Research articles for the 2021-01-07

A self-organized criticality participative pricing mechanism for selling zero-marginal cost products
Daniel Fraiman

In today's economy, selling a new zero-marginal cost product is a real challenge, as it is difficult to determine a product's "correct" sales price based on its profit and dissemination. As an example, think of the price of a new app or video game. New sales mechanisms for selling this type of product need to be designed, in particular ones that consider consumer preferences and reality. Current auction mechanisms establish a time deadline for the auction to take place. This deadline is set to increase the number of bidders and thus the final offering price. Consumers want to obtain the product as quickly as possible from the moment they become interested in it, and this time does not always coincide with the seller's deadline. Naturally, consumers also want to pay a price they consider "fair". Here we introduce an auction model where buyers continuously place bids and the challenge is to decide quickly whether or not to accept them. The model does not include a deadline for placing bids, and exhibits self-organized criticality; it presents a critical price from which a bid is accepted with probability one, and avalanches of sales above this value are observed. This model is of particular interest for startup companies interested in profit as well as making the product known on the market.

Adaptation to Climate Change: Evidence from Banks’ Loan Loss Provisions
Cui, Chenyu,Lin, Yupeng,Zhang, Zilong
This paper examines whether and how banks adapt to long-run climate change. We show that banks increase their loan loss provisions by 7% in response to a 1°F increase in three-year weighted average abnormal temperature. Such an effect is more pronounced when banks have larger pre-existing credit exposure to the agriculture sector, the real-estate sector, or personal loans. It also becomes stronger when the local economic condition is poorer. We further entertain the possibility that the net effect documented in the baseline analysis could mask the nuanced heterogeneity of climate change’s impacts. Our further analyses reveal that that short-run capital market pressure and securitization can act as countervailing forces, reducing the loan loss provision sensitivity to climate change.

Adverse Climate Incidents and Bank Loan Contracting
Anginer, Deniz,Hrazdil, Karel,Li, Jiyuan,Zhang, Ray
We investigate how a borrower’s adverse climate-related incidents affect bank loan contracting. Using a sample of 2,622 publicly traded US firms over the period 2000â€"2016, we construct event-based measures of corporate climate performances based on firm-level adverse climate incidents such as oil spills, excess carbon emissions and deforestation projects. We show that loans initiated after the occurrence of firms’ first adverse climate-related incidents have significantly higher spreads, shorter maturities, more covenant restrictions, and higher likelihood of being secured with collateral. In cross-sectional tests, we find that the intensity and influence of adverse climate-related incidents exacerbate the pricing of bank loans. Our results support the notion that banks incorporate firm-specific climate performance into their lending contracts.

Analyzing Impact of a Crisis on Bank Financial Ratios
Nal, Osman,Cai, Andrew
In this study we provide a practical framework and methodology for analyzing the effects of banking shocks (economic or financial in nature) on bank fundamentals, that avoids the use of complicated econometrics methods. For this, we focus our attention to the effects of the 2007-2008 global financial crisis on the four largest US banks and examine the variation of trends in the select financial ratios for those institutions using quarterly regulatory data running from 2002-Q4 to 2020-Q2. We start by plotting time series charts of those financial ratios for each bank and compare the before-crisis, transition and after-crisis periods. For this, we simply fit trend lines with three parameters of shift, slope, and volatility to the banking data. The shift parameter describes the level change of the variable when before- and after-crisis periods are compared. The slope parameter pronounces the difference in steepness of the trend lines, while the volatility parameter is associated with all three periods and describe the variation in the data during each period. Our results indicate that capital ratios, an important regulatory financial ratio, are higher across the board in the after-crisis period compared to before-crisis period, suggesting a positive shift. We don’t see significant changes in slope parameter for the capital ratio series leading us to suggest the use of dummy variable regression model where slope is treated as a fixed constant. We further show that pre-crisis and transition periods are characterized by higher volatilities that ultimately subside in the after-crisis period. Lastly, we conclude by suggesting that financial practitioners use the shift, slope and volatility parameters in understanding trends in financial time series data since it is easy to implement and interpret the results compared to more sophisticated econometric models.

Analyzing the response to TV serials retelecast during COVID19 lockdown in India
Sandeep Ranjan

TV serials are a popular source of entertainment. The ongoing COVID19 lockdown has a high probability of degrading the publics mental health. The Government of India started the retelecast of yesteryears popular TV serials on public broadcaster Doordarshan from 28th March 2020 to 31st July 2020. Tweets corresponding to the Doordarshan hashtag were mined to create a dataset. The experiment aims to analyze the publics response to the retelecast of TV serials by calculating the sentiment score of the tweet dataset. Datasets mean sentiment score of 0.65 and high share 64.58% of positive tweets signifies the acceptance of Doordarshans retelecast decision. The sentiment analysis result also reflects the positive state of mind of the public.

Bank Leverage and Capital Bias Adjustment Through the Macroeconomic Cycle
Yeh, Andy
We assess the quantitative effects of the recent proposal for more robust bank capital adequacy. Our theoretical proof and evidence accord with the core thesis that banks become more stable by increasing their equity capital cushion to absorb extreme losses in times of severe financial stress. This analysis contributes to the ongoing policy debate on total capital adequacy. Our Monte Carlo simulation helps develop an analytical solution for the default probability adjustment through the macroeconomic cycle. This study poses a conceptual challenge to the normative view that banks should maintain high leverage over time.

