgent need for high-quality, fine-grained near-real-time CO2 emissions estimates to support global emissions monitoring across various spatial scales. We show the spatial patterns of emission changes for power, industry, residential consumption, ground transportation, domestic and international aviation, and international shipping sectors between 2019 and 2020. This help us to give insights on the relative contributions of various sectors and provides a fast and fine-grained overview of where and when fossil CO2 emissions have decreased and rebounded in response to emergencies (e.g. COVID-19) and other disturbances of human activities than any previously published dataset. As the world recovers from the pandemic and decarbonizes its energy systems, regular updates of this dataset will allow policymakers to more closely monitor the effectiveness of climate and energy policies and quickly adapt

Government Transparency and Firm-Level Operational Efficiency
Hope, Ole-Kristian,Jiang, Shushu,Vyas, Dushyantkumar
SSRN
We examine the informational role of governments in the private sector in emerging economies. Using a large sample of private firms, we show that governmentsâ€™ ability and willingness to collect and disseminate economic information (government transparency) is positively associated with firm-level operational efficiency and access to external financing. Several cross-sectional analyses corroborate our main findings. We find that the effect of government transparency is stronger for firms operating in weaker alternative information environments. We also find a reduced effect of government transparency in countries with better-developed capital markets that facilitate capital allocation and production efficiency. Additional analyses using the World Bank-supported Open Government Data initiative as a staggered shock to government transparency provides further support to our primary results. Overall, our paper sheds light on the important role played by governments in emerging markets in aggregating and disseminating economic information.

How Have Corporate Codes of Ethics Responded to an Era of Increased Scrutiny?
Loughran, Tim ,McDonald, Bill,Otteson, James
SSRN
Over the past decade, corporate scandals have proliferated. These scandals along with the emergence of the #MeToo movement and Environmental, Social, and Corporate Governance (ESG) mandates, have increased the scrutiny of corporationsâ€™ ethics culture. How have companies responded in terms of the language appearing in their public ethics documents? We compare the Code of Ethics in 2008 versus 2019 for a sample of S&P 500 firms. The general trend is for firms to lengthen their Code of Ethics. On average, the 2019 codes are 28 percent longer (more than 1,690 words) than in 2008. The language of the codes has also changed. Words like bribery, corruption, sustainability, speak up, intimidation, slavery, and human rights all saw significantly higher usage in the later period. We review possible reasons for the dramatic changes, and suggest what questions remain about the motivations behind them. Whether the changes we observe are primarily intrinsically motivated or simply market responses to public pressures is yet to be determined.

How Much Does Racial Bias Affect Mortgage Lending? Evidence from Human and Algorithmic Credit Decisions
Bhutta, Neil,Hizmo, Aurel,Ringo, Daniel
SSRN
We compare mortgage lendersâ€™ credit decisions to algorithmic recommendations â€" on the same set of loan applications â€" from widely used Automated Underwriting Systems (AUS) to assess discrimination. In 2018-19, lenders were more likely to deny minority applicants than non-Hispanic white applicants. This paper is the first to document that â€œcolor-blindâ€ AUS also recommend higher denial rates for minorities. Controlling for AUS recommendation, credit score, debt-to-income ratio, and loan-to-value ratio explains most of the racial and ethnic gaps in denials, although not the entirety. We show that lenders with the largest unexplained racial and ethnic denial gaps tend to also have the largest unexplained denials for non-Hispanic white applicants, suggesting that tight standards on unobservables might explain part of the remaining gaps. Additionally, our analysis of lendersâ€™ reported denial reasons suggests that the remaining gaps could partially reflect differences by race and ethnicity in the successful completion of the final stages of loan approval (e.g. documentation of income). Overall, this evidence suggests a much more limited role for disparate treatment by lenders in the approval process than has been suggested in recent research.

Information-Based Trading in China's Option Markets
Wang, Yan,Zhou, Xin
SSRN
We study China's flagship option market, Shanghai Stock Exchange (SSE) 50 ETF option market, and the information content of trading volume using a proprietary dataset. We find that open buy put-call ratio, defined as put volume over the sum of put and call volumes, of financial institutional investors negatively forecasts future SSE 50 ETF returns. We also estimate an upper bound on the trading volume of volatility strategy straddles. The open buy straddle ratio, defined as the estimated straddle volume over the sum of put and call volumes, of financial institutional investors positively forecasts one-day ahead SSE 50 ETF realised volatility.

