Research articles for the 2020-09-22
A One-Factor Model of Corporate Bond Premia
SSRN
We test whether long-run consumption risk can explain the cross-section of corporate bond risk premiums. We find that a one-factor model with long-run consumption growth explains the risk premiums on bond portfolios sorted on credit spreads, maturity, credit rating, downside risk, idiosyncratic volatility, and the betas with respect to shocks to financial intermediary's capital of He, Kelly, and Manela (2017). Furthermore, the estimated risk aversion coefficient declines as we increase the horizon to measure consumption growth, and a model with relatively low values of risk-aversion can match the observed risk premiums if we use 24-month growth rate as a risk factor.
SSRN
We test whether long-run consumption risk can explain the cross-section of corporate bond risk premiums. We find that a one-factor model with long-run consumption growth explains the risk premiums on bond portfolios sorted on credit spreads, maturity, credit rating, downside risk, idiosyncratic volatility, and the betas with respect to shocks to financial intermediary's capital of He, Kelly, and Manela (2017). Furthermore, the estimated risk aversion coefficient declines as we increase the horizon to measure consumption growth, and a model with relatively low values of risk-aversion can match the observed risk premiums if we use 24-month growth rate as a risk factor.
Ambiguity Resolution, the Coming U.S. Market Crash of October 2020 and Ensuing Golden Age of Finance
SSRN
It is uncanny that historically, the large majority of U.S. market crashes have occurred in the month of October. I assert that three key conditions are gathered for this to happen. 1) There is a market-wide or macroeconomic informational ambiguity that has been lingering since before the summer months with high downside risk; 2) that despite this ambiguity, leverage is used to create a bubble and 3) that investors are driven by what I call the “ambiguity-forced-resolution bias.†I apply this reasoning to predict a crash in October 2020. I show that there currently is a bubble in the U.S. using a new indicator. I test that ambiguity/uncertainty was unusually high in months prior October crashes. Finally, I discuss why this upcoming crash is an opportunity for investors to reorder the equity market’s priorities to fund sectors that tackle rising societal and environmental challenges.
SSRN
It is uncanny that historically, the large majority of U.S. market crashes have occurred in the month of October. I assert that three key conditions are gathered for this to happen. 1) There is a market-wide or macroeconomic informational ambiguity that has been lingering since before the summer months with high downside risk; 2) that despite this ambiguity, leverage is used to create a bubble and 3) that investors are driven by what I call the “ambiguity-forced-resolution bias.†I apply this reasoning to predict a crash in October 2020. I show that there currently is a bubble in the U.S. using a new indicator. I test that ambiguity/uncertainty was unusually high in months prior October crashes. Finally, I discuss why this upcoming crash is an opportunity for investors to reorder the equity market’s priorities to fund sectors that tackle rising societal and environmental challenges.
Are Women Better Borrowers in Microfinance? A Global Analysis
SSRN
Women are universally considered good microfinance clients. The reason behind this is a popular belief in the microfinance industry that women are better credit risks than men. Female targeting has been suggested to generate higher repayment rates for micro-lenders. Such a belief, however, has not been widely examined, and the very scant research so far only shows mixed results. Moreover, high repayment rates do not always warrant profitability for microfinance institutions (MFIs). An empirical investigation is thus needed to understand not only the nature of gender-repayment relationship, but also the impact of such gender targeting on overall MFI sustainability and profitability. Using a sample of more than 5,400 observations from 42 countries over a period of 14 years, this study examines the effect of female focus on MFI performance. Results suggest that women are indeed better microfinance borrowers as they have significant negative relationship with MFI portfolio at risk. Findings also reveal their positive impact on self-sufficiency and profitability of microfinance organizations. The study results have important implications for microfinance practitioners and policymakers. The paper concludes suggesting some potential avenues for future research.
