# Research articles for the 2020-11-04

Bilateral Home Bias: A New Measure of Proximity
Pungulescu, Crina
SSRN
This paper uses recent developments from the fields of cognitive neuroscience and psycho-linguistics to introduce a new measure of proximity to the set of typical gravity variables in a model for bilateral home bias. Given the weightlessness' of financial assets, gravity variables (among which geographical distance is the most prominent) are meaningful only as proxies for information or familiarity. The new measure of country similarity aims to directly capture the conceptual closeness of countries by comparing their semantic fingerprints. An AI solution which emulates the way the human brain learns and establishes associations among concepts, called the Retina engine, makes it possible to analyse text with human-level accuracy and to extract its semantic fingerprint (a numerical representation of meanings associated with the given term or a text). Akin to an artificial investor' who has read virtually the entire Wikipedia, the Retina engine is able to quantify and compare textual descriptions of any pair of countries. In a model for bilateral home bias, the resulting measures of country similarity appear informative above and beyond distance and other gravity variables (common language, border, colonial link etc.). At its best, country similarity outperforms distance both in terms of statistical significance and impact on the dependent variable.

Business Purpose and the Objective of the Corporation
RPS Submitter, NYU Law,Rock, Edward B.
SSRN

Cash Compensation Changes in Light of the Current Economic Crisis
Reda, James
SSRN
This article focuses on cash compensation, which includes base salaries and annual bonuses (also referred to as â€œshort-term incentivesâ€). As of the outset of this current economic crisis (early April 2020), the state of change is as follows: Many companies have already begun reducing base salariesâ€"particularly at the executive level and in some cases extending to outside directors and even the broadbased employee population; and, while the vast majority of companies (especially those with a calendar year end) have not yet made any changes to their short-term incentive plans that were put in place prior to mid-March, boards are likely to begin announcing plans to materially change the performance metrics, goals (or targets) and corresponding payout schedules used in these plans.

China Markets and Global Stock Return Predictability
Sun, Yulong
SSRN
We have seen Chinaâ€™s growing role in the past decades, and the world economy has become more exposed to the influence of China. This paper explores emerging China's impact on the global equity market through the lens of asset pricing. We study the predictive properties of the lagged China returns for global stock returns and find that the lagged China returns can significantly predict other markets' stock returns, but not vice versa. We augmented the predictive model with Chen, Roll, and Ross (1986)'s macroeconomic risk factors, and find that the macro fundamentals cannot explain the predictive power of the lagged China returns. Further evidence shows the lagged China returns during the low investor-attention period have stronger predictability compared to performance during the high attention period, which is in line with the information friction theory that the attention-constrained investors fail to allocate attention to certain economic state variables when making decisions, meanwhile, cause the slow information diffusion across markets. Overall, our results indicate that the lagged China returns should be regarded as a global state variable that helps us predict future stock returns.

Comparing the collective behavior of banking industry
Hanie.Vahabi,Ali Namaki,Reza Raei
arXiv

One of the most important features of capital markets as an adaptive complex networks is their collective behavior. In this paper, we have analyzed the banking sectors of 4 world stock markets,which composed of emerging and matures ones. By applying one the important complexity notions, Random matrix theory(RMT), it is founded that mature markets have a higher degree of collective behavior,Even though we used RMT tools: participation ratio(PR), node participation ratio(NPR)and relative participation ratio(RPR) , which NPR illustrated independent banks than whole market and RPR compared collective behavior of markets by a normal range. By applying local and global perturbations, we concluded that mature markets are more vulnerable to perturbations due to the high level of collective behavior. Finally, by drawing the dendrograms and heat maps of the correlation matrices,

Consequences of Interim Reporting: A Literature Review and Future Research Directions
KajÃ¼ter, Peter,Lessenich, Arne,Nienhaus, Martin,van Gemmern, Florian
SSRN
This study provides the first comprehensive literature review on interim reporting based on 112 papers published between 1961 and 2020. The review focuses on both the firm-specific consequences (capital market-based and real effects) and externalities of interim reporting. We analyze three primary interim reporting characteristics: (1) frequency, (2) contents, and (3) assurance. The review allows us to summarize the existing literature, reconcile different findings, identify trends in the literature, and present avenues for future research. We observe that investors perceive interim reports to be useful. However, no clear evidence exists for strong capital market-based benefits of higher reporting frequency, such as increases in liquidity. Instead, recent evidence even points to negative externalities of diverging reporting frequencies in terms of liquidity decreases for firms reporting at a lower frequency. Higher reporting frequency seems to imply stricter monitoring, especially in the absence of other effective monitoring mechanisms. Nonetheless, it can also induce myopic decision-making. More comprehensive reports convey more information at the costs of increases in reporting lags and processing time. Surprisingly, the current literature does not find that interim assurance leads to higher interim report quality.

