Research articles for the 2020-07-31
A Continuous-Time Model of Financial Clearing
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We present a simple continuous-time model of clearing in financial networks. Financial ï¬rms are represented as “tanks†filled with fluid (money), flowing in and out. Once “pipes†connecting “tanks†are open, the system reaches the clearing payment vector in ï¬nite time. This approach provides a simple recursive solution to a classical static model of financial clearing in bankruptcy, and suggests a practical payment mechanism. With sufficient resources, a system of mutual obligations can be restructured into an equivalent system that has a cascade structure: there is a group of banks that paid off their debts, another group that owes money only to banks in the first group, and so on. Technically, we use the machinery of Markov chains to analyze evolution of a deterministic dynamical system.
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We present a simple continuous-time model of clearing in financial networks. Financial ï¬rms are represented as “tanks†filled with fluid (money), flowing in and out. Once “pipes†connecting “tanks†are open, the system reaches the clearing payment vector in ï¬nite time. This approach provides a simple recursive solution to a classical static model of financial clearing in bankruptcy, and suggests a practical payment mechanism. With sufficient resources, a system of mutual obligations can be restructured into an equivalent system that has a cascade structure: there is a group of banks that paid off their debts, another group that owes money only to banks in the first group, and so on. Technically, we use the machinery of Markov chains to analyze evolution of a deterministic dynamical system.
A Data-Driven Framework for Consistent Financial Valuation and Risk Measurement
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In this paper, we propose a general data-driven framework that unifies the valuation and risk measurement of financial derivatives, which is especially useful in markets with thinly-traded derivatives. We first extract the empirical characteristic function from market-observable time series for the underlying asset prices, and then utilize Fourier techniques to obtain the physical non-parametric density and cumulative distribution function for the log-returns process, based on which we compute risk measures. Then we risk-neutralize the non-parametric density and distribution functions to model-independently valuate a variety of financial derivatives, including path-independent European options and path-dependent exotic contracts. By estimating the state-price density explicitly, and utilizing a convenient basis representation, we are able to greatly simplify the pricing of exotic options all within a consistent model-free framework.Numerical examples, and an empirical example using real market data (Brent crude oil prices) illustrate the accuracy and versatility of the proposed method in handling pricing and risk management of multiple financial contracts based solely on observable time series data.
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In this paper, we propose a general data-driven framework that unifies the valuation and risk measurement of financial derivatives, which is especially useful in markets with thinly-traded derivatives. We first extract the empirical characteristic function from market-observable time series for the underlying asset prices, and then utilize Fourier techniques to obtain the physical non-parametric density and cumulative distribution function for the log-returns process, based on which we compute risk measures. Then we risk-neutralize the non-parametric density and distribution functions to model-independently valuate a variety of financial derivatives, including path-independent European options and path-dependent exotic contracts. By estimating the state-price density explicitly, and utilizing a convenient basis representation, we are able to greatly simplify the pricing of exotic options all within a consistent model-free framework.Numerical examples, and an empirical example using real market data (Brent crude oil prices) illustrate the accuracy and versatility of the proposed method in handling pricing and risk management of multiple financial contracts based solely on observable time series data.
A Measure of Pure Causality: Application to the CAPM Framework
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An observed correlation between two variables, unless there are some special conditions, includes the possibility of multiple relations among the two and a third variable. The correlation coefficient is therefore not sufficient to measure the pure relation between two variables. I propose a measure of pure causality (pure predictability) and a linear regression model to estimate it. I apply this method to the capital asset pricing model (CAPM) framework, and analyze the pure predictability of asset returns.
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An observed correlation between two variables, unless there are some special conditions, includes the possibility of multiple relations among the two and a third variable. The correlation coefficient is therefore not sufficient to measure the pure relation between two variables. I propose a measure of pure causality (pure predictability) and a linear regression model to estimate it. I apply this method to the capital asset pricing model (CAPM) framework, and analyze the pure predictability of asset returns.
Asset Sales and Subsequent Acquisitions
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In this paper, we find that the decisions to retain asset sale proceeds are positively related to the likelihood of subsequent acquisitions. We demonstrate that retention decisions destroy the wealth of shareholders. First, we document negative market reactions towards a retention decision, and the effect is more pronounced when the decision is followed by an unexpected acquisition. Second, we show that subsequent acquisitions reduce the wealth of shareholders, especially when the acquisitions are unexpected by the market. Third, retention sellers' long-run performance declines when they pursue an acquisition following the sale of their assets. Altogether, we provide novel evidence suggesting that retention sellers tend to reallocate proceeds to specific acquisitions that are detrimental to shareholders' wealth.
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In this paper, we find that the decisions to retain asset sale proceeds are positively related to the likelihood of subsequent acquisitions. We demonstrate that retention decisions destroy the wealth of shareholders. First, we document negative market reactions towards a retention decision, and the effect is more pronounced when the decision is followed by an unexpected acquisition. Second, we show that subsequent acquisitions reduce the wealth of shareholders, especially when the acquisitions are unexpected by the market. Third, retention sellers' long-run performance declines when they pursue an acquisition following the sale of their assets. Altogether, we provide novel evidence suggesting that retention sellers tend to reallocate proceeds to specific acquisitions that are detrimental to shareholders' wealth.
Building Modular Dividend Discount Models Using a 'Super Annuity Formula'
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The dramatic increase in the importance of U.S. dividends since 2001 means that financial analysts may soon demand access to updated dividend discount models (DDMs). To address this need, we introduce a new “super annuity formula†that can be used in the modular construction of multiple-stage level-growth DDMs. We also use the super annuity formula to approximate a three-stage transitional-growth DDM very accurately. We show that these advanced DDMs are relatively robust to the input assumptions. Going forward, every financial analyst should have knowledge of and access to these updated DDMs, so as to capitalize on the growing importance of dividends.
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The dramatic increase in the importance of U.S. dividends since 2001 means that financial analysts may soon demand access to updated dividend discount models (DDMs). To address this need, we introduce a new “super annuity formula†that can be used in the modular construction of multiple-stage level-growth DDMs. We also use the super annuity formula to approximate a three-stage transitional-growth DDM very accurately. We show that these advanced DDMs are relatively robust to the input assumptions. Going forward, every financial analyst should have knowledge of and access to these updated DDMs, so as to capitalize on the growing importance of dividends.