Interest Rate Sensitivity as Motivation for Acquisitions: Evidence from Bank Holding Companies
LÃ³pez-VilarÃ³, Joe,Rawson, Caleb,Rowe, Stephen P.
SSRN
We examine the role of interest rate sensitivity for bank acquisitions. We expect that the interest rate sensitivity of a bank impacts the likelihood that it is acquired as the fair value of fixed rate loans increases (decrease) when interest rates decrease (increase) while book values remain unchanged. We find that banks with greater fixed-rate loan portfolios are more likely to be acquired in decreasing rate environments as bank acquirers seek to acquire fixed-rate assets with higher rates than can be achieved through new loan originations. Further, this effect is stronger for targets that cannot fully benefit from their fixed-rate portfolio due to either poor operating performance or a weaker information environment. In further tests we find positive returns for acquirers at the time the fair values of the target are reported. This study sheds light on how bank acquisitions are impacted by interest rate sensitivity in low-rate environments.

Is Capital Reallocation Really Procyclical?
Yang, Lingyan
SSRN
Aggregate reallocation is procyclical. This empirical observation is puzzling given the documented fact that the benefits to reallocation are countercyclical. I show that this procyclicality is entirely driven by reallocation of bundled capital, which is highly correlated with market valuation and bears no consistent relation to measures of productivity dispersion. Reallocation of unbundled capital, on the contrary, is countercyclical and highly correlated with dispersion in productivity growth, both within industry and across industries. To rationalize these facts, I propose a heterogeneous agent model of investment featuring two distinct used-capital markets and a sentiment component. In equilibrium, firms mostly reallocate unbundled capital for productivity gains and bundled capital for real, or perceived synergies in the equity market. Equity overvaluation has two offsetting effects on productivity efficiency: (1) encouraging excessive trading of capital assets in the bundled capital market; (2) easing frictions to reallocation in the unbundled market. Its net impact on aggregate total factor productivity (TFP) relies on the extent to which equity distortion is transmitted to real asset prices.

Is to Forgive to Forget? Sovereign Risk in the Aftermath of a Default
Marchesi, Silvia,Masi, Tania,Bomprezzi, Pietro
SSRN
We examine the link between sovereign defaults and credit risk, by taking into account the depth of a debt restructuring and by distinguishing between commercial and official debt. The focus is on debt restructuring events, which take place at the end of a default spell. We use a novel methodology (JordÃ  and Taylor 2016) to estimate the average treatment effect of a default episode on our outcome variables, agency ratings and bond yield spreads, accounting for the endogeneity of the default. Our results show that the average treatment effect on ratings is negative (and positive for bond spreads) up to seven years following a default, while the opposite holds for a default with official creditors. Our results are robust to using a panel analysis, which allows us to investigate on the importance of the (final) haircut size. Specifically, we and that the rating (spread) variation (increase) is larger for cases with deeper haircuts. Therefore, we and evidence that official and private defaults may have different costs and then induce selective defaults.

Language and Management Forecasts around the World
Guan, Yuyan,Wang, Zheng,Wong, M.H. Franco,Xin, Xiangang
SSRN
Speakers of weak future-time reference (FTR) languages perceive the future as closer and more imminent. In this study, we examine the important question of whether the FTR properties of languages spoken by investors affect their demand for forward-looking information, thereby influencing corporate management forecast practices in different countries. We predict that investors who speak weak-FTR languages are more concerned about the future prospects of their investments and the ability of company management to respond to future changes, leading to a greater demand for management forecasts from these companies. We find that firms in weak-FTR language countries exhibit a greater propensity for and frequency of issuing management forecasts and that they also issue more long-horizon forecasts, compared to those in strong-FTR language countries. Our results hold after controlling for other country-level cultural factors. Within the same countries, firms with more foreign institutional ownership from weak-FTR countries issue more (long-horizon) management forecasts than their counterparts. Finally, firms from strong-FTR countries significantly increase their issuance of (long-horizon) management forecasts, after cross-listing their stocks in Germany, a weak-FTR country. This is the first study to examine language FTR as an antecedent to voluntary disclosures. We document a linguistic trait as a novel investor environment factor that shapes corporate voluntary disclosures and explains the cross-country variations in management forecast practices.

