Research articles for the 2020-07-27

'Please Stop Talking About the VIX So Much' Revisited
Raju, Rajan
Asness (2017) wrote a short piece in 2017 titled Please Stop Talking About the VIX So Much. He was cautioning about reading too much in the VIX. Figure 1 shows VIX (CBO, 2019) since 1990. In 2020, VIX has scaled new peaks and remains elevated over its long term average. When Asness wrote his note in 2017, VIX was less than the 1st percentile low. More recently, it has been more than the 1st percentile highs. In this environment, it is reasonable to ask the question whether Asness' conclusion `VIX and realized volatility are almost entirely the same thing' holds true.

A well-timed switch from local to global agreements accelerates climate change mitigation
Vadim A. Karatayev,Vítor V. Vasconcelos,Anne-Sophie Lafuite,Simon A. Levin,Chris T. Bauch,Madhur Anand

Recent attempts at cooperating on climate change mitigation highlight the limited efficacy of large-scale agreements, when commitment to mitigation is costly and initially rare. Bottom-up approaches using region-specific mitigation agreements promise greater success, at the cost of slowing global adoption. Here, we show that a well-timed switch from regional to global negotiations dramatically accelerates climate mitigation compared to using only local, only global, or both agreement types simultaneously. This highlights the scale-specific roles of mitigation incentives: local incentives capitalize on regional differences (e.g., where recent disasters incentivize mitigation) by committing early-adopting regions, after which global agreements draw in late-adopting regions. We conclude that global agreements are key to overcoming the expenses of mitigation and economic rivalry among regions but should be attempted once regional agreements are common. Gradually up-scaling efforts could likewise accelerate mitigation at smaller scales, for instance when costly ecosystem restoration initially faces limited public and legislative support.

Advanced Mathematical Business Strategy Formulation Design

This paper deals with the explicit design of strategy formulations to make the best strategic choices from a conventional matrix form for managing strategies. The explicit strategy formulation is a new mathematical model which provides the analytical strategy framework to find the best moment for strategy shifting to prepare rapid market changes. Analytically tractable results are obtained by using the fluctuation theory. These results predict not only the moment for changing strategy in a matrix form but also the prior moment of the change. This explicit model could be adapted into practically every strategic decision making situations which are described as a matrix form with the quantitative measures of the decision parameters. This research helps strategy decision makers who want to find the optimal moments of shifting present strategies.

Are All Outside Directors Created Equal With Respect to Firm Disclosure Policy?
Enache, Luminita,Srivastava, Anup,Parbonetti, Antonio
Empirical evidence on the association between outside directors and firms’ voluntary disclosures is mixed and controversial. We hypothesize that the outside directors do not represent a homogeneous group of people as considered in the literature. Using hand-collected data from a sample of biotechnology firms, we find that the aforesaid association differs based on the directors’ professional backgrounds. Our results are consistent with two ideas. First, an outside director’s influence on firm disclosure policy is shaped by her professional background. Second, firms match outside directors’ professional backgrounds with their disclosure policy. We cannot distinguish between the two explanations. Yet, we make an important contribution to the literature. We show that the impact and the selection prospects of outside directors are not as uniform as previously considered in the literature. Thus, the researchers examining financial disclosures must take into account the background characteristics of all outside directors, not just of those in the audit committee. And investor bodies must consider the background characteristics of candidates in their recommendation for outside-director selection.

Are low frequency macroeconomic variables important for high frequency electricity prices?
Claudia Foroni,Francesco Ravazzolo,Luca Rossini

We analyse the importance of low frequency hard and soft macroeconomic information, respectively the industrial production index and the manufacturing Purchasing Managers' Index surveys, for forecasting high-frequency daily electricity prices in two of the main European markets, Germany and Italy. We do that by means of mixed-frequency models, introducing a Bayesian approach to reverse unrestricted MIDAS models (RU-MIDAS). Despite the general parsimonious structure of standard MIDAS models, the RU-MIDAS has a large set of parameters when several predictors are considered simultaneously and Bayesian inference is useful for imposing parameter restrictions. We study the forecasting accuracy for different horizons (from $1$ day ahead to $28$ days ahead) and by considering different specifications of the models. Results indicate that the macroeconomic low frequency variables are more important for short horizons than for longer horizons. Moreover, accuracy increases by combining hard and soft information, and using only surveys gives less accurate forecasts than using only industrial production data.

Cheapest-to-Deliver Pricing and Endogenous MBS Heterogeneity
Huh, Yesol,Kim, You Suk
We study optimal securitization when the secondary market has cheapest-to-deliver pricing. More specifically, we study theoretically and empirically how lenders pool mortgages to create agency mortgage-backed securities (MBS) taking into account how To-Be-Announced (TBA) markets operate. First, we document that lenders separate out and pool high-value loans by themselves to create high-value MBS, which is then traded outside the TBA market to avoid its cheapest-to-deliver pricing. Second, we present a model that features key elements of the agency MBS market. Creating high-value MBS increases heterogeneity in MBS values, which leads to a higher adverse selection problem and lower liquidity in the TBA market. In equilibrium, lenders choose a lower degree of pooling than the social planner would, creating more high-value MBS and thereby decreasing TBA market price and volume. A decrease in the difference between the parallel specified-pool market and TBA market trading costs or an increase in loan value dispersion amplifies these mechanisms, leading to a lower degree of pooling, lower TBA market volume, and lower lenders' revenue. Lastly, we provide empirical evidence consistent with model predictions.