Debt liquidity and recession economics during the pandemic: a blessing or a curse?
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Normal demand will return to pre-pandemic levels only when conditions for living a normal life also gradually come back. And this will not happen before a vaccine is discovered, produced and administered or a cure is in place. The article questions the wisdom of prematurely using recession economics when the impact of these measures are likely to fail. In particular it is argued that the Cyprus Government response to the pandemic crisis is a recipe for economic disaster as it subsidises special interest groups, increases the debt, dilutes investor equity and will be maintaining labour and other operational costs artificially high. These are bound to hinder the country’s prospect of recovery amidst increasing world competition when the pandemic is finally over and the real reconstruction of the economy begins.
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Normal demand will return to pre-pandemic levels only when conditions for living a normal life also gradually come back. And this will not happen before a vaccine is discovered, produced and administered or a cure is in place. The article questions the wisdom of prematurely using recession economics when the impact of these measures are likely to fail. In particular it is argued that the Cyprus Government response to the pandemic crisis is a recipe for economic disaster as it subsidises special interest groups, increases the debt, dilutes investor equity and will be maintaining labour and other operational costs artificially high. These are bound to hinder the country’s prospect of recovery amidst increasing world competition when the pandemic is finally over and the real reconstruction of the economy begins.
Do Announcement Returns Contain Information About Value Creation?
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Stock returns around acquisition announcements are widely viewed as reflective of the net present value created by these transactions. As such, announcement returns should correlate with acquisition outcomes. Using a new measure of realized transaction-level acquisition failure, as well as acquirer firm-level performance, we show that while these outcomes can be predicted based on observable deal and firm characteristics, they are largely uncorrelated with announcement returns. Our results cast doubt on the usefulness of announcement returns as a measure of the value created in acquisitions and in other contexts.
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Stock returns around acquisition announcements are widely viewed as reflective of the net present value created by these transactions. As such, announcement returns should correlate with acquisition outcomes. Using a new measure of realized transaction-level acquisition failure, as well as acquirer firm-level performance, we show that while these outcomes can be predicted based on observable deal and firm characteristics, they are largely uncorrelated with announcement returns. Our results cast doubt on the usefulness of announcement returns as a measure of the value created in acquisitions and in other contexts.
Dynamics between Financial Development, Renewable Energy Consumption, and Economic Growth: Some International Evidence
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This thesis investigates the dynamics between financial development, renewable energy consumption, and economic growth in comparative analyses across 123 countries from 1990 to 2017. In the comparative analyses, we considered four income groups, namely low-income (LIC), lower-middle-income (LMC), upper-middle-income (UMC) and high-income (HIC) countries, but also five major regions such as Asia Pacific (APA), Europe & Central Asia (ECS), America (AMA, North America & Latin America and The Caribbean), Middle-East and North Africa (MENA) and Sub-Saharan Africa (SSA). This research is motivated by the need to show whether financial development may contribute to the protection of the planet (clean energy) and the eradication of poverty around the world. We also highlight the importance of good governance quality and renewable energies for achieving sustainable development goals (SDGs). This project is in line with the SDGs initiated by the United Nations to arouse attention towards clean water and sanitation, decent work and economic growth, peace, justice, and strong institutions affordable and clean energy in response to global warming. Hence, energy-saving technologies, i.e., renewable energies and sustainable growth, may play critical roles in this regard. The scrutiny of the empirical literature reveals that few studies have examined the nonlinear relationship between financial development, renewable energy consumption and economic growth in comparative analyses across different income groups and different regions while considering the multidimensional aspects of financial development. Notably, this study analyzes the nonlinear effects of financial development on renewable energy consumption and economic growth using different financial indicators. In a disaggregated approach, we alternatively use these indicators to represent four aspects of financial development, i.e., financial depth, financial efficiency, financial inclusion, and financial stability. Besides, this study examines the moderating effect of the quality of governance of public institutions on the relationship between financial development, renewable energy consumption, and economic growth across income levels and regions, unlike previous studies. In an aggregated approach, we built composite indexes of financial development and governance quality using eight (8) financial variables and six (6) indicators of governance quality. We make these indexes through the principal component analysis (PCA) technique to derive the overall effect of financial development on renewable energy consumption and growth while avoiding multicollinearity problems and the arbitrary choices of variables. The study also includes ten (10) control variables to avoid bias arising from omitted variables. The different estimations were performed by using two-stage least squares (2SLS), difference-GMM and system-GMM in most cases to deal with endogeneity problems, as well as to provide robust and reliable results. We also examined the causal relationships between financial development, renewable energy consumption, and economic growth using the panel vector autoregressive model (Panel VAR) following a similar approach to Granger causality framework with the GMM models. The study also provides detailed discussions of the results and specific policy implications for achieving the sustainable development goals in response to global warming across countries. These policy implications are well discussed in the last section of this thesis.