COVID19-HPSMP: COVID-19 Adopted Hybrid and Parallel Deep Information Fusion Framework for Stock Price Movement Prediction
Farnoush Ronaghi,Mohammad Salimibeni,Farnoosh Naderkhani,Arash Mohammadi

The novel of coronavirus (COVID-19) has suddenly and abruptly changed the world as we knew at the start of the 3rd decade of the 21st century. Particularly, COVID-19 pandemic has negatively affected financial econometrics and stock markets across the globe. Artificial Intelligence (AI) and Machine Learning (ML)-based prediction models, especially Deep Neural Network (DNN) architectures, have the potential to act as a key enabling factor to reduce the adverse effects of the COVID-19 pandemic and future possible ones on financial markets. In this regard, first, a unique COVID-19 related PRIce MOvement prediction (COVID19 PRIMO) dataset is introduced in this paper, which incorporates effects of social media trends related to COVID-19 on stock market price movements. Afterwards, a novel hybrid and parallel DNN-based framework is proposed that integrates different and diversified learning architectures. Referred to as the COVID-19 adopted Hybrid and Parallel deep fusion framework for Stock price Movement Prediction (COVID19-HPSMP), innovative fusion strategies are used to combine scattered social media news related to COVID-19 with historical mark data. The proposed COVID19-HPSMP consists of two parallel paths (hence hybrid), one based on Convolutional Neural Network (CNN) with Local/Global Attention modules, and one integrated CNN and Bi-directional Long Short term Memory (BLSTM) path. The two parallel paths are followed by a multilayer fusion layer acting as a fusion centre that combines localized features. Performance evaluations are performed based on the introduced COVID19 PRIMO dataset illustrating superior performance of the proposed framework.

Chronological Hurst exponent elucidates latent persistency within patents and trademarks applications reflecting strength of innovation initiatives between 1977 and 2016
Iraj Daizadeh

Understanding the dynamics of patents and trademarks is a key aspect of tracking innovative progress/egress. This paper empirically explores the chronological Hurst exponent (CHE), an approach that calculates the Hurst exponent over an increasing duration of time windows to quantify long-memory dynamics, in the monthly numbers of United States patent and trademark applications from 1977 to 2016. The CHE is found to increase in a clear 3-period S-curve pattern, achieving persistence (Period 3: H~1) from non-persistence (Period 1: H~0.5). For patents, Period 2, the time-varying period, occurred over a span of 10 years (1980-1990), while it was much sharper (3 years) for trademarks (1977-1980). Based on these data, it is hypothesized that the rapid augmentation in exogenous variables (such as increasing R&D expenditure or specific policy initiatives (viz., Bayh Dole, Stevenson-Wydler) are the key impetuses behind the increase of persistency during Period 2. Post-1990s exogenic variables led to the maintenance of the high degree and consistency of the persistency metric. These findings suggest investigators should consider latent persistency when using these data and the CHE may be an important tool to investigate the impact of substantive exogenous variables on growth dynamics.

Contracting Costs and Reputational Contracts
Badoer, Dominique C.,Emin, Mustafa,James, Christopher M.
Reputational capital is a frequently cited attribute of private equity transactions. In this paper we construct a simple model to illustrate the relationship between reputational capital, covenants and loan spreads in the leveraged loan market. Our model predicts that reliance on reputational capital varies inversely with a sponsor’s past loan performance and the efficiency of the enforcement formal contracts terms. Our model also predicts that for sponsored deals, spreads will be lower on Cov-Lite loans than loans with maintenance covenants. Using a large sample of leveraged loans originated between 2005 and 2018, we find evidence consistent with these predictions.

Cryptocurrency Trading: A Comprehensive Survey
Fan Fang,Carmine Ventre,Michail Basios,Hoiliong Kong,Leslie Kanthan,Lingbo Li,David Martinez-Regoband,Fan Wu

In recent years, the tendency of the number of financial institutions including cryptocurrencies in their portfolios has accelerated. Cryptocurrencies are the first pure digital assets to be included by asset managers. Even though they share some commonalities with more traditional assets, they have a separate nature of its own and their behaviour as an asset is still under the process of being understood. It is therefore important to summarise existing research papers and results on cryptocurrency trading, including available trading platforms, trading signals, trading strategy research and risk management. This paper provides a comprehensive survey of cryptocurrency trading research, by covering 126 research papers on various aspects of cryptocurrency trading (eg., cryptocurrency trading systems, bubble and extreme condition, prediction of volatility and return, crypto-assets portfolio construction and crypto-assets, technical trading and others). This paper also analyses datasets, research trends and distribution among research objects (contents/properties) and technologies, concluding with some promising opportunities that remain open in cryptocurrency trading.

Do economic effects of the anti-COVID-19 lockdowns in different regions interact through supply chains?
Hiroyasu Inoue,Yohsuke Murase,Yasuyuki Todo

To prevent the spread of COVID-19, many cities, states, and countries have `locked down', restricting economic activities in non-essential sectors. Such lockdowns have substantially shrunk production in most countries. This study examines how the economic effects of lockdowns in different regions interact through supply chains, a network of firms for production, simulating an agent-based model of production on supply-chain data for 1.6 million firms in Japan. We further investigate how the complex network structure affects the interactions of lockdowns, emphasising the role of upstreamness and loops by decomposing supply-chain flows into potential and circular flow components. We find that a region's upstreamness, intensity of loops, and supplier substitutability in supply chains with other regions largely determine the economic effect of the lockdown in the region. In particular, when a region lifts its lockdown, its economic recovery substantially varies depending on whether it lifts lockdown alone or together with another region closely linked through supply chains. These results propose the need for inter-region policy coordination to reduce the economic loss from lockdowns.