Learning from Trading Activity in Laboratory Security Markets with Higher-Order Uncertainty
SSRN

Lessons To Be Learned From Ukraineâ€™s Positioning in International Rankings: The Need for Institutional Support and Financial Support for Economic Creativity
Britchenko, Igor,Svydruk, Irena,Pidlypnyi, Yurii,Krupskyi, Oleksandr P.
SSRN
Purpose: To develop proposals on the directions of institutional support for the processes of creativity of the Ukrainian economy.Design/methodology/approach: The analysis of trends in the creativity of the Ukrainian economy is carried out and proposals are developed for conceptualizing institutional support for these processes. The authors set out to develop proposals for institutional support for creativity processes and offer recommendations for systematic updating of Ukrainian legislation in the areas of state regulation of high-tech business. The information base was the information materials of the State Statistics Service of Ukraine, Ministry of Economic Development and Trade of Ukraine, the statistical databases of the European Commission, OECD and World Bank for the period 2014â€"2020. The research methodology is based on scientific tools that include comparative analysis and economic and mathematical modeling.Findings: Building a national program of public investment in creative development will allow us to systematically approach the issue of institutional support for technological breakthroughs.Research limitations/implications: Recommendations on the development and improvement of legislative instruments of deregulatory policy, harmonization with European standards are substantiated. Directions of systematic updating of legislation on guaranteeing foreign investment of creative projects and targeted investment of joint research projects of academic science and creative organizations are proposed. The implementation will allow a systematic approach to the issue of institutional support for the technological breakthrough of Ukraine.Originality/value: There is a need to step up institutional activities in the field of organizing research centers, introduce targeted investment in the academic science and research activity of creative organizations.

Mean-$\rho$ portfolio selection and $\rho$-arbitrage for coherent risk measures
Martin Herdegen,Nazem Khan
arXiv

We revisit mean-risk portfolio selection in a one-period financial market where risk is quantified by a positively homogeneous risk measure $\rho$. We first show that under mild assumptions, the set of optimal portfolios for a fixed return is nonempty and compact. However, unlike in classical mean-variance portfolio selection, it can happen that no efficient portfolios exist. We call this situation $\rho$-arbitrage, and prove that it cannot be excluded -- unless $\rho$ is as conservative as the worst-case risk measure.

After providing a primal characterisation of $\rho$-arbitrage, we focus our attention on coherent risk measures that admit a dual representation and give a necessary and sufficient dual characterisation of $\rho$-arbitrage. We show that the absence of $\rho$-arbitrage is intimately linked to the interplay between the set of equivalent martingale measures (EMMs) for the discounted risky assets and the set of absolutely continuous measures in the dual representation of $\rho$. A special case of our result shows that the market does not admit $\rho$-arbitrage for Expected Shortfall at level $\alpha$ if and only if there exists an EMM $\mathbb{Q} \approx \mathbb{P}$ such that $\Vert \frac{\text{d}\mathbb{Q}}{\text{d}\mathbb{P}} \Vert_\infty < \frac{1}{\alpha}$.

Meeting new peers: The effects of Morningstar category reassignment on fund flows and star ratings
Fang, Dawei,Holmen, Martin,Mavruk, Taylan
SSRN
We investigate how the reassignment of a fund's Morningstar category affects fund flow and Morningstar star rating. We find that funds assigned to a different category gain positive abnormal flows and this effect is significant mainly for high-rated funds. Category reassignment does not improve a fund's star rating on average, and flows are less responsive to a star-rating change if the rating change is likely to be driven by category reassignment. The positive abnormal flows captured by high-rated funds after category reassignment are consistent with a visibility story: some investors filter funds by Morningstar category and star rating, and category reassignment makes a fund more visible to a new group of investors if the fund is highly rated. In contrast, a low-rated fund is likely to be selected only by investors who do not refer to the fund's Morningstar information and, hence, gains little visibility from category reassignment. We also find evidence that more sophisticated investors are more likely to consider not only fund rating but also fund category when evaluating fund performance.

MiFID II: the Impact of Double Volume Cap Mechanism on Market Quality
Ran, Zhenkai
SSRN
We provide a comprehensive evaluation of the Double Volume Cap mechanism, a regulation that regularly triggers dark trading suspension based on a stockâ€™s historical dark trading activity. By analysing the impact of each suspension wave occurring between 2018 and 2020, we show that, during the pre-COVID-19 pandemic period, the dark trading suspension improves market liquidity, worsens informational efficiency, and reduces return volatility, whereas, during the post-COVID-19 pandemic period, the suspension imposes exactly opposite effects on market quality. We also find that lifting the dark trading suspension induces exactly opposite impacts, with a larger effect size, compared to triggering suspension, providing more statistically powerful evidence of how dark trading affects market quality. These results imply that the Double Volume Cap mechanism may have brought about many unintended consequences to the market when the market needs liquidity and stability the most and when the suspension is relaxed. Nevertheless, we do identify evidence that the market gradually learns and adapts to the new trading environment as market participants reduce their reliance on dark pools over time, a result consistent with the policymakerâ€™s original objective.