Copula-based Local Dependence Framework
Huang, Zaixin
This paper proposes a novel copula-based local Kendall’s tau framework to uncover richer nonlinear local dependence between two financial return series. This framework nests the concepts of global dependence, tail dependence and local dependence. Closed form solutions of local Kendall’s tau in terms of copula link local dependence with their global dependence structure together, providing a generalized framework for investigating dependence between two return series. We further extend the copula-based local dependence framework to Spearman’s rho. Using this framework, we draw the local Kendall’s tau surfaces in different quadrants for some common used bivariate Archimedean copulas. Finally, we demonstrate the advantages of copula-based local Kendall’s tau relative to global Kendall’s tau with stock market data.

Cryptocurrency Valuation and Machine Learning
Liu, Yulin,Zhang, Luyao
As in stock and commodity markets, investors and financial analysts are constantly seeking a reliable indicator to assess the price of cryptocurrency assets. However, there are currently no convincing proxies for the fundamentals of cryptocurrency assets. We propose a new methodology for cryptocurrency valuation by considering insights from classic Monetary Economics and Machine Learning in data science. We then illustrate and evaluate the methodology using big data of Bitcoin as a case study. The results indicate a significant improvement from other existing approaches in explaining asset valuation and informing investment strategies. Moreover, we propose an automated trading strategy based on the simple indicator alone for further industry applications and document its outstanding performance in comparison to the conventional strategies.

Deep neural network for optimal retirement consumption in defined contribution pension system
Wen Chen,Nicolas Langrené

In this paper, we develop a deep neural network approach to solve a lifetime expected mortality-weighted utility-based model for optimal consumption in the decumulation phase of a defined contribution pension system. We formulate this problem as a multi-period finite-horizon stochastic control problem and train a deep neural network policy representing consumption decisions. The optimal consumption policy is determined by personal information about the retiree such as age, wealth, risk aversion and bequest motive, as well as a series of economic and financial variables including inflation rates and asset returns jointly simulated from a proposed seven-factor economic scenario generator calibrated from market data. We use the Australian pension system as an example, with consideration of the government-funded means-tested Age Pension and other practical aspects such as fund management fees. The key findings from our numerical tests are as follows. First, our deep neural network optimal consumption policy, which adapts to changes in market conditions, outperforms deterministic drawdown rules proposed in the literature. Moreover, the out-of-sample outperformance ratios increase as the number of training iterations increases, eventually reaching outperformance on all testing scenarios after less than 10 minutes of training. Second, a sensitivity analysis is performed to reveal how risk aversion and bequest motives change the consumption over a retiree's lifetime under this utility framework. Third, we provide the optimal consumption rate with different starting wealth balances. We observe that optimal consumption rates are not proportional to initial wealth due to the Age Pension payment. Forth, with the same initial wealth balance and utility parameter settings, the optimal consumption level is different between males and females due to gender differences in mortality.

Defined Benefit Pension Policies and Social Responsibility Performance: Do Socially Responsible Firms Walk the Talk?
Harjoto, Maretno A.,Laksmana, Indrarini
This study examines whether socially responsible firms have well-funded employee pension programs and whether corporate social responsibility (CSR) performance is associated with management discretionary choice of pension accounting assumptions. Based on the signaling theory, this study explains how senders view the signaling process as a channel to build their reputation, and the correspondent inference theory to explain how receivers process and assess the signal. Using a panel data of 13,099 firms-years across 1,428 U.S. firms from 1992 to 2015, this study finds that firms with higher CSR scores report higher pension net assets and are less likely to have underfunded pension than their counterparts. These firms also adopt more responsible (conservative) pension accounting assumptions (i.e., lower discount rate and higher rate of compensation increase) to estimate pension benefit obligations. Results are stronger for firms that operate in the materials and industrial sectors and for the post-2000 period when underfunded pension has become more prevalent. Firms with higher CSR scores are also less likely to have a pension freeze. This study provides inputs for public accountants providing assurance services that CSR performance has a significant impact on management reporting choices.

Depressive Realism and Analyst Forecast Accuracy
Jannati, Sima,Khalaf, Sarah,Nguyen, Du
Whether a bad mood enhances or hinders problem-solving and financial decision making is an open question. Using the Gallup Analytics survey, we test the depressive realism hypothesis in the earnings forecasts provided by Estimize users. The depressive realism hypothesis states that mild forms of depression improve judgment tasks because of higher attention to detail and slower information processing. We find that a 1-standard-deviation increase in the segment of the U.S. population with depression leads to a 0.25\% increase in future forecast accuracy, supporting the hypothesis. This influence is comparable to other determinants of Estimize users' accuracy, like the geographic proximity of users to firms, users' experience, and their professional status. Our result is robust to using an IV analysis, different measures of forecast accuracy and mood, as well as alternative explanations.

Distributionally Robust Markov Decision Processes and their Connection to Risk Measures
Nicole Bäuerle,Alexander Glauner

We consider robust Markov Decision Processes with Borel state and action spaces, unbounded cost and finite time horizon. Our formulation leads to a Stackelberg game against nature. Under integrability, continuity and compactness assumptions we derive a robust cost iteration for a fixed policy of the decision maker and a value iteration for the robust optimization problem. Moreover, we show the existence of deterministic optimal policies for both players. This is in contrast to classical zero-sum games. In case the state space is the real line we show under some convexity assumptions that the interchange of supremum and infimum is possible with the help of Sion's minimax Theorem. Further, we consider the problem with special ambiguity sets. In particular we are able to derive some cases where the robust optimization problem coincides with the minimization of a coherent risk measure. In the final section we discuss two applications: A robust LQ problem and a robust problem for managing regenerative energy.