SSRN
Women are universally considered good microfinance clients. The reason behind this is a popular belief in the microfinance industry that women are better credit risks than men. Female targeting has been suggested to generate higher repayment rates for micro-lenders. Such a belief, however, has not been widely examined, and the very scant research so far only shows mixed results. Moreover, high repayment rates do not always warrant profitability for microfinance institutions (MFIs). An empirical investigation is thus needed to understand not only the nature of gender-repayment relationship, but also the impact of such gender targeting on overall MFI sustainability and profitability. Using a sample of more than 5,400 observations from 42 countries over a period of 14 years, this study examines the effect of female focus on MFI performance. Results suggest that women are indeed better microfinance borrowers as they have significant negative relationship with MFI portfolio at risk. Findings also reveal their positive impact on self-sufficiency and profitability of microfinance organizations. The study results have important implications for microfinance practitioners and policymakers. The paper concludes suggesting some potential avenues for future research.
Banking Euro Area Stress Test Model
SSRN
The Banking Euro Area Stress Test (BEAST) is a large scale semi-structural model developed to assess the resilience of the euro area banking system from a macroprudential perspective. The model combines the dynamics of a high number of euro area banks with that of the euro area economies. It reflects banks’ heterogeneity by replicating the structure of their balance sheets and profit and loss accounts. In the model, banks adjust their assets, interest rates, and profit distribution in line with the economic conditions they face. Bank responses feed back to the macroeconomic environment affecting credit supply conditions. When applied to a stress test of the euro area banking system, the model reveals higher system-wide capital depletion than the analogous constant balance sheet exercise.
SSRN
The Banking Euro Area Stress Test (BEAST) is a large scale semi-structural model developed to assess the resilience of the euro area banking system from a macroprudential perspective. The model combines the dynamics of a high number of euro area banks with that of the euro area economies. It reflects banks’ heterogeneity by replicating the structure of their balance sheets and profit and loss accounts. In the model, banks adjust their assets, interest rates, and profit distribution in line with the economic conditions they face. Bank responses feed back to the macroeconomic environment affecting credit supply conditions. When applied to a stress test of the euro area banking system, the model reveals higher system-wide capital depletion than the analogous constant balance sheet exercise.
Built-In Challenges Within the New Supervisory Architecture of the Eurozone
SSRN
We analyse a sample of systemically important European financial intermediaries that fall under the Single Supervisory Mechanism, which is part of the new institutional supervisory architecture of the Eurozone. Theory suggests that herding among financial intermediaries raises cross-sectional correlations and has negative implications for systemic risk. Empirically, herding behaviors are associated with clusters identifying commonalities in asset allocations and risk strategies. By adopting a novel clustering approach, we analyse whether some pre-determined classifications and criteria associated with this new supervisory framework can adequately capture financial intermediaries’ herding behavior. We find that simple classifications and criteria, which are less likely to be policy-biased, are more efficient than complex ones when it comes to identifying commonalities posing the highest threats to systemic risk. The findings also confirm the need for a macro- rather than micro- prudential approach to financial supervision by highlighting the importance of using a supervisory toolkit that includes indicators with a stronger cross-sectional and network dimension. Our methodology can serve as a final consistency check for quantitative-based classifications and criteria employed by supervisory authorities.
SSRN
We analyse a sample of systemically important European financial intermediaries that fall under the Single Supervisory Mechanism, which is part of the new institutional supervisory architecture of the Eurozone. Theory suggests that herding among financial intermediaries raises cross-sectional correlations and has negative implications for systemic risk. Empirically, herding behaviors are associated with clusters identifying commonalities in asset allocations and risk strategies. By adopting a novel clustering approach, we analyse whether some pre-determined classifications and criteria associated with this new supervisory framework can adequately capture financial intermediaries’ herding behavior. We find that simple classifications and criteria, which are less likely to be policy-biased, are more efficient than complex ones when it comes to identifying commonalities posing the highest threats to systemic risk. The findings also confirm the need for a macro- rather than micro- prudential approach to financial supervision by highlighting the importance of using a supervisory toolkit that includes indicators with a stronger cross-sectional and network dimension. Our methodology can serve as a final consistency check for quantitative-based classifications and criteria employed by supervisory authorities.