Does double-blind peer-review reduce bias? Evidence from a top computer science conference
Mengyi Sun,Jainabou Barry Danfa,Misha Teplitskiy

Peer review is widely regarded as essential for advancing scientific research. However, reviewers may be biased by authors' prestige or other characteristics. Double-blind peer review, in which the authors' identities are masked from the reviewers, has been proposed as a way to reduce reviewer bias. Although intuitive, evidence for the effectiveness of double-blind peer review in reducing bias is limited and mixed. Here, we examine the effects of double-blind peer review on prestige bias by analyzing the peer review files of 5027 papers submitted to the International Conference on Learning Representations (ICLR), a top computer science conference that changed its reviewing policy from single-blind peer review to double-blind peer review in 2018. We find that after switching to double-blind review, the scores given to the most prestigious authors significantly decreased. However, because many of these papers were above the threshold for acceptance, the change did not affect paper acceptance decisions significantly. Nevertheless, we show that double-blind peer review may have improved the quality of the selections by limiting other (non-author-prestige) biases. Specifically, papers rejected in the single-blind format are cited more than those rejected under the double-blind format, suggesting that double-blind review better identifies poorer quality papers. Interestingly, an apparently unrelated change - the change of rating scale from 10 to 4 points - likely reduced prestige bias significantly, to an extent that affected papers' acceptance. These results provide some support for the effectiveness of double-blind review in reducing prestige bias, while opening new research directions on the impact of peer review formats.

European Stock Markets’ Response to Covid-19, Lockdowns, Government Response Stringency and Central Banks’ Interventions
Rubbaniy, Ghulame,Khalid, Ali Awais,Umar, Muhammad ,Mirza, Nawazish
Using daily data of Covid-19 fear index and stock indices of 29 European countries over the period from January 1, 2020 to September 17, 2020, this study finds no evidence of adverse impact of Covid-19 outbreak on European stock markets at the level of full sample nor at European sub-regional levels. However, we report a significantly negative time-varying reaction of European stock markets to Covid-19 eruption. Our results document that the response of European stock markets to oil price shocks is dependent on the choice of the proxy; and exchange rate changes have a negative influence on European stock markets. Our study provides the evidence that neither lockdowns nor the stringent measures taken by the governments to improve effect of Covid-19 on European stock markets are effective. The findings of the study reveal that most of the temporary interventions by the central banks of different European countries do not improve the adverse impact of Covid-19 on European stock markets. However, some of the financial measures by central banks (e.g., reduction in capital buffers) help mitigating the adverse impacts of Covid-19 on European stock markets. Our findings have important implications for investors in their decision making and, for policy makers and central banks in terms of improving their quantitative easing to support European stock markets during turbulent times such as pandemics.

Financial Autonomy among Emerging Adults in Australia
Botha, Ferdi,Broadway, Barbara,de New, John,Wong, Clement
This paper investigates how financial autonomy develops in young adults and under what circumstances that development process is hastened or hindered. The paper uses longitudinal data from the Household, Income, and Labour Dynamics in Australia (HILDA) survey for persons aged 15-25, thus following young people from the time they are adolescents and into adulthood. We develop a novel measure of financial autonomy based on an individual’s degree of responsibility for household decision-making related to (a) managing day-to-day spending, (b) making large household purchases, and (c) savings and investments. Measuring financial autonomy allows us to observe a period of “emerging adulthood” as opposed to merely delaying nest-leaving due to cost-constraints (i.e. costs of living). If emerging adulthood plays an important role in young adults’ development, we would expect to see steadily increasing levels of financial autonomy while the young adults are still at home. If on the other hand, delayed nest-leaving is only due to costs-constraints, we would not expect to observe such a period of systematic preparation for independent living. We estimate a correlated random-effects model for the latent financial autonomy construct, specifying a range of covariates related to individual demographic and resource characteristics, household characteristics, and regional factors. For men, there is a significant and positive age gradient associated with financial autonomy. There is no evidence of an age profile for young women whose level of financial autonomy is mostly explained by their household- and regional characteristics. This suggests that the phase of “emerging adulthood”, in which financial autonomy is learned over time at home, plays an important role for young men but not for young women. This systematically puts young women at a potential disadvantage compared to young men, and consequently at a higher risk of low financial literacy and poor financial decision-making in the period after nest-leaving.

Financial Services Trade in Special Economic Zones
Delimatsis, Panos
The mushrooming of Special Economic Zones (SEZs) in recent years has led to a significant increase in the supply of attractive incentives for investors looking for opportunities abroad. SEZs are self-contained regimes, inextricably associated with investment promotion policies and domestic industrial policy in general, that many times form part of a broader strategic governmental planning that aims at experimenting with economic rule-making in strictly defined territorial and jurisdictional boundaries. While empirical evidence still is inconclusive, SEZs can contribute to economic development at the domestic level through a varying degree of channels. This is even more the case with services-only SEZs, a new phenomenon that exemplifies the rising important of trade in services but also the ‘servicification trend’ that drives global economic activity. Against this background, this article examines the case for services in SEZs and offers a tour d’horizon of the current services-related SEZ landscape. Furthermore, the article critically reviews the patterns, traits and limits of trade in financial services within SEZ and discusses the relevance of the General Agreement on Trade in Services (GATS) at this juncture. The article concludes with a discussion of potential development-related benefits ensuing from trade in financial services within SEZs.

Financing Severe Climate Risk: Evidence from Businesses During Hurricane Harvey
Collier, Benjamin,Powell, Lawrence,Ragin, Marc A.,You, Xuesong
We examine small business financing outcomes approximately one year after Hurricane Harvey. Our data include the credit reports of 8,219 businesses and a detailed survey of 273 businesses in the affected area. We find that Harvey-related flooding increased credit delinquencies, especially short-term delinquencies. We also find that firms without existing debt took on debt following Harvey; however, firms most commonly reported financing recovery using earnings and the owner's personal resources. Finally, we find that firms with owners who are worried about climate change increased their risk financing following Harvey. Our analyses provide novel insights into firms' risk management and financing choices.

GMM Estimation of Stochastic Volatility Models Using Transform-Based Moments of Derivatives Prices
Dillschneider, Yannick,Maurer, Raimond
Derivatives, especially equity and volatility options, contain valuable and oftentimes essential information for estimating stochastic volatility models. Absent strong assumptions, their typically highly nonlinear pricing dependence on the state vector prevents or at least severely impedes their inclusion into standard estimation approaches. This paper develops a novel and unified methodology to incorporate moments involving derivatives prices into a GMM-type estimation procedure. Invoking new results from generalized transform analysis, we derive analytically tractable expressions for exact moments and devise a computationally efficient approximation procedure. We exemplify our methodology with an estimation problem that jointly accounts for stock returns as well as prices of equity and volatility options.

