# Research articles for the 2019-10-03

A Model of the Islamic Sovereign Wealth Fund
Bahoo, Salman,Hassan, Kabir M.
SSRN
Purpose â€" The purpose of this paper is to propose a model of the Islamic sovereign wealth funds (ISWFs) based on Islamic finance principles to modify the precarious image of SWFs from Muslim countries. The Shariah laws are the cardinal direction for this study. Design/methodology/approach â€" The authors applied a qualitative research technique that consists of three approaches: exploratory case study approach to critically examine and rank the existing status of SWFs; descriptive analysis; and content analysis to present a model of ISWFs in comparison of conventional SWFs. Findings â€" The authors propose a model of the â€œIslamic Sovereign Wealth Fundsâ€ based on four key pillars: the major Shariah principles; the Islamic corporate governance framework; the Islamic transparency and disclosure framework; and the Islamic corporate social responsibility framework. Furthermore, the authors argue that the potential effect of the ISWFs on Islamic finance and economy will be positive. Research limitations/implications â€" The model is an initial work and idea to convert SWFs from Muslim countries into ISWFs, which required an in-depth policy review by governments. Practical implications â€" The findings of the paper are useful for policymakers and governments of the Muslim countries to overcome the issues and criticism on SWFs by converting them in ISWFs. Originality/value â€" This paper contributes to the literature related to Islamic finance and sovereign wealth fund by presenting a first model of ISWFs for Muslim countries.

A Robust Transferable Deep Learning Framework for Cross-sectional Investment Strategy
Kei Nakagawa,Masaya Abe,Junpei Komiyama
arXiv

Stock return predictability is an important research theme as it reflects our economic and social organization, and significant efforts are made to explain the dynamism therein. Statistics of strong explanative power, called "factor" have been proposed to summarize the essence of predictive stock returns. Although machine learning methods are increasingly popular in stock return prediction, an inference of the stock returns is highly elusive, and still most investors, if partly, rely on their intuition to build a better decision making. The challenge here is to make an investment strategy that is consistent over a reasonably long period, with the minimum human decision on the entire process. To this end, we propose a new stock return prediction framework that we call Ranked Information Coefficient Neural Network (RIC-NN). RIC-NN is a deep learning approach and includes the following three novel ideas: (1) nonlinear multi-factor approach, (2) stopping criteria with ranked information coefficient (rank IC), and (3) deep transfer learning among multiple regions. Experimental comparison with the stocks in the Morgan Stanley Capital International (MSCI) indices shows that RIC-NN outperforms not only off-the-shelf machine learning methods but also the average return of major equity investment funds in the last fourteen years.

A Simple Robust Asset Pricing Model Under Statistical Ambiguity
GarcÃ­a-FeijÃ³o, Luis,Viale, Ariel
SSRN
We derive and test empirically a robust one-factor asset pricing model consistent with the multiple-priors approach of the ambiguity literature. The robust CAPM can explain the cross-section of expected U.S. stock returns without the need for additional risk factors. Further, observed anomalies such as size and value appear as statistical characteristics of misspecified asset pricing models because idiosyncratic ambiguity, unlike idiosyncratic risk, cannot be diversified away. Using a robust Bayesian econometric procedure, we recover the market price of statistical ambiguity, which sets a lower bound for stock prices that corresponds to investorsâ€™ worst-case scenario in terms of indirect utility.

A Simple Sovereign Default Model
Sarmiento, Camilo
SSRN
This paper adapts Vacisekâ€™s model structure to capture the likelihood of sovereign defaults in a portfolio of Latin American exposures. Specifically, we model default as a balance of payment crisis that results in a domestic currency run that is reflected in a large drop in foreign reserve assets. Specifically, as a corollary to Vacisekâ€™s model, we assume that when the stochastic component of the countryâ€™s foreign reserve assets drops below a certain threshold, the country defaults on its foreign currency obligations. Historically, in Latin America, a significant drop in international reserves has consistently preceded a sovereign default event.

A tale of two sentiment scales: Disentangling short-run and long-run components in multivariate sentiment dynamics
Danilo Vassallo,Giacomo Bormetti,Fabrizio Lillo
arXiv

We propose a novel approach to sentiment data filtering for a portfolio of assets. In our framework, a dynamic factor model drives the evolution of the observed sentiment and allows to identify two distinct components: a long-term component, modeled as a random walk, and a short-term component driven by a stationary VAR(1) process. Our model encompasses alternative approaches available in literature and can be readily estimated by means of Kalman filtering and expectation maximization. This feature makes it convenient when the cross-sectional dimension of the sentiment increases. By applying the model to a portfolio of Dow Jones stocks, we find that the long term component co-integrates with the market principal factor, while the short term one captures transient swings of the market associated with the idiosyncratic components and captures the correlation structure of returns. Finally, using quantile regressions, we assess the significance of the contemporaneous and lagged explanatory power of sentiment on returns finding strong statistical evidence when extreme returns, especially negative ones, are considered.

