# Research articles for the 2020-07-09

A Bivariate Compound Dynamic Contagion Process for Cyber Insurance
Jiwook Jang,Rosy Oh
arXiv

As corporates and governments become more digital, they become vulnerable to various forms of cyber attack. Cyber insurance products have been used as risk management tools, yet their pricing does not reflect actual risk, including that of multiple, catastrophic and contagious losses. For the modelling of aggregate losses from cyber events, in this paper we introduce a bivariate compound dynamic contagion process, where the bivariate dynamic contagion process is a point process that includes both externally excited joint jumps, which are distributed according to a shot noise Cox process and two separate self-excited jumps, which are distributed according to the branching structure of a Hawkes process with an exponential fertility rate, respectively. We analyse the theoretical distributional properties for these processes systematically, based on the piecewise deterministic Markov process developed by Davis (1984) and the univariate dynamic contagion process theory developed by Dassios and Zhao (2011). The analytic expression of the Laplace transform of the compound process and its moments are presented, which have the potential to be applicable to a variety of problems in credit, insurance, market and other operational risks. As an application of this process, we provide insurance premium calculations based on its moments. Numerical examples show that this compound process can be used for the modelling of aggregate losses from cyber events. We also provide the simulation algorithm for statistical analysis, further business applications and research.

A Review of Monetary Neutrality Literature
Guo, Yanling
SSRN
In this paper, I review some selected literature about or related to the monetary neutrality and show that specific aspects of the monetary (non-)neutrality are actually derived from the underlying welfare consideration and thus their validity or desirability depend on the current state and way of organising the economy. On the other hand, the spirit of the monetary neutrality, namely the success of financial innovations should be measured in the success of real business and that market is the default solution and the government only intervenes if necessary, remains unchallenged.

An Adaptive and Explicit Fourth Order Runge-Kutta-Fehlberg Method Coupled with Compact Finite Differencing for Pricing American Put Options
Chinonso Nwankwo,Weizhong Dai
arXiv

We propose an adaptive and explicit fourth-order Runge-Kutta-Fehlberg method with a fourth-order compact scheme to solve the American put options problem. First, the free boundary problem is converted into a system of partial differential equations with a fixed domain by using logarithm transformation and taking additional derivatives. With the addition of an intermediate function with a fixed free boundary, a quadratic formula is derived to compute the velocity of the optimal exercise boundary analytically. This is based on the work of Kim et al. (2013, 2017). Precisely, it enables us to employ fourth-order spatial and temporal discretization with Dirichlet boundary conditions for obtaining the numerical solution of the asset option, option Greeks, and the optimal exercise boundary. The advantage of the Runge-Kutta-Fehlberg method over the classical fourth-order Runge-Kutta method is based on error control and the adjustment of the time step to maintain the error at a certain threshold. We further compare the performance of the Runge-Kutta-Fehlberg method with the implicit Crank-Nicholson and classical fourth-order Runge-Kutta methods. The adaptive method proves to be superior and provides a better numerical approximation.

An\'alise dos fatores determinantes para o decreto de pris\~ao preventiva em casos envolvendo acusa\c{c}\~oes por roubo, tr\'afico de drogas e furto: Um estudo no \^ambito das cidades mais populosas do Paran\'a
Giovane Cerezuela Policeno,Mario Edson Passerino Fischer da Silva,Vitor Pestana Ostrensky
arXiv

Based on the theoretical assumptions of the Labeling Approach, Critical Criminology and Behavioral Economics, taking into account that almost half of the Brazilian prison population is composed of individuals who are serving pre-trial detention, it was sought to assess the characteristics of the flagranteated were presented as determinants to influence the subjectivity of the judges in the decision to determine, or not, the custody of these. The research initially adopted a deductive methodology, based on the principle that external objective factors encourage magistrates to decide in a certain sense. It was then focused on the identification of which characteristics of the flagranteated and allegedly committed crimes would be relevant to guide such decisions. Subsequently, after deduction of such factors, an inductive methodology was adopted, analyzing the data from the theoretical assumptions pointed out. During the research, 277 decisions were analyzed, considering decision as individual decision and not custody hearing. This sample embarked decisions of six judges among the largest cities of the State of Paran\'a and concerning the crimes of theft, robbery and drug trafficking. It was then concluded that the age, gender, social class and type of accusation that the flagranteated suffered are decisive for the decree of his provisional arrest, being that, depending on the judge competent in the case, the chances of the decree can increase in Up to 700%, taking into account that the circumstantial and causal variables are constant. Given the small sample size, as far as the number of judges is concerned, more extensive research is needed so that conclusions of national validity can be developed.

Asset Productivity, Local information Diffusion, and Commercial Real Estate Returns
Ling, David C.,Wang, Chongyu,Zhou, Tingyu
SSRN
The geography of a firmâ€™s assets is an important determinant of its investment decisions and productivity, which, in turn, drives stock returns. We construct a novel measure of the returns earned by each equity REIT on its underlying property portfolio. We then risk-adjust these quarterly property portfolio returns (PPRs) by regressing each against the sensitivities of the REITâ€™s returns to returns in the private commercial real estate (CRE) market at the national level, to private CRE market turnover (liquidity) at the national level, as well as to standard systematic risk factors. We find that these risk-adjusted property portfolio returns (Î±PPRs) predict the cross-section of returns in the public REIT market, suggesting a slow diffusion of asset-level information into stock returns. This slow diffusion of information about the performance of local markets into stock prices that we uncover is at least partially explained by the link between the price appreciation component of the private CRE market and stock return. In addition to improving our understanding of the extent to which â€œlocalâ€ information about the productivity of a firmâ€™s assets is capitalized into stock prices and the speed at which it is capitalized, this study contributes to the literature on the predictability of REIT returns and the relation between private and public CRE returns using firm-level, instead of index level, returns.

Asymptotic minimization of expected time to reach a large wealth level in an asset market game
Mikhail Zhitlukhin
arXiv

We consider a stochastic game-theoretic model of a discrete-time asset market with short-lived assets and endogenous asset prices. We prove that the strategy which invests in the assets proportionally to their expected relative payoffs asymptotically minimizes the expected time needed to reach a large wealth level. The result is obtained under the assumption that the relative asset payoffs and the growth rate of the total payoff during each time period are independent and identically distributed.