Diversification Within Large Cap Equity Mutual Funds in India
Raju, Rajan,Mittal, Ananya,Baruah, Rajiv
We ask whether a portfolio of large-cap mutual funds in India generates any diversification benefits as compared to holding a single large-cap index tracking exchange-traded fund. Using a mix of traditional measures like correlation and covariance of excess returns, and measures like tracking error, information ratio, and active share, we show that there are limited diversification benefits in a portfolio of two or more large-cap funds. A majority of the funds have similar risk return characteristics and negative information ratios versus a NIFTY100 tracking ETF. A cross-sectional analysis of active shares of the funds at the end of June 2020 shows that underlying holdings of funds are crowded together and funds do not have significant active share.

Does Joining the S&P 500 Index Hurt Firms?
Bennett, Benjamin,Stulz, René M.,Wang, Zexi
We investigate the impact on firms of joining the S&P 500 index from 1997 to 2017. We find that the positive announcement effect on the stock price of index inclusion has disappeared and the long-run impact of index inclusion has become negative. Inclusion worsens stock price informativeness and some aspects of governance. Compensation, investment, and financial policies change with index inclusion. For instance, payout policies of firms joining the index become more similar to the policies of their index peers. ROA falls following inclusion. There is no evidence of an impact of inclusion on competition.

Duality for optimal consumption under no unbounded profit with bounded risk
Michael Monoyios

We give a definitive treatment of duality for optimal consumption over the infinite horizon, in a semimartingale incomplete market satisfying no unbounded profit with bounded risk (NUPBR). Rather than base the dual domain on (local) martingale deflators, we use a class of supermartingale deflators such that deflated wealth plus cumulative deflated consumption is a supermartingale for all admissible consumption plans. This yields a strong duality, because the enlarged dual domain of processes dominated by deflators is naturally closed, without invoking its closure. In this way we automatically reach the bipolar of the set of deflators. We complete this picture by proving that the set of processes dominated by local martingale deflators is dense in our dual domain, confirming that we have identified the natural dual space. In addition to the optimal consumption and deflator, we characterise the optimal wealth process. At the optimum, deflated wealth is a supermartingale and a potential, while deflated wealth plus cumulative deflated consumption is a uniformly integrable martingale. This is the natural generalisation of the corresponding feature in the terminal wealth problem, where deflated wealth at the optimum is a uniformly integrable martingale. We use no constructions involving equivalent local martingale measures. This is natural, given that such measures typically do not exist over the infinite horizon and that we are working under NUPBR, which does not require their existence. The structure of the duality proof reveals an interesting feature compared with the terminal wealth problem. There, the dual domain is $L^{1}$-bounded, but here the primal domain has this property, and hence many steps in the duality proof show a marked reversal of roles for the primal and dual domains, compared with the proofs of Kramkov and Schachermayer.

Dynamic Networks in Large Financial and Economic Systems
Ellington, Michael,Baruník, Jozef
We propose new measures to characterize dynamic network connections in large financial and economic systems. In doing so, our measures allow one to describe and understand causal network structures that evolve throughout time and over horizons using variance decomposition matrices from time-varying parameter VAR (TVP VAR) models. These methods allow researchers and practitioners to examine network connections over any horizon of interest whilst also being applicable to a wide range of economic and financial data. Our empirical application redefines the meaning of “big” in big data, in the context of TVP VAR models, and track dynamic connections among illiquidity ratios of all S&P500 constituents. We then study the information content of these measures for the market return and real economy.

Economies of Scale Revisited: Evidence from Italian Banks
Bonaccorsi di Patti, Emilia,Ciocchetta, Federica
This paper provides new estimates of cost scale economies for Italian banks, based on a model of bank production that takes into account a comprehensive definition of output including different categories of loans, deposits, off-balance sheet items, payment services, and brokerage and asset management activities. The output definition is more in line with the current business model of banks than previous studies since it explicitly accounts for transaction banking and IT capital. We find returns to scale in operating costs, especially for small and medium-sized institutions. For the largest institutions there is on average no statistically significant evidence of returns from scale on the cost side; however, banks falling into this latter category are quite heterogeneous in size and business model. A more extensive adoption of digital technologies in the future could expand the size range over which positive returns to scale are achievable. These results are robust to alternative input and output specifications and functional forms. An important caveat to this conclusion is that we focus solely on operating costs.

Empirical Asset Pricing via Machine Learning: Evidence from the European Stock Market
Drobetz, Wolfgang,Otto, Tizian
This paper evaluates the performance of machine learning methods in forecasting stock returns. Compared to a linear benchmark model, interactions and non-linear effects help improve predictive performance. But machine learning models must be adequately trained and tuned to overcome the high dimensionality issue and to avoid over-fitting. Across all machine learning methods, the most important predictors are based on price trends and fundamental signals from valuation ratios. However, the models exhibit disparities in statistical performance that translate into pronounced differences in economic profitability. The return and risk measures of long-only trading strategies indicate that machine learning models produce size-able gains relative to our benchmark. Neural networks perform best, even after adjusting for risk and accounting for transaction costs. However, a classification-based portfolio formation, utilizing a support vector machine that avoids estimating stock-level expected returns, performs even better than the neural network architecture.