CEO-to-Employee Pay Ratio and CEO Diversity
SSRN
The motivation behind Section 953(b) of Dodd-Frank Act was the increasing pay inequality and supposed CEOs’ rent extraction. It required public companies to disclose CEO-to-employee pay ratios. Using the ratios reported by S&P1500 firms in 2017-18, this paper examines whether companies led by women and minority CEOs have lower ratios than those led by white male CEOs. Results indicate that CEO-to-employee pay ratios are 22-28% higher for female CEOs compared to their male counterparts, controlling for other determinants of pay ratios. There is, however, no statistically significant difference between the pay ratios of minority vs. white male CEOs. Minority female CEOs have lower CEO-to-employee pay ratios than white female CEOs. Consistent with literature, larger and more profitable firms have higher CEO-to-employee pay ratios. While prior studies on determinants of CEO-to-employee pay ratios have used either industry-level or self-reported data for a small subset of firms (resulting in selection bias), this paper uses firm-level data that is available for all S&P 1500 firms because of new disclosure requirements due to the Dodd-Frank Act Section 953(b). Moreover, this is the first paper to test whether gender or ethnicity of a CEO affects within-firm pay inequality.
SSRN
The motivation behind Section 953(b) of Dodd-Frank Act was the increasing pay inequality and supposed CEOs’ rent extraction. It required public companies to disclose CEO-to-employee pay ratios. Using the ratios reported by S&P1500 firms in 2017-18, this paper examines whether companies led by women and minority CEOs have lower ratios than those led by white male CEOs. Results indicate that CEO-to-employee pay ratios are 22-28% higher for female CEOs compared to their male counterparts, controlling for other determinants of pay ratios. There is, however, no statistically significant difference between the pay ratios of minority vs. white male CEOs. Minority female CEOs have lower CEO-to-employee pay ratios than white female CEOs. Consistent with literature, larger and more profitable firms have higher CEO-to-employee pay ratios. While prior studies on determinants of CEO-to-employee pay ratios have used either industry-level or self-reported data for a small subset of firms (resulting in selection bias), this paper uses firm-level data that is available for all S&P 1500 firms because of new disclosure requirements due to the Dodd-Frank Act Section 953(b). Moreover, this is the first paper to test whether gender or ethnicity of a CEO affects within-firm pay inequality.
Cash as a Perpetual Option
SSRN
We consider the option value of cash when nominal interest rates are no longer constrained by the zero lower bound. We provide a general valuation principle and solve for the value of cash in semi-closed form under Vasicek (1977) dynamics for the nominal short rate. In the absence of a zero lower bound, cash can have substantial option value and becomes a powerful recessionary hedge. However, a significant fraction of the value derives from the ability to hold cash over an extremely long horizon, and the risk of early redemption decreases the value and hedging performance of cash.
SSRN
We consider the option value of cash when nominal interest rates are no longer constrained by the zero lower bound. We provide a general valuation principle and solve for the value of cash in semi-closed form under Vasicek (1977) dynamics for the nominal short rate. In the absence of a zero lower bound, cash can have substantial option value and becomes a powerful recessionary hedge. However, a significant fraction of the value derives from the ability to hold cash over an extremely long horizon, and the risk of early redemption decreases the value and hedging performance of cash.