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This thesis investigates the dynamics between financial development, renewable energy consumption, and economic growth in comparative analyses across 123 countries from 1990 to 2017. In the comparative analyses, we considered four income groups, namely low-income (LIC), lower-middle-income (LMC), upper-middle-income (UMC) and high-income (HIC) countries, but also five major regions such as Asia Pacific (APA), Europe & Central Asia (ECS), America (AMA, North America & Latin America and The Caribbean), Middle-East and North Africa (MENA) and Sub-Saharan Africa (SSA). This research is motivated by the need to show whether financial development may contribute to the protection of the planet (clean energy) and the eradication of poverty around the world. We also highlight the importance of good governance quality and renewable energies for achieving sustainable development goals (SDGs). This project is in line with the SDGs initiated by the United Nations to arouse attention towards clean water and sanitation, decent work and economic growth, peace, justice, and strong institutions affordable and clean energy in response to global warming. Hence, energy-saving technologies, i.e., renewable energies and sustainable growth, may play critical roles in this regard. The scrutiny of the empirical literature reveals that few studies have examined the nonlinear relationship between financial development, renewable energy consumption and economic growth in comparative analyses across different income groups and different regions while considering the multidimensional aspects of financial development. Notably, this study analyzes the nonlinear effects of financial development on renewable energy consumption and economic growth using different financial indicators. In a disaggregated approach, we alternatively use these indicators to represent four aspects of financial development, i.e., financial depth, financial efficiency, financial inclusion, and financial stability. Besides, this study examines the moderating effect of the quality of governance of public institutions on the relationship between financial development, renewable energy consumption, and economic growth across income levels and regions, unlike previous studies. In an aggregated approach, we built composite indexes of financial development and governance quality using eight (8) financial variables and six (6) indicators of governance quality. We make these indexes through the principal component analysis (PCA) technique to derive the overall effect of financial development on renewable energy consumption and growth while avoiding multicollinearity problems and the arbitrary choices of variables. The study also includes ten (10) control variables to avoid bias arising from omitted variables. The different estimations were performed by using two-stage least squares (2SLS), difference-GMM and system-GMM in most cases to deal with endogeneity problems, as well as to provide robust and reliable results. We also examined the causal relationships between financial development, renewable energy consumption, and economic growth using the panel vector autoregressive model (Panel VAR) following a similar approach to Granger causality framework with the GMM models. The study also provides detailed discussions of the results and specific policy implications for achieving the sustainable development goals in response to global warming across countries. These policy implications are well discussed in the last section of this thesis.
Human vs. Machine: Underwriting Decisions in Finance
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Using a randomized experiment in the auto lending industry, we provide causal evidence of higher loan profitability and lower default rates with algorithmic machine underwriting, relative to human underwriting. We find that machine-underwritten loans generate 10.2% higher profit than human-underwritten loans in a sample of 140,000 randomly assigned loans. When loans to otherwise identical borrowers are compared, the loans underwritten by machines not only have higher APRs but also sustain a 6.8% lower incidence of default, relative to loans underwritten by humans. The performance gap is more pronounced with more complex loans and at discrete cutoffs. The use of a discontinuous variable space to categorize consumer credit profiles by human underwriters is associated with a 40.2% increase in default rates and 24.7% less profit. These results are consistent with findings on the human mind's limited capacity for analyzing complex problems and with agency conflicts in the underwriting process.
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Using a randomized experiment in the auto lending industry, we provide causal evidence of higher loan profitability and lower default rates with algorithmic machine underwriting, relative to human underwriting. We find that machine-underwritten loans generate 10.2% higher profit than human-underwritten loans in a sample of 140,000 randomly assigned loans. When loans to otherwise identical borrowers are compared, the loans underwritten by machines not only have higher APRs but also sustain a 6.8% lower incidence of default, relative to loans underwritten by humans. The performance gap is more pronounced with more complex loans and at discrete cutoffs. The use of a discontinuous variable space to categorize consumer credit profiles by human underwriters is associated with a 40.2% increase in default rates and 24.7% less profit. These results are consistent with findings on the human mind's limited capacity for analyzing complex problems and with agency conflicts in the underwriting process.
Inside the ESG Ratings: (Dis)Agreement and Performance
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We analyze the ESG rating criteria used by prominent agencies and show that there is a lack of a commonality in the definition of ESG (i) characteristics, (ii) attributes and (iii) standards in defining E, S and G components. We provide evidence that heterogeneity in rating criteria can lead agencies to have opposite opinions on the same evaluated companies and that agreement across those providers is substantially low. Those alternative definitions of ESG also affect sustainable investments leading to the identification of different investment universes and consequently to the creation of different benchmarks. This implies that in the asset management industry it is extremely difficult to measure the ability of a fund manager if financial performances are strongly conditioned by the chosen ESG benchmark. Finally, we find that the disagreement in the scores provided by the rating agencies disperses the effect of preferences of ESG investors on asset prices, to the point that even when there is agreement, it has no impact on financial performances.
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We analyze the ESG rating criteria used by prominent agencies and show that there is a lack of a commonality in the definition of ESG (i) characteristics, (ii) attributes and (iii) standards in defining E, S and G components. We provide evidence that heterogeneity in rating criteria can lead agencies to have opposite opinions on the same evaluated companies and that agreement across those providers is substantially low. Those alternative definitions of ESG also affect sustainable investments leading to the identification of different investment universes and consequently to the creation of different benchmarks. This implies that in the asset management industry it is extremely difficult to measure the ability of a fund manager if financial performances are strongly conditioned by the chosen ESG benchmark. Finally, we find that the disagreement in the scores provided by the rating agencies disperses the effect of preferences of ESG investors on asset prices, to the point that even when there is agreement, it has no impact on financial performances.
Is Dodd-Frank the Biggest Law Ever?
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The passage of the Dodd-Frank Wall Street Reform and Consumer Protection Act in 2010 continued a trend toward lengthier and more complex acts of Congress. We use novel metrics of the size, scope, and complexity of acts of Congress to assess Dodd-Frank’s place in this trend. Our analysis is consistent with the hypothesis that, in terms of its regulatory effects, Dodd-Frank is the biggest act of Congress in recent history and may become the biggest ever. We argue that this trend toward longer and more complex laws can cause deterioration in the quality of the regulations the laws authorize for two procedural reasons. First, a large act can create a regulatory surge that overwhelms the quality control process. Second, because a large act can precipitate the creation of many regulations by different agencies that target the same industry, the agencies create rules in relative ignorance of their potential interactions.
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The passage of the Dodd-Frank Wall Street Reform and Consumer Protection Act in 2010 continued a trend toward lengthier and more complex acts of Congress. We use novel metrics of the size, scope, and complexity of acts of Congress to assess Dodd-Frank’s place in this trend. Our analysis is consistent with the hypothesis that, in terms of its regulatory effects, Dodd-Frank is the biggest act of Congress in recent history and may become the biggest ever. We argue that this trend toward longer and more complex laws can cause deterioration in the quality of the regulations the laws authorize for two procedural reasons. First, a large act can create a regulatory surge that overwhelms the quality control process. Second, because a large act can precipitate the creation of many regulations by different agencies that target the same industry, the agencies create rules in relative ignorance of their potential interactions.