Employee Sentiment and Stock Return Predictability
Symitsi, Efthymia,Stamolampros, Panagiotis
We propose a new measure of investor sentiment based on predictions of firms' near-term prospects, disclosed in online platforms by their employees. By aggregating this forward-looking information, we construct an Employee Sentiment Index (ESI) and find that it is a strong predictor of stock market returns with lower future returns following high employee sentiment. Its predictive ability is superior compared to existing measures of investor sentiment and commonly-studied macroeconomic variables. Further, it predicts cross-sectional returns from difficult to value and costly to arbitrage stocks. The predictive power of the ESI is explained by investors' biased beliefs about expected cash flows.

Factors for Successful E-Government Adoption in Palestine: A Conceptual Framework
Obaid, Tareq,Abu Mdallalah , Samir ,Jouda, Haitham,Abu Jarad , Ali
Despite the fact that the success of e-Government adoption is subject to the citizens’ willingness to use it, little consideration has been paid to explore the adoption of e-government from citizens' perspective. However, it seems that the rate of adoption of e-Government has globally fallen below expectations although some countries are doing better than others. Therefore, improving the comprehension of the residents’ reasons and methods of using government sites, including their behaviour towards e-Government, is crucial. This article discusses this matter by suggesting a conceptual model of e-Government adoption and mainly emphasising the users in the method of applying e-Government. Notably, the analysis of the primary elements in the analysis, namely the technical, personal, and reliability elements, improves the comprehension of the adoption of e-Government services in Palestine.

Financial Crises, Macroprudential Policy and the Reliability of Credit-to-GDP Gaps
Alessandri, Piergiorgio,Bologna, Pierluigi,Galardo, Maddalena
The Basel III regulation explicitly prescribes the use of Hodrick-Prescott filters to estimate credit cycles and calibrate countercyclical capital buffers. However, the filter has been found to suffer from large ex-post revisions, raising concerns over its fitness for policy use. To investigate this problem, we studied the credit cycles of a panel of 26 countries between 1971 and 2018. We reached two conclusions. The bad news is that the limitations of the one-sided HP filter are serious and pervasive. The good news is that they can easily be mitigated. The filtering errors are persistent and hence predictable. This can be exploited to construct real-time estimates of the cycle that are less subject to ex-post revisions, forecast financial crises more reliably, and stimulate the build-up of bank capital before a crisis.

Impact of Coronavirus Pandemic on the Global Economy: Demand and Supply Shock
Nwokolo, Chinenye Ifeoma ,Ogbuagu, Matthew Ikechukwu ,Iwegbu, Onyebuchi
COVID-19 pandemic has been accompanied with a shrink in global economic activities. To examine the impact of coronavirus pandemic on the global economy, the paper employed the Granger causality test and the Vector Autoregression (VAR) technique. Utilising daily data on COVID-19 cases, stock indexes and commodity prices spanning from January 1st, 2020 till April 31st, 2020; the study revealed that COVID-19 pandemic does not cause a change in the regional stock markets. Similarly, the causality test supports that the COVID-19 confirmed cases do not cause a change in the commodity prices within these regions; except for the price of natural gas which changed as a result of the COVID-19 pandemic in Europe. Besides the EURONEXT market in the Eastern Mediterranean region, the impulse response shows that other regional stock markets respond positively to shocks in daily report of COVID-19 confirmed cases. The study concluded that within the study period, the HSBC’s stock index was the worst-hit. Thus, aggressive effort targeted at developing vaccine as well as coordinated policy measures aimed at increasing the stock market pause above 15 minutes when the stock prices fall below the lower bound.

Insurance Asset-Liability Management: Time To Reduce Duration.
Verbiest, Eddy H.
A new return and risk measure is presented that captures the whole Assets -Liabilities Runoff for an insurance company. It shows:(1) that short duration allocations with higher yielding diversified assets are currently safer and more rewarding what refutes duration matching as a method to reduce risk, (2) that a high Solvency 2 ratio is counterproductive and (3) that the Solvency 2 framework falls short by being return agnostic.

Integrating Big Data and Intellectual Capital: Resource Complementarity in Business Value Creation
Alomari, Izzeideen,Shehada, Feras ,El-Daour, Jaber
Intellectual capital is gaining increasing attention, especially through the adoption of innovative technologies such as big data. Literature has scrutinized the impact of big data and intellectual capital independently and reveals a positive influence on the value of business from their utilization. Nevertheless, relying on the theory of based-view resource and the experience of practitioners in the field, this study proposes that the effects of their complementary and shared utilization should be much bigger. Such a proposal has not been discussed and empirically examined so far. This paper discusses how to deploy big data and intellectual capital concurrently in the framework of accounting and information systems, with a discussion of the interaction of big data and intellectual capital as resources that could pull out the most complementary value for companies and establish a future research agenda.

