Research articles for the 2019-09-07
(When) Does Transparency Hurt Liquidity?
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Conventional wisdom suggests that transparency improves market liquidity. However, if greater public information incentivizes only a subset of investors to produce private information, it could exacerbate information asymmetry among investors and thereby reduce liquidity. To test this proposition, we examine the liquidity effects of a European regulation that requires banks to provide detailed disclosures about the individual loans underlying their mortgage-backed securities (MBSs). We find that the liquidity of treated MBSs declines by 14% post-regulation. By exploiting tranche seniority and collateral quality, we also document that the effect of transparency on liquidity non-monotonically varies with investors’ incentives to seek information.
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Conventional wisdom suggests that transparency improves market liquidity. However, if greater public information incentivizes only a subset of investors to produce private information, it could exacerbate information asymmetry among investors and thereby reduce liquidity. To test this proposition, we examine the liquidity effects of a European regulation that requires banks to provide detailed disclosures about the individual loans underlying their mortgage-backed securities (MBSs). We find that the liquidity of treated MBSs declines by 14% post-regulation. By exploiting tranche seniority and collateral quality, we also document that the effect of transparency on liquidity non-monotonically varies with investors’ incentives to seek information.
A Descriptive Study of High-Frequency Trade and Quote Option Data
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This paper provides a guide to high frequency option trade and quote data disseminated by the Options Price Reporting Authority (OPRA). First, we present a comprehensive overview of the fragmented U.S. option market, including details on market regulation and the trading processes for all 15 constituent option exchanges. Then, we review the general structure of the OPRA dataset and present a thorough empirical description of the observed option trades and quotes for a selected sample of underlying assets that contains more than 25 billion records. We outline several types of irregular observations and provide recommendations for data filtering and cleaning. Finally, we illustrate the usefulness of the high frequency option data with two empirical applications: option-implied variance estimation and risk-neutral density estimation. Both applications highlight the richer information content of the high frequency OPRA data relative to the widely used end-of-day OptionMetrics data.
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This paper provides a guide to high frequency option trade and quote data disseminated by the Options Price Reporting Authority (OPRA). First, we present a comprehensive overview of the fragmented U.S. option market, including details on market regulation and the trading processes for all 15 constituent option exchanges. Then, we review the general structure of the OPRA dataset and present a thorough empirical description of the observed option trades and quotes for a selected sample of underlying assets that contains more than 25 billion records. We outline several types of irregular observations and provide recommendations for data filtering and cleaning. Finally, we illustrate the usefulness of the high frequency option data with two empirical applications: option-implied variance estimation and risk-neutral density estimation. Both applications highlight the richer information content of the high frequency OPRA data relative to the widely used end-of-day OptionMetrics data.
A European Safe Asset to Complement National Government Bonds
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This paper expands the growing literature on common safe assets in the context of the euro area financial system by employing credit risk simulation techniques to investigate the properties of different safe asset models and their impact on national bond markets. The paper explores in particular the E-bonds model, whereby a supranational institution would raise funds in the markets and provide bilateral senior loans to Member States corresponding to a fixed proportion of GDP, complementing the issuance of national government bonds, without risks of mutualisation. The main findings are that E-bonds could reach a volume of 15 to 30% of euro area GDP with a high degree of safety while becoming the reference safe asset for the banking sector, capital markets and monetary policy operations in the euro area. As regards the impact on remaining national bonds, such volumes would be consistent with Germany maintaining its top credit rating. The average funding costs of Member States would remain broadly stable, while marginal funding costs would tend to experience limited increases, which should enhance market discipline. [DISCLAIMER: The opinions expressed in this paper are the authors' and do not necessarily correspond to those of their institutions of afiliation or the European Commission, to which they should not be attributed.]
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This paper expands the growing literature on common safe assets in the context of the euro area financial system by employing credit risk simulation techniques to investigate the properties of different safe asset models and their impact on national bond markets. The paper explores in particular the E-bonds model, whereby a supranational institution would raise funds in the markets and provide bilateral senior loans to Member States corresponding to a fixed proportion of GDP, complementing the issuance of national government bonds, without risks of mutualisation. The main findings are that E-bonds could reach a volume of 15 to 30% of euro area GDP with a high degree of safety while becoming the reference safe asset for the banking sector, capital markets and monetary policy operations in the euro area. As regards the impact on remaining national bonds, such volumes would be consistent with Germany maintaining its top credit rating. The average funding costs of Member States would remain broadly stable, while marginal funding costs would tend to experience limited increases, which should enhance market discipline. [DISCLAIMER: The opinions expressed in this paper are the authors' and do not necessarily correspond to those of their institutions of afiliation or the European Commission, to which they should not be attributed.]
A New Chinese Financial Sentiment Dictionary for Textual Analysis in Accounting and Finance
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Using a multi-stage filtering procedure based on both algorithms and human judgement, we develop a Chinese Financial Sentiment Dictionary (CFSD) with the hope to help advance textual analysis of Chinese documents in accounting and finance. There are 1,489 negative words and 1,108 positive words in the CFSD. We translate all 2,597 words into English. We also briefly discuss two unique settings in which researchers can investigate some important and interesting research questions that are rarely studied due to lack of data.
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Using a multi-stage filtering procedure based on both algorithms and human judgement, we develop a Chinese Financial Sentiment Dictionary (CFSD) with the hope to help advance textual analysis of Chinese documents in accounting and finance. There are 1,489 negative words and 1,108 positive words in the CFSD. We translate all 2,597 words into English. We also briefly discuss two unique settings in which researchers can investigate some important and interesting research questions that are rarely studied due to lack of data.
Bank-Platform Competition in the Credit Market
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The paper analyzes the equilibrium on the credit market when a bank and a platform compete to offer credit to borrowers. The platform does not manage deposit accounts, but acts as an intermediary between the borrower and the investor, offering a risky contract such that the investor is only reimbursed if the borrower is successful. We first characterize the optimal contracts proposed by the platform, depending on the two-sided structure of the market. Then, we study the impact of bank-platform competition on the average risk of bank loans and the relative level of interest rates. We derive the conditions on the lending and the deposit markets such that the bank accomodates platform entry.
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The paper analyzes the equilibrium on the credit market when a bank and a platform compete to offer credit to borrowers. The platform does not manage deposit accounts, but acts as an intermediary between the borrower and the investor, offering a risky contract such that the investor is only reimbursed if the borrower is successful. We first characterize the optimal contracts proposed by the platform, depending on the two-sided structure of the market. Then, we study the impact of bank-platform competition on the average risk of bank loans and the relative level of interest rates. We derive the conditions on the lending and the deposit markets such that the bank accomodates platform entry.
Belief Updating on Bank Credit Availability and Cash Holdings
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Contrary to recent studies, we find that firms reduced cash holdings after experiencing financial distress, exploiting Japanese data from around the 2008 financial crisis. The reduction was long-lasting â€" for nearly ten years. The substitution between in-crisis borrowing and post-crisis cash holdings was one-to-one in the five years after the crisis. We attribute our finding to these firms’ belief updating on bank credit availability through their success in obtaining emergency loans, in line with the implicit insurance theory of relationship banking. We observe this negative association among firms which had the following characteristics prior to the crisis: above-median market-to-book-ratio, above-median cash holdings, and firms whose main bank had merged. Interestingly, firms received loans primarily from non-main banks. It suggests that they had diversified their pool of lenders to avoid a hold-up problem. Furthermore, these firms spent the cash on equity investment in their affiliates through internal capital markets. Our paper highlights the critical role of the banking sector in mitigating the negative consequences of financially distressed experiences.
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Contrary to recent studies, we find that firms reduced cash holdings after experiencing financial distress, exploiting Japanese data from around the 2008 financial crisis. The reduction was long-lasting â€" for nearly ten years. The substitution between in-crisis borrowing and post-crisis cash holdings was one-to-one in the five years after the crisis. We attribute our finding to these firms’ belief updating on bank credit availability through their success in obtaining emergency loans, in line with the implicit insurance theory of relationship banking. We observe this negative association among firms which had the following characteristics prior to the crisis: above-median market-to-book-ratio, above-median cash holdings, and firms whose main bank had merged. Interestingly, firms received loans primarily from non-main banks. It suggests that they had diversified their pool of lenders to avoid a hold-up problem. Furthermore, these firms spent the cash on equity investment in their affiliates through internal capital markets. Our paper highlights the critical role of the banking sector in mitigating the negative consequences of financially distressed experiences.