Generalized Transform Analysis for Asset Pricing and Parameter Estimation
Dillschneider, Yannick
In this paper, we extend the existing generalized transform analysis in a way that allows us to propose a novel GMM approach for estimating asset pricing models. Our methodology is capable of incorporating a broad class of assets within both reduced-form and structural models, while avoiding the drawbacks of competing approaches. To formulate moment conditions, we derive expressions for moments involving transform-based asset prices. Our theory yields analytically tractable expressions for exact moments and an additionally computationally efficient strategy to obtain approximate moments, whose convergence we establish under standard conditions. Exact and approximate moments induce exact and approximate GMM estimators, respectively, for which we discuss asymptotic properties. Finally, we exemplify and numerically support our methodology with a worked-out estimation problem involving equity options.

Green Data or Greenwashing? Do Corporate Carbon Emissions Data Enable Investors to Mitigate Climate Change?
Kalesnik, Vitali,Wilkens, Marco,Zink, Jonas
Absent mandatory reporting, and although many companies report their carbon emissions, much of the emissions data are estimated by data providers. As we evaluate the forward-looking carbon scores from several popular data providers, we find no evidence that these scores predict future changes in emissions. Further, we find that data on estimated emissions are at least 2.4 times less effective than reported data in identifying the worst emitters and provide little information to identify green companies in brown sectors. Our results debunk the belief that third-party estimated emissions are a satisfactory substitute for company-reported emissions and call for mandatory and audited carbon emissions disclosure.

Inflation Compensation and Monetary Policy
Zhu, Xingyu (Sonya),Dedes, Vasilis
We examine the transmission mechanism of monetary policy to inflation markets. We decompose monetary policy shocks in the United States into two orthogonal channels: the policy channel, measured by the change in 2-year nominal Treasury yield, and the communication channel, measured by the orthogonal change in 10-year nominal Treasury yield. We find that the conventional monetary policy affects long-term market-based inflation compensation through the communication channel, while the unconventional monetary policy affects short-term market-based inflation compensation through the policy channel. Our analysis also indicates that an announcement of quantitative easing corrects the short-term mispricing between the two inflation compensation measures, but amplifies long-term mispricing.

Irreducible Risks: Fallacy of Risk-Neutral Approach to Options
Sundberg, Margaret,Freeman, Jake,Kapoor, Vivek
This paper compares two approaches to options: (1) Risk-Aware Approach, and (2) Risk-Neutral Approach. The risk-aware approach requires a probabilistic specification of the underlying’s returns, addressing higher than second moments, as hedging errors are singularly dependent on the excess kurtosis of the returns. Becoming risk-aware requires explicitly assessing hedge slippage around a hedging strategy to attempt option replication. In contrast, the risk-neutral tautology sets the option price equal to an expectation of option payoff under a risk-neutral probability that is inferred from option prices and under which the asset does not expect to accrete/deplete wealth. In the presence of irreducible risks, while a risk-neutral probability measure may be fit to observed option prices, it does not inform about the partitioning between expected attempted replication costs and compensation for irreducible risks. In segmented option markets with distinct risk premiums such a risk-neutral probability measure fails to exist.

Measurement of Global Value Chain (GVC) Participation in World Development Report 2020
Sourish Dutta

As we can understand with the spread of GVCs, a lot of new questions emerge regarding the measurement of participation and positioning in the globalised production process. The World Development Report (WDR) 2020 explains the GVC phenomenon and then focus on participation and the prospects especially in a world of change in technology. From the overview section, we can figure out that nowadays, goods and services flow across borders as intermediate inputs rather than final goods. In traditional trade, we need two countries with the notions of export and import. However, in GVC trade, the goods and services cross borders multiple times requiring more than two countries. Remarkable improvements in information, communication, and transport technologies have made it possible to fragment production across national boundaries. So the question is: how to conceptualise this type of new trade to justify the measurement of participation.

Mining the Relationship Between COVID-19 Sentiment and Market Performance
Ziyuan Xia,Jeffery Chen

At the beginning of the COVID-19 outbreak in March, we observed one of the largest stock market crashes in history. Within the months following this, a volatile bullish climb back to pre-pandemic performances and higher. In this paper we study the stock market behavior during the initial few months of the COVID-19 pandemic in relation to COVID-19 sentiment. Using text sentiment analysis of Twitter data, we look at tweets that contain key words in relation to the COVID-19 pandemic and the sentiment of the tweet to understand whether sentiment can be used as an indicator for stock market performance. There has been previous research done on applying natural language processing and text sentiment analysis to understand the stock market performance, given how prevalent the impact of COVID-19 is to the economy, we want to further the application of these techniques to understand the relationship that COVID-19 has with stock market performance. Our findings show that there is a strong relationship to COVID-19 sentiment derived from tweets that could be used to predict stock market performance in the future.

Modeling Loss Given Default Regressions
Li, Phillip,Zhang, Xiaofei,Zhao, Xinlei
We investigate the puzzle in the literature that various parametric loss given default (LGD) statistical models perform similarly, by comparing their performance in a simulation framework. We find that, even using the full set of explanatory variables from the assumed data-generating process where noise is minimized, these models still show a similarly poor performance in terms of predictive accuracy and rank-ordering when mean predictions and squared error loss functions are used. However, the sophisticated parametric modes that are specifically designed to address the bimodal distributions of LGD outperform the less sophisticated models by a large margin in terms of predicted distributions. Our results also suggest that stress testing may pose a challenge to all LGD models due to a lack of loss data and the limited availability of relevant explanatory variables, and that model selection criteria based on goodness-of-fit may not serve the stress testing purpose well.Copyright Infopro Digital Limited. All rights reserved.