Misvaluation and the Corporate Propensity to Hold Cash
Chen, Hsuan-Chi,Chou, Robin K.,Lu, Chien-Lin
SSRN
This study adopts a new perspective, misvaluation, to explain corporate propensity to hold cash. We find a strong cross-sectional relationship between misvaluation and the propensity to hold cash, which can be attributed to firmsâ€™ equity-raising activities and the exercise of employee stock options. The results are robust after controlling for endogeneity issues. Several additional robustness tests reject alternative explanations, such as precautionary motives, agency conflicts, near-term cash needs, and tax motives. Additionally, the study examines the value of cash and shows that misvaluation can increase the value of cash held by firms that are financially constrained or have greater growth opportunities.

Mobile Payment: Reforming the Banking Sector?
Kholia, Tushar
SSRN
This paper is concentrated on researching and expanding thoughts about different ideas identified with Electronic Payment Systems (EPS) or commonly known as Mobile-Based Payment System including its favorable circumstances, difficulties, and security contemplations. The proposed paper additionally assesses the selection of mobile payment frameworks and the subsequent effect on the economy of a country. Strategies/Statistical Analysis: In this paper, a complete overview of all the parts of electronic payment was led after examination of a few concentrates on online payment frameworks. The latest references and data have been investigated to acquire huge data about electronic payment ecosystems. Discoveries: From the investigation led, it tends to be clarified that despite different issues that utilization of mobile payment represent, these are distinguished as a positive advance towards the monetary improvement of a country. Coincidentally, its maximum capacity can be acknowledged simply by raising its mindfulness among individuals. Applications/Improvements: With the progression in innovation and notoriety of the Internet, the view of making on-the-web transactions will undoubtedly acquire energy. Later on, the payment modes as of now utilized and upheld will see a declining pattern inferable from the various advantages offered by electronic payment frameworks or simply put as Mobile Payments.

Model-free price bounds under dynamic option trading
Ariel Neufeld,Julian Sester
arXiv

In this paper we extend discrete time semi-static trading strategies by also allowing for dynamic trading in a finite amount of options, and we study the consequences for the model-independent super-replication prices of exotic derivatives. These include duality results as well as a precise characterization of pricing rules for the dynamically tradable options triggering an improvement of the price bounds for exotic derivatives in comparison with the conventional price bounds obtained through the martingale optimal transport approach.

Modelling uncertainty in financial tail risk: a forecast combination and weighted quantile approach
Giuseppe Storti,Chao Wang
arXiv

A novel forecast combination and weighted quantile based tail-risk forecasting framework is proposed, aiming to reduce the impact of modelling uncertainty in tail-risk forecasting. The proposed approach is based on a two-step estimation procedure. The first step involves the combination of Value-at-Risk (VaR) forecasts at a grid of quantile levels. A range of parametric and semi-parametric models is selected as the model universe in the forecast combination procedure. The quantile forecast combination weights are estimated by optimizing the quantile loss. In the second step, the Expected Shortfall (ES) is computed as a weighted average of combined quantiles. The quantiles weighting structure for ES forecasting is determined by minimizing a strictly consistent joint VaR and ES loss function of the Fissler-Ziegel class. The proposed framework is applied to six stock market indices and its forecasting performance is compared to each individual model in the universe, a simple average approach and a weighted quantile approach. The forecasting results support the proposed framework.

Monitoring multidimensional phenomena with a multicriteria composite performance interval approach
arXiv

In the last two decades, composite indicators' construction to measure and compare multidimensional phenomena in a broad spectrum of domains has increased considerably. Different methodological approaches are used to summarize huge data sets of information in a single figure. This paper proposes a new approach that consists of computing a multicriteria composite performance interval based on different aggregation rules. The suggested approach provides an additional layer of information as the performance interval displays a lower bound from a non-compensability perspective, and an upper bound allowing for full-compensability. The outstanding features of this proposal are: (i) a distance-based multicriteria technique is taken as the baseline to construct the multicriteria performance interval (ii) the aggregation of distances/separation measures is made using particular cases of Minkowski's $L_p$ metrics; (iii) the span of the multicriteria performance interval can be considered as a sign of the dimensions or indicators balance.