Beyond Carry and Momentum in Government Bonds
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This article revisits recent literature on factor investing in government bonds, in particular regarding the definition of value and defensive investing. Using techniques derived from machine learning, the authors identify the key drivers of government bond futures and the groups of factors that are most genuinely relevant. Beyond carry and momentum, they propose an approach to defensive investing that considers the safe-haven nature of government bonds. These two main styles may be complemented by value and a reversal factor in order to achieve returns independently from broad movements in interest rates.
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This article revisits recent literature on factor investing in government bonds, in particular regarding the definition of value and defensive investing. Using techniques derived from machine learning, the authors identify the key drivers of government bond futures and the groups of factors that are most genuinely relevant. Beyond carry and momentum, they propose an approach to defensive investing that considers the safe-haven nature of government bonds. These two main styles may be complemented by value and a reversal factor in order to achieve returns independently from broad movements in interest rates.
Blockchain: Post-Quantum Security & Legal Economics
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Blockchain technology is subject to security vulnerabilities resulting from recent developments in quantum computing and cryptography. All the while, the technical complexities of blockchain’s peer-to-peer system require the intervention of third-party intermediaries to facilitate financial transactions across blockchain networks. Current legal scholarship describes blockchain technology as a peer-to-peer system without a central authority, supporting the secure decentralization of economies and financial markets. Yet, with consideration to recent advancements in quantum computing, blockchain technology is not secure. Further, the technology’s legality is subject to the will of the central authorities whose economic systems it seeks to decentralize. This article contributes the first post-quantum analysis of the intersections of blockchain security and law. Additionally, this is the first piece of legal scholarship to analyze the complex relationships between Congress, the Federal Reserve, and blockchain technology in the creation of money. In doing so, this article challenges conventional assumptions relating to blockchain technology’s decentralizing economic impact. Ultimately, this article takes an interdisciplinary approach, drawing on informatics, law, and economics scholarship, to argue blockchain fails to provide a legal or secure means of establishing a peer-to-peer payment system.
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Blockchain technology is subject to security vulnerabilities resulting from recent developments in quantum computing and cryptography. All the while, the technical complexities of blockchain’s peer-to-peer system require the intervention of third-party intermediaries to facilitate financial transactions across blockchain networks. Current legal scholarship describes blockchain technology as a peer-to-peer system without a central authority, supporting the secure decentralization of economies and financial markets. Yet, with consideration to recent advancements in quantum computing, blockchain technology is not secure. Further, the technology’s legality is subject to the will of the central authorities whose economic systems it seeks to decentralize. This article contributes the first post-quantum analysis of the intersections of blockchain security and law. Additionally, this is the first piece of legal scholarship to analyze the complex relationships between Congress, the Federal Reserve, and blockchain technology in the creation of money. In doing so, this article challenges conventional assumptions relating to blockchain technology’s decentralizing economic impact. Ultimately, this article takes an interdisciplinary approach, drawing on informatics, law, and economics scholarship, to argue blockchain fails to provide a legal or secure means of establishing a peer-to-peer payment system.
CEO Compensation in Early-Stage Firms
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Prior studies on chief executive officer (CEO) compensation have mainly focused on large firms from a broad spectrum of industries. This study aims to provide further evidence on the determinants of CEO compensation for small, homogeneous firms. Using a sample of Australian early-stage mining exploration entities (MEEs) over the 2004âˆ'2017 period, we document a set of predictors of CEO compensation that are unique to this group of firms. First, fluctuations in commodity prices are found to be positively associated with CEO stock options value. Second, we find that signals of MEEs’ future prospects, conveyed through additions to and acquisition of capitalised exploration and evaluation expenditure, have positive impacts on CEO compensation. Third, proceeds from equity raisings indicate CEOs’ effort and skills to improve shareholder wealth, resulting in higher compensation. Lastly, we find some evidence supporting the relevance of non-executive directors’ advisory role over their monitoring role.
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Prior studies on chief executive officer (CEO) compensation have mainly focused on large firms from a broad spectrum of industries. This study aims to provide further evidence on the determinants of CEO compensation for small, homogeneous firms. Using a sample of Australian early-stage mining exploration entities (MEEs) over the 2004âˆ'2017 period, we document a set of predictors of CEO compensation that are unique to this group of firms. First, fluctuations in commodity prices are found to be positively associated with CEO stock options value. Second, we find that signals of MEEs’ future prospects, conveyed through additions to and acquisition of capitalised exploration and evaluation expenditure, have positive impacts on CEO compensation. Third, proceeds from equity raisings indicate CEOs’ effort and skills to improve shareholder wealth, resulting in higher compensation. Lastly, we find some evidence supporting the relevance of non-executive directors’ advisory role over their monitoring role.
Can a Deliberative Mindset Prompt Reduce Investors’ Reliance on Fake News?
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We examine if prompting investors to be in a deliberative mindset reduces their reliance on financial news when the news is later revealed to be fake. Consistent with theory, results show that investors reduce their reliance on news revealed to be fake, and that this reduction is magnified for investors who were previously prompted to be in a deliberative mindset. Importantly, results also reveal that prompting investors to be in a deliberative mindset does not affect their judgments when the news is later revealed to be true. Our study contributes to research on fake news in the financial markets and has practical implications for investors when evaluating news that may be true or fake.
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We examine if prompting investors to be in a deliberative mindset reduces their reliance on financial news when the news is later revealed to be fake. Consistent with theory, results show that investors reduce their reliance on news revealed to be fake, and that this reduction is magnified for investors who were previously prompted to be in a deliberative mindset. Importantly, results also reveal that prompting investors to be in a deliberative mindset does not affect their judgments when the news is later revealed to be true. Our study contributes to research on fake news in the financial markets and has practical implications for investors when evaluating news that may be true or fake.
Carbon Beta - A Framework for Determining Carbon Price Impacts on Valuation
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Greenhouse gas (GHG) emissions create a cost liability for firms exposed to the implementation of carbon pricing. We propose a framework for public equities that links Scope 1 and Scope 2 emissions with changes in firm valuation. This framework considers both 1) larger operating costs that lead to a decrease in value as well as 2) new revenues generated by “green†sales that increase the value of firms. From an initial carbon tax “shockâ€, we distribute the tax costs across market sectors based on Scope 1 emissions and estimate higher electricity costs based on Scope 2 emissions. In addition, we consider an increase in revenues for companies generating solutions for mitigation of GHG emissions. The framework relies on a host of assumptions that we outline and test through sensitivity analysis. We find negative price responses in four sectors: Energy, Utilities, Materials and Transportation, while we find positive price responses in several sectors including Automobiles, Software and Capital Goods.
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Greenhouse gas (GHG) emissions create a cost liability for firms exposed to the implementation of carbon pricing. We propose a framework for public equities that links Scope 1 and Scope 2 emissions with changes in firm valuation. This framework considers both 1) larger operating costs that lead to a decrease in value as well as 2) new revenues generated by “green†sales that increase the value of firms. From an initial carbon tax “shockâ€, we distribute the tax costs across market sectors based on Scope 1 emissions and estimate higher electricity costs based on Scope 2 emissions. In addition, we consider an increase in revenues for companies generating solutions for mitigation of GHG emissions. The framework relies on a host of assumptions that we outline and test through sensitivity analysis. We find negative price responses in four sectors: Energy, Utilities, Materials and Transportation, while we find positive price responses in several sectors including Automobiles, Software and Capital Goods.
Cater to Thy Client: Analyst Responsiveness to Institutional Investor Attention
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We study how institutional investor attention to a firm affects the timeliness of analysts’ forecasts for that firm. We measure abnormal institutional attention (AIA) using Bloomberg news search activity for the firm on earnings announcement days. We find that analysts issue more timely forecasts when AIA is high on the earnings announcement day. Analyst responsiveness to AIA is stronger when analysts have more resources and experience, and analyst responsiveness is weaker when the AIA of other covered firms is high. Analysts who are more responsive to AIA are more likely to be named all-star analysts and less likely to be demoted to a smaller brokerage. We address endogeneity concerns using an ex ante measure of expected AIA that is unaffected by concurrent information. Our findings suggest that responsiveness to institutional attention is an important factor that affects the production of analyst research and analysts’ career outcomes.
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We study how institutional investor attention to a firm affects the timeliness of analysts’ forecasts for that firm. We measure abnormal institutional attention (AIA) using Bloomberg news search activity for the firm on earnings announcement days. We find that analysts issue more timely forecasts when AIA is high on the earnings announcement day. Analyst responsiveness to AIA is stronger when analysts have more resources and experience, and analyst responsiveness is weaker when the AIA of other covered firms is high. Analysts who are more responsive to AIA are more likely to be named all-star analysts and less likely to be demoted to a smaller brokerage. We address endogeneity concerns using an ex ante measure of expected AIA that is unaffected by concurrent information. Our findings suggest that responsiveness to institutional attention is an important factor that affects the production of analyst research and analysts’ career outcomes.