On the International Spillover Effects of Country-Specific Financial Sector Bailouts and Sovereign Risk Shocks
Greenwood‐Nimmo, Matthew,Nguyen, Viet Hoang,Wu, Eliza
We use sign-identified macroeconomic models to study the interaction of financial sector and sovereign credit risks in Europe. We find that country-specific financial sector bailout shocks do not generate strong international spillovers, because they primarily transfer private sector risk onto the local sovereign. By contrast, sovereign risk shocks generate substantial spillovers onto the global financial sector and for international sovereign debt markets. We conclude that any financial sector bailout policy that undermines the creditworthiness of the affected sovereign is likely to exacerbate global credit risk. Our findings highlight the unintended global consequences of country-specific financial sector bailout programmes.

Optimal Macroprudential and Fiscal Policy in a Monetary Union
Malmierca, María
The growing concern about the financial system stability has turned macroprudential policy into a key instrument of the policy mix. Through a two-country model for a monetary union, I evaluate the optimal combinations of macroprudential and fiscal policy, both in terms of welfare maximization and loss function minimization (stability). I find that the advisability to coordinate macroprudential and fiscal policy depends on the kind of shock that drives the business cycle fluctuations. In the event of financial shocks, macroprudential-fiscal coordination at the national level entails the highest welfare improvements. Under supply shocks, the best option regarding welfare, is the scenario where macroprudential and fiscal policies coordinate to stabilize union aggregate variables. And, in the case of a preference shock, the macroprudential-fiscal non-coordination scenario achieves the largest increases in welfare.

Optimal portfolios for different anticipating integrals under insider information
Carlos Escudero,Sandra Ranilla-Cortina

We consider the non-adapted version of a simple problem of portfolio optimization in a financial market that results from the presence of insider information. We analyze it via anticipating stochastic calculus and compare the results obtained by means of the Russo-Vallois forward, the Ayed-Kuo, and the Hitsuda-Skorokhod integrals. We compute the optimal portfolio for each of these cases with the aim of establishing a comparison between these integrals in order to clarify their potential use in this type of problem. Our results give a partial indication that, while the forward integral yields a portfolio that is financially meaningful, the Ayed-Kuo and the Hitsuda-Skorokhod integrals do not provide an appropriate investment strategy for this problem.

Ownership Structure and Earnings Management: Empirical Evidence from Listed Pharmaceuticals and Chemical Firms of Bangladesh
Hossain, Dewan Azmal
Objective â€" This study aims to examine the relationship between ownership structure (determined by institutional and foreign ownership) and earnings management in the context of Bangladeshi Pharmaceuticals and Chemical firms.Methodology/Technique â€" Out of 32 listed firms, this study examined 29 firms from the pharmaceuticals and chemical industry of Bangladesh from 2014 to 2018. Three firms are omitted as they got listed in 2018 and 2019 respectively. This study uses discretionary working capital accrual to measure earnings management that is the dependent variable. Ordinary least square regression analysis is conducted to assess the result of this study. Institutional and foreign ownership are independent variables. ROA, size, cash flow from operation, and leverage are control variables.Findings â€" It is found that institutional ownership is negatively related to earnings management and foreign ownership is positively related to earnings management but none of them are statistically significant indicating institutional and foreign ownership do not help in resolving or reducing the earnings management problems in the context of Bangladeshi pharmaceuticals and chemical firms.Novelty â€" Previous studies in Bangladesh deal only with the techniques of earnings management. To my knowledge, it is the first study that tries to assess the relationship of ownership structure defined by institutional and foreign shareholdings with earnings management in the context of Bangladeshi pharmaceuticals and chemical firms. These two ownership patterns are selected because they are supposed to increase the quality of financial information and also because in Bangladesh state and general shareholders are too dispersed to monitor the governance issues. The practical implications of this study is that investors should not consider institutional and foreign ownership percentage as a determining factor of good governance when considering investment decisions rather should look for other firm-specific factors as institutional and foreign shareholders are found to be inactive in increasing the quality of financial information in the context of Bangladesh. Policymakers should identify why institutional and foreign shareholders are not active and should revise the governance mechanisms accordingly.Type of Paper: Empirical

Predicting CEO Compensation in Non-Controlled Public Corporations with the Canonical Regression Quantile Method
Joseph Haimberg,Stephen Portnoy

The use of the Canonical Regression Quantiles Index proved that non-controlled companies that engage in long-term operational and financial goals post superior future performance. The Index indicates that current CEO compensation influences future performance. The Index provides a method for determining CEO pay for the next 1-2 year and is a useful method to distinguish over/underpaid CEOs as an unbiased alternative to the peer groups comparison used by most compensation consultants. This determination is statistically weak, but future research using the Canonical Regression Quantiles with a larger data set may lead to increased sensitivity and a powerful unbiased method for replacing compensation consultants who are responsible for the decoupling of CEO compensation and corporate performance.

Predicting S&P500 Index direction with Transfer Learning and a Causal Graph as main Input
Djoumbissie David Romain

We propose a unified multi-tasking framework to represent the complex and uncertain causal process of financial market dynamics, and then to predict the movement of any type of index with an application on the monthly direction of the S&P500 index. our solution is based on three main pillars: (i) the use of transfer learning to share knowledge and feature (representation, learning) between all financial markets, increase the size of the training sample and preserve the stability between training, validation and test sample. (ii) The combination of multidisciplinary knowledge (Financial economics, behavioral finance, market microstructure and portfolio construction theories) to represent a global top-down dynamics of any financial market, through a graph. (iii) The integration of forward looking unstructured data, different types of contexts (long, medium and short term) through latent variables/nodes and then, use a unique VAE network (parameter sharing) to learn simultaneously their distributional representation. We obtain Accuracy, F1-score, and Matthew Correlation of 74.3 %, 67 % and 0.42 above the industry and other benchmark on 12 years test period which include three unstable and difficult sub-period to predict.