Corporate Liquidity Risk Management: Coping with Corona and the Clearing Obligation
Lehrbass, Frank
SSRN
The European Markets Infrastructure Regulation (EMIR) allows burdening a clearing obligation on non-financial corporates, which formerly did not necessarily clear their business. We give ten recommendations on how to cope with this obligation. These are motivated by a case study for which we consider a stylized German power producer. For this entity, we derive optimal levels of planned production and forward sales of power using microeconomic theory. Since this results in a significant short position in the German power forward market, we investigate the resulting variation margin call dynamics with a special interest in the ability to forecast worst-case price up moves. We compare different models for the forward log-returns and their performance in 99% quantile forecasting. A GARCH model with Student-t distribution emerges as the most suitable model. This is used in the case study, which is inspired by data published by the power producer E.ON. Using recent material from the Basel Committee on Banking Supervision we distill the reliable liquidity buffer from an allegedly rich liquidity position and show how suddenly it can be eroded. We point to feedback loops, which make the challenges - posed by the clearing obligation - even more severe. We also spend some thoughts on how to cope with the crisis caused by Corona.

Cybersecurity Risk
Florackis, Chris,Louca, Christodoulos,Michaely, Roni,Weber, Michael
SSRN
We develop a novel firm-level measure of cybersecurity risk using textual analysis of cybersecurity risk disclosures in annual corporate filings. The measure successfully identifies firms extensively discussing cybersecurity risk in their 10-K, displays intuitive relations with quantitative measures of cybersecurity risk disclosure language, it exhibits a positive trend over time, it is more prevalent among industries relying more on information technology systems, it correlates with several characteristics linked to firms hit by cyber-attacks and, importantly, it predicts future cyber-attacks. Stocks with high exposure to cybersecurity risk exhibit high expected returns on average, but they perform poorly in periods of increasing attention to cybersecurity risk. Standard risk factors do not subsume exposure to cybersecurity risk and a simple long-short strategy delivers value-weighted alphas between 6.7% and 7.9% per annum with t-statistics well above 3.

Dividend Policy Implementation Modeling Within Neutral Approach Conditions As Analysis and Forecasting Instrument
Krylov, Sergey
SSRN
The article treats a concept of the formalized modeling of the dividend policy scores and company marketing performance scores derived (stock market position) within neutral dividend policy implementation approach conditions as an instrument of the scores analysis and forecasting. The methodology of the research consists of the Dividend Irrelevance theory, Dividend Policy Significance theory and sustainable company development concept. It has been stated that a formalized approach of the dividend policy implementation presumes a construction of the basic relevent scores models characterizing the company dividend policy and its marketing performance as Dividend Payout, Dividend Cover, expected Share Price, Dividend Yield, Price / Earnings Ratio (common stock price/earnings ratio). The formalized models of the scores mentioned are applicable for a forecast-analytical scores evaluation and their variances as well by estimating an impact of the models defining factors exercised by the appropriate factoring analysis method within the neutral dividend policy implementation approach conditions. The conclusion is drawn, that the formalized models of the dividend policy scores and company marketing performance scores derived, having been developed, are an effective instrument for their forecasting and analysis so that proactive decisions to manage the company dividend policy implementation within neutral approach conditions are ensured.

Dividend Policy and the COVID-19 Crisis
Mazur, Mieszko,Dang, Man,Vo, Thi Thuy Anh
SSRN
This paper examines dividend payment behavior of the S&P1500 firms during the COVID-19 crisis characterized by the stock market crash and a V-shaped stock price recovery propelled by technology stocks. We find that the great majority of firms either maintain or increase the level of dividend payment during the crisis period. Yet, the relationship between the dividend payout and bottom-line earnings available to common shareholders is significantly negative. This relationship holds even for dividend-increasing firms whose earnings streams should be relatively higher (or increasing) compared to other firms in the sample. We also find that forecast earnings of up to one year in the future are negatively associated with the current dividend level implying that the existing payout policies are unsustainable. Interestingly, we document similar patterns for stock repurchases.