Accounting for Financial Instruments under IFRS 9 â€" First-Time Application Effects on European Banksâ€™ Balance Sheets
Loew, Edgar,Schmidt, Lisa E.,Thiel, Lars F.
SSRN
IFRS 9 was introduced by the IASB in 2014 and became mandatory for fiscal years starting in 2018. It bears fundamental changes in the accounting requirements for financial instruments, especially in the areas of recognition, categorisation and measurement, impairment and loan loss provision. As bank balance sheets consists of financial instruments by more than 95 per cent, the application of the new standard was expected to bear major impacts on the bankÂ´s balance sheets. This working paper covers a review of pre-application impact assessments publishes by regulating authorities, such as EBA, auditors and researchers. Main part of the working paper is a comprehensive overall balance sheet impact with a closer look at the effects on CET1 ratios. Therefore, detailed movements between previous and current classification categories as well as the portfolio composition per category are analysed. A specific look on the classification of equity instruments as well as potential changes in maturity of long term investments in loans and bonds are taken. It can be shown that the equity investments usually are not specifically categorised and that IFRS 9 doesnâ€™t have an effect on long term investments by banks. The study also outlines the transition impact from the incurred loss to the expected loss model with a focus on the allocation of assets to the newly introduced three impairment stages and the development of loan loss reserves. The data of the study is clustered by characteristics to show the influence of size, credit risk approach, business model and country and tests the findings for statistical significance. That allows to outline visible trends affecting the new standardÂ´s impact severity.

Bitcoin Spot and Futures Market Microstructure
Aleti, Saketh,Mizrach, Bruce
SSRN
We study the microstructure of Bitcoin (BTC) trading on the CME futures market and the four spot exchanges that determine the settlement price. The five trading centers exchange a combined $160 million per day in the BTC/USD pair. Median trade sizes in the spot market range from$75 to $1,300 but are over$18,000 on the CME. Bid-ask spreads are much narrower than on equity exchanges. The opening and closing of the US futures and global equity markets contribute to diurnal patterns in liquidity. The market is very resilient. Trade sizes of over $2 million move the most liquid markets by less than 1%. Cancellation to execution ratios are roughly double US equity market averages. 2.5% of aggressive trades and 15.6% of cancellations on Coinbase take place within 50 milliseconds. Bid-ask spreads exceed 0.8% in 379 episodes totalling 392 seconds. We construct an NBBO for the four spot exchanges, and find that the majority of executions trade through better quotes on other exchanges, resulting in potential losses of up to$36 million. The majority of price discovery takes place in the futures market. Finally, we find that BTC is more liquid than Ethereum (ETH), with higher volume and lower execution costs. BTC leads ETH price adjustment, but not vice versa.

Can Investment Incentives Crowd Out Innovation? Evidence from China
Ke, Shaowei,Lu, Yao,Shi, Xinzheng,Zhang, Yeqing
SSRN
We analyze the spillover effects of fixed-asset investment tax credits on firmsâ€™ innovation. We estimate the effects by exploring the 2004 value-added-tax reform in China. The difference-in-difference-in-differences estimation results show that the reform significantly reduces firmsâ€™ innovation by 9.51%. Moreover, the crowding-out effect appears only in firms with intermediate-level financial constraints, consistent with the prediction of our simple model with heterogeneous production technologies and financial constraints. Similar non-monotonic effects also appear in other firm decisions, such as the labor input. Since innovation is an important economic growth engine, our findings suggest that fiscal investment incentive policies may generate unintended consequences.

Compound Option Valuation with Maturity Varying Volatility, Maturity Varying Yields, and Maturity Varying Interest Rates
Brooks, Robert
SSRN
In this paper, a detailed proof is provided for the value of compound options based on geometric Brownian motion with maturity varying yields, maturity varying volatility, and maturity varying interest rates. Most research papers focused on compound options do not address yields on the underlying option nor maturity varying parameters. The purpose of this paper is to fill this gap in the literature. The model is also illustrated along with important implementation insights. Various intriguing avenues of research are also indicated.

Consumer Perceptions of Financial Advisory Titles and Implications for Title Regulation
Tharp, Derek
SSRN
Many professionals in the financial services industry refer to themselves as financial advisers despite tremendous variation in business practices, compensation methods, and duties to act in the best interest of their clients. As a result, both the Securities and Exchange Commission (SEC) and state securities regulators have considered title regulation aimed at promoting consumer clarity. While a recent SEC proposal was ultimately discarded, there is little empirical evidence to inform how consumers actually perceive the use of such titles. This study examines consumer perceptions via a survey of US consumers conducted using Amazonâ€™s Mechanical Turk (n = 665). Findings suggest that consumers perceive common industry titles as different from one another in a manner that is consistent with the differentiation of advice professions (e.g., financial adviser, financial planner, financial consultant, investment consultant, investment adviser) from sales professions (e.g., investment salesperson, stockbroker, life insurance agent). Implications regarding the potential efficacy of proposed regulatory frameworks are discussed.