Probability Distortions, Collectivism, and International Stock Prices
Hollstein, Fabian,Sejdiu, Vulnet
We introduce a novel composite probability distortion (CPD) score based on investors’ stock valuations derived from a pure-probability-weighting version of cumulative prospect theory and from salience theory. This measure is strongly and consistently priced in the cross-section of international stock returns: stocks with low CPD scores are underpriced while stocks with high such scores appear overpriced. Individualism is the main driver of international differences in the CPD premium. Consistent with the substantially lesser degree of probabilistic thinking in collectivist cultures documented by the psychology literature, we find that the CPD premium is substantially higher in these than in individualistic countries.

Regulatory Peers
Kalmenovitz, Joseph,Chen, Jason
Using a hand-collected administrative dataset, we develop a new concept of regulatory peers: companies with similar regulatory challenges. The majority of regulatory peers belong to different sectors, offer distinctive products, and lack substantial business connections. Nevertheless, we document a significant sensitivity of firm investment to its regulatory peers' investment. The sensitivity increases if the peers have strong government ties and when the firm has more investment opportunities or faces greater regulatory uncertainty, suggesting that firms may interpret peer investment as a signal about the true value of regulation. The results uncover an economically important link between companies and demonstrate how information frictions shape the economic impact of regulation.

Robo-Advising for Small Investors
Bianchi, Milo,Briere, Marie
We study the effects of robo-advising on investors' attention, trading, and performance on a large set of Employees Saving Plans covering a representative sample of French employees. We find that relative to self-managing, accessing the robo services is associated to an increase in the time investors spend to follow their portfolios and to an increase in trading activities. After having taken up the robo, investors are willing to increase their investment, bear more risk, and to rebalance their portfolio in a way to keep their allocation closer to the target. They also experience higher risk-adjusted returns. These effects tend to be stronger for investors with smaller portfolios, who are less likely to have access to traditional advice. Our results shed light on the dynamics of investors' trust towards the robo service and suggest that automated advice can promote financial inclusion.

Security Design for Private Acquisitions
Jansen, Mark,Noe, Thomas H. ,Phalippou, Ludovic
We consider the security design problem of an acquirer with value-add capacity for a target firm. The target firm has a single owner with private information about the suitability of his firm for the value-add plan. The parties disagree about the magnitude of the acquirer's value-add. The acquirer's offer consists of a mix of cash and securities. Although the acquirer can choose any monotone limited liability security, we show that, under general conditions, the only security she employs is non-recourse debt provided by the seller. The cash-debt mix depends on the degree of both information asymmetry and disagreement.

Series expansions and direct inversion for the Heston model
Simon J.A. Malham,Jiaqi Shen,Anke Wiese

Efficient sampling for the conditional time integrated variance process in the Heston stochastic volatility model is key to the simulation of the stock price based on its exact distribution. We construct a new series expansion for this integral in terms of double infinite weighted sums of particular independent random variables through a change of measure and the decomposition of squared Bessel bridges. When approximated by series truncations, this representation has exponentially decaying truncation errors. We propose feasible strategies to largely reduce the implementation of the new series to simulations of simple random variables that are independent of any model parameters. We further develop direct inversion algorithms to generate samples for such random variables based on Chebyshev polynomial approximations for their inverse distribution functions. These approximations can be used under any market conditions. Thus, we establish a strong, efficient and almost exact sampling scheme for the Heston model.

Showing off Cleaner Hands: Mandatory Climate-Related Disclosure by Financial Institutions and the Financing of Fossil Energy
Mésonnier, Jean-Stéphane,Nguyen, Benoît
We investigate the real effects of mandatory climate-related disclosure by financial institutions on the funding of carbon-intensive industries. Our impact metric is the amount invested into securities, bonds and stocks, issued by fossil fuel companies. A French law, which came into force in January 2016 in the aftermath of the Paris Agreement on climate change, provides us with a quasi-natural experiment. The new regulation, unique in Europe at that time, requires institutional investors (i.e., insurers, pension funds and asset management firms), but not banks, to report annually on both their climate-related exposure and climate change mitigation policy. Using a unique dataset of security-level portfolio holdings by each institutional sector in each euro area country, we compare the portfolio choices of French institutional investors with those of French banks and all financial institutions located in other EA countries. We find that investors subject to the new disclosure requirements curtailed their financing of fossil energy companies by some 40% compared to investors in the control group.

Social Capital, Trusting, and Trustworthiness: Evidence from Peer-to-peer Lending
Hasan, Iftekhar,He, Qing,Lu, Haitian
How does social capital affect trust? Evidence from a Chinese peer-to-peer lending platform shows regional social capital affects the trustee’s trustworthiness and the trustor’s trust propensity. Ceteris paribus, borrowers from higher social capital regions receive larger bid from individual lenders, have higher funding success, larger loan size, and lower default rates, especially for low-quality borrowers. Lenders from higher social capital regions take higher risks and have higher default rates, especially for inexperienced lenders. Cross-regional transactions are most (least) likely to be realized between parties from high (low) social capital regions.

The Importance of Compound Risk in the Nexus of Covid-19, Climate Change and Finance
Monasterolo, Irene,Billio, Monica,Battiston, Stefano
Current approaches to manage the COVID-19 pandemic have a narrow focus on public health and on the short-term economic and financial repercussions. This prevents us to look at how pandemic risk interplays with sustainable and inclusive development goals in the next decade. To fill this gap, we analyse how risk can compound in the nexus of non-linear interactions among pandemic, climate change and finance. We show that neglecting compound risk can lead to a massive underestimation of losses, which can be amplified by financial complexity, as well as to policies that impose unnecessary trade-offs among the economic recovery, health and climate objectives. To address these challenges, we propose an interdisciplinary research agenda to inform effective policies and improve the resilience of our socio-economic systems.