Board Diversity and Cost of Equity (CoE)
Hossain, Ashrafee T,Kryzanowski, Lawrence
SSRN
We examine the effects of board diversity on corporate cost of equity (CoE). Using a composite index for diversity, we find that greater diversity leads to lower CoE. In further analysis, we report that this association is more prominent when the firm is experiencing lower internal (or external) monitoring or facing higher agency issues or suffering from greater financial constraints. Our results are robust to, e.g. propensity score matching; instrumental variable approach; use of alternate measures of CoE; use of additional (possibly influential omitted) variables, and various other sensitivity and endogeneity tests.

COVID-19 Implications for Banks: the Case of An Emerging Economy
Barua, Bipasha,Barua, Suborna
SSRN
The COVID-19 pandemic is damaging economies across the world including financial markets and institutions in all possible dimensions. Particularly for banks, the pandemic generates multifaceted crisis, mostly through increases in default rates. This is likely to be worse in developing economies with poor financial market architecture. As a case of emerging economies, this paper considers Bangladesh and examines the possible impacts of the pandemic on the countryâ€™s banking sector. Bangladeshâ€™s banking sector already has a high level of NPLs and the pandemic is likely to worsen the situation. Using a state-designed stress testing model, the paper estimates the impacts of COVID-19 pandemic on three particular dimensions â€" firm value, capital adequacy, and interest income under different NPL shock scenario. Findings suggest that all banks are likely to see a fall in risk-weighted asset values, capital adequacy ratio, and interest income at the individual bank and sectoral levels. The decline in all three dimensions will be disproportionately larger if NPL shocks become larger. Further, estimates show that larger banks are relatively more vulnerable. Findings call for an immediate and innovative policy measures to prevent a large-scale and contagious bank sustainability crisis in Bangladesh. The paper offers lessons for other developing and emerging economies similar to Bangladesh.

COVID-19 and the Value of CEOs: The Unintended Effect of Soccer Games across European Stocks
Gomez, Juan-Pedro,Mironov, Maxim
SSRN
This paper studies the effect of the number of cases of COVID-19 on stock returns from over 3,500 publicly listed firms headquartered across 167 regions in 10 European countries. We instrument the number of cases per million inhabitant in each region with its population, density, and the soccer games celebrated in the region. Daily cases of COVID-19 grow faster in regions where a soccer game took place two weeks earlier, consistent with the estimated incubation period of the virus. In addition, regions that hosted a soccer match during March show 30% more accumulated cases of COVID-19 in the same month. Within the same country and industry, an increase in the number of instrumented cases per million people in the region during March implies a decrease in stock returns over March and April. The market discount increases significantly among firms managed by CEOs 60 years and older. Overall, we interpret this as evidence of the market anticipating the potential loss of firm value in the event of the CEO dies of COVID-19.

Color Intensity Variations and Art Prices: An Examination of Latin American Art
SSRN
Most existing literature has ignored the potential effects that color intensity may have on art prices (bearing a few recent exceptions). We examine 1,627 paintings executed by the â€œBig fiveâ€ Latin American artists (Rivera, Tamayo, Lam, Matta, and Botero) and sold at Sothebyâ€™s and Christieâ€™s between 2003 and 2017 to analyze this impact. We find strong evidence indicating that paintings that are more intense in color fetch higher prices, but only up to a certain degree (paintings whose color is â€œtoo intenseâ€, â€œtoo vividâ€ or â€œtoo darkâ€ actually fetch lower prices). To the best of our knowledge, these results are the first to confirm, for the case of the art market, early experimental evidence in the psychology literature pointing to the existence of an inverse â€œUâ€ pattern on the preferences for color intensity. Our findings have implications for other areas such as psychology and consumer behavior.

Competitive Prices in Large Markets with Private Information
Mihm, Maximilian,Siga, Lucas
SSRN
Siga and Mihm (2020) characterize the information environments where prices can aggregate information in a competitive auction market with an atomless population of traders. In this paper, we provide an explicit model of the large population where implications of the law of large numbers for aggregate demand and prices can be formally derived, and also show how the characterization result for a large market can be approximated with a sequence finite markets as the population size grows.

Contagious Margin Calls: How COVID-19 Threatened Global Stock Market Liquidity
Foley, Sean,Kwan, Amy,Philip, Richard,Ã˜degaard, Bernt Arne
SSRN
The COVID-19 epidemic has caused some of the largest - and fastest - market dislocations in modern history. Contemporaneous with the significant fall in equity market values is the evaporation of market liquidity. We document the evolution of transactions costs, depth and rewards to liquidity suppliers across a variety of countries affected by the virus. We show that transactions costs increase sharply in a coordinated fashion across global markets, with depth drying up almost overnight. The withdrawal of global liquidity suppliers is correlated with the increase of over 400\% in margin requirements, driving a pro-cyclical downwards liquidity spiral. These affects are shown to be concentrated in securities most exposed to electronic market-makers.

Credit Expansion, Bank Liberalization, and Structural Change in Bank Asset Accounts
Liu, Keqing,Fan, Qingliang
SSRN
This paper studies the links among credit supply expansion, commercial bank asset account structures, and the housing boom preceding the 2007-2009 financial crisis. We propose a real business cycle model with a housing market and financial intermediaries (banks) subject to leverage constraints. In our model, banks channel funds to firms for production and provide collateralized loans to mortgage borrowers; thus, banks determine their asset account structures endogenously. We show that a credit supply expansion to banks can account for four key facts that characterize the housing boom: (1) an increase in real house prices; (2) an increase in the mortgage-to-GDP ratio; (3) a decrease in the real mortgage interest rate; and (4) an increase in the ratio of mortgages to firm loans in commercial bank asset accounts. In our model, a credit supply expansion to banks can also generate a boom-bust cycle through the collateral value channel via mortgage borrowers. Asset-side bank regulations that reduce excessive mortgage issuance during a credit boom can help to dampen the subsequent economic downturn.