MyPortfolio: The IKEA Effect in Financial Investment Decisions
SSRN
Creating an own financial portfolio has never been easier than today. While the recent literature shows that people overvalue self-built consumer goods ("IKEA effect") we ask the following question: How do investors value and trade a self-built financial portfolio compared to one they did not self-build? Our pre-registered experimental design allows us to rule out any confounding customization, actual ownership, or learning effects. We find that self-building a portfolio significantly increases attachment towards it. However, neither valuation of the portfolio nor trading decisions are affected. Thus, our precise estimates suggest that there is no economically relevant "IKEA effect" in financial investment decisions. These results indicate that common portfolio self-building opportunities per se do not directly distort financial markets.

National Culture and Corporate Investment Efficiency
Abdallah, Wissam,Mira, Svetlana,Abdallah, Abed Al-Nasser
SSRN
This paper explores whether national culture explains the deviation from the optimal investment, as measured by under- and over-investment compared to the optimal investment level, and the impact of this deviation across cultural dimensions on shareholdersâ€™ wealth. Using an international sample of firms listed in 38 countries between 1990 and 2015, we find that assertiveness and gender egalitarianism lead to a greater deviation from the optimal investment whereas institutional and in-group collectivism, as well as future and performance orientation, result in investment policies closer to the optimal investment. Specifically, we find that firms from assertive nations tend to over-invest. In contrast, firms from societies characterized by greater male and female equality, higher institutional and in-group collectivism as well as from societies which reward future performance adopt more conservative investment strategies, and ultimately under-invest. Our results also show that investors are averse to firms which deviate from the optimal investment and they are more sensitive to over-investment than under-investment. Over-investment is valued higher in societies characterized by greater gender equality and future planning but less so in societies that care more about the interest of the collective. To the best of our knowledge, this is the first study exploring the relationship between the national culture and the under- and over-investment policies of a firm and, importantly, whether this deviation affects the wealth of the shareholders. Our results show that national culture plays an essential role in the efficient allocation of investment.

National Wealth and Private Poverty through Civil Law? A review of the book
SchÃ¤fer, Hans-Bernd
SSRN
The central thesis of Katharina Pistor's book is that private law, in conjunction with its increasingly global outreach, serves the interests of the rich and enables â€œrule by lawâ€ (p. 205) rather than a â€œrule of the lawâ€. The rules of contract law, corporate law, insolvency law, property law and private international law are of particular importance in this regard. According to the author, these areas of the law shape or "encode" the domination of resources and capital in ways that increase wealth and inequality. The book seeks to understand, from a jurisprudential perspective, disruptive economic developments such as the Lehman crisis, rising inequality and the lagging of wages behind general economic development in the US and Western industrialised economies, and it makes proposals for legal policy. The English version, published in 2019, has been widely discussed and largely positively reviewed. This essay presents a decidedly critical perspective. It does not doubt important lines of thought in the book but questions central statements and hypotheses made in it.

Nudging Debtors to Pay Their Debt: Two Randomized Controlled Trials
Holzmeister, Felix,Huber, Juergen,Kirchler, Michael,Schwaiger, Rene
SSRN
We conducted two large-scale, highly powered randomized controlled trials intended to encourage consumer debt repayments. In Study 1, we implemented five treatments varying the design of envelopes sent to debtors. We did not find any treatment effects on response and repayment rates compared to the control condition. In Study 2, we varied the letters' contents in nine treatments, implementing factorial combinations of social norm and (non-)deterrence nudges, which were either framed emotively or non-emotively. We find that all nudges are ineffective compared to the control condition and even tend to induce backfiring effects compared to the agency's original letter. Since comparable nudges have been shown to be highly effective in other studies, our study supports the literature, emphasizing that the success of nudging interventions crucially depends on the domain of application.

Optimal sports betting strategies in practice: an experimental review
Matej Uhrín,Gustav Šourek,Ondřej Hubáček,Filip Železný
arXiv

We investigate the most popular approaches to the problem of sports betting investment based on modern portfolio theory and the Kelly criterion. We define the problem setting, the formal investment strategies, and review their common modifications used in practice. The underlying purpose of the reviewed modifications is to mitigate the additional risk stemming from the unrealistic mathematical assumptions of the formal strategies. We test the resulting methods using a unified evaluation protocol for three sports: horse racing, basketball and soccer. The results show the practical necessity of the additional risk-control methods and demonstrate their individual benefits. Particularly, we show that an adaptive variant of the popular fractional Kelly'' method is a very suitable choice across a wide range of settings.