The Index Effect: Evidence from the Option Market
Hollstein, Fabian,Wese Simen, Chardin
We document a significantly positive response of delta-hedged option positions on companies entering or leaving the S&P 500 index. Our findings (i) hold for both call and put options, (ii) are robust to placebo- and risk-adjustments, and (iii) are stronger for companies that are likely subject to more demand pressure from stock index investors. The inclusion effect is permanent, while the exclusion effect is transitory. We explore various mechanisms to explain these results, including leading theories of benchmarking, investor recognition, noise trading, and dispersion trading. We find that these explanations cannot individually account for all our novel results.

The Materiality and Measurement of Physical Climate Risk: Evidence from Form 8-K
Gostlow, Glen
Pricing firm-level exposure to physical risk, such as hurricanes, wildfires and floods, poses large informational challenges to investors and policymakers. This leads to difficulties in estimating how the market is pricing climate risk. This paper explores whether Form 8-K, a filing that allows firms to immediately report on unscheduled material events to shareholders, holds any relevant and latent information on physical risk. By utilising a simple textual approach, Form 8-K offers a way to identify material firm-level physical risk information related to severe weather and natural disasters. This paper also compares the measure to others in the literature. When compared to measures of keywords in annual reports, Form 8-K can detect realised and real-time physical risk from firms that predict they will be exposed. This allows for the validation of these less frequent and forward-looking measures. When compared to more frequent measures that utilise quarterly earnings call transcripts between managers and investors, Form 8-K identifies physical risk exposure that is not mentioned in the earnings calls. This is taken as evidence that Form 8-K may hold some latent real time information on physical risk exposure.

The Shaky Case for a Business Cash-Flow Tax Over a Business Income Tax
Batchelder, Lily L.
Traditional economic theory holds that a business cash-flow tax is superior to a business income tax because it is more efficient and progressive. But much of the literature espousing this view does not explicitly specify the full range of assumptions underlying these claims, let alone explore and empirically justify them. This paper summarizes 11 assumptions underlying the traditional view and considers how well supported they are empirically and as a matter of political economy. It concludes that when each assumption is examined closely, the case for a cash-flow tax over a business income tax becomes considerably shakier and may well collapse.

Theory and Applications of Financial Chaos Index
Masoud Ataei,Shengyuan Chen,Zijiang Yang,M.Reza Peyghami

We develop a new stock market index that captures the chaos existing in the market by measuring the mutual changes of asset prices. This new index relies on a tensor-based embedding of the stock market information, which in turn frees it from the restrictive value- or capitalization-weighting assumptions that commonly underlie other various popular indexes. We show that our index is a robust estimator of the market volatility which enables us to characterize the market by performing the task of segmentation with a high degree of reliability. In addition, we analyze the dynamics and kinematics of the realized market volatility as compared to the implied volatility by introducing a time-dependent dynamical system model. Our computational results which pertain to the time period from January 1990 to December 2019 imply that there exist a bidirectional causal relation between the processes underlying the realized and implied volatility of the stock market within the given time period, where it is shown that the later has a stronger causal effect on the former as compared to the opposite. This result connotes that the implied volatility of the market plays a key role in characterization of the market's realized volatility.

Time consistency for scalar multivariate risk measures
Zachary Feinstein,Birgit Rudloff

In this paper we present results on dynamic multivariate scalar risk measures, which arise in markets with transaction costs and systemic risk. Dual representations of such risk measures are presented. These are then used to obtain the main results of this paper on time consistency; namely, an equivalent recursive formulation of multivariate scalar risk measures to multiportfolio time consistency. We are motivated to study time consistency of multivariate scalar risk measures as the superhedging risk measure in markets with transaction costs (with a single eligible asset) (Jouini and Kallal (1995), Roux and Zastawniak (2016), Loehne and Rudloff (2014)) does not satisfy the usual scalar concept of time consistency. In fact, as demonstrated in (Feinstein and Rudloff (2020)), scalar risk measures with the same scalarization weight at all times would not be time consistent in general. The deduced recursive relation for the scalarizations of multiportfolio time consistent set-valued risk measures provided in this paper requires consideration of the entire family of scalarizations. In this way we develop a direct notion of a "moving scalarization" for scalar time consistency that corroborates recent research on scalarizations of dynamic multi-objective problems (Karnam, Ma, and Zhang (2017), Kovacova and Rudloff (2020)).

Upswing in Industrial Activity and Infant Mortality during Late 19th Century US
Nahid Tavassoli,Hamid Noghanibehambari,Farzaneh Noghani,Mostafa Toranji

This paper aims to assess the effects of industrial pollution on infant mortality between the years 1850-1940 using full count decennial censuses. In this period, US economy experienced a tremendous rise in industrial activity with significant variation among different counties in absorbing manufacturing industries. Since manufacturing industries are shown to be the main source of pollution, we use the share of employment at the county level in this industry to proxy for space-time variation in industrial pollution. Since male embryos are more vulnerable to external stressors like pollution during prenatal development, they will face higher likelihood of fetal death. Therefore, we proxy infant mortality with different measures of gender ratio. We show that the upswing in industrial pollution during late nineteenth century and early twentieth century has led to an increase in infant mortality. The results are consistent and robust across different scenarios, measures for our proxies, and aggregation levels. We find that infants and more specifically male infants had paid the price of pollution during upswing in industrial growth at the dawn of the 20th century. Contemporary datasets are used to verify the validity of the proxies. Some policy implications are discussed.

Volume Dynamics around FOMC Announcements
Zhu, Xingyu (Sonya)
The stock market volume decreases in anticipation of FOMC announcements and increases afterward. I find, in the cross-section, that stocks with higher market risk exposure experience greater volume changes. I also find that volume dynamics around FOMC announcements are unlikely to be attributable to changes in volatility. Instead, they are linked to discretionary liquidity trading resulting from the presence of private information. I set up a model that guides my investigation of the information environment in the stock market around FOMC announcements. Consistent with the model’s implication, volume dynamics are accompanied by changes in the information environment. I find that information asymmetry increases ahead of FOMC announcements, but only for high-beta stocks.