Detecting p-hacking
Graham Elliott,Nikolay Kudrin,Kaspar Wuthrich
arXiv

We analyze what can be learned from tests for p-hacking based on distributions of t-statistics and p-values across multiple studies. We analytically characterize restrictions on these distributions that conform with the absence of p-hacking. This forms a testable null hypothesis and suggests statistical tests for p-hacking. We extend our results to p-hacking when there is also publication bias, and also consider what types of distributions arise under the alternative hypothesis that researchers engage in p-hacking. We show that the power of statistical tests for detecting p-hacking is low even if p-hacking is quite prevalent.

Disengaged Owners and Financial Reporting: Evidence From Index Funds
Rawson, Caleb,Rowe, Stephen P.
SSRN
The amount of equity held by index funds is an increasingly important share of the U.S. stock market. This rise in ownership by passive investors that are, by construction, restricted from making trading decisions has the potential to dramatically impact firm decisions. We expect that compared to other owners, index funds have lower levels of engagement with portfolio firms, leading firm managers to make systematically different decisions as the percent of firm owners who are â€œdisengagedâ€ increases. Using fund-level stock holdings, we directly measure index fund ownership for each firm and examine its association with financial reporting. Consistent with lower engagement with financial reporting, we find that greater ownership by index funds is associated with fewer accruals, greater frequency of missing earnings expectations, and a greater likelihood of misstatements. Our findings are consistent with index funds engaging with firms less, leading to decreased managerial incentives to both bias earnings information and invest in financial reporting quality.

Do Appraisal Challenges Benefit Target Shareholders Through Narrowing Arbitrage Spread?
Jetley, Gaurav,Huang, Yuxiao
SSRN
There is an on-going debate regarding the extent to which the increased appraisal litigation in Delaware Chancery courts is beneficial from a public policy perspective. Boone et al. (2019) documents that, compared to deals without appraisal challenges, deals subject to appraisal challenges have 6% lower post-announcement arbitrage spread on average. Based on this observed gap in arbitrage spread, the authors claim that appraisal challenges benefit target shareholders through narrowing arbitrage spread. We find that the observed gap in arbitrage spread is driven by outliers and sampling biases. In fact, after controlling for these biases, the gap completely closes. Therefore, there is no evidence that target shareholders share the gains from merger arbitrage through narrowing arbitrage spread.

Does Doing Good Pay Off? Social Impact Bonds and Lessons for Islamic Finance to Serve the Real Economy
Marwan, Syed,Haneef, Mohamed
SSRN
Purpose â€" The purpose of this paper is to examine the worldâ€™s first social impact bond (SIB) and the lessons that can be learned for the Islamic finance industry to fulfil its true objectives. Design/methodology/approach â€" The Peterborough SIB was recently announced to be successful in achieving its targeted social and investment outcomes, reducing recidivism by 9 per cent and paying back investors a 3 per cent pa return. The paper compares Peterborough SIB with socially responsible investment (SRI) sukuk in terms of form and substance, and finds that there are various lessons from the Peterborough SIB that can be useful for future development of Islamic financial products. Findings â€" Innovative social financial tools such as SIB exemplify the true spirit of risk sharing and social responsibility, which is arguably missing in current practices of the Islamic finance industry. With the growing interest towards SRI strategies and increase in socially motivated investors, such financial tools may not only help the sustainable growth of the Islamic finance industry, but also fill in the gap between its theory and practice. Practical implications â€" As such, the paper also proposes a social impact sukuk model which integrates the key aspects learned from Peterborough SIB. This includes prioritising social impact, measurable success indicators, data and management systems, flexible contracts, third sector integration, risk sharing and fostering the culture of innovation. Originality/value â€" The findings can offer some practical insights in dealing with the issue of Islamic finance practice being overly concerned with its formal adherence with Islamic legal rules whilst neglecting its true fundamental values.

Does Financial Inclusion Drive House Prices in the Major Economies? Evidence from Augmented Mean Group Estimator
Paramati, Sudharshan Reddy,Eduardo, Roca
SSRN
Financial inclusion is being actively promoted by governments and multilateral institutions worldwide based on the belief that it promotes economic growth. In addition, it is hoped that financial inclusion would assist in alleviating the very serious problem of housing affordability as it enables individuals and households to obtain more access to credit towards buying a home. However, it is feared that financial inclusion may ironically worsen, instead of alleviating the housing affordability problem as it increases the demand for houses, directly as well as indirectly, through its positive impact on economic growth, which consequently pushes up house prices. We therefore investigate whether the increase in financial inclusion has contributed to the rise in house prices based on a sample of 20 major economies from the OECD group. We use yearly data, 1988 â€" 2016 and recently developed panel econometric techniques that are robust to the cross-sectional dependence. The long-run estimates confirm that, indeed, financial inclusion is one of the major drivers of housing prices in the selected OECD economies. On the other hand, the stronger institutional set up seems to be adversely affecting housing prices. These results remain same for various robustness measures and techniques.