Compensation and Risk: A Perspective on the Lake Wobegon Effect
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We investigate an alternative economic channel of a positive relationship between risk and compensation, as documented by Cheng, Hong, and Scheinkman (2015). We propose that when information asymmetry exists, firms generally seek to use compensation as a signal of their CEOs’ ability. The risks arising from information asymmetry tend to encourage firms to pay higher compensation to their CEOs in a pattern of financial incentives we call the “Lake Wobegon effectâ€. However, when individual firms pursue complete signaling, a higher equilibrium compensation level can be achieved. This paper explores the factors that give rise to the “Lake Wobegon effect†and the learning process by which this effect can be counterbalanced over time(Hayes and Schaefer 2009).
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We investigate an alternative economic channel of a positive relationship between risk and compensation, as documented by Cheng, Hong, and Scheinkman (2015). We propose that when information asymmetry exists, firms generally seek to use compensation as a signal of their CEOs’ ability. The risks arising from information asymmetry tend to encourage firms to pay higher compensation to their CEOs in a pattern of financial incentives we call the “Lake Wobegon effectâ€. However, when individual firms pursue complete signaling, a higher equilibrium compensation level can be achieved. This paper explores the factors that give rise to the “Lake Wobegon effect†and the learning process by which this effect can be counterbalanced over time(Hayes and Schaefer 2009).
Contagious Defaults in a Credit Portfolio: A Bayesian Network Approach
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Robustness of credit portfolio models is of great interest for financial institutions and regulators, since misspecified models translate to insufficient capital buffers and a crisis-prone financial system. In this paper, we propose a method to enhance credit portfolio models based on the model of Merton by incorporating contagion effects. While in most models the risks related to financial interconnectedness are neglected, we use Bayesian network methods to uncover the direct and indirect relationships between credits, while maintaining the convenient representation of factor models. A range of techniques to learn the structure and parameters of financial networks from real Credit Default Swaps (CDS) data is studied and evaluated. Our approach is demonstrated in detail in a stylized portfolio and the impact on standard risk metrics is estimated.
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Robustness of credit portfolio models is of great interest for financial institutions and regulators, since misspecified models translate to insufficient capital buffers and a crisis-prone financial system. In this paper, we propose a method to enhance credit portfolio models based on the model of Merton by incorporating contagion effects. While in most models the risks related to financial interconnectedness are neglected, we use Bayesian network methods to uncover the direct and indirect relationships between credits, while maintaining the convenient representation of factor models. A range of techniques to learn the structure and parameters of financial networks from real Credit Default Swaps (CDS) data is studied and evaluated. Our approach is demonstrated in detail in a stylized portfolio and the impact on standard risk metrics is estimated.
Credit Supply and Capital Structure Adjustments
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Using the staggered deregulation of the U.S. banking industry as a series of exogenous shocks, I study the effect of the credit supply on the speed of capital structure adjustment. I find robust evidence that interstate and intrastate banking deregulation are positively associated with leverage adjustments. Specifically, the speeds of adjustment to target leverage are faster in the post-deregulation periods. I also find that the positive effect is driven by firms that are financially constrained, are financially dependent on banks, and have less access to the public debt market and by deregulated banks’ ability to geographically diversify the credit risk.
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Using the staggered deregulation of the U.S. banking industry as a series of exogenous shocks, I study the effect of the credit supply on the speed of capital structure adjustment. I find robust evidence that interstate and intrastate banking deregulation are positively associated with leverage adjustments. Specifically, the speeds of adjustment to target leverage are faster in the post-deregulation periods. I also find that the positive effect is driven by firms that are financially constrained, are financially dependent on banks, and have less access to the public debt market and by deregulated banks’ ability to geographically diversify the credit risk.
Do CEOs Use the Media for Reputation Management?
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This study aims to investigate whether CEOs use the media as a strategic tool to manage and enhance reputation. This is pursued by examining the tendency of CEOs to provide interviews to the financial press as a reaction to past, present, and future events that influence their reputation. The tendency of CEOs to give press interviews is examined as a function of a set of proxies that are used for gauging CEOs’ reputations: CEO tenure, press coverage, being a CEO appointed from inside/outside of the ï¬rm, and ï¬rm performance during CEO tenure.The results of this paper reveal that the timing of CEOs’ decisions to give interviews is not random and provides evidence that is consistent with the notion that CEOs use the media as a strategic tool to manage and enhance reputation.The author shows that interviews tend to follow positive firm performance, and tend to precede extremely negative firm performance. This behavior is more pronounced for CEOs with lower initial reputation. In addition, low future performance motivates CEOs to give more interviews in advance, which could be an attempt to influence investors' expectations.The paper sheds new light on the selective usage of the media for shaping public perceptions. This study has practical value for both regulators and investors by virtue of analyzing information that is provided via the media.
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This study aims to investigate whether CEOs use the media as a strategic tool to manage and enhance reputation. This is pursued by examining the tendency of CEOs to provide interviews to the financial press as a reaction to past, present, and future events that influence their reputation. The tendency of CEOs to give press interviews is examined as a function of a set of proxies that are used for gauging CEOs’ reputations: CEO tenure, press coverage, being a CEO appointed from inside/outside of the ï¬rm, and ï¬rm performance during CEO tenure.The results of this paper reveal that the timing of CEOs’ decisions to give interviews is not random and provides evidence that is consistent with the notion that CEOs use the media as a strategic tool to manage and enhance reputation.The author shows that interviews tend to follow positive firm performance, and tend to precede extremely negative firm performance. This behavior is more pronounced for CEOs with lower initial reputation. In addition, low future performance motivates CEOs to give more interviews in advance, which could be an attempt to influence investors' expectations.The paper sheds new light on the selective usage of the media for shaping public perceptions. This study has practical value for both regulators and investors by virtue of analyzing information that is provided via the media.
Do Mergers Save Lives?
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Using novel data from the pharmaceutical industry, we study the impact of mergers on product prices and innovation. Drugs produced by acquiring firms increase in price approximately 5% more than drugs sold by matched non-acquiring firms. Price increases are more pronounced for deals resulting in greater market power consolidation and within drugs whose consumers are less price sensitive, but absent for drugs already shielded from competition. Rival drug prices rise as well, consistent with a spillover effect into the broader product market. We find no evidence of mergers facilitating or incentivizing innovation â€" a potential tradeoff to higher product prices. In sum, the average pharmaceutical merger increases drug prices without expanding new drug development.
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Using novel data from the pharmaceutical industry, we study the impact of mergers on product prices and innovation. Drugs produced by acquiring firms increase in price approximately 5% more than drugs sold by matched non-acquiring firms. Price increases are more pronounced for deals resulting in greater market power consolidation and within drugs whose consumers are less price sensitive, but absent for drugs already shielded from competition. Rival drug prices rise as well, consistent with a spillover effect into the broader product market. We find no evidence of mergers facilitating or incentivizing innovation â€" a potential tradeoff to higher product prices. In sum, the average pharmaceutical merger increases drug prices without expanding new drug development.
Does Debt Curb Controlling Shareholders’ Private Benefits? Modelling in a Contingent Claim Framework
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Debt is not frequently analyzed in relation to the conflict between controlling and outside shareholders. At the same time, debt leverage stands as a key variable in the design of a control contract as it has a strong disciplinary role. A simple option valuation model is used to show that debt is also a governance variable because it can moderate or enhance private benefits. It is argued that a asymmetrical self-regulation mechanism may develop in the case of control by a dominant shareholder. At low levels of leverage, debt is relatively less disciplinary compared with a non-private benefits case. When leverage exceeds a certain threshold point, it becomes strongly disciplinary. We show that under given conditions, a self-regulation mechanism develops where the controlling shareholder is incentivized to hold less debt when he/she wants to increase his/her private appropriation rate.
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Debt is not frequently analyzed in relation to the conflict between controlling and outside shareholders. At the same time, debt leverage stands as a key variable in the design of a control contract as it has a strong disciplinary role. A simple option valuation model is used to show that debt is also a governance variable because it can moderate or enhance private benefits. It is argued that a asymmetrical self-regulation mechanism may develop in the case of control by a dominant shareholder. At low levels of leverage, debt is relatively less disciplinary compared with a non-private benefits case. When leverage exceeds a certain threshold point, it becomes strongly disciplinary. We show that under given conditions, a self-regulation mechanism develops where the controlling shareholder is incentivized to hold less debt when he/she wants to increase his/her private appropriation rate.