Las necesidades de liquidez y la solvencia de las empresas no financieras españolas tras la perturbación del Covid-19 (Spanish Non-Financial Corporations’ Liquidity Needs and Solvency After the COVID-19 Shock)
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Spanish abstract: La epidemia de Covid-19 está teniendo un impacto negativo sin precedentes sobre la actividad económica y, en particular, sobre los ingresos de las empresas, provocando que en algunos casos estos sean insuficientes para hacer frente a los pagos comprometidos. En este documento se presentan los resultados de un ejercicio de simulación de las necesidades de liquidez de las empresas no financieras españolas, para los cuatro trimestres de este año, derivadas tanto de los posibles déficits generados por la evolución de la actividad de explotación como de las inversiones en activos fijos y los pagos asociados a las amortizaciones de deuda. De acuerdo con los resultados, dichas necesidades de liquidez podrÃan superar los 230 mm de euros entre abril y diciembre. Se estima que, a través de los programas de avales públicos para los créditos a las empresas, podrÃan cubrirse cerca de las tres cuartas partes de dicho déficit. Para financiar el resto, las empresas podrÃan utilizar sus colchones de liquidez o recurrir a nueva deuda sin avalar. En este sentido, hay que tener en cuenta que, durante los últimos meses, las compañÃas con un mejor acceso al crédito han conseguido captar un volumen elevado de fondos sin recurrir a garantÃas públicas. Por otra parte, a pesar de la caÃda sin precedentes de la facturación empresarial, un porcentaje no desdeñable de empresas (en torno a un 40?%) habrÃan podido hacer frente a esta situación sin registrar déficit de liquidez ni experimentar un deterioro de su situación patrimonial. No obstante, en el resto de las compañÃas el retroceso de la actividad habrÃa llevado a elevar significativamente los niveles de vulnerabilidad financiera, haciéndolo con mayor intensidad dentro del segmento de las pymes y, especialmente, entre las empresas de los sectores más afectados por la pandemia, como los de turismo y ocio, vehÃculos de motor, y transporte y almacenamiento.English abstract: The COVID-19 pandemic is exerting an unprecedented adverse impact on economic activity and, in particular, on firms’ income. In some cases this means firms’ income is insufficient to meet payments to which they have committed. This article presents the results of an exercise simulating Spanish non-financial corporations’ liquidity needs for the four quarters of this year. The needs derive both from the possible shortfalls caused by developments in operating activity and from investments in fixed assets and payments associated with debt repayment. According to the results, these liquidity needs, between April and December, might exceed €230 billion. It is estimated that, through the public guarantee programmes for lending to firms, almost three-quarters of this shortfall might be covered. To finance the remainder, companies could use their liquidity buffers and/or resort to new unsecured debt. In this respect, it should be borne in mind that, in recent months, firms with better access to credit have managed to raise a high volume of funds without resorting to public guarantees. Further, despite the unprecedented fall in business turnover, a significant percentage of companies (around 40%) is estimated to have been able to withstand this situation without posting a liquidity shortfall or undergoing a downturn in their financial position. However, at the remaining companies, the fall-off in activity has led to significant increases in their level of financial vulnerability, doing so more sharply within the SME segment and especially among the firms in the sectors most affected by the pandemic, such as tourism and leisure, motor vehicles, and transport and storage.Note: Downloable document is in Spanish.
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Spanish abstract: La epidemia de Covid-19 está teniendo un impacto negativo sin precedentes sobre la actividad económica y, en particular, sobre los ingresos de las empresas, provocando que en algunos casos estos sean insuficientes para hacer frente a los pagos comprometidos. En este documento se presentan los resultados de un ejercicio de simulación de las necesidades de liquidez de las empresas no financieras españolas, para los cuatro trimestres de este año, derivadas tanto de los posibles déficits generados por la evolución de la actividad de explotación como de las inversiones en activos fijos y los pagos asociados a las amortizaciones de deuda. De acuerdo con los resultados, dichas necesidades de liquidez podrÃan superar los 230 mm de euros entre abril y diciembre. Se estima que, a través de los programas de avales públicos para los créditos a las empresas, podrÃan cubrirse cerca de las tres cuartas partes de dicho déficit. Para financiar el resto, las empresas podrÃan utilizar sus colchones de liquidez o recurrir a nueva deuda sin avalar. En este sentido, hay que tener en cuenta que, durante los últimos meses, las compañÃas con un mejor acceso al crédito han conseguido captar un volumen elevado de fondos sin recurrir a garantÃas públicas. Por otra parte, a pesar de la caÃda sin precedentes de la facturación empresarial, un porcentaje no desdeñable de empresas (en torno a un 40?%) habrÃan podido hacer frente a esta situación sin registrar déficit de liquidez ni experimentar un deterioro de su situación patrimonial. No obstante, en el resto de las compañÃas el retroceso de la actividad habrÃa llevado a elevar significativamente los niveles de vulnerabilidad financiera, haciéndolo con mayor intensidad dentro del segmento de las pymes y, especialmente, entre las empresas de los sectores más afectados por la pandemia, como los de turismo y ocio, vehÃculos de motor, y transporte y almacenamiento.English abstract: The COVID-19 pandemic is exerting an unprecedented adverse impact on economic activity and, in particular, on firms’ income. In some cases this means firms’ income is insufficient to meet payments to which they have committed. This article presents the results of an exercise simulating Spanish non-financial corporations’ liquidity needs for the four quarters of this year. The needs derive both from the possible shortfalls caused by developments in operating activity and from investments in fixed assets and payments associated with debt repayment. According to the results, these liquidity needs, between April and December, might exceed €230 billion. It is estimated that, through the public guarantee programmes for lending to firms, almost three-quarters of this shortfall might be covered. To finance the remainder, companies could use their liquidity buffers and/or resort to new unsecured debt. In this respect, it should be borne in mind that, in recent months, firms with better access to credit have managed to raise a high volume of funds without resorting to public guarantees. Further, despite the unprecedented fall in business turnover, a significant percentage of companies (around 40%) is estimated to have been able to withstand this situation without posting a liquidity shortfall or undergoing a downturn in their financial position. However, at the remaining companies, the fall-off in activity has led to significant increases in their level of financial vulnerability, doing so more sharply within the SME segment and especially among the firms in the sectors most affected by the pandemic, such as tourism and leisure, motor vehicles, and transport and storage.Note: Downloable document is in Spanish.