Does Governance Quality Moderate the Finance-Renewable Energy-Growth Nexus?: Evidence from Five Major Regions in the World
Kassi, Diby Francois
SSRN
This paper investigates the moderating role of governance quality on the finance-renewable energy-growth nexus in five major regions in the world, including 123 countries from 1990 to 2017. These regions concern the Asia Pacific, Europe & Central Asia, America (North America and Latin America & Caribbean), Middle-East and North Africa (MENA), and Sub-Saharan African (SSA) regions. Following the principal component analysis (PCA), we constructed composite indexes of governance quality and financial development using six institutional indicators and eight financial variables. Next, we applied the two-stage least squares, difference-GMM, and system-GMM methods, as well as the Granger non-causality test in Dumitrescu and Hurlin (2012). First, the results show that better governance quality wipes out the harmful effects of financial development and renewable energy consumption on economic growth in the Asia Pacific, MENA, and SSA regions, respectively. Conversely, the level of governance quality reduces the positive effects of financial development and renewable energy consumption on economic growth in America, with few exceptions in Europe & Central Asia region, respectively. Second, we find marginal adverse effects of financial development and renewable energy consumption on growth in the Asia Pacific, MENA, and SSA regions due to their low levels of governance quality. However, the marginal effect of renewable energy consumption on growth is positive in America and Europe& Central Asia regions, whereas the marginal effect of financial development is negative in these regions in most cases. Third, there is bidirectional causality between financial development and economic growth in all areas, whereas the bidirectional causality between renewable energy consumption and growth is only confirmed in America and SSA regions, respectively. This study reveals the threshold effect of governance quality on the renewable energy-finance-growth nexus across regions. Thus, financial development, renewable energy consumption, and governance quality are complementary factors to enhance economic growth in the Asia Pacific, MENA and SSA regions, contrary to America and Europe & Central Asia regions, with some exceptions. Therefore, policymakers should improve the level of governance quality, the efficiency of financial systems and renewable energy consumption to promote sustainable development in the different regions, especially in the Asia Pacific, MENA, and SSA regions.

Downside Performance Measures and the Sharpe Ratio
Hoechner, Benedikt,Reichling, Peter,Schulze, Gordon
SSRN
In a mean-downside risk framework, portfolio lines that combine the market portfolio and the risk-free asset (i.e., passive benchmark strategies) are non-linear if the target differs from the risk-free rate. Here, downside risk-based performance measures assign different performance levels to passive strategies depending on the composition of the passive portfolio. The same applies for the evaluation of mutual funds. Therefore, we analyze the shape of portfolio lines for arbitrary targets above the risk-free rate in detail. We show that these portfolio lines can be characterized by the Kappa ratio with a target equal to the risk-free rate and, surprisingly, the Sharpe ratio. In addition, we show that minimum downside risk portfolios with varying target can be positioned on a straight line. This allows us to apply target-independent performance measures, even if portfolio lines depend on the target set by the investor. We substantiate our analytical results with an empirical study.

Equity Returns After Large Price Shocks: Global Evidence
SSRN
Using a sample of stocks experiencing large price changes in 40 countries over 20 years, we investigate the association between investorsâ€™ traits that vary by national culture â€" overconfidence, conservatism, and risk tolerance â€" and proposed theoretical explanations for short-term equity returns following large price shocks. We find evidence of overreaction in more individualistic (overconfident) countries; and underreaction in less trusting (more conservative) countries. Additionally, investors in countries with lower levels of risk tolerance overreact less to positive shocks but react similar to more risk-tolerant investors to negative price shocks, which is inconsistent with the uncertain information hypothesis. Institutional differences across countries, such as short-selling restrictions and levels of investor protection, also help explain variation in returns after price shocks. Overall, our findings lend strong support for the overreaction hypothesis, but also demonstrate the importance of cultural and institutional factors to understand investorsâ€™ reaction to new information.

Laby, Arthur B.
SSRN
The importance of investment advisers to the financial well-being of their clients cannot be overstated. Individuals and institutions entrust trillions of dollars to investment advisers to manage on their behalf. This paper discusses and explains fiduciary principles in investment advice. Looking at United States federal and state law, the paper first addresses when an adviser is considered a fiduciary. Next, it discusses the fiduciary duty of loyalty and how the duty is expressed and applied in investment advisory relationships. The paper then takes up the fiduciary duty of care and how it differs from other standards of conduct, such as a duty of suitability. The paper then reviews other legal obligations imposed on investment advisers and explains how those obligations relate to an adviserâ€™s fiduciary duty. It then examines whether an investment adviserâ€™s fiduciary duties are mandatory or can be subject to modification by the parties. Finally, the paper discusses remedies available for breaches of fiduciary duty.

Homogeneity and heterogeneity of cryptocurrencies
Xiao Fan Liu,Zeng-Xian Lin,Xiao-Pu Han
arXiv

Thousands of cryptocurrencies have been issued and publicly exchanged since Bitcoin was invented in 2008. The total cryptocurrency market value exceeds 300 billion US dollars as of 2019. This paper analyzes the prices, volumes, blockchain transactions, coin difficulties and public opinion popularities of 3607 actively exchanged cryptocurrencies. We aim to reveal and explain the homogeneity, i.e., the strong correlation of market performance, and the heterogeneity, i.e., the imbalance of popularities and sophistications, of the cryptocurrencies.