Economies of Diversification in Microfinance: Evidence from Quantile Estimation on Panel Data
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Prior studies of the diversification-driven cost savings from the joint provision of credit and deposits in microfinance usually ignore the multi-way heterogeneity across MFIs which vary substantially in size, business model, target clientele and operate in diverse environments. Using a quantile panel data model with correlated effects capable of accommodating multiple heterogeneity, we show that the typical measurement of economies of diversification at the mean provides an incomplete and distorted picture of their magnitude and prevalence in the industry. While we find statistically significant estimates, they are modest for most small-size MFIs but are quite substantial for large-scale institutions.
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Prior studies of the diversification-driven cost savings from the joint provision of credit and deposits in microfinance usually ignore the multi-way heterogeneity across MFIs which vary substantially in size, business model, target clientele and operate in diverse environments. Using a quantile panel data model with correlated effects capable of accommodating multiple heterogeneity, we show that the typical measurement of economies of diversification at the mean provides an incomplete and distorted picture of their magnitude and prevalence in the industry. While we find statistically significant estimates, they are modest for most small-size MFIs but are quite substantial for large-scale institutions.
Entrenchment through Discretion over M&A Contractual Provisions
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We apply the idea that managers of acquiring firms intend to entrench themselves through M&A in the sense of Shleifer and Vishny’s (1989) entrenchment strategy through manager-specific investments. We propose that these managers implement bidder termination fee provisions in M&A contracts to make it costly for acquirers’ shareholders to disapprove the deal after announcement and to prevent the manager from such entrenchment through M&A. In such cases, managers announce M&A deals before getting dismissed after bad performance. Consistently, we find that the market reacts on average negatively to deal announcements if bidder termination fees are high and if the likelihood of imminent forced CEO turnover is high. For these firms we detect significant increases in their level of entrenchment post offer announcement. Our effect is also economically significant and is more pronounced if the CEO’s wealth is less sensitive to firm’s stock price changes, if the deal is characterized as a diversifying takeover, and if internal as well as external governance mechanisms are weak. The results suggest that small- to moderate-sized bidder termination fees might serve as efficiency enhancing contractual devices, whereas excessively high fees destroy shareholder value and possibly signal agency problems.
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We apply the idea that managers of acquiring firms intend to entrench themselves through M&A in the sense of Shleifer and Vishny’s (1989) entrenchment strategy through manager-specific investments. We propose that these managers implement bidder termination fee provisions in M&A contracts to make it costly for acquirers’ shareholders to disapprove the deal after announcement and to prevent the manager from such entrenchment through M&A. In such cases, managers announce M&A deals before getting dismissed after bad performance. Consistently, we find that the market reacts on average negatively to deal announcements if bidder termination fees are high and if the likelihood of imminent forced CEO turnover is high. For these firms we detect significant increases in their level of entrenchment post offer announcement. Our effect is also economically significant and is more pronounced if the CEO’s wealth is less sensitive to firm’s stock price changes, if the deal is characterized as a diversifying takeover, and if internal as well as external governance mechanisms are weak. The results suggest that small- to moderate-sized bidder termination fees might serve as efficiency enhancing contractual devices, whereas excessively high fees destroy shareholder value and possibly signal agency problems.
Fat-Finger Trade and Market Quality: The First Evidence from China
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More trading is algorithmic or computer generated, and in markets where it is allowed, high frequency. However, what happens when there is an algorithmic trading error? This study attempts to answer that question by examining the August 16, 2013, fatâ€finger trade in Chinese equity and equity futures markets. We find that both markets were excessively volatile, illiquid, and positively skewed. Moreover, we document that index returns are predictable for a short time, indicating that the fatâ€finger event induced an inefficient market. Our results highlight the importance of market surveillance and regulation to lessen the damage of future fatâ€finger events.
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More trading is algorithmic or computer generated, and in markets where it is allowed, high frequency. However, what happens when there is an algorithmic trading error? This study attempts to answer that question by examining the August 16, 2013, fatâ€finger trade in Chinese equity and equity futures markets. We find that both markets were excessively volatile, illiquid, and positively skewed. Moreover, we document that index returns are predictable for a short time, indicating that the fatâ€finger event induced an inefficient market. Our results highlight the importance of market surveillance and regulation to lessen the damage of future fatâ€finger events.
Financial Attention Frequency and Trading
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Based on daily users’ behavior data from securities service mobile applications (SSM-APPs), we measure investor financial attention frequency, which reflects how often investors use SSM-APPs to obtain information from the two dimensions, namely, startup frequency and online length. We find that the financial attention frequency shows an obvious ostrich effect, suggesting that investors acquire financial information less frequently following previous lower market returns and higher volatility. In addition, financial attention frequency significantly promotes market trading activity. And this driving effect still remains in a series of robustness tests with controlling more market factors, such as investor attention and sentiment, and after addressing some endogeneity concerns. Finally, the financial attention frequency also increases individuals’ net buying transactions.
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Based on daily users’ behavior data from securities service mobile applications (SSM-APPs), we measure investor financial attention frequency, which reflects how often investors use SSM-APPs to obtain information from the two dimensions, namely, startup frequency and online length. We find that the financial attention frequency shows an obvious ostrich effect, suggesting that investors acquire financial information less frequently following previous lower market returns and higher volatility. In addition, financial attention frequency significantly promotes market trading activity. And this driving effect still remains in a series of robustness tests with controlling more market factors, such as investor attention and sentiment, and after addressing some endogeneity concerns. Finally, the financial attention frequency also increases individuals’ net buying transactions.
Financial Intermediaries as Suppliers of Housing Quality
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I document a recent surge in improvements to rental housing quality, and I show how financial intermediaries have contributed to this surge by reallocating financing to improvements from other types of real estate investment. Using exogenous variation generated by a 2015 change in regulatory capital requirements, I find that a reallocation of bank credit accounts for 44% of post-2015 improvements. The shock increases the supply of high-quality housing, which raises average rent but lowers high-quality rent, and it accounts for 31% of post-2015 rent growth. Finally, I show how a reallocation of private equity has also increased real improvement activity.
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I document a recent surge in improvements to rental housing quality, and I show how financial intermediaries have contributed to this surge by reallocating financing to improvements from other types of real estate investment. Using exogenous variation generated by a 2015 change in regulatory capital requirements, I find that a reallocation of bank credit accounts for 44% of post-2015 improvements. The shock increases the supply of high-quality housing, which raises average rent but lowers high-quality rent, and it accounts for 31% of post-2015 rent growth. Finally, I show how a reallocation of private equity has also increased real improvement activity.
Financial Market Development and Firm Investment in Tax Avoidance: Evidence from Credit Default Swap Market
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Lenders reduce their monitoring efforts after hedging their credit risk exposure through credit default swap (CDS) contracts, which are akin to insurance against borrowers’ adverse credit events. In this study, we examine whether, upon observing the reduced lender monitoring following CDS trading, shareholders demand that borrowing firms invest in more aggressive tax planning strategies, which were previously constrained by risk-averse lenders. Using a difference-in-differences design that exploits the variation in timing of the inception of CDS trading, we document that borrowers exhibit greater tax avoidance after the inception of CDS trading. Consistent with shareholders stepping up their demands post-CDS, we find that the increase in tax avoidance is stronger for (i) firms with more powerful and influential shareholders, as measured by dedicated institutional investors, (ii) firms with stronger shareholder defenders, as measured by board independence and board size, and (iii) firms with more strategic default options. We also find that borrowers with higher levels of tax avoidance are less likely to file for bankruptcy in the future. Our findings are robust to a battery of sensitivity checks, including controlling for cost of debt and endogeneity, as well as using alternative measures of tax avoidance.
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Lenders reduce their monitoring efforts after hedging their credit risk exposure through credit default swap (CDS) contracts, which are akin to insurance against borrowers’ adverse credit events. In this study, we examine whether, upon observing the reduced lender monitoring following CDS trading, shareholders demand that borrowing firms invest in more aggressive tax planning strategies, which were previously constrained by risk-averse lenders. Using a difference-in-differences design that exploits the variation in timing of the inception of CDS trading, we document that borrowers exhibit greater tax avoidance after the inception of CDS trading. Consistent with shareholders stepping up their demands post-CDS, we find that the increase in tax avoidance is stronger for (i) firms with more powerful and influential shareholders, as measured by dedicated institutional investors, (ii) firms with stronger shareholder defenders, as measured by board independence and board size, and (iii) firms with more strategic default options. We also find that borrowers with higher levels of tax avoidance are less likely to file for bankruptcy in the future. Our findings are robust to a battery of sensitivity checks, including controlling for cost of debt and endogeneity, as well as using alternative measures of tax avoidance.