Evaluate the Performance of Russian Banks
Abu-Alrop, Jalal Hafeth
SSRN
This paper aims to analyze and evaluate the performance of Russian banks in the period 2008-2017. This goal aims to assess the performance of Russian banks according to their different sizes. The study uses traditional performance indicators, namely, return on equity, return on assets and net interest margin to assess the performance of Russian banks. This study includes 85 banks in Russia, whose total assets (87%) of the total assets of the banking sector in Russia. The results confirm that the performance of Russian banks was good from (2011-2013), on the other hand, the performance of Russian banks was weak from (2014-2017), this indicates a decrease in the performance of Russian banks in recent years, the study concluded that medium banks were the most efficient In its performance during the study period, while the small banks were more efficient than the big banks.

Explicit approximations for option prices via Malliavin calculus for the Stochastic Verhulst volatility model
Kaustav Das,Nicolas Langrené
arXiv

We consider explicit approximations for European put option prices within the Stochastic Verhulst model with time-dependent parameters, where the volatility process follows the dynamics $dV_t = \kappa_t (\theta_t - V_t) V_t dt + \lambda_t V_t dB_t$. Our methodology involves writing the put option price as an expectation of a Black-Scholes formula, reparameterising the volatility process and then performing a number of expansions. The difficulties faced are computing a number of expectations induced by the expansion procedure explicitly. We do this by appealing to techniques from Malliavin calculus. Moreover, we deduce that our methodology extends to models with more general drift and diffusion coefficients for the volatility process. We obtain the explicit representation of the form of the error generated by the expansion procedure, and we provide sufficient ingredients in order to obtain a meaningful bound. Under the assumption of piecewise-constant parameters, our approximation formulas become closed-form, and moreover we are able to establish a fast calibration scheme. Furthermore, we perform a numerical sensitivity analysis to investigate the quality of our approximation formula in the Stochastic Verhulst model, and show that the errors are well within the acceptable range for application purposes.

Financial Fragility During the Covid-19 Pandemic
Clark, Robert L.,Lusardi, Annamaria,Mitchell, Olivia S.
SSRN
Early in the COVID-19 pandemic, much of the US economy was closed to limit the virusâ€™ spread, and several emergency interventions were implemented. Our analysis of older (45-75) respondents fielded in April-May of 2020 indicates that about one in five respondents was financially fragile and would have difficulty facing a mid-size emergency expense. Some subgroups were at particular risk of facing financial difficulties, especially younger respondents, those with larger families, Hispanics, and the low income. Moreover, the more financially literate were better able to handle such shocks, indicating that knowledge can provide some additional protection during a pandemic.

Forecasting the Equity Premium with Frequency-Decomposed Technical Indicators
Stein, Tobias
SSRN
Technical trading rules are widely used by practitioners to forecast the U.S. equity premium. I decompose technical indicators into components with frequency-specific information, showing that the predictive power comes from medium-frequency variation in buy and sell signals, without much evidence of predictability outside of this frequency band. This pattern can be observed for commonly used strategies based on volume, momentum, and moving-average rules. A mean-variance investor who only forecasts with these medium-frequency components generates economically sizable gains compared to the historical average and the basic technical indicators. Combined forecasts from filtered indicators provide utility gains that are often twice as large as gains from the basic indicators. I show that the improvements mainly result from a better market timing around recessions. Overall, the choice of frequency matters more than the choice of technical indicator. I provide evidence that filtered buy and sell signals increase economic gains for several country indices, thereby ruling out data-snooping concerns.

Foreign Market Portfolio Concentration and Performance
Fjesme, Sturla Lyngnes
SSRN
Using security holdings of 49,857 foreign investors on the Oslo Stock Exchange (OSE), I test whether concentrated investment strategies in international markets result in excess risk-adjusted returns. I find that investors with higher learning capacity increase returns, while investors with lower learning capacity decrease returns from the portfolio concentration. I measure learning capacity as institutional classification, geographical proximity to Norway, and cultural closeness to Norwegian investors (as based on the Hofstede cultural closeness measures). I conclude, consistent with the information advantage theory, that concentrated investment strategies in foreign markets can be optimal (disastrous) for investors with higher (lower) learning capacity.