In-Sample and Out-of-Sample Sharpe Ratios of Multi-Factor Asset Pricing Models
Kan, Raymond,Wang, Xiaolu,Zheng, Xinghua
SSRN
For many multi-factor asset pricing models proposed in the recent literature, their implied tang-ency portfolios have substantially higher sample Sharpe ratios than that of the value-weighted market portfolio. In contrast, such high sample Sharpe ratio is rarely delivered by professional fund managers. This makes it difficult for us to justify using these asset pricing models for performance evaluation. In this paper, we explore if estimation risk can explain why the high sample Sharpe ratios of asset pricing models are difficult to realize in reality. In particular, we provide finite sample and asymptotic analyses of the joint distribution of in-sample and out-of-sample Sharpe ratios of a multi-factor asset pricing model. For an investor who does not know the mean and co-variance matrix of the factors in a model, the out-of-sample Sharpe ratio of an asset pricing model is substantially worse than its in-sample Sharpe ratio. After taking into account of estimation risk, our analysis suggests that many of the newly proposed asset pricing models do not provide superior out-of-sample performance than the value-weighted market portfolio.

Individual Claims Reserving in Creditor Protection Insurance Using Machine Learning
Ticconi, Damiano
SSRN
In the context of individual claims reserving in non-life insurance, a new perspective involving machine learning techniques was recently introduced. We focused on credit insurance which, despite being seldom explored, can represent an interesting challenge for machine learning techniques because of its volatile nature, sensitive to economic trends. In a framework where insurance undertakings are collecting an increasing amount of data, methods like Neural Networks and Support Vector Machines could provide a valid alternative to traditional reserving techniques, offering an easy way to include macro-economic information in the estimation process. While recent machine learning literature have focused mainly on case reserving and on analysis of loss development triangles, in this work we provide a complete evaluation of each component of the Claims Reserve in a granular sense and we compare, in terms of both bias and variability, their results with Generalised Linear Models, which can be considered a standard actuarial tool.

Information Transparency in Drug Development: Evidence from Mandatory Disclosure of Clinical Trials
Hsu, Po-Hsuan,Lee, Kyungran,Moon, S. Katie,Oh, Seungjoon
SSRN
Using Section 801 of the Food and Drug Administration Amendments Act of 2007 (FDAAA) that requires drug developers to disclose clinical trial plans and results publicly, we provide novel evidence for the effect of information transparency on drug development. We find significantly more clinical trial suspensions in industry-sponsored clinical trials after the FDAAA, which has a causal interpretation based on a difference-in-differences analysis that compares the suspension rates of industry-sponsored and academic clinical trials before and after the FDAAA. Further evidence supports peer learning as a mechanism that helps explain increased suspension decisions after the FDAAA. Finally, we analyze the social welfare implications of increased information transparency; while the FDAAA helps improve drug quality, it leads to more suspensions of potential new drugs that could have reduced mortality and morbidity.

Innovative Solutions to Tap 'Micro, Small and Medium Enterprises' (MSME) Market a Way Forward for Islamic Banks
SSRN
Purpose â€" The purpose of this paper is to indicate an innovative solution to address the financing issues faced by â€œMicro-, Small and Medium Enterprisesâ€ (MSME) in emerging economies. Design/methodology/approach â€" Islamic Financial Institutions (IFIs) especially Islamic banks are competing for high net worth individuals, whereas the MSME sector is largely untapped. A collaborative model for IFIs is suggested, to explore the MSME sector. Islamic Non-Banking Financial Institutions (NBFIs) are operating in these markets through their extensive gross route networks. The multistep collaborative model proposes â€œSpecial Purpose Entity (SPE)â€ partially owned by a single Islamic Bank or consortium and NBFI/s. SPEs can be incorporated with a defined scope, focus areas, risk profile, budget and shareholding patterns. Findings â€" Risk and profit sharing instruments also known as Musharakah and Mudarabah have less than 6 percent share within total financing offered by Islamic banks globally. Risk sharing products offered by Islamic banks are not targeting this sector due to the underdevelopment of instruments, lack of knowledge and resources. Proposed SPEs can operate regionally with a concentration on specific business sectors. Originality/value â€" The SPE model would enable Islamic banks to enter the huge MSME market while mitigating risk. On the contrary, it would enable the large segments of emerging economies (bottom 40 percent population of developing nations) to get involved and actively play their role to attain long-term development goals.

Macroeconomic and Financial Policies for Climate Change Mitigation: A Review of the Literature
Krogstrup, Signe,Oman, William
SSRN
Climate change is one of the greatest challenges of this century. Mitigation requires a large-scaletransition to a low-carbon economy. This paper provides an overview of the rapidlygrowing literature on the role of macroeconomic and financial policy tools in enabling thistransition. The literature provides a menu of policy tools for mitigation. A key conclusion isthat fiscal tools are first in line and central, but can and may need to be complemented byfinancial and monetary policy instruments. Some tools and policies raise unansweredquestions about policy tool assignment and mandates, which we describe. The literature is scarce, however, on the most effective policy mix and the role of mitigation tools and goalsin the overall policy framework.