Global Crises and Contagion: Does the Capitalization Size Matter?
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This paper investigates the spread of the Global Financial Crisis (GFC) and the Eurozone Sovereign Debt Crisis (ESDC) to different market capitalization segments across countries and regions. Specifically, it tests for capitalization-specific contagion across both crises and their phases by examining large, medium and small capitalization indices of G-20 equity markets. The analysis across stable and the two crisis periods shows the existence of a stronger largecap transmission channel for the majority of countries. On the other hand, the contagion dynamics across the phases of the two crises do not provide a clear pattern of a specific cap size-based contagion across all markets. However, there is evidence that the Pacific region and the three cap groups of some individual markets of different regions are less severely affected. Further, all three cap groups of developed markets are mostly affected during the last phase of the ESDC, while emerging and frontier markets show a more diverse pattern of contagion across the phases of both crises. Finally, the Lehman Brothers’ collapse triggers a dramatic increase of the infection rate, while the ESDC seems to be more contagious than the GFC.
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This paper investigates the spread of the Global Financial Crisis (GFC) and the Eurozone Sovereign Debt Crisis (ESDC) to different market capitalization segments across countries and regions. Specifically, it tests for capitalization-specific contagion across both crises and their phases by examining large, medium and small capitalization indices of G-20 equity markets. The analysis across stable and the two crisis periods shows the existence of a stronger largecap transmission channel for the majority of countries. On the other hand, the contagion dynamics across the phases of the two crises do not provide a clear pattern of a specific cap size-based contagion across all markets. However, there is evidence that the Pacific region and the three cap groups of some individual markets of different regions are less severely affected. Further, all three cap groups of developed markets are mostly affected during the last phase of the ESDC, while emerging and frontier markets show a more diverse pattern of contagion across the phases of both crises. Finally, the Lehman Brothers’ collapse triggers a dramatic increase of the infection rate, while the ESDC seems to be more contagious than the GFC.
Hard or Soft Information? The Informational Role of Imagery
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What is the incremental information in imagery? In this study we explore the impact of imagery on investor decision making and find that both the information content in images and their appeal convey valuable information to investors. Using a novel data set of equity crowdfunding campaign text descriptions, company logos, background images, and financial information from two major crowdfunding platforms as a natural testing ground, we find that the funds raised in crowdfunding transactions are in part affected by the imagery surrounding the transaction. After presenting two new dichotomies (reinforcement of textual information and appeal) to represent a new dimension in news that may be material in general to investors, we introduce an image processing and textual decoding methodology to extract the informational content of images and map their correspondence with the textual information content of written campaign descriptions. Our results show that pictorial representations with additive information content and certain appeal characteristics significantly affect investors,after controlling for sentiment and financial information. Finally, investor size and the stage of project funding completion are shown to be significant determinants in the analysis. The methodology we develop in this paper provides the groundwork for a new framework within which to discuss news, information and investor reactions in today’s digital and visual age.
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What is the incremental information in imagery? In this study we explore the impact of imagery on investor decision making and find that both the information content in images and their appeal convey valuable information to investors. Using a novel data set of equity crowdfunding campaign text descriptions, company logos, background images, and financial information from two major crowdfunding platforms as a natural testing ground, we find that the funds raised in crowdfunding transactions are in part affected by the imagery surrounding the transaction. After presenting two new dichotomies (reinforcement of textual information and appeal) to represent a new dimension in news that may be material in general to investors, we introduce an image processing and textual decoding methodology to extract the informational content of images and map their correspondence with the textual information content of written campaign descriptions. Our results show that pictorial representations with additive information content and certain appeal characteristics significantly affect investors,after controlling for sentiment and financial information. Finally, investor size and the stage of project funding completion are shown to be significant determinants in the analysis. The methodology we develop in this paper provides the groundwork for a new framework within which to discuss news, information and investor reactions in today’s digital and visual age.
International Transmission of US Monetary Policy Shocks: Are Bond and Stock Markets Different?
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Using local projection and event studies, I investigate the non-linear effects of US monetary policy shocks on financial asset prices in five advanced economiesâ€"Australia, Canada, New Zealand, South Korea, and the United Kingdomâ€"from 1990 to 2014. The international asset prices show evidence of asymmetric or state-dependent propagation of US monetary shocks. Moreover, the results indicate that the nature of non-linearity in the shock propagation is distinctive across two asset classes, bond yields and equity prices. Contractionary US monetary policy shocks are quite influential in sovereign bond markets, while their impacts are largely insignificant in stock markets, and vice versa for expansionary monetary policy shocks. These results are quite stylized across the open economies and may imply that US monetary announcements and subsequent reactions of international risk premiums can play a critical role in international shock propagation.
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Using local projection and event studies, I investigate the non-linear effects of US monetary policy shocks on financial asset prices in five advanced economiesâ€"Australia, Canada, New Zealand, South Korea, and the United Kingdomâ€"from 1990 to 2014. The international asset prices show evidence of asymmetric or state-dependent propagation of US monetary shocks. Moreover, the results indicate that the nature of non-linearity in the shock propagation is distinctive across two asset classes, bond yields and equity prices. Contractionary US monetary policy shocks are quite influential in sovereign bond markets, while their impacts are largely insignificant in stock markets, and vice versa for expansionary monetary policy shocks. These results are quite stylized across the open economies and may imply that US monetary announcements and subsequent reactions of international risk premiums can play a critical role in international shock propagation.
Leveraging Overconfidence
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In theory, overconfident investors with a budget constraint use leverage more, trade more, and perform worse than well-calibrated investors. We confirm these predictions empirically by analyzing the overconfidence, trading, and performance of retail investors who use margin. Using survey data, we measure overconfidence as the difference between an investor’s self-assessment of knowledge and tested knowledge; margin investors have greater overconfidence than cash investors. Using broker data, we find margin investors trade more, speculate more, and have worse security selection ability than cash investors. A long-short portfolio that follows the trades of margin investors loses 35 bps per day.
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In theory, overconfident investors with a budget constraint use leverage more, trade more, and perform worse than well-calibrated investors. We confirm these predictions empirically by analyzing the overconfidence, trading, and performance of retail investors who use margin. Using survey data, we measure overconfidence as the difference between an investor’s self-assessment of knowledge and tested knowledge; margin investors have greater overconfidence than cash investors. Using broker data, we find margin investors trade more, speculate more, and have worse security selection ability than cash investors. A long-short portfolio that follows the trades of margin investors loses 35 bps per day.
Machine Learning Solutions to Challenges in Finance: An Application to the Pricing of Financial Products
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The recent fast development of machine learning provides new tools to solve challenges in many areas. In finance, average options are popular financial products among corporations, institutional investors, and individual investors for risk management and investment because average options have the advantages of cheap prices and their payoffs are not very sensitive to the changes of the underlying asset prices at the maturity date, avoiding the manipulation of asset prices and option prices. The challenge is that pricing arithmetic average options requires traditional numerical methods with the drawbacks of expensive repetitive computations and simplified models with non-realistic assumptions. This paper proposes a machine-learning method to price arithmetic and geometric average options accurately and in particular quickly. We show the effectiveness of the new method by carrying out comprehensive numerical experiments. Finally, the method is verified by an empirical test. This empirical test actually shows that the machine learning method provides a new model-free method for asset pricing.
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The recent fast development of machine learning provides new tools to solve challenges in many areas. In finance, average options are popular financial products among corporations, institutional investors, and individual investors for risk management and investment because average options have the advantages of cheap prices and their payoffs are not very sensitive to the changes of the underlying asset prices at the maturity date, avoiding the manipulation of asset prices and option prices. The challenge is that pricing arithmetic average options requires traditional numerical methods with the drawbacks of expensive repetitive computations and simplified models with non-realistic assumptions. This paper proposes a machine-learning method to price arithmetic and geometric average options accurately and in particular quickly. We show the effectiveness of the new method by carrying out comprehensive numerical experiments. Finally, the method is verified by an empirical test. This empirical test actually shows that the machine learning method provides a new model-free method for asset pricing.
Machine Valuation
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We present a machine learning approach to firm valuation that requires only historical accounting data as input. The machine learning model generates a median absolute percentage error of 17.2% in out-of-sample firm value predictions. The model out-performs a sample of final-year finance students (41.3%) and individual analyst forecasts of one-year-ahead firm value (22.4%). We show that subsequent market valuations move towards the model valuation, generating return predictability over horizons of up to five years.