Credit Risk Signals in CDS Market vs. Agency Ratings
Jacobs, Michael,Karagozoglu, Ahmet K,Layish, Dina Naples
SSRN
This research aims to model the relationship between the credit risk signals in the credit default swap (CDS) market and agency credit ratings, and determines the factors that help explain the variation in such signals. A comprehensive analysis of the differences in the relative credit risk assessments of CDS-based risk signals and agency ratings is provided. It is shown that the divergence between credit risk signals in the CDS market and agency ratings is explained by factors which the rating agencies may consider differently than credit market participants. The results suggest that agency credit ratings of relative riskiness of a reference entity do not always correspond with assessments by CDS spreads, as the price of risk is a function of additional macro and micro factors that can be explained using statistical analysis. This research is unique in modeling the relationship between the credit risk assessments of the CDS market and the agency ratings, which to the best of the authorsâ€™ knowledge has not been analyzed before in terms of their agreement and the level of discrepancy between them. This model can be used by investors in debt instruments that are not explicitly CDSs or which have illiquid CDS contracts, to replicate market-based, point-in-time credit risk signals. Based on both market-based and firm-specific factors in this model, the results can be used to augment through-the-cycle credit risk assessments, analyze issues surrounding the pricing of CDSs and examine the policies of credit rating agencies.

Determinants of Art Prices and Performance by Movements: Long-Run Evidence from an Emerging Market
Garay, Urbi
SSRN
Art has become an increasingly important asset in the portfolios of investors. However, the literature on the investment attributes of art from emerging markets is limited. We address this gap by analyzing 5,961 artworks executed by 69 Venezuelan artists and sold at auctions worldwide between 1969 and 2014, the longest art returns period ever assembled for an emerging market, estimating a hedonic price regression. Geometric mean nominal annual returns were 4.3%, slightly above inflation. Ceteris-paribus, artist reputation explains art prices, the most expensive artworks are sold at Sothebyâ€™s and Christieâ€™s, are dated and executed in oil, and correspond to the following topics: Abstract, self-portraits, objects, still life, urban and landscape. Venezuelan art exhibits low correlation with Venezuelan and U.S. stocks and bonds. We find, contrary to most of the literature, a strong â€œmasterpiece effectâ€ for Venezuelan art, and also that abstract artworks outperformed portfolios of figurative and landscape paintings.

Disturbing the Peace: Anatomy of the Hostile Takeover of China Vanke Co
Taurai Muvunza,Terrill Frantz
arXiv

Wang Shi, a business mogul who created his empire of wealth from scratch, relished in his fame and basked in the glory of his affluent business. Nothing lasts forever! After mastering the turbulent business of real estate development in his country and therefore enjoying a rising and robust stock price, China Vanke Co. Ltd ("Vanke") founder and Chairman of the Board of Directors, Wang Shi was suddenly presented with a scathing notice from the Hong Kong Stock Exchange: rival Baoneng Group ("Baoneng") filed the regulatory documentation indicating that it had nicodemously acquired 5% of his company and was looking to buy more. Vanke case became brutal and sparked national controversy over corporate governance and the role of Chinese government in capital markets.

Do Corporates Set Pension Discount Rates Strategically?
chu, liping,Goldstein, Michael A.,Li, Xin,Yu, Tong
SSRN
A significant number of the U.S. publicly listed firms fail to lower their discount rates used to discount future pension obligations when interest rates decrease, resulting in an understatement of their pension liabilities and a lower charge against corporate earnings. Following the idea that mandatory contributions to underfunded pensions constrain corporate investments, we model and present empirical evidence that a relaxation of such constraint by setting higher pension discount rates helps to improve firm value. We show that rate inflations concentrate among highly capital intensive corporates who are facing tight financing constraints. We also show that such behavior has a positive effect on the operating and stock performance of underfunded firms, which supports the view that the imperfect elasticity of pension discount rates to market interest rates offers firms a way to reduce the constraints from defined benefit pension plans.

Does Gold Act as a Hedge Against Exchange Rates?
wei, xiaomeng
SSRN
This paper investigates the roles of hedging and safe haven of gold against exchange rates using data from six major markets. We find that exchange rate Granger-causes the return on gold in both mean and variance level except for some extreme quantiles. The quantile-on-quantile regression results imply that gold can act as a hedge for exchange rates in France, India, Japan, the UK and the USA. This safe haven role presents a dynamic pattern depending on specific extreme quantiles. In China, however, there are no significant hedging opportunities.

Does High Frequency Trading Affect Analyst Research Production?
Bilinski, Pawel,Karamanou, Irene,Kopita, Anastasia,Panayides, Marios A.
SSRN
Using the SECâ€™s Tick Size Pilot experiment, we examine the causal relation between the intensity of trades by high frequency traders (HFTs) and analyst research production. We propose that HFTs pre-empt other investorsâ€™ trades, which lowers non-HFTsâ€™ profitability of trades on analyst reports and, as a result, non-HFTs demand for analyst investment advice. Consistently, stocks where a large proportion of trades is HFT driven have (1) fewer profitable trades on analyst reports that non-HFTs can exploit and (2) fewer analyst research reports and lower analyst coverage. The negative effect HFTs have on analyst research production is moderated by institutional investors who demand analyst research for the monitoring purpose. Overall, our results suggest that a consequence of high frequency trading is lower analyst research production.

Does Religiosity Matter to Corporate Philanthropy?
Chourou, Lamia
SSRN
This study explores whether the degree of religiosity at the country level affects the amount of corporate philanthropy. Using a large sample of firms from 41 countries, I find that firms located in more religious countries donate more than those located in less religious countries. Results based on propensity score matching and 2SLS analysis, strongly confirm that religiosity induces more corporate giving. A quasi-natural experiment further confirms these findings. I show that firms located in more religious countries donated more following the 2004 Indian Ocean earthquake and tsunami than did firms located in less religious countries.