Foundations and Trends at the Interface of Finance, Operations, and Risk Management
Babich, Volodymyr,Birge, John R.
SSRN
In this work we define the characteristics of the interface of finance, operations, and risk management (iFORM) research and provide examples of iFORM research questions. We illustrate why this is an interesting area and discuss where the two disciplines overlap in a meaningful way. Our goal is to lower the entry cost for new researchers by providing primers on (1) key finance results and papers that OM researchers endeavoring to enter into this field must know; (2) key OM results and papers that finance researchers endeavoring to enter into this field must know. Furthermore, we offer our perspective on resources to help readers to accelerate their iFORM research and on how to write, publish, and referee iFORM papers.

How do the Covid-19 Prevention Measures Interact with Sustainable Development Goals?
Shima Beigi
arXiv

Washing hands, social distancing and staying at home are the preventive measures set in place to contain the spread of the COVID-19, a disease caused by SARS-CoV-2. These measures, although straightforward to follow, highlight the tip of an imbalanced socio-economic and socio-technological iceberg. Here, a System Dynamic (SD) model of COVID-19 preventive measures and their correlation with the 17 Sustainable Development Goals (SDGs) is presented. The result demonstrates a better informed view of the COVID-19 vulnerability landscape. This novel qualitative approach refreshes debates on the future of SDGS amid the crisis and provides a powerful mental representation for decision makers to find leverage points that aid in preventing long-term disruptive impacts of this health crisis on people, planet and economy. There is a need for further tailor-made and real-time qualitative and quantitative scientific research to calibrate the criticality of meeting the SDGS targets in different countries according to ongoing lessons learned from this health crisis.

Information Discreteness and the Lead-lag Returns Puzzle
Huang, Shiyang,Lee, Charles M.C.,Song, Yang,Xiang, Hong
SSRN
We re-examine the puzzling pattern of lead-lag returns among economically linked firms. Our results show these patterns are driven largely by investorsâ€™ tendency to ignore information that arrives continuously in small amounts. In contrast, when information with the same cumulative returns arrives in discrete amounts, it is quickly incorporated into price. Consistent with investorsâ€™ belief revision being colored by a representativeness heuristic, the price adjustment process is more complete when a signal is more representative of the underlying news. Our results indicate that how information manifests itself can drive return predictability, irrespective of the nature of the economic linkage between firms.

Fjesme, Sturla Lyngnes
SSRN
It is well documented in the finance literature how share prices go up when companies increase dividend payouts. The long-term trend, however, is that more companies now retain excess cash rather than paying dividends. In this paper I investigate if companies retain cash to invest on private information in domestic stock markets. I look at 20,620 domestic non-financial companies trading shares on the Oslo Stock Exchange (OSE) over the period 1993 to 2006. I find that companies earn excess risk-adjusted-returns from active trading. I conclude that companies retain at least some cash to take advantage of private information.

Insights into Fairness through Trust: Multi-scale Trust Quantification for Financial Deep Learning
Alexander Wong,Andrew Hryniowski,Xiao Yu Wang
arXiv

The success of deep learning in recent years have led to a significant increase in interest and prevalence for its adoption to tackle financial services tasks. One particular question that often arises as a barrier to adopting deep learning for financial services is whether the developed financial deep learning models are fair in their predictions, particularly in light of strong governance and regulatory compliance requirements in the financial services industry. A fundamental aspect of fairness that has not been explored in financial deep learning is the concept of trust, whose variations may point to an egocentric view of fairness and thus provide insights into the fairness of models. In this study we explore the feasibility and utility of a multi-scale trust quantification strategy to gain insights into the fairness of a financial deep learning model, particularly under different scenarios at different scales. More specifically, we conduct multi-scale trust quantification on a deep neural network for the purpose of credit card default prediction to study: 1) the overall trustworthiness of the model 2) the trust level under all possible prediction-truth relationships, 3) the trust level across the spectrum of possible predictions, 4) the trust level across different demographic groups (e.g., age, gender, and education), and 5) distribution of overall trust for an individual prediction scenario. The insights for this proof-of-concept study demonstrate that such a multi-scale trust quantification strategy may be helpful for data scientists and regulators in financial services as part of the verification and certification of financial deep learning solutions to gain insights into fairness and trust of these solutions.