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We present a machine learning approach to firm valuation that requires only historical accounting data as input. The machine learning model generates a median absolute percentage error of 17.2% in out-of-sample firm value predictions. The model out-performs a sample of final-year finance students (41.3%) and individual analyst forecasts of one-year-ahead firm value (22.4%). We show that subsequent market valuations move towards the model valuation, generating return predictability over horizons of up to five years.
Need for Speed? International Transmission Latency, Liquidity and Volatility
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Using a measure of the transmission latency between exchanges in Frankfurt and London and exploiting speed-inducing technological upgrades, we investigate the impact of international transmission latency on liquidity and volatility. We find that a decrease in transmission latency increases liquidity and volatility. In line with existing theoretical models, we show that the amplification of liquidity and volatility is associated with variations in adverse selection risk and aggressive trading. We then investigate the net economic effect of high latency and find that the liquidity deterioration effect of high latency dominates its volatility reducing effect. This implies that the liquidity enhancing benefit of increased trading speed in financial markets outweighs its volatility-inducing effect.
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Using a measure of the transmission latency between exchanges in Frankfurt and London and exploiting speed-inducing technological upgrades, we investigate the impact of international transmission latency on liquidity and volatility. We find that a decrease in transmission latency increases liquidity and volatility. In line with existing theoretical models, we show that the amplification of liquidity and volatility is associated with variations in adverse selection risk and aggressive trading. We then investigate the net economic effect of high latency and find that the liquidity deterioration effect of high latency dominates its volatility reducing effect. This implies that the liquidity enhancing benefit of increased trading speed in financial markets outweighs its volatility-inducing effect.
No Pain, No Gain? Household Beliefs and Stock Market Participation
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This paper investigates whether household beliefs on the determinants of success affect their stock market participation decisions. Using national survey data from China, I show that Chinese households believe that personal effort is the most influential factor in people’s success, followed by family social connections, aptitude, and luck. Moreover, households that believe more in effort are less likely to participate in the stock market, while those who place more emphasis on family social connections are more likely to participate. The negative (positive) effects of effort (family social connections) are more profound for agricultural (workplace-affiliated) households. Further, I offer belief mechanisms to explain the heterogeneity of stock market participation for different occupations.
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This paper investigates whether household beliefs on the determinants of success affect their stock market participation decisions. Using national survey data from China, I show that Chinese households believe that personal effort is the most influential factor in people’s success, followed by family social connections, aptitude, and luck. Moreover, households that believe more in effort are less likely to participate in the stock market, while those who place more emphasis on family social connections are more likely to participate. The negative (positive) effects of effort (family social connections) are more profound for agricultural (workplace-affiliated) households. Further, I offer belief mechanisms to explain the heterogeneity of stock market participation for different occupations.
Quantifying Stakeholder Theory via Modelling Stakeholder Attributes and Power Dynamics
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We advance a unifying theoretical framework for stakeholder analysis by way of a rigorous mathematical formulation that can be used to inform both qualitative and quantitative research. The framework comprises five components contributing to stakeholder salience. Three of these relate to power, legitimacy and urgency, well known from classical stakeholder theory. The remaining two components represent types of resistance to change within an organization. Stakeholders are modeled as interactive entities, while legitimacy arises through a mathematical projection mechanism. Individual stakeholder groups seek to maximize esteem while minimizing pressure exerted on them by other agents. A novel mechanism transforms wealth into esteem; wealth forms only part of a stakeholder group's total utility.
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We advance a unifying theoretical framework for stakeholder analysis by way of a rigorous mathematical formulation that can be used to inform both qualitative and quantitative research. The framework comprises five components contributing to stakeholder salience. Three of these relate to power, legitimacy and urgency, well known from classical stakeholder theory. The remaining two components represent types of resistance to change within an organization. Stakeholders are modeled as interactive entities, while legitimacy arises through a mathematical projection mechanism. Individual stakeholder groups seek to maximize esteem while minimizing pressure exerted on them by other agents. A novel mechanism transforms wealth into esteem; wealth forms only part of a stakeholder group's total utility.
Reverse Regulation? National Political Budget Cycles and the Moderating Power of Transnational Rating Agencies
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Regulatory theory assumes that national governments seek to constrain undesirable firm behavior, either through direct governmental oversight, or through oversight delegated to non-governmental organizations. We reverse that assumed relationship with the first study investigating when and how certain for-profit businesses of international scope constrain undesirable national government behavior. We ground our study in transnational regime theory explaining when and how for-profit firms position themselves as private regulators, and political budget cycle theory explaining when national governments are more likely to violate regulatory policies and respond to private regulatory enforcement by these for-profit firms. We document empirical support for our framework through analyses of sovereign credit ratings published by major credit rating agencies (CRAs) and borrowing by 63 national governments holding 111 executive elections from 2001-2011. Governments borrow less excessively during election years when CRAs put them on watch for a sovereign rating downgrade, which hurts re-election prospects in the short term and raises national borrowing costs in the longer run. Our study suggests new avenues of management research investigating when other for-profit firms (e.g., insurance firms) are more likely to constrain undesirable government behavior, and new avenues of public policy research aimed at using for-profit firms to discipline developing country governments (e.g., Cape Verde) trying to maintain responsible fiscal policies as they democratize.
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Regulatory theory assumes that national governments seek to constrain undesirable firm behavior, either through direct governmental oversight, or through oversight delegated to non-governmental organizations. We reverse that assumed relationship with the first study investigating when and how certain for-profit businesses of international scope constrain undesirable national government behavior. We ground our study in transnational regime theory explaining when and how for-profit firms position themselves as private regulators, and political budget cycle theory explaining when national governments are more likely to violate regulatory policies and respond to private regulatory enforcement by these for-profit firms. We document empirical support for our framework through analyses of sovereign credit ratings published by major credit rating agencies (CRAs) and borrowing by 63 national governments holding 111 executive elections from 2001-2011. Governments borrow less excessively during election years when CRAs put them on watch for a sovereign rating downgrade, which hurts re-election prospects in the short term and raises national borrowing costs in the longer run. Our study suggests new avenues of management research investigating when other for-profit firms (e.g., insurance firms) are more likely to constrain undesirable government behavior, and new avenues of public policy research aimed at using for-profit firms to discipline developing country governments (e.g., Cape Verde) trying to maintain responsible fiscal policies as they democratize.
Revisiting the Stealth Trading Hypothesis: Does Time-Varying Liquidity Explain the Size-Effect?
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Large trades have a smaller price impact per share than medium-sized trades. So far, the literature has attributed this effect to the informational content of trades. In this paper, we show that this effect can arise from strategic order placement. We introduce the concept of a liquidity elasticity, measuring the responsiveness of liquidity demand with respect to changes in liquidity supply, as a major driver for a declining price impact per share. Empirical evidence based on Nasdaq stocks strongly supports theoretical predictions and shows that the aspect of liquidity coordination is an important complement to rationales based on asymmetric information.
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Large trades have a smaller price impact per share than medium-sized trades. So far, the literature has attributed this effect to the informational content of trades. In this paper, we show that this effect can arise from strategic order placement. We introduce the concept of a liquidity elasticity, measuring the responsiveness of liquidity demand with respect to changes in liquidity supply, as a major driver for a declining price impact per share. Empirical evidence based on Nasdaq stocks strongly supports theoretical predictions and shows that the aspect of liquidity coordination is an important complement to rationales based on asymmetric information.
Risk Transmission Beyond Financial Crises: Volatility Spillovers and Spillbacks Between SMICs and the U.S.
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Utilizing VAR-DCC-MVGARCH model and volatility spillover index, we examine international spillovers and spillbacks between SMICs and the U.S. Results show that SMICs and the U.S. present dynamic and asymmetric volatility spillovers and spillbacks during and beyond financial crisis. The effects of previous long-term spillovers on the dynamics of current conditional variances are stronger than previous short-term innovations. Volatility spillbacks from China, South Africa and Mexico vary greatly, being more significant in the post global financial crisis. Furthermore, India and China present significant net spillovers to the other SMICs, whilst South Africa shows more net volatility transmission to Brazil and Mexico.
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Utilizing VAR-DCC-MVGARCH model and volatility spillover index, we examine international spillovers and spillbacks between SMICs and the U.S. Results show that SMICs and the U.S. present dynamic and asymmetric volatility spillovers and spillbacks during and beyond financial crisis. The effects of previous long-term spillovers on the dynamics of current conditional variances are stronger than previous short-term innovations. Volatility spillbacks from China, South Africa and Mexico vary greatly, being more significant in the post global financial crisis. Furthermore, India and China present significant net spillovers to the other SMICs, whilst South Africa shows more net volatility transmission to Brazil and Mexico.