Downside Variance Premium, Firm Fundamentals, and Expected Corporate Bond Returns
Huang, Tao,Jiang, Liang,Li, Junye
SSRN
We find a positive relationship between individual downside variance premia, the difference between risk-neutral and physical expected downside variances, and future corporate bond returns. The hedge portfolio earns the economically substantial and statistically significant excess return of 0.35% (0.39%) per month in value (equal)-weighted returns. The predictive power of downside variance premium is stronger in non-investment-grade (long-maturity) corporate bonds than in investment-grade (short-maturity) ones. We show that downside variance premium positively relates to the likelihood of future default and cash flow uncertainty and negatively relates to future cash flow. When rational investors anticipate a high likelihood of future default, high cash flow uncertainty, or low future cash flow, the current bond price has to decline, resulting in higher future bond returns.

Effects of Short-Sale Constraints and Information Asymmetry on Index Futures Trading
Fabozzi, Frank J.,Karagozoglu, Ahmet K,Wang, Na
SSRN
We analyze the effects of spot market short-sale constraints on derivatives trading using a unique Chinese stock market futures trading database. Due to short-sale constraints, investorsâ€™ pessimistic views on the underlying index can be expressed solely through short futures positions, while investorsâ€™ optimistic views are dispersed through their spot and futures trading. We hypothesize that trading of pessimistic investors (with net short futures positions) contains more information than that of optimistic investors. We document the negative volatilityâ€"volume relation is associated with pessimistic investorsâ€™ trading, which attenuates with less-restricted spot market short-sale rules. Large pessimistic investorsâ€™ net demand can predict future returns, but not the case for optimistic investors.

Equally Diversified or Equally Weighted?
Fusai, Gianluca,Mignacca, Domenico,Nardon, Andrea,Human, Ben
SSRN
The aim of this paper is to shed new light on the concept of diversification showing that it is not necessarily related to the reduction of the volatility of a portfolio, as it is commonly perceived. We introduce a diversification index that exploits the decomposition of portfolio volatility into undiversified volatility and a diversification component. The diversification component offsets the undiversified part leaving as a final result the portfolio volatility itself. Our decomposition has a clear statistical interpretation because it relates the diversification component to the so-called partial covariances, i.e. the covariances between the residuals of the regressions of the weighted asset returns with respect to the portfolio return. On this basis, we advocate the construction of an equally diversified portfolio versus an equally weighted portfolio. An empirical analysis illustrates the superior performance of the equally diversified portfolios with respect to the equally weighted portfolio.

Framing
Bhagwat, Vineet,Shirley, Sara,Stark, Jeffrey
SSRN
We examine the impact framing of information has on the ability of market participants to process information in an earnings conference call. Following conference callsâ€™ use of greater linguistic framing, uncertainty is higher. We show that firms experience up to three months of higher total and idiosyncratic risk, greater trading activity, and lower excess returns. Framing impacts financial analysts as well, as we observe significantly larger analyst forecast errors during the subsequent quarter. Forecast characteristics such as the size of revisions, forecast dispersion, and analyst disagreement also increase with the use of framing. Consistent across our results, the impact of framing is significantly larger among firms that underperform earnings expectations and thus have an incentive to obfuscate negative information. Overall, our evidence is consistent with linguistic framing reducing the ability of financial markets to effectively evaluate the information of an earnings conference call.

Gintropy: Gini index based generalization of Entropy
Tamás S. Biró,Zoltán Néda
arXiv

Entropy is being used in physics, mathematics, informatics and in related areas to describe equilibration, dissipation, maximal probability states and optimal compression of information. The Gini index on the other hand is an established measure for social and economical inequalities in a society. In this paper we explore the mathematical similarities and connections in these two quantities and introduce a new measure that is capable to connect these two at an interesting analogy level. This supports the idea that a generalization of the Gibbs--Boltzmann--Shannon entropy, based on a transformation of the Lorenz curve, can properly serve in quantifying different aspects of complexity in socio- and econo-physics.

Growing Pains: The Evolution of New Stock Index Futures in Emerging Markets
Alan, Nazli Sila,Karagozoglu, Ahmet K,Korkmaz, Sibel
SSRN
Analyzing the first seven years of trading in Turkish stock index futures (BIST 30) and contrasting that to the progress of Korean (KOSPI 200) and Taiwanese (TAIEX) markets, we find that BIST 30 initially experiences a persistent mispricing and speculative trading similar to KOSPI 200 but it also experiences the largest increase in hedge effectiveness, becoming hedger-dominated similar to TAIEX. Most significantly, we demonstrate that spot market short-sell quote volume is a good measure of short-sale constraints and a significant determinant of mispricing in BIST 30. A methodological contribution of this paper is a four-equation multivariate VAR framework to analyze the volatility impact of futures.

Hazard Stocks and Expected Returns
DeLisle, Jared,Ferguson, Michael F.,Kassa, Haim
SSRN
Hazard stocks are opposite of lottery stocks. We proxy hazard stocks with the minimum daily idiosyncratic return over the past month, a negative shock labelled IMIN, and examine the relation between hazard stocks and expected returns. The literature on lottery-stocks implies that investors should discount hazard stocks. However, we find that investors under-react to hazard stocks, with negative return continuations for up to 24 months without subsequent reversals. An IMIN-based long-short arbitrage portfolio strategy generates monthly alphas of 0.52% to 0.75%. We find consistent results using Fama-MacBeth (1973) regressions and controlling for characteristics such as MAX (Bali et al., 2011), idiosyncratic volatility, and corporate events such as earnings announcements. Furthermore, we find that both firm-level information uncertainty and limits to arbitrage, but not limited investor attention, contribute significantly to the documented under-reaction to hazard stocks.

Heterogeneity in Retail Investors: Evidence from Comprehensive Account-Level Trading and Holdings Data
Jones, Charles M.,Shi, Donghui,Zhang, Xiaoyan,Zhang, Xinran
SSRN

Impacts of COVID-19 on Banking
Seelye, Nancy,Ziegler, Paul
SSRN
COVID-19 has had major impacts for banking, with the United States government making various efforts to shore up the financial system. These have included temporary and permanent rule changes, easing Capital requirements in an effort to spur lending and maintain bank solvency. Using publicly available data on bank holdings, we constructed tests for the changes in lending and allocation for pending loan loss. Our study finds that there has been a significant increase in loan loss reserves, yet the ratio of these reserves to total lending is not significant. This work will be extended with 2020-Q2 data when it becomes available.