Managerial Opportunism and Corporate Investment Efficiency
Silverstein, Brian
SSRN
How does managerial opportunism affect corporate investment efficiency? Prior research establishes corporate investment efficiency as a function of the firmâ€™s information environment and internal governance. We examine how managerial opportunism is an agency conflict that distorts corporate investment policy. We use an ex-ante firm level measure of managerial opportunism proxied with the insider trading activity of top executives and test its effects on firm investment efficiency and performance. Our results show that managerial opportunism decreases firm investment efficiency and has negative effects on both accounting and stock performance. Further tests show that both the quality of the information environment and internal governance moderate the negative effects of managerial opportunism, providing a unique perspective on how insider trading policy and regulation can affect corporate investment policy. Our results are robust to alternative proxies for firm governance, which include forced CEO turnover and board co-option, alternative model specifications, and tests for endogeneity.

Market Uncertainty and the Importance of Media Coverage at Earnings Announcements
Bonsall, Samuel B.,Green, Jeremiah,Muller, Karl A.
SSRN
We investigate whether increased investor demand for financial information arising from higher market uncertainty leads to greater media coverage of earnings announcements. We also investigate whether greater coverage during times of higher uncertainty further destabilizes financial markets because of greater attention-based trading or, alternatively, improves trading and pricing by lowering investor acquisition and interpretation costs. When uncertainty is higher, we find evidence of greater media coverage of earnings announcements and that the greater coverage leads to improvements in investor informedness, information asymmetry, and intraperiod price timeliness, and greater trade by both retail and institutional investors. In contrast to the media serving an expanded role in improving capital markets during more uncertain times, we fail to find that changes in firm-initiated disclosures lead to similar improvements and find that less frequent analyst forecast revisions exacerbate problems in capital markets during earnings announcements.