Kripto Paraların İslam Para Sistemi Açısından Uygunluğu: Türkiye İçin Uygulanabilir İslami Kripto Para Modeli Önerisi (Convenience of Cryptocurrency in terms of Islamic Monetary System: Proposal of Islamic Cryptocurrency Model Applicable in Turkey)
KAZAK, Hasan
Turkish abstract: Çalışmanın Amacı: Günümüzde finans dünyasında önemli bir hacme ulaşan kripto paraların İslami finans sistemi içerisindeki durumunu ortaya koyarak İslami para ve finans sistemine uygun Türkiye için uygulanabilir kripto para model önerisi geliştirmek amaçlanmıştır. Çalışmanın Metodolojisi: Yapılan çalışmada öncelikle paranın ilk icadından günümüze kadar olan seyri ortaya konmuş, bu seyir içerisinde insanlığın ve İslam aleminin ilk zamanlardan bugüne kadar ortaya çıkan durumlar ve bu durumlar karşısında ortaya koydukları tepki ve çözüm yolları incelenmiştir. Bu tespitler ışığında uygun bir model geliştirilmeye çalışılmıştır. Çalışmanın Bulguları: Yapılan literatür çalışmalarında kripto paralar konusunda çok fazla çalışmanın olduğu İslami kripto para konusunda ise çalışmaların sınırlı sayıda olduğu görülmüştür. İslami kripto para konusunda yapılan çalışmaların halen yeterli olgunluğa ulaşmadığı, sistem üzerinde halen tartışmaların devam ettiği, üzerinde uzlaşılan bir modelin ortaya konulamadığı ve bu nedenle de üzerinde çalışma yapılmaya ihtiyaç olduğu görülmüştür. Çalışmanın Önemi: Çalışmada İslami para ve finans sistemine uygun kullanılabilir bir kripto para modeli önerilmiştir. Literatürde yer alan çalışmalardan farklı unsurları içeren ve İslam’ın para kriterlerini taşıdığı düşünülen bu modelin en önemli avantajı modelin hemen uygulanabilmesinin mümkün olması ve İslam dünyasının gelişen bu para sistemi içerisinde yer almasını mümkün kılabilecek bir öneri sunmasıdır.English abstract: Objective of the Study: It is aimed in this study to develop a model of cryptocurrency which is applicable in Turkey and suitable for Islamic monetary and financial system, by presenting the condition of cryptocurrency, which has reached a significant size in the world of finance, in the system of Islamic finance. Methodology of the Study: In this study, first of all, the course of money from its invention and first use to the present time has been revealed, and the cases that have emerged in this course since the earliest days of humanity and the Islamic world, and their reactions as well as solutions to these cases have been examined. In the light of these findings, an appropriate model has been tried to be developed. Findings of the Study: With a close review of literature, it has been observed that while there are limited number of studies on cryptocurrencies, and that number is limited when it comes to the studies on Islamic cryptocurrency. It has also been seen that studies on Islamic cryptocurrency are still not ground, discussions on the system still continue, a model that is not agreed upon has not, yet, been put forth, and therefore there is a need to conduct more studies on it. Significance of the Study: In the study, a practicable cryptocurrency model that is suitable for Islamic money and financial system has been proposed. The most important advantage of this model, which contains different elements from those stated in studies available in the literature and which is thought to meet the monetary criteria of Islam, is that it is possible to apply it immediately and that it offers a proposal that enables it to be included in this developing monetary system of the Islamic world.

Market Sentiment and Innovation Activities
Xu, Zhaoxia,Dang, Tri Vi
We investigate potential mechanisms through which market-wide sentiment affects firms’ innovation activities. We provide evidence for the financing channel by showing that financially constrained firms are more likely to issue equity and invest more in research and development (R&D) than financially unconstrained firms at high market sentiment. Using time-varying manager sentiment measures, we find suggestive evidence for a sentiment spillover channel whereby market sentiment affects R&D investments through influencing manager sentiment. Furthermore, better patent portfolios are produced from R&D investments stimulated by high market sentiment. Market sentiment has a stronger impact on R&D than the capital expenditures of financially constrained firms.

Matching the Bloomberg Curve S45 with QuantLib
Caspers, Peter,Palermo, Andrea
In this short note we summarise one of the results achieved in a project conducted by SoftSolutions! with the goal of aligning some of the bond analytics result in their system nexRates with those that are produced in Bloomberg. By adding a global bootstrapper to the QuantLib library we are able to apply a certain smoothing algorithm to the Euribor 6M curve bootstrapping. Thereby we achieve a very close match of the corresponding Bloomberg S45 curve, which is the basis for the computation of the Z-Spread for bonds.

Measuring Competition in M&A Negotiations
Schubert, Richard
This paper provides novel insights about competition among bidders during the whole takeover process, its effect on offered deal premiums, bidder announcement returns, and post-bid dynamics. Exploiting a representative sample of 780 public U.S. transactions, extended with comprehensive hand-collected data from SEC filings, I find that takeover premiums are higher, the higher pre-announcement competition among bidders is. I measure competition during the private sales process with a ratio that relates the number of bids submitted to the target to the number of signed confidentiality agreements with the target, the Proposals-to-CA-Ratio. A one-standard deviation increase of this ratio corresponds to a statistically and economically significant 5.99% increase of the deal initiation premium (Eaton, Liu, and Officer (2020)), 0.87% lower announcement returns for the winning bidder in auctions, a 130% increased probability of receiving a rival bid prior to closing, and a 44.5% increased probability of cancelling the originally announced deal (measured relative to the unconditional probability). The latter two results are more pronounced if the announcement returns of the acquirer are positive, suggesting that competing bidders are lured by potentially value-increasing deals. By applying Heckman (1979) two-stage selection models with instrumented regressors, I show that my results are robust to endogeneity concerns, especially to target’s decision to initiate the deal as well as the decision of the subsequent selling procedure (auction vs. one-to-one negotiation). The advantages of this competition measure are that (1) it relies on data as reported in target firm’s official merger documents filed with the SEC, which creates a strong incentive to report truthfully, and (2) it takes the evolution of bidding into account, controlling for the number of submitted bids. I conclude that competitive private negotiations stay competitive during the public phase of the deal, and that target boards fulfill their fiduciary duties by selecting the highest-bidding acquirer.