Loan Syndication under Basel II: How Credit Ratings Affect Cost of Credit?
Hasan, Iftekhar,Kim, Suk-Joong,Politsidis, Panagiotis N.,Wu, Eliza
SSRN
This paper investigates how lenders react to borrowersâ€™ rating changes under heterogeneous conditions and different regulatory regimes. Our findings suggest that corporate downgrades that increase capital requirements for lending banks under the Basel II framework are associated with increased loan spreads and deteriorating non-price loan terms relative to downgrades that do not affect capital requirements. Ratings exert an asymmetric impact on loan spreads, as these remain unresponsive to rating upgrades, even when the latter are associated with a reduction in risk weights for corporate loans. The increase in firm borrowing costs is mitigated in the presence of previous bank-firm lending relationships and for borrowers with relatively strong performance, high cash flows and low leverage.

Managing Earnings to Appear Truthful: The Effect of Public Scrutiny on Exactly Meeting a Threshold
Hobson, Jessen L.,Stirnkorb, Sebastian
SSRN
The past two decades have not eliminated managersâ€™ willingness to manage earnings to meet and beat earnings thresholds, but have increased investorsâ€™ skepticism of earnings that exactly meet those thresholds, providing perverse incentives to not meet earnings expectations exactly. Using a low-external-context experiment, we find that managers avoid exactly meeting a benchmark, even when they must alter true earnings and incur a monetary cost to do so. We manipulate the effect of intensified scrutiny of managers and find that when earnings exactly meet a benchmark, managers are more likely to misreport earnings when they report under high public scrutiny. This is particularly the case for managers who are sensitive to othersâ€™ perceptions (and thus low on the Dark Triad scale). Further, we show that this misreporting increases managersâ€™ belief that the market will accept their reports, consistent with managers misreporting for self-presentational goals. Thus, we examine a new incentive to manage earnings: misreporting to appear truthful. These results help explain otherwise undetectable behavior around earnings benchmarks and are important as managers are increasingly scrutinized by critical media, activists, and political oversight bodies, and as they face skepticism via more intimate forms of disclosure and communication, such as social media.

Missouri's Medicaid Contraction and Consumer Financial Outcomes
Bailey, James,Blascak, Nathan,Mikhed, Vyacheslav
SSRN
In July 2005, a set of cuts to Medicaid eligibility and coverage went into effect in the state of Missouri. These cuts resulted in the elimination of the Medical Assistance for Workers with Disabilities program, more stringent eligibility requirements, and less generous Medicaid coverage for those who retained their eligibility. Overall, these cuts removed about 100,000 Missourians from the program and reduced the value of the insurance for the remaining enrollees. Using data from the Medical Expenditure Panel Survey, we show how these cuts increased out-of-pocket medical spending for individuals living in Missouri. Using data from the Federal Reserve Bank of New York/Equifax Consumer Credit Panel (CCP) and employing a border discontinuity differences-in-differences empirical strategy, we show that the Medicaid reform led to increases in both credit card borrowing and debt in third-party collections. When comparing our results with the broader literature on Medicaid and consumer finance, which has generally measured the effects of Medicaid expansions rather than cuts, our results suggest there are important asymmetries in the financial effects of shrinking a public health insurance program when compared with a public health insurance expansion.

Money Creation and Banksâ€™ Interest Rate Setting
Ponomarenko, Alexey
SSRN
The conventional view on banksâ€™ interest rate-setting strategy implies that the decisions on the deposit and loan rates may be made independently. An alternative approach is based on the assumption of a bankâ€™s predetermined liabilities structure. Such an assumption requires that the availability of deposits automatically increases (decreases) when more (fewer) loans are granted. Arguably, that they may be partially true considering that deposits are created via lending. We set up a microsimulation model and show that in certain environments it may be beneficial for large banks to incorporate information on the retail funding costs into the lending rate-setting decision.

Mutual Fund Competition and Fund Manager Strategy Choice
Stein, Roberto
SSRN
The increasing number of mutual funds and assets under management of the industry are credited with restricting opportunities and stifling incentives for fund managers to generate alpha. I show that some managers are able to adapt to the more competitive market environment by tilting their investment strategy towards 'quality'. Using the fund's loading on the QMJ factor to proxy for quality management, I find that high quality funds outperform their peers, and generate annual alphas of 2.88\%. Besides peer competition, a clientele effect seems to influence the choice of strategy. Clients of high quality funds are more sophisticated and focus on risk-adjusted returns, while those of low quality funds fit the description of uninformed investors, and seem unresponsive to both gross returns and alphas.