Manager Uncertainty and Cross-Sectional Stock Returns
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This paper evidences the explanatory power of managers’ uncertainty for cross-sectional stock returns. I introduce a novel measure of the degree of managers’ uncertain beliefs about future states: manager uncertainty (MU), defined as the count of the word “uncertainty†over the sum of the count of the word “uncertainty†and the count of the word “risk†in filings and conference calls. I find that manager’s level of uncertainty reveals valuation information about real options and thereby has significantly negative explanatory power for cross-sectional stock returns. Beyond existing market-based uncertainty measures, the manager uncertainty measure has incremental pricing power by capturing information frictions between managers’ reported uncertainty and investors’ perception of uncertainty. Moreover, a short-long portfolio sorted by manager uncertainty has a significantly positive premium and cannot be spanned by existing factor models. An application on COVID-19 uncertainty shows consistent results.
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This paper evidences the explanatory power of managers’ uncertainty for cross-sectional stock returns. I introduce a novel measure of the degree of managers’ uncertain beliefs about future states: manager uncertainty (MU), defined as the count of the word “uncertainty†over the sum of the count of the word “uncertainty†and the count of the word “risk†in filings and conference calls. I find that manager’s level of uncertainty reveals valuation information about real options and thereby has significantly negative explanatory power for cross-sectional stock returns. Beyond existing market-based uncertainty measures, the manager uncertainty measure has incremental pricing power by capturing information frictions between managers’ reported uncertainty and investors’ perception of uncertainty. Moreover, a short-long portfolio sorted by manager uncertainty has a significantly positive premium and cannot be spanned by existing factor models. An application on COVID-19 uncertainty shows consistent results.
Managing the Maturity Structure of Marketable Treasury Debt: 1953-1983
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This paper examines the evolution of the maturity structure of marketable Treasury debt from 1953 to 1983. Average maturity contracted erratically from 1953 to 1960, expanded through mid-1965, contracted again through late 1975, and then expanded into the early 1980s. What accounts for these broad trends? In particular, what were the maturity objectives of Treasury debt managers? Were they able to achieve their objectives? Why or why not?
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This paper examines the evolution of the maturity structure of marketable Treasury debt from 1953 to 1983. Average maturity contracted erratically from 1953 to 1960, expanded through mid-1965, contracted again through late 1975, and then expanded into the early 1980s. What accounts for these broad trends? In particular, what were the maturity objectives of Treasury debt managers? Were they able to achieve their objectives? Why or why not?
Missing the Boat: Lengthy Regulatory Approval Diminishes Investment Opportunities at the Project Level
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By using unique hand-collected project-level investment data, we show that lengthy equity issuance regulation is positively related to the probability of subsequent project changes and a deterioration in project returns. The effects are more pronounced for firms in a highly competitive industry and with a comparative disadvantage. We further establish that this relationship is causal by exploiting the exogenous shock to approval delay caused by changes in the China Securities Regulation Commission chairman. In response, equity issuers mitigate the delay impact by temporarily increasing short-term debt. Finally, we show that the traditional firm-level investment data fail to detect such effects.
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By using unique hand-collected project-level investment data, we show that lengthy equity issuance regulation is positively related to the probability of subsequent project changes and a deterioration in project returns. The effects are more pronounced for firms in a highly competitive industry and with a comparative disadvantage. We further establish that this relationship is causal by exploiting the exogenous shock to approval delay caused by changes in the China Securities Regulation Commission chairman. In response, equity issuers mitigate the delay impact by temporarily increasing short-term debt. Finally, we show that the traditional firm-level investment data fail to detect such effects.
Most Explanatory Independent Component Analysis
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We propose a uniquely identified version of independent component analysis, that represents the non-linear, independent counterpart of principal component analysis.As in principal component analysis, the (non-linear, in this case) factors are uniquely identified recursively as those that are decreasingly most responsible for the randomness in the original variables. Unlike in principal component analysis, the (non-linear, in this case) transformations that extract the factors make the factors independent, rather than simply uncorrelated.
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We propose a uniquely identified version of independent component analysis, that represents the non-linear, independent counterpart of principal component analysis.As in principal component analysis, the (non-linear, in this case) factors are uniquely identified recursively as those that are decreasingly most responsible for the randomness in the original variables. Unlike in principal component analysis, the (non-linear, in this case) transformations that extract the factors make the factors independent, rather than simply uncorrelated.
Must Public Information Always Crowd Out Private Information?
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No. This paper overturns the conventional wisdom in a dynamic model of financial markets where information is linked intertemporally: more information today affects the volatility of resale asset prices in the future. This dynamic complementarity gives rise to multiple information equilibria. Under a tractable global game refinement, the unique equilibrium features crowding in: more public information can induce more private information acquisition. This is due to a novel coordination effect: public disclosure affects prices tomorrow, raising the payoff risk today and hence the value of information. A higher value of information facilitates coordination on the good information equilibrium, thus crowding in more private information acquisition. This effect is more pronounced when fundamental uncertainty is high and reverts back to crowding out when uncertainty is low. Omitting this coordination effect could lead the regulator to falsely disclose too little public information, especially in recessions, which are often associated with rising uncertainty.
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No. This paper overturns the conventional wisdom in a dynamic model of financial markets where information is linked intertemporally: more information today affects the volatility of resale asset prices in the future. This dynamic complementarity gives rise to multiple information equilibria. Under a tractable global game refinement, the unique equilibrium features crowding in: more public information can induce more private information acquisition. This is due to a novel coordination effect: public disclosure affects prices tomorrow, raising the payoff risk today and hence the value of information. A higher value of information facilitates coordination on the good information equilibrium, thus crowding in more private information acquisition. This effect is more pronounced when fundamental uncertainty is high and reverts back to crowding out when uncertainty is low. Omitting this coordination effect could lead the regulator to falsely disclose too little public information, especially in recessions, which are often associated with rising uncertainty.