When Green Meets Green
Degryse, Hans,Goncharenko, Roman,Theunisz, Carola,Vadazs, Tamas
What is the impact of environmental consciousness (i.e., being green) as borrower and as lender on loan rates? We investigate this question employing an international sample of syndicated loans over the period 2011-2019. We find that green firms borrow at a significantly lower spread, especially when the lender consortium can also be classified as green, i.e., when "green-meets-green". Further tests reveal that the impact of "green-meets-green" became significant and large negative only after the acceptance of the Paris Agreement in December 2015. We argue that this is evidence for lenders responding to policy events which affect environmental attitudes.

사외이사 활동성과 저축은행 연체대출비율: 대í'œì´ì‚¬, 사외이사 재직기간 및 수익성 Savings Banks’ Outside Director Activity and Loan Delinquency: CEO and Outside Director’s Tenures and Profitability
Kim, Hakkon
Korean Abstract:본고ëŠ" 저축은행을 대상으로 사외이사의 활동성과 연체대출비율의 관계를 분석하였으며 ì¶"ê°€ 분석을 통해 저축은행의 대í'œì´ì‚¬ 및 사외이사의 재직기간, 수익성이 사외이사 활동성과 연체대출비율의 관계에 미치ëŠ" 영향을 살펴보았다. 분석결과, 사외이사 활동성과 저축은행의 연체대출비율은 유의한 ì—­(-)의 관계가 나타났다. 이러한 ê²°ê³¼ëŠ" 이사회 참석을 통한 사외이사의 적극적 활동이 사외이사의 감시·정보획ë" 능력을 제고하기 때문으로 보인다. 또한 본고ëŠ" 저축은행의 대í'œì´ì‚¬ 및 사외이사의 재직기간이 짧을수록 부정적 효과가 연체대출비율에 나타날 수 있으나 사외이사의 적극적인 활동은 이러한 영향을 완í™"í•  수 있음을 발견하였다. 반면, 저축은행 수익성과 관련하여 본고ëŠ" 유의한 결과를 확인하지 못 하였다. 본 연구결과ëŠ" 사외이사 활동성에 대한 연구가 미흡한 저축은행을 대상으로 사외이사의 활발한 활동이 저축은행의 연체대출비율에 긍정적 영향을 줄 수 있음을 보여주며, 대í'œì´ì‚¬ 및 사외이사의 재직기간이 짧은 저축은행일수록 사외이사의 적극적인 활동을 유인할 í•„ìš"ê°€ 있음을 시사한다.English Abstract:This paper studies how the activity of outside director effects on the loan delinquency of Korean savings banks. In addition, this study shows the effects of CEO and outside director’s tenures and savings banks’ profitability on the relation between the activity of outside director and loan delinquency. First, we find a negative relation between outside director activity and loan delinquency. The result implies that a high level of outside director’s activity can strengthen monitoring effects by alleviating information asymmetry and improving the ability of outside director and then reduce the loan delinquency. Second, it seems that the vigorous activity of outside director can alleviate the negative effects of CEO and outside director’s short tenures. However, the interaction term between the activity and low-profitability is insignificant. These results imply that savings banks might entice outside directors to attend the board of directors, especially if CEO and outside director have short tenures.

시스템리스크 대ì'을 위한 과제와 예금보험공사의 ì—­í•  Systemic Risk and the Role of Deposit Insurance Authority in Korea
Park, Rae Soo,Jung, Hyunjae
Korean Abstract: 2008ë…„ 글로벌 금융위기 이후 한국은행, 금융감독원, 예금보험공사 ë"± 금융안전망 기구ë"¤ì€ 거시건전성 제고를 위한 시스템리스크 대ì'체계를 지속적으로 정비해 ì™"지만 해외 주ìš"êµ­ë"¤ê³¼ëŠ" 달리 법적 지위를 갖춘 거시건전성정책 총괄기구의 부재, 금융안전망기구ë"¤ ê°„ 정보공유 부족, 부실í™" 이전의 정상금융회사에 대한 자금지원체계 미비 ë"±ì˜ 문제점은 여전하다.특히, 비은행권 리스크와 업권 ê°„ 상호연계성으로 인한 내생적 위험ìš"인이 확대되고 있ëŠ" 국내금융시스템 특성을 고려하면 위기대ì'체계 구축에 있어 예금보험공사의 역할이 긴ìš"하다. 최근 COVID-19 팬데믹 선언과 함께 경기부ì–'을 위한 전방위적인 통í™"・재정 정책이 동원되고 있지만, 실물경기 침체가 장기í™"될 경우 금융회사 부실로 인한 금융위기 재연의 우려도 커지고 있ëŠ" 상황이기에 정상금융회사에 대한 자금지원체계 수립이 구체적으로 논의되어야 í•  시점이다.English Abstract:Since the Global Financial Crisis in 2008, financial safety nets, such as the Bank of Korea, the Financial Supervisory Service, and the Korea Deposit Insurance Corporation (KDIC) have continued to improve their risk-response systems to improve the macroprudential measures. However, unlike other major countries, problems still remain in Korea; lack of a macroprudential policy authority with legal status, lack of information sharing system among financial safety nets, and lack of funding schemes for financial companies prior to their insolvency.Given the nature of the domestic financial industry, where endogenous risk factors continue to rise due to the risks in non-banking sectors and the interconnectedness among financial sectors, the role of the deposit insurance authority is crucial in building a crisis response system.Recently, with the COVID-19 pandemic declaration, all-round monetary and fiscal policies are being mobilized to stimulate the economy. However, if the economic downturn is prolonged, there will be a growing concern over the next financial crisis that may be triggered by the insolvencies of financial institutions. Therefore, an in-depth discussion should be held on setting up a funding scheme for financial companies.