Option Hedging with Risk Averse Reinforcement Learning
Vittori, Edoardo,Trapletti, Michele,Restelli, Marcello
SSRN
In this paper we show how risk-averse reinforcement learning can be used to hedge options. We apply a state-of-the-art risk-averse algorithm: Trust Region Volatility Optimization (TRVO) to a vanilla option hedging environment, considering realistic factors such as discrete time and transaction costs.Realism makes the problem twofold: the agent must both minimize volatility and contain transaction costs, these tasks usually being in competition.We use the algorithm to train a sheaf of agents each characterized by a different risk aversion, so to be able to span an efficient frontier on the volatility-p&l space.The results show that the derived hedging strategy not only outperforms the Black & Scholes delta hedge, but is also extremely robust and flexible, as it can efficiently hedge options with different characteristics and work on markets with different behaviors than what was used in training.

Quantum Speedup of Monte Carlo Integration in the Direction of Dimension and its Application to Finance
Kazuya Kaneko,Koichi Miyamoto,Naoyuki Takeda,Kazuyoshi Yoshino
arXiv

Monte Carlo integration using quantum computers has been widely investigated, including applications to concrete problems. It is known that quantum algorithms based on quantum amplitude estimation (QAE) can compute an integral with a smaller number of iterative calls of the quantum circuit which calculates the integrand, than classical methods call the integrand subroutine. However, the issues about the iterative operations in the integrand circuit have not been discussed so much. That is, in the high-dimensional integration, many random numbers are used for calculation of the integrand and in some cases similar calculations are repeated to obtain one sample value of the integrand. In this paper, we point out that we can reduce the number of such repeated operations by a combination of the nested QAE and the use of pseudorandom numbers (PRNs), if the integrand has the separable form with respect to contributions from distinct random numbers. The use of PRNs, which the authors originally proposed in the context of the quantum algorithm for Monte Carlo, is the key factor also in this paper, since it enables parallel computation of the separable terms in the integrand. Furthermore, we pick up one use case of this method in finance, the credit portfolio risk measurement, and estimate to what extent the complexity is reduced.

Seasoned Equity Issuersâ€™ Prospectus Filings: How Informative Are the Tones?
Huang, Rongbing,Qian, Hong,Ramalingegowda, Santhosh
SSRN
Seasoned equity issuers file Forms S and 424B with the Securities and Exchange Commission. We find that weak-modal tones of these filings are positively related to offer price discounts and negatively related to offer-day stock returns. Increases in cautionary tones from the initial S filing to the 424B filing are associated with lower abnormal stock returns after the offer date. However, we find no significant evidence that cautionary filing tones are related to underpricing. Overall, our findings suggest that cautionary tones of seasoned equity issuersâ€™ prospectus filings have significant negative information content, which is gradually incorporated into the stock prices.

Shadow Prices of Non-performing Loans for Chinese Banks in the Post-Crisis Era
Zhao, Shirong
SSRN
This paper examines how non-performing loans (NPLs) affect Chinese commercial banks before, during, and after the 2008 global financial crisis as well as the subsequent 2008â€"2010 stimulus. By accounting for NPLs as undesirable outputs, banks' technical efficiency is estimated using directional output distance function. The envelop theorem is applied to calculate the shadow price of NPLs. The shadow price of NPLs is the opportunity cost of reducing NPLs by one Chinese yuan. Empirical results show that the four major state-owned banks are the least technically efficient while foreign banks are the most efficient over the sample period 2007â€"2014. I also find that the crisis has a negative effect on banks' technical efficiency while the stimulus initially has a positive effect on four major state-owned commercial banks and joint-stock commercial banks, but later shows a negative effect with a higher default ratio and lower efficiency. Finally, the data show that the stimulus has greatly increased the shadow price of NPLs for four major state-owned commercial banks. Starting in 2011, the shadow prices of NPLs for four major state-owned commercial banks are much higher than all other bank types.