Mobile Banking Adoption: Decomposed Theory of Planned Behavior with Perceived Trust
Jouda, Haitham,Abu Jarad , Ali ,Obaid, Tareq,Abu Mdallalah , Samir ,Awaja, Ahmed
For financial institutions, mobile banking has represented a breakthrough in terms of remote banking services. However, many customers remain uncertain due to its security. This study aims to shed light on the factors that determine user acceptance of mobile banking applications in Palestine by developing a new acceptance technology model that incorporates the decomposed theory of planned behavior along with perceived trust. Data were collected by conducting a survey questionnaire completed by 682 participants. Collected data were analyzed by structural equation modeling technique. The results indicated a significant positive impact of attitude, perceived behavior control, and perceived trust toward mobile banking in Palestine. Surprisingly, the effects of subjective norms on mobile banking adoption were insignificant.

Online Appendix for 'Feedback and Contagion through Distressed Competition'
Chen, Hui,Dou, Winston,Guo, Hongye,Ji, Yan
This is the supplemental material to the paper titled "Feedback and Contagion through Distressed Competition." It includes additional empirical, theoretical, and quantitative results. It also includes illustration for the numerical algorithm for our model solution.

Option Pricing in Markets with Informed Traders
Yuan Hu,Abootaleb Shirvani,Stoyan Stoyanov,Young Shin Kim,Frank J. Fabozzi,Svetlozar T. Rachev

The objective of this paper is to introduce the theory of option pricing for markets with informed traders within the framework of dynamic asset pricing theory. We introduce new models for option pricing for informed traders in complete markets where we consider traders with information on the stock price direction and stock return mean. The Black-Scholes-Merton option pricing theory is extended for markets with informed traders, where price processes are following continuous-diffusions. By doing so, the discontinuity puzzle in option pricing is resolved. Using market option data, we estimate the implied surface of the probability for a stock upturn, the implied mean stock return surface, and implied trader information intensity surface.

Personal and Organizational Higher Purpose, Corporate Governance and Shareholder Value: Survey Results
Bunderson, Stuart,Thakor, Anjan V.
This paper reports the findings of a recent survey of 1019 individuals to learn about their commitment to and perceived value from personal and organizational higher purpose, and examines the implications of the findings for corporate governance and the stated corporate goal of shareholder value maximization. We found that personal higher purpose promotes personal well-being, including greater happiness and lower stress from COVID-19, and this effect was stronger when the purpose statement was written down. This notwithstanding, while many individuals stated that they have a personal higher purpose, very few had a written statement of purpose. The incidence of written higher purpose statements is higher among organizations than among individuals. Employees of organizations with higher purpose statements were happier and prouder of their organizations. Two of the findings have potentially important implications for corporate governance: (i) The effects we documented were stronger when the purpose statement was written down and tied to society, employees, and customers, rather than shareholders; and (ii) employees trusted their leaders to make better business decisions when they endorsed the social value of the corporate higher purpose.

Playing to Adapt: Crowdsourcing Historical Climate Data with Gamification to Improve Farmer's Risk Management Instruments
Hernandez-Aguilera, J. Nicolas,Mauerman, Max,Osgood, Daniel
Ground-truthed community-based information over time and space can improve the design of climate risk instruments, reducing the mismatch between farmers’ reported events and remote sensing datasets. However, increasing constraints on direct interaction and a lack of incentives for rural communities’ participation can compromise crowdsourced verification. To address these issues, we designed a game, KON, that uses “gamified” incentives and behavioral elements to gather accurate historical climate data by priming memory through the pairwise comparisons of years and incentivizing accuracy through a points-reward matching system. Our preliminary results suggest that pairwise comparison can facilitate historical bad years recalling, and there is a high correspondence between farmers reporting and satellite sources. Moreover, farmers’ reporting clarifies the story when satellite sources disagree. In addition, the number of responses to the online prototype of the game and the level of participant engagement demonstrated that our game can be easily adapted to different types of weather events and facilitate the collection of a large amount of data in a short amount of time. To adapt and generalize the impact of gamification in diverse agricultural settings, future stages in this project include improve and expand game versions and interphases (i.e., smartphone, SMS), and perform an RCT evaluation for additional hypothesis testing.

Scrutinizing Financial Inclusion: A Critical Review of Its Definitions
Balliester Reis, Thereza
Financial inclusion (FI) has become a key policy for poverty reduction in developing countries. However, there is no consensus on what FI comprises, who should be included and who will deliver this inclusion. The different interpretations of the concept may lead to implementations that do not correspond to the original intent. Moreover, by making certain assumptions implicit, FI may be a policy that merely replicates microfinance initiatives. In order to illustrate the inconsistencies in the existing literature, this article displays a literature review of 67 studies about the definition of FI. Built on the systematic review approach, studies are selected based on inclusion and exclusion criteria, as well as an explicit search strategy, thus providing a reliable and replicable outcome. After identifying the studies, we present a critical discussion about the underlying theoretical and empirical implications of the definitions of FI. This assessment enables a better understanding of FI and its framing. To conclude, a novel definition is suggested to ensure transparency and comparability of FI research.