Net Systemic Risk
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The emphasis of this paper is on understanding the proliferation of financial institutions beyond movements of the entire market, namely, systemic risk net of systematic risk. I present economic foundation for this new notion of risk I term “net systemic risk†and propose two metrics: Net Systemic Risk (NSR) and Reverse Net Systemic Risk (RevNSR). I also provide a theoretical link between net systemic risk and other risk classes including total, systemic, systematic, and idiosyncratic risk. The empirical analysis for NSR and RevNSR demonstrates that these measures would be able to predict systemic pressure during the financial crisis of 2007-2009.
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The emphasis of this paper is on understanding the proliferation of financial institutions beyond movements of the entire market, namely, systemic risk net of systematic risk. I present economic foundation for this new notion of risk I term “net systemic risk†and propose two metrics: Net Systemic Risk (NSR) and Reverse Net Systemic Risk (RevNSR). I also provide a theoretical link between net systemic risk and other risk classes including total, systemic, systematic, and idiosyncratic risk. The empirical analysis for NSR and RevNSR demonstrates that these measures would be able to predict systemic pressure during the financial crisis of 2007-2009.
Pension Deficits and Corporate Financial Policy: Does Accounting Transparency Matter?
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We study changes in financial policies following a regulatory shock to the accounting transparency of defined benefit pension plans. We estimate the hidden pension deficits of French companies subject to mandatory IAS 19 adoption in 2005 using disclosures of early adopters of IAS 19. We find that financially risky companies reporting unexpectedly high pension deficits on first-time IAS 19 adoption subsequently reduce leverage and incur higher cost of debt. Our results suggest that in the absence of transparency the credit market anticipates off-balance sheet pension deficits. However, the introduction of the more transparent IAS 19 regime allows the credit market to correct estimation errors. Our study is one of the first to show that the greater transparency offered by IFRS has negative economic consequences for some companies.
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We study changes in financial policies following a regulatory shock to the accounting transparency of defined benefit pension plans. We estimate the hidden pension deficits of French companies subject to mandatory IAS 19 adoption in 2005 using disclosures of early adopters of IAS 19. We find that financially risky companies reporting unexpectedly high pension deficits on first-time IAS 19 adoption subsequently reduce leverage and incur higher cost of debt. Our results suggest that in the absence of transparency the credit market anticipates off-balance sheet pension deficits. However, the introduction of the more transparent IAS 19 regime allows the credit market to correct estimation errors. Our study is one of the first to show that the greater transparency offered by IFRS has negative economic consequences for some companies.
Perturbations Around the Risky Steady State
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We obtain a novel formulation for first-order perturbations around the risky steady of a general class of dynamic equilibrium models with time-varying and non-Gaussian risk. We offer explicit formulas and conditions for their local existence and uniqueness. First-order perturbations around the risky steady state are not nested in perturbations of arbitrary order around the deterministic steady state. We apply this approximation technique to models featuring Campbell-Cochrane habits, recursive preferences, and time-varying disaster risk. In many applications the proposed approximation represents similarly to global solution methods the implications of the model for asset prices and quantities. Finally, we argue that these perturbations can be viewed as a generalized version of the heuristic loglinear-lognormal approximations commonly used in the macro-finance literature. Therefore, we unify existing theories of risk-adjusted linearizations.
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We obtain a novel formulation for first-order perturbations around the risky steady of a general class of dynamic equilibrium models with time-varying and non-Gaussian risk. We offer explicit formulas and conditions for their local existence and uniqueness. First-order perturbations around the risky steady state are not nested in perturbations of arbitrary order around the deterministic steady state. We apply this approximation technique to models featuring Campbell-Cochrane habits, recursive preferences, and time-varying disaster risk. In many applications the proposed approximation represents similarly to global solution methods the implications of the model for asset prices and quantities. Finally, we argue that these perturbations can be viewed as a generalized version of the heuristic loglinear-lognormal approximations commonly used in the macro-finance literature. Therefore, we unify existing theories of risk-adjusted linearizations.
Pirates without Borders: The Propagation of Cyberattacks through Firms’ Supply Chains
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We document the propagation effects through supply chains of the most damaging cyberattack in history and the important role of banks in mitigating its impact. Customers of directly hit ï¬rms saw reductions in revenues, proï¬tability, and trade credit relative to similar ï¬rms. The losses were larger for customers with fewer alternative suppliers and suppliers producing high-speciï¬city inputs. Internal liquidity buffers and increased borrowing, mainly through bank credit lines at higher rates due to increased risk, helped affected customers to maintain investment and employment. However, the shock led to persisting adjustments to the supply chain network.
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We document the propagation effects through supply chains of the most damaging cyberattack in history and the important role of banks in mitigating its impact. Customers of directly hit ï¬rms saw reductions in revenues, proï¬tability, and trade credit relative to similar ï¬rms. The losses were larger for customers with fewer alternative suppliers and suppliers producing high-speciï¬city inputs. Internal liquidity buffers and increased borrowing, mainly through bank credit lines at higher rates due to increased risk, helped affected customers to maintain investment and employment. However, the shock led to persisting adjustments to the supply chain network.
Political Risk and Portfolio Performance: Implications for Shariah-Compliant Investors
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Political risk is an important determinant of portfolio returns. In this study, we revisit the importance of political risk in the context of a constrained portfolio, namely a Shariah-compliant equity portfolio, invested in 61 international markets. The weights of each constituent are driven by its relative exposure to political risk for the period 1996â€"2018.Results show that, in comparison with conventional investors, the Shariah-compliant investors gain substantial benefits when the allocation decision is based on political risk. A Shariah-compliant portfolio outperforms its conventional counterpart by 7.98% annually when tilted toward politically stable countries. The economic benefits further increase to 804 basis points when the portfolio allocates more funds to politically unstable countries. The tilted Shariah-compliant equity portfolio successfully reduces the downside risk, and hence results in improved stability in financial performance.