Improving the Robustness of Trading Strategy Backtesting with Boltzmann Machines and Generative Adversarial Networks
Edmond Lezmi,Jules Roche,Thierry Roncalli,Jiali Xu
arXiv

This article explores the use of machine learning models to build a market generator. The underlying idea is to simulate artificial multi-dimensional financial time series, whose statistical properties are the same as those observed in the financial markets. In particular, these synthetic data must preserve the probability distribution of asset returns, the stochastic dependence between the different assets and the autocorrelation across time. The article proposes then a new approach for estimating the probability distribution of backtest statistics. The final objective is to develop a framework for improving the risk management of quantitative investment strategies, in particular in the space of smart beta, factor investing and alternative risk premia.

Inefficiencies of Basis Swaps to Hedge Foreign Exchange Risk
Sarmiento, Camilo
SSRN
We find that a cross currency basis swap between the U.S. and emerging economies should not be interpreted as a currency hedge, as the exchange rate risk associated with these transactions is quite high. These risks are significantly lower for a basis swap between the U.S. Libor and Euro Libor. Overall, the use of a cross-currency basis swap requires an assessment of the expected trajectories of exchange rates and the associated risks. Offshore funding is thus an imperfect substitute for onshore funding of operations in a local currency.

Introduction of Bond Market: Would It Be a Possible Solution for Bangladesh?
Rahman, Md. Nafizur,Nower, Nowshin,Abbas, Syed Mahdee,Nahian, Abdullah Hill,Tushar, Raqibul Hasan
SSRN
This study aims at investigating the prospects of a bond market in Bangladesh. Most of the developed and developing economies have an active and successful bond market. But Bangladesh despite being one of the fastest-growing economies, does not have an active bond market. Hence, this study was designed to investigate the impact of a bond market on the economic growth of Asian countries and what are the prospects and challenges in Bangladesh. To investigate the benefits of a bond market in Bangladesh, this study examined the relationship between bond market return and economic growth of 4 Asian economies which included, India, Indonesia, Hong Kong, and Japan. The average annual yield of 10-year bonds was used as the independent variable and the annual GDP growth rate of these countries was used as the dependent variable in the econometric model. Data for the last 20 years from 2000 to 2019 were used for all the variables. The Unit Root Test showed that 3 variables were stationary at first difference and the other five variables were stationary at level. The Johansen Co-integration test identified the long-run association among the variables indicating the long-run relationship between bond market return and economic growth. Granger Causality revealed a bi-directional relationship for India; unidirectional relationship for Indonesia (Bondïƒ GDP growth) and Japan (GDP Growthïƒ Bond); and no unidirectional or bidirectional relationship among the bond market return and economic growth of Hong Kong. The various new projects, the overextension of the banking sector, and perhaps the overall good condition of the economy has created the perfect situation to develop a bond market in Bangladesh. As there are conditions that provide advantages in bond market creation, there are also various challenges that the government must overcome. Some of the most important challenges to clear up are the underdeveloped tax system, the illiquid or absent secondary market, the alternative source of debt, and the overall lack of investors. Considering the various developed bond markets these policy implications could seriously aid the development process.

Investigating Financial Statement Fraud in Ghana using Beneish M-Score: A Case of Listed Companies on the Ghana Stock Exchange (GSE)
SSRN
This quantitative research was conducted to detect the possibility of earnings manipulation by listed companies on the Ghana Stock Exchange, determine which company size engages more in creative accounting and find out whether there is a correlation between share price and earnings manipulation. Using 22 companies out of a total of 41 listed companies, financial data gathered from published financial statements on the companiesâ€™ websites, Ghana Stock Exchange website and Annual Report Ghana website were examined from 2011 to 2016. Applying Beneish M-score model for the period 2011-2016, it was found that 26.2% of the sample size on the average were involved in creative accounting. The study also found that 28.4% of the small companies on the average were involved in earnings manipulation during the period 2011-2016 as compared to 25.4% of the big companies. However, the Mann-Whitney U test conducted revealed that there is no statistically significant difference between the level of earnings manipulation amongst small and big companies. Spearmanâ€™s correlation analysis was conducted, first on the entire sample and subsequently conducted separately on the small and big companies. The results of the analysis showed that earnings manipulation and share price, statistically, were not significantly related. The quantitative research provides an insight into the level of earnings management amongst public companies in Ghana and the appropriateness of the M-score model in detecting earnings manipulation. The evidence of incidence of creative accounting amongst the sampled companies is an indication of the need for more stringent measures to curb such practice to ensure the stability of the Ghanaian stock market and protect investor interest.

Itâ€™s Who You Know That Counts: Board Connectedness and CSR Performance
Amin, Abu S.,Chourou, Lamia,Malik, Mahfuja,Kamal, Syed M,Zhao, Yang
SSRN
We examine whether and how board connections affect the firm's corporate social responsibilities (CSR). Grounded in the agency, resource dependence, and social network theory, our research predicts and finds that board connectedness is positively associated with CSR performance. This result is robust to a quasi-natural experiment, alternative measurement specifications, and an instrumental variable approach. Our findings suggest firms that operate in a complex business environment or require more advising (i.e. where demand for information is greater) benefit more from a well-networked board. Also, firms that are poorly governed, have high stock return volatility, low market capitalization, or low institutional ownership tend to benefit more from the well-connected board when the cost of acquiring information is higher. In addition, we show that independent directorsâ€™ abilities to gather information and resources from their networks can facilitate the transmission of information. Collectively, our study documents the informational advantage of a network as the predominant channel that allows a well-connected board to improve a firmâ€™s CSR performance.

Machine Learning Portfolio Allocation
Michael Pinelis,David Ruppert
arXiv

We find economically and statistically significant gains when using machine learning for portfolio allocation between the market index and risk-free asset. Optimal portfolio rules for time-varying expected returns and volatility are implemented with two Random Forest models. One model is employed in forecasting the sign probabilities of the excess return with payout yields. The second is used to construct an optimized volatility estimate. Reward-risk timing with machine learning provides substantial improvements over the buy-and-hold in utility, risk-adjusted returns, and maximum drawdowns. This paper presents a new theoretical basis and unifying framework for machine learning applied to both return- and volatility-timing.