Robust Asset-Liability Management with CRRA Utility in Regime-Switching Market: A Continuous-time Model
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This paper describes a robust continuous-time asset-liability management problem under Markov regime-switching. Firstly, we use the "homothetic robustness" methodology, which preserves the performance of robustness independent with wealth process, to protect the ALM model not only run well in exactly modified state variables, but also perform reasonably well if there are some forms of model misspecification. Secondly, we consider the asset-to-liability ratio instead of the difference between assets and liabilities, which ensures that we use relative values instead of absolute values for comparison, to modify the wealth process. Besides, we use the stochastic dynamic programming method to get some closed-form results and analyze the impacts of parameters on the investment strategy and value function, respectively, by numerical examples.
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This paper describes a robust continuous-time asset-liability management problem under Markov regime-switching. Firstly, we use the "homothetic robustness" methodology, which preserves the performance of robustness independent with wealth process, to protect the ALM model not only run well in exactly modified state variables, but also perform reasonably well if there are some forms of model misspecification. Secondly, we consider the asset-to-liability ratio instead of the difference between assets and liabilities, which ensures that we use relative values instead of absolute values for comparison, to modify the wealth process. Besides, we use the stochastic dynamic programming method to get some closed-form results and analyze the impacts of parameters on the investment strategy and value function, respectively, by numerical examples.
Sentiment Analysis of European Bonds 2016 â€" 2018
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We revisit the discussion of market sentiment in European sovereign bonds using a correlation analysis toolkit based on influence networks and hierarchical clustering. We focus on three case studies of political interest. In the case of the 2016 Brexit referendum, the market showed negative correlations between core and periphery only in the week before the referendum. Before the French presidential elections in 2017, the French bond spread widened together with the estimated Le Pen election probability, but the position of French bonds in the correlation blocks did not weaken. In summer 2018, during the budget negotiations within the new Italian coalition, the Italian bonds reacted very sensitively to changing political messages but did not show contagion risk to Spain or Portugal for several months. The situation changed during the week from October 22 to 26, as a spillover pattern of negative sentiment also to the other peripheral countries emerged.
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We revisit the discussion of market sentiment in European sovereign bonds using a correlation analysis toolkit based on influence networks and hierarchical clustering. We focus on three case studies of political interest. In the case of the 2016 Brexit referendum, the market showed negative correlations between core and periphery only in the week before the referendum. Before the French presidential elections in 2017, the French bond spread widened together with the estimated Le Pen election probability, but the position of French bonds in the correlation blocks did not weaken. In summer 2018, during the budget negotiations within the new Italian coalition, the Italian bonds reacted very sensitively to changing political messages but did not show contagion risk to Spain or Portugal for several months. The situation changed during the week from October 22 to 26, as a spillover pattern of negative sentiment also to the other peripheral countries emerged.
Socially Responsible Investments: Costs and Benefits for University Endowment Funds
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We examine the socially responsible investment (SRI) policies of university endowment funds over 2009-2017. SRI policies are more common when funds face greater stakeholder pressure to adopt such policies, and among universities that are more donation-dependent and located in environments with greater corporate social responsibility. SRI policy adoption predicts greater donations, especially from “socially-conscious†donors, but impose a drag on fund performance. On balance, SRI and non-SRI funds produce similar total additions (investment income plus donations), consistent with an optimal contracting equilibrium. SRI policies also yield non-pecuniary benefits, including enhanced risk management practices by the fund and higher student enrollment.
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We examine the socially responsible investment (SRI) policies of university endowment funds over 2009-2017. SRI policies are more common when funds face greater stakeholder pressure to adopt such policies, and among universities that are more donation-dependent and located in environments with greater corporate social responsibility. SRI policy adoption predicts greater donations, especially from “socially-conscious†donors, but impose a drag on fund performance. On balance, SRI and non-SRI funds produce similar total additions (investment income plus donations), consistent with an optimal contracting equilibrium. SRI policies also yield non-pecuniary benefits, including enhanced risk management practices by the fund and higher student enrollment.
Softer Lips Tell Sweeter Lies
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This study investigates the notion that women are perceived as more trustworthy than men in the context of abnormal release returns to 10-K filings. We find that female executives elicit more favorable stock market reactions when advertising their trustworthiness than their male counterparts. We address the issue of executive gender endogeneity by employing a propensity score matching and a difference-in-difference research design that compares the effects of male-to-female CEO transitions to male-to-male CEO transitions. However, we find no evidence that trust rhetoric from women executives is more sincere than that of man.
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This study investigates the notion that women are perceived as more trustworthy than men in the context of abnormal release returns to 10-K filings. We find that female executives elicit more favorable stock market reactions when advertising their trustworthiness than their male counterparts. We address the issue of executive gender endogeneity by employing a propensity score matching and a difference-in-difference research design that compares the effects of male-to-female CEO transitions to male-to-male CEO transitions. However, we find no evidence that trust rhetoric from women executives is more sincere than that of man.
Terrorist Attacks and Household Trading
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Using two sources of household data, we show that in response to psychological distress induced by terrorist attacks, households significantly reduce their trading activity and equity ownership, are less likely to enter the market, and increase the value of their savings accounts. We find that the effects of attacks are stronger in months with more casualties and increased news coverage, as well in households with a male head and in those located in the same state as the attack. Further tests on security selection suggest that our findings are consistent with risk shifting and inattention as implied by an anxiety-based utility model.
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Using two sources of household data, we show that in response to psychological distress induced by terrorist attacks, households significantly reduce their trading activity and equity ownership, are less likely to enter the market, and increase the value of their savings accounts. We find that the effects of attacks are stronger in months with more casualties and increased news coverage, as well in households with a male head and in those located in the same state as the attack. Further tests on security selection suggest that our findings are consistent with risk shifting and inattention as implied by an anxiety-based utility model.
The Application of Affine Processes in Cohort Mortality Risk Models
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This paper assesses and compares multi-factor continuous time affine mortality models applied to age-cohort mortality curves that are well suited for theoretical and practical application in finance and insurance. Models based on Gaussian distributed mortality rates, as well as the Cox-Ingersoll-Ross (CIR) process allowing for Gamma distributed mortality rates, are compared, also quantifying the probability of negative rates in the Gaussian models. In particular, we introduce the Gaussian Arbitrage-Free Nelson-Siegel (AFNS) mortality model incorporating level, slope and curvature factors. The models have appealing features including efficient estimation and computation. We estimate models using age-cohort data to capture cohort effects more effectively and in order to explain the variability in cohort mortality curves in the continuous time framework. The models allow for Poisson variation in the model estimation using the Kalman filter. The affine mortality models facilitate the derivation of closed-form survivor curves allowing for efficient valuation of mortality-linked claims. The models can also incorporate factor dependence allowing for age-dependence in the mortality curves. Importantly we show that the Gaussian independent factor AFNS model performs very well in explaining and forecasting cohort mortality.
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This paper assesses and compares multi-factor continuous time affine mortality models applied to age-cohort mortality curves that are well suited for theoretical and practical application in finance and insurance. Models based on Gaussian distributed mortality rates, as well as the Cox-Ingersoll-Ross (CIR) process allowing for Gamma distributed mortality rates, are compared, also quantifying the probability of negative rates in the Gaussian models. In particular, we introduce the Gaussian Arbitrage-Free Nelson-Siegel (AFNS) mortality model incorporating level, slope and curvature factors. The models have appealing features including efficient estimation and computation. We estimate models using age-cohort data to capture cohort effects more effectively and in order to explain the variability in cohort mortality curves in the continuous time framework. The models allow for Poisson variation in the model estimation using the Kalman filter. The affine mortality models facilitate the derivation of closed-form survivor curves allowing for efficient valuation of mortality-linked claims. The models can also incorporate factor dependence allowing for age-dependence in the mortality curves. Importantly we show that the Gaussian independent factor AFNS model performs very well in explaining and forecasting cohort mortality.
The Capital Structure Dynamics of European Listed SMEs
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This article investigates the capital structure dynamics of European SMEs by assessing the impact of firm-specific, institutional, and macroeconomic factors over the period 2005â€"2015, including the European Sovereign Debt Crisis (ESDC). In this setup, we perform a dynamic panel data analysis, along with several model specifications and robustness tests on listed SMEs of EU-28, dividing them into firm categories (micro, small, and medium) and country groups (core, periphery, high technology, and new EU member countries). We find that the effect of capital structure determinants do not differ significantly across size and country groups. The results suggest that profitability, asset structure, and size have been the driving forces of listed SME’s leverage, regardless of the size of the companies and the country group. At a macroeconomic and institutional level, taxation is the most significant variable for all the subgroups. Finally, the ESDC seems to increase the leverage of the listed SMEs in the periphery and the new member states countries, leaving the core countries practically unaffected.