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Political risk is an important determinant of portfolio returns. In this study, we revisit the importance of political risk in the context of a constrained portfolio, namely a Shariah-compliant equity portfolio, invested in 61 international markets. The weights of each constituent are driven by its relative exposure to political risk for the period 1996â€"2018.Results show that, in comparison with conventional investors, the Shariah-compliant investors gain substantial benefits when the allocation decision is based on political risk. A Shariah-compliant portfolio outperforms its conventional counterpart by 7.98% annually when tilted toward politically stable countries. The economic benefits further increase to 804 basis points when the portfolio allocates more funds to politically unstable countries. The tilted Shariah-compliant equity portfolio successfully reduces the downside risk, and hence results in improved stability in financial performance.
Regime Dependent Optimization across Various Risk Measures for Asia-Pacific Markets for a Diversifying Portfolios
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The aim of this paper is to examine the diversification capability of energy commodities in a portfolio comprising the stock market index, crude oil and natural gas in the Asia-Pacific region. In a first step, we identify the impact of market disturbances on the selected sample period on the causal linkage between commodity and stock markets. In the second step, we identify regime-specific multivariate copulas which are come into because of time-varying dependence shape and included various risk measures such as variance, Value at Risk(VaR) and tail risk. Finally, these risk measures are minimized with and without constraint set on established expected return of an established portfolio. We find shape changes with various regime in the joint behaviour of energy commodities and stock market index over time. Thus the paper incorporates regime linked variance and therefore improve the portfolio of energy commodities and stock index against selected risk measure. We also find evidence that restricting short-selling of the stock index by assign positive weight on the stock index alleviate return from the portfolio over assign regimes. Finally, the tail risk optimal portfolio provides the best risk-return trade-off (i.e lowest risk and highest return) with a constraint set on the expected return and also without constraint set on the expected return. Although tail risk optimal portfolio provides best risk-return trade-off, one can use other optimal portfolios such as VaR optimal portfolios and variance optimal portfolios in those cases where we do not have the constraint on a return.
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The aim of this paper is to examine the diversification capability of energy commodities in a portfolio comprising the stock market index, crude oil and natural gas in the Asia-Pacific region. In a first step, we identify the impact of market disturbances on the selected sample period on the causal linkage between commodity and stock markets. In the second step, we identify regime-specific multivariate copulas which are come into because of time-varying dependence shape and included various risk measures such as variance, Value at Risk(VaR) and tail risk. Finally, these risk measures are minimized with and without constraint set on established expected return of an established portfolio. We find shape changes with various regime in the joint behaviour of energy commodities and stock market index over time. Thus the paper incorporates regime linked variance and therefore improve the portfolio of energy commodities and stock index against selected risk measure. We also find evidence that restricting short-selling of the stock index by assign positive weight on the stock index alleviate return from the portfolio over assign regimes. Finally, the tail risk optimal portfolio provides the best risk-return trade-off (i.e lowest risk and highest return) with a constraint set on the expected return and also without constraint set on the expected return. Although tail risk optimal portfolio provides best risk-return trade-off, one can use other optimal portfolios such as VaR optimal portfolios and variance optimal portfolios in those cases where we do not have the constraint on a return.
Regulating Financial Networks Under Uncertainty
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I study the problem of regulating a network of interdependent financial institutions that is prone to contagion when there is uncertainty regarding its precise structure. I show that such uncertainty reduces the scope for welfare-improving interventions. While improving network transparency potentially reduces this uncertainty, it does not always lead to welfare improvements. Under certain conditions, regulation that reduces the risk-taking incentives of a small set of institutions can improve welfare. The size and composition of such a set crucially depend on the interplay between (i) the (expected) susceptibility of the network to contagion, (ii) the cost of improving network transparency, (iii) the cost of regulating institutions, and (iv) investors’ preferences.
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I study the problem of regulating a network of interdependent financial institutions that is prone to contagion when there is uncertainty regarding its precise structure. I show that such uncertainty reduces the scope for welfare-improving interventions. While improving network transparency potentially reduces this uncertainty, it does not always lead to welfare improvements. Under certain conditions, regulation that reduces the risk-taking incentives of a small set of institutions can improve welfare. The size and composition of such a set crucially depend on the interplay between (i) the (expected) susceptibility of the network to contagion, (ii) the cost of improving network transparency, (iii) the cost of regulating institutions, and (iv) investors’ preferences.
The (Un)Predictable Impact of Technology on Corporate Governance
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Technological developments have dramatically changed the way enterprises do business, with far-reaching consequences in many fields. From an organizational perspective, the broad question is whether and how new technologies â€" such as big-data extraction and analytics, algorithms, artificial intelligence, the block-chain, and smart contracts â€" will impact and eventually improve corporate organizations and governance. While the answer depends, at least to some extent, on the time frame chosen and on the specific technology considered, this paper shows that one of the most significant and immediate effects of new technologies on corporations concerns the distribution of competences and responsibilities among corporate bodies. The paper identifies five primary determinants of the current balance of powers in corporate organizations: (i) the speed and frequency of the decisions; (ii) the information necessary to decide and who has access to it; (iii) the costs of assigning decision-making responsibilities to a collegial body; (iv) the decision-makers’ incentives and interests; and (v) their competence and skills. Looking at whether and how these five dimensions are altered by technological innovation is the essential, and yet unexamined, analytical tool to reliably and accurately predict the impact of technology on corporate governance. While, in some cases, technological innovations may simply require managers to possess or acquire new competences and skills or may strengthen existing corporate roles, providing those who already make decisions with new tools to operate more efficiently, in other cases technology may shift the balance on who is the best decision-maker within the corporation. Technology may reduce some of the transaction costs that make collective decision-making burdensome for some corporate actors, suggesting, for example, that decisions that have been traditionally reserved for the board of directors may be made by shareholders. Similarly, competences that have commonly been delegated to executive officers and managers because of the need of particular operating expertise may shift back to the board of directors due to the informational decision-making support provided by technological tools. The result may not seem revolutionary at first glance, but it has potentially disruptive consequences for existing corporate governance models and demands renewed attention to ad hoc contractual solutions.