Mechanisms of Market Inefficiency
Judge, Kathryn
SSRN
Mechanisms of market inefficiency are some of the most important and least understood institutions in financial markets today. A growing body of empirical work reveals a strong and persistent demand for â€œsafe assets,â€ financial instruments that are sufficiently low risk and opaque that holders readily accept them at face value. The production of such assets, and the willingness of holders to treat them as information insensitive, depends on the existence of mechanisms that promote faith in the value of the underlying assets while simultaneously discouraging information production specific to the value of those assets. Such mechanisms include private arrangements, like securitization structures that repackage cash flows from debt instruments to produce new financial instruments that are less risky and more opaque than the underlying debt, and public ones, like the rules allowing many money market mutual funds to use a net asset value of $1.00. This essay argues that recognizing these mechanisms of market inefficiency as such is a critical first step in devising policy interventions that achieve desired aims. This runs counter to the instincts of many market regulators, like the Securities and Exchange Commission, and academics who have often assumed that markets should be structured to promote information generation and efficiency. The essay further shows, however, that defenders of the information-insensitive paradigm have failed to provide a robust institutional account of how those mechanisms can remain robust across different states of the world or the government support required if they cannot. When an adverse shock or other signal raises questions about the value of the assets underlying an information-insensitive instrument, market participants can refuse, en masse, to treat those instruments as safe. Unless the government or some other actor can provide credible information about the value of the underlying assets or financial support that renders such information irrelevant, widespread market dysfunction can follow. When that happens, the very mechanisms of market inefficiency that had enabled a market to develop can exacerbate dysfunction. Following Ronald Gilson and Reineer Kraakmanâ€™s admonishment that institutions always matter, this essay calls for the development of rich institutional accounts of how the mechanisms of market inefficiency work, when and how they can fail, and what these dynamics reveal about the role regulators should play in these domains. Mispricing or Q-Theory: Testing the Accruals Anomaly Based on the Speed of Price Adjustment Choy, Siu Kai,Lobo, Gerald J.,Tan, Yongxian SSRN Recent studies find that a q-theory based approach can accommodate most evidence in the accruals anomaly literature without assuming investor irrationality. In this study, we test the mispricing hypothesis related to the accruals anomaly against the q-theory approach using the speed of price adjustment to accruals information. Consistent with the mispricing hypothesis, the results of filing return tests, quarter-ahead return tests, and short interest tests indicate that the speed of price adjustment to accruals information is higher among low limits-to-arbitrage stocks and during periods of increased arbitrage activity. Measuring accruals premium starting from the filing date, we find evidence inconsistent with the q-theory of investment. On the Market Timing of Hedging: Evidence from U.S. Oil and Gas Producers Hong, Liu,Li, Yongjia,Xie, Kangzhen,Yan, Claire J. SSRN Using a hand-collected data, we provide evidence of extensive use of commodity derivative in hedging among U.S oil and gas producers. We find large variations in hedging intensity and hedging profits while on average they generate significant positive profits. The profits relate positively to the intensity of hedging. We further decompose the hedge ratio into two components: the pure hedging component and the market timing component. We find that the hedging profits relate strongly and positively to the market timing component. We also identify a group of firms that can consistently generate profits from their hedging activities. Among firms who actively change their hedging positions, the winners tend to be larger firms. The hedging outcome does not increase equity beta while the pure hedging component tends to decrease equity beta. The positive profits are exclusive for the commodity derivative transactions of the oil and gas producers, while they do not profit from their interest rate or foreign exchange derivative transactions. Optimal Converge Trading with Unobservable Pricing Errors Sühan Altay,Katia Colaneri,Zehra Eksi arXiv We study a dynamic portfolio optimization problem related to convergence trading, which is an investment strategy that exploits temporary mispricing by simultaneously buying relatively underpriced assets and selling short relatively overpriced ones with the expectation that their prices converge in the future. We build on the model of Liu and Timmermann (2013) and extend it by incorporating unobservable Markov-modulated pricing errors into the price dynamics of two co-integrated assets. We characterize the optimal portfolio strategies in full and partial information settings both under the assumption of unrestricted and beta-neutral strategies. By using the innovations approach, we provide the filtering equation that is essential for solving the optimization problem under partial information. Finally, in order to illustrate the model capabilities, we provide an example with a two-state Markov chain. Performance of Initial Public Offerings (IPOs): The Case of Shariah-Compliant Companies Yaakub, Nurwahida ,Sherif, Mo SSRN Purpose â€" The purpose of this paper is to examine the informational value of Shariah-compliant disclosure in the Malaysian initial public offerings (IPOs) prospectus and whether Shariah-compliant status has an impact on the IPO initial return when adopted as a signalling mechanism. Design/methodology/approach â€" It uses data from 320 IPOs for Shariah-compliant companies listed on the Bursa Malaysia between 2004 and 2013. Findings â€" It finds that the degree of IPO underpricing for Shariah-compliant companies is 19.97 per cent with investors earning significant returns on the first trading day. For the effect of different factors on the degree of IPO, we find that the size and type of IPO offers have a significant impact on the degree of IPO underpricing. Other economic confidence factor models fail to yield economically plausible parameter values. Originality/value â€" The study contributes to the literature in a number of ways. It is the first to evaluate the effect of Shariah-compliance status regulation in Malaysian market, hence it provides an insight into the effectiveness of such regulation. Second, while the existing Shariah-compliant IPO studies in the same market focus on Shariah status at the date of the studies being conducted, this study uses the information around IPO time. The information that investors receive around IPO time may influence investorsâ€™ decision and valuation of the IPOs in the aftermarket. Specifically, this study is different from the previous research, as it investigates whether Shariah-compliant companies would change the average degree of IPO underpricing for companies listed on Bursa Malaysia. Playing Hide and Seek: How Lenders Respond to Consumer Protection. Benzarti, Youssef SSRN This paper uses the universe of mortgage contracts along with a quasi-experimental design to estimate the response of high-interest lenders to borrower protection regulations aimed at simplifying and making loan terms more transparent. We find that lenders substantially reduce interest rates, by an average of 10%, in order to avoid being subject to consumer protection, without reducing amounts lent nor the number of loans originated. This finding implies that high interest lenders prefer the ability to issue obfuscatory mortgage contracts to mortgages with higher interest rates and is consistent with the model of Gabaix & Laibson (2006), which shows that firms may not educate consumers if sufficiently many consumers are inattentive. Real Estate and Infrastructure Resolution Varma, Jayanth Rama,Morris, Sebastian SSRN We propose a mechanism that uses the financial markets to mobilize the resources of a large population of investors, to revive the impaired assets in the real sector in India today. This should also allow the economy to escape from the strangle hold of the â€œdoom loopâ€, in which the financial sector, the infrastructure and real estate sectors and the economy in general through their feedback effects on each other, portend to take the economy deeper into the recession. The mechanism where the government covers the left tail risk in infrastructure and real estate, has the potential to revive these assets to the benefit of the home buyers, users and the public, with the government earning a handsome return, while being fair to the developers as well. With such a mechanism in place, in the future, developers would know that using distressed public value to their advantage would not be possible in the future. Stock Price Informativeness, CSR and Corporate Governance Shan, Yuan George,Yang, Joey (Wenling),Zhang, Junru SSRN We examine the mediation role played by corporate governance (CG) in the relationship between CSR and price informativeness. In a sample of U.S. firms from 2006 to 2018, our results suggest that CG serves as a partial mediator to complement the influence of CSR on price informativeness. Further analyses show that in firms with low governance score, no mediation effect of governance is found, rather it exhibits a substitution effect with CSR; while firms with superior CSR performance have more informative stock price through CG as a mediator. Additionally, we find the mediation effect through CG more pronounced for with the environmental component of CSR. Stocks versus Bonds and the Investment Horizon Levy, Haim,Levy, Moshe SSRN Many investors and institutions have a long-run investment perspective, hence the question of stocks versus bonds in the long-run is of central importance. Despite the great deal of research attention devoted to this issue, views remain conflicting. Indeed, neither stocks nor bonds dominate when compared in isolation, but we show that incorporating into the analysis the long-term riskless asset (TIPS) offers a clear-cut resolution. For any horizon greater than 3 years, stocks dominate bonds by First-degree Stochastic Dominance with a Riskless asset (FSDR). This implies that for any combination of bonds with TIPS, there exists a combination of stocks with TIPS that dominates it for any investor with non-decreasing preferences. Thus, the dominance of stocks over bonds for the long-run holds not only for expected utility maximizers, but also for Prospect Theory investors and investors with various aspiration levels as well. Student Selectivity and Higher Education Institutions Credit Ratings Gottesman, Aron A.,Ismailescu, Iuliana SSRN This paper investigates whether the creditworthiness of U.S. institutions of higher education is related to student selectivity (i.e., demand and quality) and whether the impact of student selectivity differs across public versus private universities; across the credit quality of the given public universityâ€™s state; and across the level of state appropriations for the given public university. We find that student quality and demand measures are significantly associated with their corresponding institutionâ€™s creditworthiness, especially for private universities. For public universities the association is weak and, contrary to our expectations, does not depend on the state credit quality or level of state funding. Our findings are robust to the inclusion of control variables. The Burden of the National Debt: Evidence from Mergers and Acquisitions Dissanayake, Ruchith,Wu, Yanhui,Zhang, Huizhong SSRN Using mergers and acquisitions (M&A) data, we test Modiglianiâ€™s (1961) proposition that the national debt places a burden on economy through a reduction in private-sector investment. We document a significant negative association between government debt and M&A activity at the aggregate and firm levels. Consistent with Modiglianiâ€™s proposition, the effects are more pronounced among more credit-worthy firms whose securities are closer substitutes for long-term treasuries. Additionally, we show that fiscal policy uncertainty is an important mechanism through which increases in national debt depress M&As. During times of rising national debt, the announced deals are associated with lower premiums and synergies. The option pricing model based on time values: an application of the universal approximation theory on unbounded domains Yang Qu,Ming-Xi Wang arXiv Hutchinson, Lo and Poggio raised the question that if learning works can learn the Black-Scholes formula, and they proposed the network mapping the ratio of underlying price to strike$S_t/K$and the time to maturity$\tau$directly into the ratio of option price to strike$C_t/K$. In this paper we propose a novel descision function and study the network mapping$S_t/K$and$\tau$into the ratio of time value to strike$V_t/K$. Time values' appearance in artificial intelligence fits into traders' natural intelligence. Empirical experiments will be carried out to demonstrate that it significantly improves Hutchinson-Lo-Poggio's original model by faster learning and better generalization performance. In order to take a conceptual viewpoint and to prove that$V_t/K$but not$C_t/K$can be approximated by superpositions of logistic functions on its domain of definition, we work on the theory of universal approximation on unbounded domains. We prove some general results which imply that an artificial neural network with a single hidden layer and sigmoid activation represents no function in$L^{p}(\RR^2 \times [0, 1]^{n})$unless it is constant zero, and that an artificial neural network with a single hidden layer and logistic activation is a universal approximator of$L^{2}(\RR \times [0, 1]^{n})$. Our work partially generalizes Cybenko's fundamental universal approximation theorem on the unit hypercube$[0, 1]^{n}\$.