Political uncertainty and institutional herding
Gavriilidis, Konstantinos,KALLINTERAKIS, VASILEIOS,Montone, Maurizio
SSRN
Political uncertainty is a key determinant of investment decisions. Specifically, the uncertainty that surrounds government policy makes beliefs noisier and depresses stock prices. In this paper, we explore whether institutional investors "herd", i.e., mimic each other's trades, in response to political uncertainty. Using U.S. institutional investors' quarterly holding data from 1985 through 2019, we find evidence consistent with our conjecture. We also find that the results are stronger in times of low presidential popularity, and among companies that are politically sensitive. Overall, the findings suggest that the effect of political uncertainty on financial markets is larger than previously thought.

Pricing Ethics in the Foreign Exchange Market: Environmental, Social and Governance Ratings and Currency Premia
Filippou, Ilias,Taylor, Mark P.
SSRN
In this paper, we examine the cross-sectional predictive ability of the Refinitiv Environmental, Social and Governance (ESG) score for returns in the foreign exchange market, using ESG scores aggregated at the national level, and find that ESG is a strong negative predictor of currency returns. Intuitively, investors require a premium for financing low-ESG countries while high-ESG countries offer lower returns and provide a hedge in the bad state of the world. We show that ESG is priced in the cross-section of currency returns. We also consider the different components of ESG and show that its predictability is driven by the environmental pillar of the ESG ratings. The profitability of the ESG currency strategy is not driven by the carry trade and is robust to transaction costs.

Relationship Capital and Financing Decisions
Geelen, Thomas,Morellec, Erwan,Rostova, Natalia
SSRN
Lending relationships matter for firm financing. In a model of debt dynamics, we study how lending relationships are formed and how they impact leverage and debt maturity choices. In the model, lending relationships evolve through repeated interactions between firms and debt investors. Stronger lending relationships lead firms to adopt higher leverage ratios, issue longer term debt, and raise funds from non-relationship lenders when relationship quality is sufficiently high. The maturity of debt contracts issued to non-relationship investors is higher than that of relationship investors. Negative shocks to relationship lenders drastically affect the financing choices of firms with intermediate relationship quality.

Risk Appetite: A Risk Management Tool
Kumar, Sonjai
SSRN
This document discusses in detail the risk appetite, setting the risk appetite, statistical ways ofrepresentation of risk appetite, and factors important for risk appetite. The document also describesthe spread of risk appetite across a 2x2 matrix and from there how risk appetite can be set.

Risk Management in Life Insurance
Kumar, Sonjai
SSRN
This paper discusses the tools and techniques for risk mitigation in Life Insurance

Risk Mitigation, Monitoring and Reporting in Life Insurance Business
Kumar, Sonjai
SSRN
A business value is created by identifying the risks in the business and developing the riskmitigation plan. Only identification of risks is of little use unless an effective advance plan isdeveloped and implemented to reduce either the likelihood or impact or both of the events. Inthis chapter, different methods of risk mitigation are discussed in the life insurance industry. Thechapter also discusses the utility of monitoring of risks and reporting.

Roughness in spot variance? A GMM approach for estimation of fractional log-normal stochastic volatility models using realized measures
Anine E. Bolko,Kim Christensen,Mikko S. Pakkanen,Bezirgen Veliyev
arXiv

In this paper, we develop a generalized method of moments approach for joint estimation of the parameters of a fractional log-normal stochastic volatility model. We show that with an arbitrary Hurst exponent an estimator based on integrated variance is consistent. Moreover, under stronger conditions we also derive a central limit theorem. These results stand even when integrated variance is replaced with a realized measure of volatility calculated from discrete high-frequency data. However, in practice a realized estimator contains sampling error, the effect of which is to skew the fractal coefficient toward "roughness". We construct an analytical approach to control this error. In a simulation study, we demonstrate convincing small sample properties of our approach based both on integrated and realized variance over the entire memory spectrum. We show that the bias correction attenuates any systematic deviance in the estimated parameters. Our procedure is applied to empirical high-frequency data from numerous leading equity indexes. With our robust approach the Hurst index is estimated around 0.05, confirming roughness in integrated variance.