Sell-side Analyst Recommendation Revisions and Institutional Trading before and after Regulation FD
Caglayan, Mustafa Onur,Celiker, Umut,Lawrence, Edward R.
We examine institutional trading in relation to changes in consensus recommendations over time. We find that pre-Reg FD’s positive contemporaneous relation between hedge fund trading and change in consensus becomes negative after Reg FD, but the positive relation between non-hedge fund trading and change in consensus continues even after Reg FD. Furthermore, during post-Reg FD, while the performance of hedge funds’ trades that contradict with analysts improve, the performance of non-hedge funds’ trades that agree with analysts significantly deteriorate. Our evidence suggests that hedge funds have better information processing skill and are more cognizant about the role of selective information in analyst recommendations.

The Disposition Effect and Returns to Acquiring Firms
Liu, Tingting,Tu, Danni
We investigate whether investor behavioral biases systematically affect acquisition announcement returns by testing the disposition effect hypothesis. We find strong evidence of overvaluation for bidder stock with large unrealized capital losses and undervaluation for bidder stock with large unrealized capital gains around merger announcement. We show that overvaluation is followed by significant price declines while undervaluation is followed by price increases in the subsequent months. These return patterns are stronger among risky deals and among bidders with more disposition investors. We further show that short sale constraints limit the ability of arbitrageurs to eliminate overvaluation. Our results are difficult to reconcile with the rational explanations and suggest the role of investor irrationality as a determinant of mis-pricing in acquisition returns.

The Matthew Effect and Modern Finance: On the Nexus Between Wealth Inequality, Financial Development and Financial Technology
Frost, Jon,Gambacorta, Leonardo,Gambacorta, Romina
This paper analyses the role of financial development and financial technology in inequality in (returns to) wealth. Using micro data from the Survey on Household Income and Wealth (SHIW) conducted by the Bank of Italy over the period 1991-2016, we find that financial development (number of bank branches) and financial technology (use of remote banking) both have a positive association with households’ financial wealth and financial returns. By applying an instrumental variable approach to control for endogeneity, we find that the two variables are, by and large, substitutes. The economic significance of both decreased in the last part of the sample period, as remote banking became more widespread. Finally, other things equal, the effects of financial development and financial technology increase when moving toward the top of the wealth distribution. This is in line with the so-called “Matthew effect” (Merton, 1968), or the capacity of wealthy households to achieve higher returns than other households.

The Substitutive Relation Between Voluntary Disclosure and Corporate Governance in Their Effects on Firm Performance
Enache, Luminita,Hussainey, Khaled
Prior literature shows that financial disclosures and corporate governance both impact firm performance. This paper documents an important topic that has been overlooked in the prior literature, their joint effect, because the two mechanisms could be independent, substitutive, or complementary in their impact on firm performance. We find a substitutive relation based on data from 2005 to 2013 for a sample of US biotech firms, but only for firms with products in advanced stages of development, because their disclosures are trustworthy about the firms’ future performance. We do not find such effect for firms with early-stage products, that would take years to convert to profits, and whose product-related disclosures are speculative at best. This paper shows that informative and reliable voluntary disclosures have similar value-increasing effect as corporate governance and that the marginal effect of trustworthy disclosures is decreasing in governance. To the extent that the two mechanisms are costly, firms can partly substitute one for the other.

The Wage Premium of Communist Party Membership: Evidence from China
Plamen Nikolov,Hongjian Wang,Kevin Acker

Social status and political connections could confer large economic benefits to an individual. Previous studies focused on China examine the relationship between Communist party membership and earnings and find a positive correlation. However, this correlation may be partly or totally spurious, thereby generating upwards-biased estimates of the importance of political party membership. Using data from three surveys spanning more than three decades, we estimate the causal effect of Chinese party membership on monthly earnings in in China. We find that, on average, membership in the Communist party of China increases monthly earnings and we find evidence that the wage premium has grown in recent years. We explore for potential mechanisms and we find suggestive evidence that improvements in one's social network, acquisition of job-related qualifications and improvement in one's social rank and life satisfaction likely play an important role. (JEL D31, J31, P2)

The role of global economic policy uncertainty in predicting crude oil futures volatility: Evidence from a two-factor GARCH-MIDAS model
Peng-Fei Dai,Xiong Xiong,Wei-Xing Zhou

This paper aims to examine whether the global economic policy uncertainty (GEPU) and uncertainty changes have different impacts on crude oil futures volatility. We establish single-factor and two-factor models under the GARCH-MIDAS framework to investigate the predictive power of GEPU and GEPU changes excluding and including realized volatility. The findings show that the models with rolling-window specification perform better than those with fixed-span specification. For single-factor models, the GEPU index and its changes, as well as realized volatility, are consistent effective factors in predicting the volatility of crude oil futures. Specially, GEPU changes have stronger predictive power than the GEPU index. For two-factor models, GEPU is not an effective forecast factor for the volatility of WTI crude oil futures or Brent crude oil futures. The two-factor model with GEPU changes contains more information and exhibits stronger forecasting ability for crude oil futures market volatility than the single-factor models. The GEPU changes are indeed the main source of long-term volatility of the crude oil futures.