Towards Federated Graph Learning for Collaborative Financial Crimes Detection
Toyotaro Suzumura,Yi Zhou,Natahalie Baracaldo,Guangnan Ye,Keith Houck,Ryo Kawahara,Ali Anwar,Lucia Larise Stavarache,Yuji Watanabe,Pablo Loyola,Daniel Klyashtorny,Heiko Ludwig,Kumar Bhaskaran
arXiv

Financial crime is a large and growing problem, in some way touching almost every financial institution. Financial institutions are the front line in the war against financial crime and accordingly, must devote substantial human and technology resources to this effort. Current processes to detect financial misconduct have limitations in their ability to effectively differentiate between malicious behavior and ordinary financial activity. These limitations tend to result in gross over-reporting of suspicious activity that necessitate time-intensive and costly manual review. Advances in technology used in this domain, including machine learning based approaches, can improve upon the effectiveness of financial institutions' existing processes, however, a key challenge that most financial institutions continue to face is that they address financial crimes in isolation without any insight from other firms. Where financial institutions address financial crimes through the lens of their own firm, perpetrators may devise sophisticated strategies that may span across institutions and geographies. Financial institutions continue to work relentlessly to advance their capabilities, forming partnerships across institutions to share insights, patterns and capabilities. These public-private partnerships are subject to stringent regulatory and data privacy requirements, thereby making it difficult to rely on traditional technology solutions. In this paper, we propose a methodology to share key information across institutions by using a federated graph learning platform that enables us to build more accurate machine learning models by leveraging federated learning and also graph learning approaches. We demonstrated that our federated model outperforms local model by 20% with the UK FCA TechSprint data set. This new platform opens up a door to efficiently detecting global money laundering activity.