Stock Movement Prediction with Financial News using Contextualized Embedding from BERT
Qinkai Chen
arXiv

News events can greatly influence equity markets. In this paper, we are interested in predicting the short-term movement of stock prices after financial news events using only the headlines of the news. To achieve this goal, we introduce a new text mining method called Fine-Tuned Contextualized-Embedding Recurrent Neural Network (FT-CE-RNN). Compared with previous approaches which use static vector representations of the news (static embedding), our model uses contextualized vector representations of the headlines (contextualized embeddings) generated from Bidirectional Encoder Representations from Transformers (BERT). Our model obtains the state-of-the-art result on this stock movement prediction task. It shows significant improvement compared with other baseline models, in both accuracy and trading simulations. Through various trading simulations based on millions of headlines from Bloomberg News, we demonstrate the ability of this model in real scenarios.

Tax haven incorporation and financial reporting transparency
Lewellen, Christina
SSRN
A widespread perception exists that tax havens facilitate corporate opacity. This study provides new evidence on the association between tax havens and the transparency of firm financial reporting using a unique group of firms whose parent companies are incorporated in tax havens but whose headquarters or primary operationsâ€"that is, their baseâ€"are in nonhaven countries. While most research suggests a negative association between tax havens and transparency, I examine whether this association depends on the firmâ€™s corporate governance environment as well as its capital market incentives. I find that the negative association is limited to firms subject to weak governance in the base country. In contrast, I find, among firms in stronger governance environments, a positive association between tax haven incorporation and transparency, which is most concentrated among firms with greater capital market incentives. My findings suggest that future researchers should use caution when assuming an unambiguous negative association between tax havens and corporate transparency. The study also provides unique evidence that tax planning can motivate higher transparency in certain settings.

The Effect of Designated Market Makers on Market Volatility: Evidence from a Natural Experiment
Kang, DongIk,Ko, Changsu,Park, Jongsang
SSRN
Designated market makers (DMMs) are utilized in many stock markets to provide liquidity and to reduce volatility, but convincing evidence regarding their effects on volatility is scarce. We estimate the effects of DMMs on securities by exploiting exogenous variation in DMM assignment to securities generated by a cutoff rule in the eligibility criteria of securities for DMM designation in the Korean Stock Exchange market. Using a regression discontinuity design, we find that DMMs not only improve the liquidity of securities but that they also increase return volatility. We investigate potential channels for the DMM-induced volatility increase and find evidence suggesting that it is a consequence of increased presence of funds whose managers, as previous studies suggest, engage in noise trading.

The Experimenters' Dilemma: Inferential Preferences over Populations
Neeraja Gupta,Luca Rigotti,Alistair Wilson
arXiv

We compare three populations commonly used in experiments by economists and other social scientists: undergraduate students at a physical location (lab), Amazon's Mechanical Turk (MTurk), and Prolific. The comparison is made along three dimensions: the noise in the data due to inattention, the cost per observation, and the elasticity of response. We draw samples from each population, examining decisions in four one-shot games with varying tensions between the individual and socially efficient choices. When there is no tension, where individual and pro-social incentives coincide, noisy behavior accounts for 60% of the observations on MTurk, 19% on Prolific, and 14% for the lab. Taking costs into account, if noisy data is the only concern Prolific dominates from an inferential power point of view, combining relatively low noise with a cost per observation one fifth of the lab's. However, because the lab population is more sensitive to treatment, across our main PD game comparison the lab still outperforms both Prolific and MTurk.

The Gerber Statistic: A Robust Co-Movement Measure for Portfolio Optimization
Gerber, Sander,Markowitz, Harry,Ernst, Philip,Miao, Yinsen,Javid, Babak,Sargen, Paul
SSRN
The purpose of this paper is to introduce the Gerber statistic, a robust co-movement measure for covariance matrix estimation for the purpose of portfolio construction. The Gerber statistic extends Kendall's Tau by counting the proportion of simultaneous co-movements in series when their amplitudes exceed data-dependent thresholds. Since the statistic is neither affected by extremely large or extremely small movements, it is especially well-suited for financial time series, which often exhibit extreme movements as well as a great amount of noise. Operating within the mean-variance portfolio optimization framework of Markowitz (1952,1959) we consider the performance of the Gerber statistic against two other commonly used methods for estimating the covariance matrix of stock returns: the sample covariance matrix (also called the historical covariance matrix) and shrinkage of the sample covariance matrix as formulated in Ledoit and Wolf (2004). Using a well-diversified portfolio of nine assets over a thirty year time period (January 1990-December 2020), we empirically find that, for almost all scenarios considered, the Gerber statistic's returns dominate those achieved by both historical covariance and by the shrinkage method of Ledoit and Wolf (2004).