Multi-Stage Stock Pricing Techniques for the Classroom
Alexander, Maura,Arnold, Tom,Wu, Ge
SSRN
A process for multi-stage stock pricing is presented with evidence of improved classroom performance. The technique is expanded upon for more advanced class presentations and for potential fintech applications by taking advantage of present value annuity and future value annuity due structures.

Multi-Stage Stock Pricing with a Financial Calculator
Arnold, Tom,Wu, Ge
SSRN
Alexander, Arnold and Wu (2020) introduce an algorithm for multi-stage stock pricing that uses a present value annuity structure. This algorithm is adapted for a financial calculator by using an iterative bond pricing structure.

Multi-regime Forecasting Model for the Impact of COVID-19 Pandemic on Volatility in Global Equity Markets
Alan, Nazli Sila,Engle, Robert F.,Karagozoglu, Ahmet K
SSRN
Using a multi-regime forecasting model, we investigate the impact of COVID-19 pandemic on market volatility. We show that daily number of active cases and the Curvature are significant predictors of daily cross-section of both realized volatility and the GJR-GARCH volatility in global equity markets. We estimate realized volatilities using intraday 5-minute returns for 46 country specific ETFs and daily GARCH volatilities are estimated using the stock market indices of 88 countries around the world. We find that stricter policy responses by individual countries, measured by higher OxCGRT Stringency Index levels, result in lower stock market volatilities while increased negative managerial sentiment, extracted from earnings call transcripts, causes an increase in realized volatilities.

Nice guys don't always finish last: succeeding in hierarchical organizations
Doron Klunover
arXiv

What are the chances of an ethical individual rising through the ranks of a political party or a corporation in the presence of unethical peers? To answer this question, I consider a four-player two-stage elimination tournament, in which players are partitioned into those willing to be involved in sabotage behavior and those who are not. I show that, under certain conditions, the latter are more likely to win the tournament.

Numerical Scheme for Game Options in Local Volatility models
Benjamin Gottesman Berdah
arXiv

In this paper we introduce a numerical method for optimal stopping in the framework of one dimensional diffusion. We use the Skorokhod embedding in order to construct recombining tree approximations for diffusions with general coefficients. This technique allows us to determine convergence rates and construct nearly optimal stopping times which are optimal at the same rate. Finally, we demonstrate the efficiency of our scheme with several examples of game options.

On Utility Maximisation Under Model Uncertainty in Discrete-Time Markets
Miklós Rásonyi,Andrea Meireles-Rodrigues
arXiv

We study the problem of maximising terminal utility for an agent facing model uncertainty, in a frictionless discrete-time market with one safe asset and finitely many risky assets. We show that an optimal investment strategy exists if the utility function, defined either over the positive real line or over the whole real line, is bounded from above. We further find that the boundedness assumption can be dropped provided that we impose suitable integrability conditions, related to some strengthened form of no-arbitrage. These results are obtained in an alternative framework for model uncertainty, where all possible dynamics of the stock prices are represented by a collection of stochastic processes on the same filtered probability space, rather than by a family of probability measures.

Optimal Dividend Strategy for an Insurance Group with Contagious Default Risk
Zhuo Jin,Huafu Liao,Yue Yang,Xiang Yu
arXiv

This paper studies the optimal dividend for a multi-line insurance group, in which each subsidiary runs a product line and is exposed to some external credit risk. The credit default contagion is considered in the sense that one default event may increase the default probabilities of all surviving subsidiaries. The total dividend problem is considered for the insurance group and we reveal that the optimal singular dividend strategy is still of the barrier type. Furthermore, we show that the optimal barrier of each subsidiary is modulated by the default state, namely how many and which subsidiaries have defaulted will determine the dividend threshold of each surviving subsidiary. These interesting conclusions are based on the analysis of the associated recursive system of Hamilton-Jacobi-Bellman variational inequalities (HJBVIs). The existence of the classical solution is established and the proof of the verification theorem is provided. In the case of two subsidiaries, the value function and optimal barriers are given in analytical forms, allowing us to conclude that the optimal barrier of one subsidiary decreases if the other subsidiary defaults.

Pruned Wasserstein Index Generation Model and wigpy Package
Fangzhou Xie
arXiv

Recent proposal of Wasserstein Index Generation model (WIG) has shown a new direction for automatically generating indices. However, it is challenging in practice to fit large datasets for two reasons. First, the Sinkhorn distance is notoriously expensive to compute and suffers from dimensionality severely. Second, it requires to compute a full $N\times N$ matrix to be fit into memory, where $N$ is the dimension of vocabulary. When the dimensionality is too large, it is even impossible to compute at all. I hereby propose a Lasso-based shrinkage method to reduce dimensionality for the vocabulary as a pre-processing step prior to fitting the WIG model. After we get the word embedding from Word2Vec model, we could cluster these high-dimensional vectors by $k$-means clustering, and pick most frequent tokens within each cluster to form the "base vocabulary". Non-base tokens are then regressed on the vectors of base token to get a transformation weight and we could thus represent the whole vocabulary by only the "base tokens". This variant, called pruned WIG (pWIG), will enable us to shrink vocabulary dimension at will but could still achieve high accuracy. I also provide a \textit{wigpy} module in Python to carry out computation in both flavor. Application to Economic Policy Uncertainty (EPU) index is showcased as comparison with existing methods of generating time-series sentiment indices.

Public Pension Reform and the 49th Parallel: Lessons from Canada for the U.S.
Lipshitz, Clive,Walter, Ingo
SSRN
Public employee pension systems around the world show remarkable diversity in design and execution. Among these, the U.S. defined benefit public pension system has drawn increased attention because of questions about the long-term sustainability of many of the underlying pension funds as well as concerns of equity between pension plan members, retirees, taxpayers, bondholders, and users of public services. The COVID-19 pandemic introduced new fissures in state and local government finances, heightening the need to bolster long-term public pension fund robustness. As an alternative model, the Canadian public pension system is widely respected. This was not foreordained. We trace difficult decisions undertaken in Canada in the 1980s and 1990s along with key descriptive features of the Canadian Model. Using a primary dataset, we benchmark the 25 largest U.S. plans against their ten largest Canadian peers, exploring key issues in a paired analysis. Calibrating the two approaches, we extract key lessons from the Canadian experience for the U.S. and end with applicable policy recommendations.