Tick Size and Financial Reporting Quality in Small-Cap Firms: Evidence from a Natural Experiment
Ahmed, Anwer S.,Li, Yiwen,Xu, Nina
Using a natural experiment (the SEC’s 2016 Tick Size Pilot Program), we investigate the effects of an increase in tick size on financial reporting quality. The tick size pilot program reduces algorithmic trading and increases fundamental investors’ information acquisition and trading activities. This in turn increases the scrutiny of managers’ financial reporting choices and reduces their incentives to engage in misreporting. Using a difference-in-differences research design, we find a significant decrease in the magnitude of discretionary accruals, a significant reduction in the likelihood of just meeting or beating analysts’ forecasts, and a marginally significant decrease in restatements for the treated firms in the pilot program. Furthermore, we find that the change in financial reporting quality is concentrated in treated firms experiencing decreases in algorithmic trading and increases in information acquisition activities. We also find that the mispricing of accruals is significantly lower for treated firms. Taken together, our results suggest that an increase in tick size has a causal effect on firms’ financial reporting quality.

Trade Credit Model: A Time Elasticity Approach
Goncalves, Adalto
We develop a theoretical model to explain the impact of market power in the product market and financial constraints on trade credit extension. Our model is based on a rational profit maximizing firm operating with a certain level of market power represented by the price elasticity of its product and with customers presenting a certain degree of financial constraint which reflects in their trade credit term-sensitivity of demand. Besides showing the detailed deduction of this model using a non-linear programming approach (Kuhn-Tucker) we show the trade-offs that firms face to increase their profit by selling on credit and compare its implications to the trade credit literature. We further confirm our findings empirically using Compustat quarterly data for 8,602 US firms drawn from 2004 to 2010.

U.S. Stock Returns, the Berry-Esseen Theorem, and Statistical Testing
Crack, Timothy Falcon,McAlevey, Lynn,Sen, Anindya
Neither existing theory nor prior empirical work can tell us the impact of non-normality on required sample sizes for Student-t tests of the mean in U.S. stock returns. Prior empirical work and bounds from a modified Berry-Esseen theorem do suggest, however, that the answer should vary with market capitalization, driven by third moments. For two-tailed nominally 5%-sized one-sample tests, we find that at least 100 observations are needed for large-capitalization stocks, and at least 200 observations are needed for small-capitalization stocks. Larger sample sizes are required for significance levels below 5%, or if one-tailed tests are used with skewed data.

Undervaluation of Employee Satisfaction
chowdhury, jaideep,Celiker, Umut,Sonaer, Gokhan
Edmans (2011) documents that firms in the “100 Best Companies (BC) to Work for in America” earn positive abnormal returns, consistent with the stock market failure to incorporate the value of employee job satisfaction in a timely manner. We find that the abnormal returns are confined to a subset of BC that have performed poorly over the past two years. Specifically, a value-weighted portfolio of loser BC earn an annualized three-factor alpha of 11.96% in the subsequent year, while the same figure for other BC is an insignificant 1.11%. Our findings are consistent with the view that mis-pricing forms over time and provide corroborating evidence for the hypothesis that undervaluing human capital plays a key role in the BC anomaly.

Visibility graph analysis of economy policy uncertainty indices
Peng-Fei Dai,Xiong Xiong,Wei-Xing Zhou

Uncertainty plays an important role in the global economy. In this paper, the economic policy uncertainty (EPU) indices of the United States and China are selected as the proxy variable corresponding to the uncertainty of national economic policy. By adopting the visibility graph algorithm, the four economic policy uncertainty indices of the United States and China are mapped into complex networks, and the topological properties of the corresponding networks are studied. The Hurst exponents of all the four indices are within $\left[0.5,1\right]$, which implies that the economic policy uncertainty is persistent. The degree distributions of the EPU networks have power-law tails and are thus scale-free. The average clustering coefficients of the four EPU networks are high and close to each other, while these networks exhibit weak assortative mixing. We also find that the EPU network in United States based on daily data shows the small-world feature since the average shortest path length increases logarithmically with the network size such that $L\left(N\right)=0.626\ln N+0.405$. Our research highlights the possibility to study the EPU from the view angle of complex networks.

When Can Quarterly Reports Resolve Uncertainty About Earnings? Evidence From ASC 606
Glaze, Jesse,Skinner, A. Nicole,Stephan, Andrew
We examine whether quarterly reports resolve uncertainty about how accruals map to cash flows and, correspondingly, how to price earnings. Although existing studies suggest quarterly reports released concurrently with earnings depress trading due to information overload, we predict that quarterly reports help investors price earnings news when they face uncertainty about how earnings map to future cash flows. We rely on the implementation of ASC 606 as a quasi-exogenous increase in uncertainty about how to price earnings. Specifically, we find that when uncertainty is high in the first quarter of ASC 606 implementation, 10-Qs released concurrently with earnings increase trading in response to earnings news. We find the relation is stronger when firms face greater uncertainty, and our results are supported by other accounting standard changes and broad, firm-quarter proxies for uncertainty. Our results suggest that quarterly reports are informative to investors when uncertainty about accounting information is especially high.

Where Do Institutional Investors Seek Shelter when Disaster Strikes? Evidence from COVID-19
Glossner, Simon,Matos, Pedro,Ramelli, Stefano,Wagner, Alexander F.
Institutional investors played a crucial role in the COVID-19 market crash. U.S. stocks with higher institutional ownership -- in particular, those held more by active, short-term, and domestic institutions -- performed worse. An analysis of changes in holdings through the first quarter of 2020 reveals that mutual funds, investment advisors, and pension funds favored stocks with strong financials (low debt and high cash), whereas hedge funds sold stocks indiscriminately. None of these institutional investor groups appear to have actively tilted their portfolios toward firms with better environmental and social performance. Data from a large discount brokerage indicate that retail investors acted as liquidity providers. Overall, the results suggest that when a tail risk realizes, institutional investors express a preference for "hard" measures of firm resilience.