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This article investigates the capital structure dynamics of European SMEs by assessing the impact of firm-specific, institutional, and macroeconomic factors over the period 2005â€"2015, including the European Sovereign Debt Crisis (ESDC). In this setup, we perform a dynamic panel data analysis, along with several model specifications and robustness tests on listed SMEs of EU-28, dividing them into firm categories (micro, small, and medium) and country groups (core, periphery, high technology, and new EU member countries). We find that the effect of capital structure determinants do not differ significantly across size and country groups. The results suggest that profitability, asset structure, and size have been the driving forces of listed SME’s leverage, regardless of the size of the companies and the country group. At a macroeconomic and institutional level, taxation is the most significant variable for all the subgroups. Finally, the ESDC seems to increase the leverage of the listed SMEs in the periphery and the new member states countries, leaving the core countries practically unaffected.
The Global Menu of Funds
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We provide the first aggregate perspective on the evolution of mutual fund offerings worldwide. Applying textual analysis to the names of over 39,000 equity mutual funds sold in 77 different countries between 1931 and 2016, we find that the dimensionality of the fund menu is small: 20 common words appear in over 50% of the fund names, and 10 categories are sufficient to classify over 85% of all funds. Moreover, the menu of funds available in each country converges over time to a common (“globalâ€) menu. We trace this surprisingly simple and uniform process of global menu convergence to the actions of individual fund families who follow similar growth paths: small families start by offering funds with more unique names but progressively conform to the main style categories as they grow. Our results shed new light on the aggregate process of financial innovation and the industrial organization of the asset management industry that appears to produce the same “wholesale†menu around the world.
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We provide the first aggregate perspective on the evolution of mutual fund offerings worldwide. Applying textual analysis to the names of over 39,000 equity mutual funds sold in 77 different countries between 1931 and 2016, we find that the dimensionality of the fund menu is small: 20 common words appear in over 50% of the fund names, and 10 categories are sufficient to classify over 85% of all funds. Moreover, the menu of funds available in each country converges over time to a common (“globalâ€) menu. We trace this surprisingly simple and uniform process of global menu convergence to the actions of individual fund families who follow similar growth paths: small families start by offering funds with more unique names but progressively conform to the main style categories as they grow. Our results shed new light on the aggregate process of financial innovation and the industrial organization of the asset management industry that appears to produce the same “wholesale†menu around the world.
The Learning, Timing, and Pricing of the Option to Invest With Guaranteed Debt and Asymmetric Information
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We assume a borrower must borrow money from a lender to start a project, in which the investment is irreversible but delayable. The debt is secured by an insurer who takes the project and pays the lender all the outstanding principal and interest in the event of default. Thus the lender is exposed to no risk of loss. In return for the guarantee, the borrower grants the insurer a fraction of the money borrowed (fee-for-guarantee swap, FGS) or of the project's equity (equity-for-guarantee swap, EGS) as guarantee cost. There is information asymmetry on the project profitability between a borrower and an insurer. The borrower knows her/his type, i.e. the expected growth rate of her/his project but the insurer merely knows it to be a random variable taking either a high or low value. An insurer can learn about the expected growth rate from the observed evolution of the project cash flow and dynamically update her/his belief on the growth rate. We find that asymmetric information makes a high-type borrower pay a higher guarantee cost than normal. The learning reduces both the guarantee cost and adverse selection cost. It accelerates the high-type borrower's investment. A sufficient high initial belief on a high-type borrower or a sufficient large funding gap makes a pooling equilibrium Pareto dominate a separation equilibrium. EGSs are generally superior to FGSs for a borrower but this assertion is not always true if there is asymmetric information.
SSRN
We assume a borrower must borrow money from a lender to start a project, in which the investment is irreversible but delayable. The debt is secured by an insurer who takes the project and pays the lender all the outstanding principal and interest in the event of default. Thus the lender is exposed to no risk of loss. In return for the guarantee, the borrower grants the insurer a fraction of the money borrowed (fee-for-guarantee swap, FGS) or of the project's equity (equity-for-guarantee swap, EGS) as guarantee cost. There is information asymmetry on the project profitability between a borrower and an insurer. The borrower knows her/his type, i.e. the expected growth rate of her/his project but the insurer merely knows it to be a random variable taking either a high or low value. An insurer can learn about the expected growth rate from the observed evolution of the project cash flow and dynamically update her/his belief on the growth rate. We find that asymmetric information makes a high-type borrower pay a higher guarantee cost than normal. The learning reduces both the guarantee cost and adverse selection cost. It accelerates the high-type borrower's investment. A sufficient high initial belief on a high-type borrower or a sufficient large funding gap makes a pooling equilibrium Pareto dominate a separation equilibrium. EGSs are generally superior to FGSs for a borrower but this assertion is not always true if there is asymmetric information.
Trading Against the Grain: When Insiders Buy High and Sell Low
SSRN
Both behavioral biases and informational advantages can drive insider trades. We first document that U.S. corporate insiders anchor on the 52-week low (high) for stock purchases (sales). We then find that insider trades made when the stock price is far away from its anchor levels are more informative, suggesting that when insiders trade against the anchoring bias, private information is providing the catalyst to overcome the bias. We further show outside investors can reap sizeable abnormal returns by piggybacking on insiders who make these “buy high and sell low†trades.
SSRN
Both behavioral biases and informational advantages can drive insider trades. We first document that U.S. corporate insiders anchor on the 52-week low (high) for stock purchases (sales). We then find that insider trades made when the stock price is far away from its anchor levels are more informative, suggesting that when insiders trade against the anchoring bias, private information is providing the catalyst to overcome the bias. We further show outside investors can reap sizeable abnormal returns by piggybacking on insiders who make these “buy high and sell low†trades.
Visuals and Attention to Earnings News on Twitter
SSRN
We propose a visual attention hypothesis that visuals in firm earnings announcements increase attention to the firm. We find that visuals in firm Twitter earnings announcements increase follower engagement with the message via retweets and likes. Consistent with attention spillover, same-day other tweets with visuals increase retweets and likes. Additionally, retweets increase at the firm level and decrease at the message level with the number of firm earnings tweets on the announcement day. Firms are more likely to use visuals in their earnings messages when earnings exceed analyst consensus expectations and are less persistent, consistent with managerial opportunism. Finally, consistent with visuals increasing investor attention, the initial return response to earnings news is stronger and the post-announcement response lower when visuals are used. Furthermore, the higher ERC from visuals is more pronounced on high investor distraction days when many other firms are also announcing earnings.
SSRN
We propose a visual attention hypothesis that visuals in firm earnings announcements increase attention to the firm. We find that visuals in firm Twitter earnings announcements increase follower engagement with the message via retweets and likes. Consistent with attention spillover, same-day other tweets with visuals increase retweets and likes. Additionally, retweets increase at the firm level and decrease at the message level with the number of firm earnings tweets on the announcement day. Firms are more likely to use visuals in their earnings messages when earnings exceed analyst consensus expectations and are less persistent, consistent with managerial opportunism. Finally, consistent with visuals increasing investor attention, the initial return response to earnings news is stronger and the post-announcement response lower when visuals are used. Furthermore, the higher ERC from visuals is more pronounced on high investor distraction days when many other firms are also announcing earnings.
What Drives Variation in the International Diversification Benefits? A Cross-Country Analysis
SSRN
In this chapter we show that, as the world becomes increasingly integrated, the benefits of global diversification still remain positive and economically significant over time. Both regression analysis and explanatory power tests show that international integration, measured by adjusted from a multifactor model, has more profound impact on the diversification benefits than correlation. Our results support Roll (2013)’s argument that, but not correlation, is an appropriate measure of market integration. We examine the impact of market integration determinants such as default risk, inflation, TED spread, past local equity market return, liquidity, and the relative performance of domestic portfolio on the potential diversification benefits.
SSRN
In this chapter we show that, as the world becomes increasingly integrated, the benefits of global diversification still remain positive and economically significant over time. Both regression analysis and explanatory power tests show that international integration, measured by adjusted from a multifactor model, has more profound impact on the diversification benefits than correlation. Our results support Roll (2013)’s argument that, but not correlation, is an appropriate measure of market integration. We examine the impact of market integration determinants such as default risk, inflation, TED spread, past local equity market return, liquidity, and the relative performance of domestic portfolio on the potential diversification benefits.