Petukhina, Alla,Reule, Raphael C. G.,HÃ¤rdle, Wolfgang K.
SSRN
This research analyses high-frequency data of the cryptocurrency market in regards to intraday trading patterns. We study trading quantitatives such as returns, traded volumes, volatility periodicity, and provide summary statistics of return correlations to CRIX (CRyptocurrency IndeX), as well as respective overall high-frequency based market statistics with respect to temporal aspects. Our results provide mandatory insight into a market, where the grand scale employment of automated trading algorithms and the extremely rapid execution of trades might seem to be a standard based on media reports. Our findings on intraday momentum of trading patterns lead to a new view on approaching the predictability of economic value in this new digital market.

Societal Biases Reinforcement Through Machine Learning â€" A Credit Scoring Perspective
Hassani, Bertrand
SSRN
Does machine learning and AI ensure that social biases thrive ? This paper aims to analyse this issue. Indeed, as algorithm are informed by data, if these are corrupted, from a social bias perspective, good machine learning algorithms would learn from the data provided and reverberate the patterns learnt on the predictions related to either the classification or the regression intended. Therefore, if the data sets are capturing the way society behaves whether it is positive or negative, then this would be reflected by the models. Using credit scoring data sets as provided by financial institutions in the US, our objective is to assess how much social biases are transmitted from the data into the scoring approach. Relying on Random Forests and SVM approaches, we details the results obtained and measure how much these biases can impact people's access to loans.

Stake Centralization in Decentralized Proof-of-Stake Blockchain Network
He, Ping,Tang, Dunzhe,Wang, Jingwen
SSRN
Decentralization is key to the security of Proof-of-Stake blockchain network. In this paper, we propose an economic framework for PoS blockchain network and evaluate stake concentration cause by PoS consensus algorithm. Specifically, we model blockchain participants' decision-making in allocating wealth between saving and stake to maximize total return. We prove that in a fully decentralized model, stake return rate equals risk-free interest rate and thus wealth discrepancy among participants is irrelevant to stake distribution in the network. However, in a more realistic setting where the number of participants in the network is limited due to the rise of staking pools for risk-sharing purpose, stake concentration might naturally happen due to decreasing return rate to participant number. As a mechanism design suggestion, we prove that lower participant cost and stakeholder selection function tilted towards smaller participants can reduce stake centralization.

Synthetic Governance
Ahn, Byung Hyun,Fisch, Jill E.,Patatoukas, Panos N.,Davidoff Solomon, Steven
SSRN
Scholars, practitioners and policymakers continue to debate what constitutes â€œgoodâ€ corporate governance. Academic efforts to evaluate the effect of governance provisions such as dual class voting structures, staggered boards of directors and separating the positions of CEO and Chairman of the Board, have produced inconsistent or inconclusive results. The consequence is that the debate over corporate governance is increasingly political and discordant.We offer a way to address this debate. The rise of index-based investing provides a market-based alternative to governance regulation. Through the creation of bespoke governance index funds, asset managers can offer investors the opportunity to choose an index that corresponds to their governance preferences. We term this approach synthetic governance. At the same time, synthetic governance offers a new tool to collect evidence on the economic impact of corporate governance by providing a market-based tool for evaluating the relationship between corporate governance and stock returns. We illustrate the potential of synthetic governance with the creation of a new governance-based index, the Dual Index, which selects portfolio companies on the basis of a dual class voting structure. We compare the performance of the Dual Index to various benchmarks and demonstrate the potential, through governance-based indexing, for investors to realize superior returns. We further modify the Dual Index by implementing synthetic sunsets to highlight the value creation of dual-class companies in their early years and provide evidence on the appropriate length of a time-based sunset provision. Finally, we expand our analysis of synthetic governance with a second index â€" the Split Index â€" which tests the effect of separating the positions of CEO and Chairman of the Board. We conclude that synthetic governance offers a meaningful way for investors and issuers to more economically adopt and invest in governance provisions. We thus provide a way out of the corporate current war over what exactly constitutes â€œgoodâ€ governance.

Tax Avoidance through Cross-Border Mergers and Acquisitions
Meier, Jean-Marie,Smith, Jake
SSRN
We document a novel form of tax avoidance: Cross-border, tax-haven mergers and acquisitions (M&A). Tax havens have $1.5 trillion in M&A deal value beyond what is predicted based on economic fundamentals. 18,310 tax-haven M&As result in$29.5 billion in recurring annual tax avoidance. Non-haven, cross-border M&A results in an additional \$30.0 billion in recurring annual tax avoidance. Our results provide the underlying mechanism for 28% of global corporate income tax avoidance. This is the first paper to document that tax havens not only affect capital flows on paper, but also affect real investment on a large scale. Moreover, we create an algorithm, which is available to others, to derive the tax residence of any company given data on the firm's country of incorporation and headquarters.

The Market for CEOs
Cziraki, Peter,Jenter, Dirk
SSRN
We study the market for CEOs of large publicly-traded US firms, analyze new CEOsâ€™ prior connections to the firm, and explore how hiring choices are determined. Our results show that firms hire from a surprisingly small pool of candidates. More than 80% of new CEOs are insiders, i.e., current or former employees or board members. More than 90% of new CEOs are executives firms are already familiar with â€" either insiders or executives its directors have worked with. Firms raid CEOs of other firms in only 3% of cases, implying a lack of talent reallocation across firms. Pay differences appear too small to explain these hiring choices. The evidence is inconsistent with standard frictionless assignment models and suggests that firm-specific human capital and personal connections determine CEO hiring.