Shall We Talk? The Role of Interactive Investor Platforms in Corporate Communication
Lee, Charles M.C.,Zhong, Qinlin
SSRN
Between 2010 and 2017, Chinese investors used an online platform to ask publicly-listed firms over 2.5 million questions, the vast majority of which received a reply from management within two weeks. Our analyses show that: (a) most questions reflect difficulties in integrating information that is already in the public domain; (b) the level of platform activity varies by market condition and company performance; and (c) higher platform activities are associated with decreases in firmsâ€™ cost-of-capital and increases in their market liquidity. Collectively, our results suggest interactive investor platforms (IIPs) can mitigate information processing costs and improve market price formation.

Superstar Uncertainty
Barnes, Spencer,Mendez, Brandon,Schrowang, Andrew
SSRN
Financial economists have long been interested in asset price uncertainty. Yet, causal estimates of price uncertainty are sparse. The art market, valued at $64 billion in 2019 and growing in financial importance, provides an opportunity to fill this gap. Specifically, this study examines the effect of superstar artists' deaths on art price pre-sale estimate dispersion. By leveraging nearly identical art pieces from both alive and dead superstar artists from 1983 to 2020, art auction records suggest a positive causal link between superstar artist death and estimate dispersion. After a superstar artist dies, estimates widen by$86,000 or 35% on average.

The Effects of Oil Price on Asia â€" Pacific Exchange Rates: Evidence from Quantile Regression Analysis
Sankarkumar, Amirdha Vasani,Selvam, Murugesan,Gunasekaran, Indhumathi,Sigo, Marxia Oli,Dhamotharan, Dhanasekar
SSRN
An attempt has been made in this paper, to investigate the effect of oil prices on the exchange rate of 13 Asia â€" Pacific sample countries against USD, for the period from 04th January 2000 to 31st March 2020. OLS and QR Models were adopted for the analysis. Japanese Yen and Hong Kong Dollar were not affected by the oil prices during the study period. Sample currencies responded differently to oil price shocks under current market conditions. The results of this study would be useful to the policymakers, in the context of variations of oil and currency markets.

The Pricing of Bank Bonds, Sovereign Credit Risk and ECBâ€™s Asset Purchase Programmes
Branco, Ricardo,Pinto, JoÃ£o,Ribeiro, Ricardo
SSRN
The 2008 Global financial crisis and the subsequent European sovereign debt crisis deteriorated banks funding conditions and lead to a substitution effect among bond instruments. We examine the pricing of straight, covered and securitization bonds issued by European banks in the 2000-2016 period, with a particular focus on the effect of sovereign credit risk and ECBâ€™s asset purchase programmes on spreads. We find that (i) straight, covered and securitization bonds are priced in segmented markets, (ii) the impact of common pricing determinants on spreads differ significantly between non-crisis and crisis periods, (iii) sovereign credit risk is an important determinant of banksâ€™ cost of funding, especially in crisis periods, (iv) ECBâ€™s asset purchase programmes exhibited mixed effectiveness in improving banks funding conditions, (v) contractual bond characteristics other than credit ratings, macroeconomic factors and bank characteristics are important determinants of spreads, and (vi) there is evidence of heterogeneity across countries.

The Rise of Dual-Class Stock IPOs
Aggarwal, Dhruv,Eldar, Ofer,Hochberg, Yael V.,Litov, Lubomir P.
SSRN
We use a novel dataset to examine the nature and determinants of voting and economic rights in dual-class IPOs. We document that not all dual-class IPOs have similar structures, and that there exist multiple different types of controlling shareholders and control wedges. Founder-controlled dual-class IPOs differ substantially from those with other types of controlling shareholders, and the wedge between founders' voting and economic rights and those of other shareholders is largest when founders have strong bargaining power. The increase in founder wedge over time appears to be due to (1) increased venture capitalist willingness to accommodate founder control, (2) technological shocks that increased founders' bargaining power by reducing the need for external financing, and (3) an increase in foreign firm IPOs.

The Value Effects of Digital Expertise on Corporate Boards
SSRN
We examine the impact of board level digital expertise on firm performance for a sample of FTSE 350 firms over the period 2013 to 2018. We find that the presence of digital experts on the boards is significantly and positively related to firm performance. We conduct several additional tests to establish the robustness of the causal relation between digital experts on board and firm performance. Using propensity score matching (PSM) analysis, we document that firms which have digital experts on board have a significant increase in their firm performance relative to a matched sample of firms without digital experts on board. Our findings underscore the significance of digital experts on board in improving firm growth, liquidity and reducing business risk, thereby enabling such firms to increase performance. Additional tests show that the presence of digital experts on board has a strong influence on information asymmetry and corporate governance mechanisms.