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Technological developments have dramatically changed the way enterprises do business, with far-reaching consequences in many fields. From an organizational perspective, the broad question is whether and how new technologies â€" such as big-data extraction and analytics, algorithms, artificial intelligence, the block-chain, and smart contracts â€" will impact and eventually improve corporate organizations and governance. While the answer depends, at least to some extent, on the time frame chosen and on the specific technology considered, this paper shows that one of the most significant and immediate effects of new technologies on corporations concerns the distribution of competences and responsibilities among corporate bodies. The paper identifies five primary determinants of the current balance of powers in corporate organizations: (i) the speed and frequency of the decisions; (ii) the information necessary to decide and who has access to it; (iii) the costs of assigning decision-making responsibilities to a collegial body; (iv) the decision-makers’ incentives and interests; and (v) their competence and skills. Looking at whether and how these five dimensions are altered by technological innovation is the essential, and yet unexamined, analytical tool to reliably and accurately predict the impact of technology on corporate governance. While, in some cases, technological innovations may simply require managers to possess or acquire new competences and skills or may strengthen existing corporate roles, providing those who already make decisions with new tools to operate more efficiently, in other cases technology may shift the balance on who is the best decision-maker within the corporation. Technology may reduce some of the transaction costs that make collective decision-making burdensome for some corporate actors, suggesting, for example, that decisions that have been traditionally reserved for the board of directors may be made by shareholders. Similarly, competences that have commonly been delegated to executive officers and managers because of the need of particular operating expertise may shift back to the board of directors due to the informational decision-making support provided by technological tools. The result may not seem revolutionary at first glance, but it has potentially disruptive consequences for existing corporate governance models and demands renewed attention to ad hoc contractual solutions.
The Bright Side of Co-Opted Boards: Evidence from Firm Innovation
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This study documents a positive and robust effect of co-opted boards on firm innovation. This effect is mainly driven by co-opted independent directors. Firms with more co-opted independent directors are associated with lower sensitivities of CEO pay-performance and turnover-performance. It suggests that co-opted boards promote innovation by insulating managers’ career concerns from innovation risk and supporting incentive contracts that motivate innovation. Overall, our study provides new evidence on co-opted boards benefiting firm innovation.
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This study documents a positive and robust effect of co-opted boards on firm innovation. This effect is mainly driven by co-opted independent directors. Firms with more co-opted independent directors are associated with lower sensitivities of CEO pay-performance and turnover-performance. It suggests that co-opted boards promote innovation by insulating managers’ career concerns from innovation risk and supporting incentive contracts that motivate innovation. Overall, our study provides new evidence on co-opted boards benefiting firm innovation.
The Network of Firms Implied by the News
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We show that the news is a rich source of data on distressed firm links that drive firm-level and aggregate risks. The news tends to report about links in which a less popular firm is distressed and may contaminate a more popular firm. This constitutes a contagion channel that yields predictable returns and downgrades. Shocks to the degree of news-implied firm connectivity predict increases in aggregate volatilities, credit spreads, and default rates, and declines in output. To obtain our results, we propose a machine learning methodology that takes text data as input and outputs a data-implied firm network.
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We show that the news is a rich source of data on distressed firm links that drive firm-level and aggregate risks. The news tends to report about links in which a less popular firm is distressed and may contaminate a more popular firm. This constitutes a contagion channel that yields predictable returns and downgrades. Shocks to the degree of news-implied firm connectivity predict increases in aggregate volatilities, credit spreads, and default rates, and declines in output. To obtain our results, we propose a machine learning methodology that takes text data as input and outputs a data-implied firm network.
The Undesirable Effect of Audit Quality: Evidence from Firm Innovation
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This study examines whether and how audit quality affects a firm’s technological innovation. Using a sample of 7,482 U.S. firms between 2000 and 2009, we demonstrate that high audit quality is associated with lower innovation output, measured by patent counts and patent citations. The effect remains valid after a series of tests for endogeneity issues, alternative measures of audit quality, and different subsamples. We also find that firms with high audit quality attract more non-dedicated institutional investors and financial analysts, who often exert excessive pressure on managers for short-term performance. These pressures, in turn, exacerbate managerial myopia and lead them to forgo investments in innovation. Our findings provide new insights into audit quality by showing its undesirable, most likely unintended, consequences.
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This study examines whether and how audit quality affects a firm’s technological innovation. Using a sample of 7,482 U.S. firms between 2000 and 2009, we demonstrate that high audit quality is associated with lower innovation output, measured by patent counts and patent citations. The effect remains valid after a series of tests for endogeneity issues, alternative measures of audit quality, and different subsamples. We also find that firms with high audit quality attract more non-dedicated institutional investors and financial analysts, who often exert excessive pressure on managers for short-term performance. These pressures, in turn, exacerbate managerial myopia and lead them to forgo investments in innovation. Our findings provide new insights into audit quality by showing its undesirable, most likely unintended, consequences.
Why Do Borrowers Default on Mortgages? A New Method for Causal Attribution
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There are two prevailing theories of borrower default: strategic defaultâ€"when debt is too high relative to the value of the houseâ€"and adverse life eventsâ€"such that the monthly payment is too high relative to available resources. It has been challenging to test between these theories in part because adverse events are measured with error, possibly leading to attenuation bias. We develop a new method for addressing this measurement error using a comparison group of borrowers with no strategic default motive: borrowers with positive home equity. We implement the method using high-frequency administrative data linking income and mortgage default. Our central finding is that only 3 percent of defaults are caused exclusively by negative equity, much less than previously thought; in other words, adverse events are a necessary condition for 97 percent of mortgage defaults. Although this finding contrasts sharply with predictions from standard models, we show that it can be rationalized in models with a high private cost of mortgage default.
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There are two prevailing theories of borrower default: strategic defaultâ€"when debt is too high relative to the value of the houseâ€"and adverse life eventsâ€"such that the monthly payment is too high relative to available resources. It has been challenging to test between these theories in part because adverse events are measured with error, possibly leading to attenuation bias. We develop a new method for addressing this measurement error using a comparison group of borrowers with no strategic default motive: borrowers with positive home equity. We implement the method using high-frequency administrative data linking income and mortgage default. Our central finding is that only 3 percent of defaults are caused exclusively by negative equity, much less than previously thought; in other words, adverse events are a necessary condition for 97 percent of mortgage defaults. Although this finding contrasts sharply with predictions from standard models, we show that it can be rationalized in models with a high private cost of mortgage default.