The Opportunity Cost of Hedging under Incomplete Information: Evidence from ETF/Ns
Cui, Zhenyu,Simaan, Majeed
SSRN
This paper considers the optimal hedge ratio problem under estimation risk. Due to incomplete information, the decision-maker evaluates the opportunity cost of hedging using exchange-traded funds or notes (ETF/Ns). Using a back-testing procedure over the last five years and 13 different hedging instruments - both inverse-equity ETFs and volatility ETNs - we quantify the proposed opportunity cost using different out-of-sample performance metrics. Given the greater accessibility of commission-free brokers for small investors along with the popularity of ETF/Ns, our paper appeals to retail investors and provides guidance in terms of choosing the optimal hedge ratio under estimation risk.

The Role of Social Media in Corporate Governance
Ang , James S.,Hsu, Charles,Tang, Di,Wu, Chaopeng
SSRN
We examine whether social media criticisms posted by small investors can predict subsequent firm acquisition decisions. Specifically, we use textual analysis to examine the Internet stock message board postings of 303 value-reducing acquisition attempts. Our empirical evidence shows that small investorsâ€™ negative postings are able to predict a potential acquirerâ€™s subsequent decision to withdraw its attempt. We further find that this predictive ability increases with the information quality of postings, and that the predictive information extracted from social media is incremental to that captured by proposal announcement returns, conventional media coverage, analyst reports, and institutional investorsâ€™ responses related to the proposed acquisition. Finally, we show that message board criticisms are also able to predict governance outcomes beyond acquisition decisions. Overall, our results are consistent with the notion that social media play a role in corporate governance by gathering crowd wisdom and uncovering additional value-relevant information.

The Statutory Liberalization of Trust Law across 152 Jurisdictions: Leaders, Laggards and the Market for Fiduciary Services
SSRN
This article reports the findings of the first systematic overview of the statutory liberalization of trust law worldwide. Using a groundbreaking, manually collected, database of the trust legislation of every jurisdiction which has a trust regime respecting 22 trust law variables, I hand coded each jurisdictionâ€™s treatments of each variable since 1925 for their relative liberality. Aggregating all jurisdictionsâ€™ scores regarding all variables, I produced a â€œtrust liberality scoreâ€ for each jurisdiction/year, expressing the extent to which trust law has been liberalized by each jurisdiction by each year. Results show the United States to be the global leader in trust law liberality: 17 of the 20 jurisdictions which have the most liberal trust laws are American states. Trust law liberalization in the U.S. is a result of the widespread adoption of the Uniform Trust Code, which includes many highly liberal positions, among the states, as well as of many states having followed an offshore dynamic in adopting highly permissive positions in order to draw users from out of state to resident service providers. The trust laws of many American states are more liberal than those of small offshore island jurisdictions. Even the laws of such relatively conservative American states, on trust matters, as New York and California are quite liberal by global standards. Much of the recent global increase in trust law liberality occurred between 1988-2016. Multivariate regression analysis of U.S. data shows that the statutory liberalization of trust law has had no effect on several indicia for the success of service provision to trusts as a commercial enterprise. It is especially clear that reforms seen as pandering to trust usersâ€™ interests at great social cost, such as self-settled spendthrift trusts and perpetual trusts, all in order to create or sustain demand for professional services in the trust context, have had no impact on any of these indicia. As an exception to the general finding of a null result, some findings with marginal statistical significance may show that law reforms which reduced trusteesâ€™ exposure to liability and entrenched their entitlement to remuneration led to a decline in their earnings per trust. Those reforms are also weakly associated with an increase in trust income. It is therefore possible that reforms widely seen as preferring trustees over their clients have resulted in trustees providing a better service at lower cost.

TransDigm in 2017: The Beginning of the End or the End of the Beginning?
Esty, Benjamin,Fisher, Daniel
SSRN
TransDigm is a highly acquisitive company that manufactures a wide range of highly engineered aerospace parts with highly successful, but controversial strategy. On the one hand, its stock price had increased by over ten times in ten years since its IPO in March 2006, and both its revenues and non-GAAP EBITDA had grown at compound annual rates in excess of 20% since the companyâ€™s founding in 1993. But in early 2017, government officials, a major investor, and even some customers had begun to question the implementation, sustainability, and ethics of the firmâ€™s strategy. That strategy consisted of acquisition-driven growth (i.e., a â€œroll-upâ€) and value-focused operations emphasizing three value drivers: value-based pricing, cost reductions, and new product development. With the firmâ€™s stock price down 30% off its recent high, TransDigm CEO Nick Howley must decide whether to respond to the rising level of criticism and, if so, how. In the longer term, he has to decide whether to change the firmâ€™s â€œvalue-focused strategy.â€ If he were going to change the firm's proven operating strategy, what aspects should he change and how should he justify the changes to his loyal shareholder base?The case has three pedagogical objectives: First, it allows students to analyze an extremely effective strategy that has generated stellar financial returns for more than two decades and to assess the criticisms leveled against it. Second, it challenges students to define value creation and distinguish it from value capture. Who along the value chain is "winning" and who, if anyone, is losing? And third, it provides an opportunity to understand bargaining power as a key determinant of market attractiveness (buyer and supplier power are two of Porter's Five Forces) and an important kind of competitive advantage (a "bargaining advantage" in Van den Steen's framework). The chosen setting, spring 2017 when the company's stock price was down ~30% and investors, customers, and government officials were questioning the firm's "value creation" strategy, naturally raises the question of whether the firm's advantage will last for another five to ten years?

When Mutual Fund Names Misinform
Allard, Anne-Florence,Krakow, Nils Jonathan,Smedts, Kristien
SSRN
Mutual funds often inform directly about their strategy in their name. This paper studies the accuracy of mutual fund names. Constructing a fund name history data set based on SEC filings and applying unsupervised machine learning techniques, we document that a significant fraction of mutual funds features an inaccurate name, i.e. a name which is not aligned with their actual investment style. Funds that provide an inaccurate name experienced lower fund inflows before the inaccuracy, under-performed in the year before, and charged higher expenses. Strikingly, after featuring an inaccurate name, funds see a worse risk-return trade-off due to an increased idiosyncratic risk. Finally, we document that investors experience difficulties in responding to this misleading information while at the same time, they do not profit from this deviating behavior of the funds. Thus, our results highlight the importance of regulatory intervention in the name dimension.