The polarizing impact of numeracy, economic literacy, and science literacy on attitudes toward immigration
arXiv

Political orientation polarizes the attitudes of more educated individuals on controversial issues. A highly controversial issue in Europe is immigration. We found the same polarizing pattern for opinion toward immigration in a representative sample of citizens of a southern European middle-size city. Citizens with higher numeracy, scientific and economic literacy presented a more polarized view of immigration, depending on their worldview orientation. Highly knowledgeable individuals endorsing an egalitarian-communitarian worldview were more in favor of immigration, whereas highly knowledgeable individuals with a hierarchical-individualist worldview were less in favor of immigration. Those low in numerical, economic, and scientific literacy did not show a polarized attitude. Results highlight the central role of socio-political orientation over information theories in shaping attitudes toward immigration.

Transforming Projects into Superior Investment Strategies Using Cash Flow Statement Analysis
Burgess, Nicholas
SSRN
Every project is fundamentally made up of cash flows. An investor may rent a factory, buy raw materials, hire workers, manufacture a product or fund an advertising campaign, all with the purpose of selling a product or service to make a profit. Every part of the project or investment opportunity results in a combination of positive and negative cash flows. Investment opportunities are assessed by estimating and valuing the cash flows that a project will generate. An optimal investment decision balances project returns against project risks and seeks the maximum return per unit risk.Cash flow statement analysis is a vital skill required to identify superior investment opportunities and to transform mediocre projects into superior investment strategies. They help the active project manager boost returns and eliminate risks, identifying project strengths to harness and weaknesses to prune.Firstly we review and explain the key items on cash flow statements. Secondly we show how to compute a projectâ€™s free cash flows. Thirdly we discuss how to evaluate the cost of capital and project risk. Fourthly we outline how to calculate the Net Present Value (NPV) of a project and discuss optimal investment criteria. We conclude with a case study and perform a detailed project valuation using cash flow statement analysis. An Excel example workbook is provided with this paper.

U.S. Monetary Policy Uncertainty and RMB Deviations From Covered Interest Parity
Lin, Zhitao,Qian, Xingwang
SSRN
This paper examines how U.S. monetary policy uncertainty (MPU) affects RMB deviations from covered interest parity (CIP) and how this effect is influenced by Chinaâ€™s capital controls, the RMB exchange rate regime, and international reserves that constrain the transmitting channel of U.S. MPU shocks. Our findings show that U.S. MPU has a spillover effect and creates deviations from RMB CIP. Capital controls insulate uncertainty shocks and alleviate the U.S. MPU spillover effect. There are some evidences that international reserves alleviate and the liberalized RMB exchange rate regime magnifies the spillover effect. However, their effects become insignificant in the presence of capital controls. Moreover, the U.S. MPU effect on RMB CIP deviation became prominent after the 2008 global financial crisis.

Volatility Measurement with Pockets of Extreme Return Persistence
Andersen, Torben G.,Li, Yingying,Todorov, Viktor,Zhou, Bo
SSRN
Increasing evidence points towards the episodic emergence of pockets with extreme return persistence. This notion refers to intraday periods of non-trivial duration, for which stock returns are highly positively autocorrelated. Such episodes include, but are not limited to, gradual jumps and prolonged bursts in the drift component. In this paper, we develop a family of integrated volatility estimators, labeled differenced-return volatility (DV) estimators, which provide robustness to these types of Ito semimartingale violations. Specifically, we show that by using differences in consecutive high-frequency returns, our DV estimators can reduce the non-trivial bias, that all commonly-used estimators exhibit during such periods of apparent short-term intraday return predictability. A Monte Carlo study demonstrates the reliability of the newly developed volatility estimators in finite samples. In our empirical volatility forecast application to S&P 500 index futures and individual equities, our DV-based Heterogeneous Autoregressive (HAR) model performs well relative to existing procedures according to standard out-of-sample MSE and QLIKE criteria.

What Matters in the Annuitization Decision?