The Long Shadows of the Great Inflation: Evidence from Residential Mortgages
Botsch, Matthew J.,Malmendier, Ulrike
SSRN
In most countries, the prevalent long-term mortgage is variable-rate. The US is an outlier, with 80% fixed-rate mortgages. We link the puzzling US market structure to long-lasting effects of the Great Inflation and structurally estimate the welfare implications. First, sentiment towards variable-rate mortgages negatively correlates with past nominal rates. Second, inflation exposure directly affects interest-rate expectations and mortgage choice. Third, we use SCF and RFS data, in combination with interest-rate surveys (PMMS and MIRS), to estimate a structural discrete-choice model and quantify payoff consequences. Our simulations imply that Baby Boomers overpaid by \$23bn for fixed-rate mortgages in the late 1980s-1990s.

The impact of prudential toolkit on loan growth in Central and Eastern European banking systems
Pochea, Miruna,NiÅ£oi, Mihai
SSRN
This paper examines the effects of prudential policy on loan growth in 11 Central and Eastern European banking systems, spanning from 2000 to 2015. Based on the measures taken by the authorities from our sample countries, we build several prudential indices. Additionally, we control for the effects of several country specific factors and bank specific characteristics. Finally, we test the homogeneity of these effects, accounting for cycle, ownership, and bank effects. Generally, the empirical findings reveal a negative correlation between prudential toolkit and credit growth, with a conspicuous impact for the tools targeting lending activity. We see that the effects of a change in lending framework on loan growth are heterogeneous when we account for crisis and cycle patterns. Furthermore, the interaction between ownership and crisis reveals that, in normal times, foreign banks recorded higher loan growth compared to domestic banks. The opposite is true in turbulent times. The analysis of interactions between credit-based measures and bank specific variables show that the effects of prudential actions depend on the bank size and leverage.

Trust radius and earnings surprises: With a humanistic approach to culture
Choi, KS (Kyeong-Seop)
SSRN
In global stock markets, I test a new measure of trust, national trust radius, and report that it is better than the existing measure. In a country with larger trust radius, information transmission is more efficient between earnings announcements and stock reactions. Tests based on various windows of returns, re-calibrations of trust radius, 2SLS, and controls corroborate this result. This tendency is most pronounced in Protestant regions, and least in Ex-Communist and Confucian regions. A humanistic approach based on a textual interpretation of classical documents (Luther, Marx, and Confucius) illumines why cultural regions have different widths of trust radius.

Wealth and Insurance Choices: Evidence from US Households
Gropper, Michael,Kuhnen, Camelia M.
SSRN
Theoretically, wealthier people should buy less insurance, and should self-insure through saving instead, as insurance entails monitoring costs. Here, we use administrative data for 63,000 individuals and, contrary to theory, find that the wealthier have better life and property insurance coverage. Wealth-related differences in background risk, legal risk, liquidity constraints, financial literacy, and pricing explain only a small fraction of the positive wealth-insurance correlation. This puzzling correlation persists in individual fixed-effects models estimated using 2,500,000 person-month observations. The fact that the less wealthy have lower coverage, though intuitively they benefit more from insurance, might increase financial health disparities among households.

Welfare Costs of Idiosyncratic and Aggregate Consumption Shocks
Constantinides, George M.
SSRN
I estimate welfare benefits of eliminating idiosyncratic consumption shocks unrelated to the business cycle as 47.3% of household utility and benefits of eliminating idiosyncratic shocks related to the business cycle as 3.4% of utility. Estimates of the former substantially exceed earlier ones because I distinguish between idiosyncratic shocks related/unrelated to the business cycle, estimate the negative skewness of shocks, target moments of idiosyncratic shocks from household-level CEX data, and target market moments. Benefits of eliminating aggregate shocks are 7.7% of utility. Policy should focus on insuring idiosyncratic shocks unrelated to the business cycle, such as the death of a householdâ€™s prime wage earner and job layoffs not necessarily related to recessions.

What's in a Faceï¼ŸAn Experiment on Facial Information and Loan Approval Decision
Liu, Yu-Jane,Chen, Zeyang,Meng, Juanjuan,Wang, Zeng
SSRN
Face-to-face communication is essential in daily life but relatively little is known about whether seeing a face improves peopleâ€™s decision quality. This experimental paper studies the loan approval decisions based on the historical cash loan data with real repayment outcomes, and exogenously varies whether and how a borrowerâ€™s facial information is provided. We find that facial information does not improve subjectsâ€™ decisions, despite the fact that it can predict repayment behavior in a machine learning algorithm. This is because subjects have various biases in evaluating facial photos; and they rely excessively on facial information in making the loan approval decisions.