Coronavirus (COVID-19) Pandemic, Economic Consequences and Strategies for Ameliorting Macroeconomic Shocks in Nigeria’s Economy
SSRN
This study provides multi-disciplinary assessment of the coronavirus pandemic transmission in Nigeria, magnitude of COVID-19 confirmed cases, recovery, deaths, and inventory of infected person with recovery lags. It applied the statistical outcomes in predicting spilling over to subsequent periods. It identifies economic sectors worst hit by COVID-19 triggered recession, simulate the estimates of potential fiscal and other macroeconomic impact of the pandemic in the country in short run alongside synthesis of restoration and sustainability strategies. Secondary data relating to coronavirus infection cases, spreads, recoveries and fatalities were assessed, using the susceptible-infected-recovered†(SIR) model in absence of mass testing and probable cessation from health crisis management. It identified economic sectors/activities being devastated by COVID-19 induced recession, provides interim estimates adverse impact based on economic peak and down-turn cycle method. The study also measured the magnitude of macroeconomic shocks in Nigeria’s economy using a standard global computable general equilibrium model and exploration of sustainability strategies based on synthesis of extant reports were employed. These data-sets were obtained from the Nigerian sources and partly from global sources. Furthermore, it utilized trend analysis derived from on empirical data of extant daily confirmed cases, discharges and hospitalized person together with tentative projection of additional confirmed cases as from Julyâ€"September, 2020. Results revealed that confirmed cases in Nigeria will increase steadily from 25694 (in June) to around 74825 by the end September and expected to reach 121000 by end of year 2020. This suggests that the pandemic is likely to persist up to the second quarter of 2021. Education, transport (aviation), hospitality, tourism and sports businesses; trade (informal sector) in the services sector; petroleum exploration in mining sub-sector are most severely contracting activities industries in the economy. Given the prevailing intensity of recession, the result indicates that a reduction of about 5-to-7% in GDP will be recorded in 2020. Result of variance analysis of fiscal budget estimates indicates adverse increase of -2% in overall fiscal deficit balances during the periods, which may aggravate debt burden with decline of about -5.7 percent and up to -7 percent in nominal GDP. Health, education, agriculture, petroleum exploration; petroleum refining and petrochemical industries, manufacturing (particularly pharmaceuticals), energy and power generation should be given priority in the sustainability programme.
SSRN
This study provides multi-disciplinary assessment of the coronavirus pandemic transmission in Nigeria, magnitude of COVID-19 confirmed cases, recovery, deaths, and inventory of infected person with recovery lags. It applied the statistical outcomes in predicting spilling over to subsequent periods. It identifies economic sectors worst hit by COVID-19 triggered recession, simulate the estimates of potential fiscal and other macroeconomic impact of the pandemic in the country in short run alongside synthesis of restoration and sustainability strategies. Secondary data relating to coronavirus infection cases, spreads, recoveries and fatalities were assessed, using the susceptible-infected-recovered†(SIR) model in absence of mass testing and probable cessation from health crisis management. It identified economic sectors/activities being devastated by COVID-19 induced recession, provides interim estimates adverse impact based on economic peak and down-turn cycle method. The study also measured the magnitude of macroeconomic shocks in Nigeria’s economy using a standard global computable general equilibrium model and exploration of sustainability strategies based on synthesis of extant reports were employed. These data-sets were obtained from the Nigerian sources and partly from global sources. Furthermore, it utilized trend analysis derived from on empirical data of extant daily confirmed cases, discharges and hospitalized person together with tentative projection of additional confirmed cases as from Julyâ€"September, 2020. Results revealed that confirmed cases in Nigeria will increase steadily from 25694 (in June) to around 74825 by the end September and expected to reach 121000 by end of year 2020. This suggests that the pandemic is likely to persist up to the second quarter of 2021. Education, transport (aviation), hospitality, tourism and sports businesses; trade (informal sector) in the services sector; petroleum exploration in mining sub-sector are most severely contracting activities industries in the economy. Given the prevailing intensity of recession, the result indicates that a reduction of about 5-to-7% in GDP will be recorded in 2020. Result of variance analysis of fiscal budget estimates indicates adverse increase of -2% in overall fiscal deficit balances during the periods, which may aggravate debt burden with decline of about -5.7 percent and up to -7 percent in nominal GDP. Health, education, agriculture, petroleum exploration; petroleum refining and petrochemical industries, manufacturing (particularly pharmaceuticals), energy and power generation should be given priority in the sustainability programme.
Countercyclical Liquidity Policy and Credit Cycles: Evidence from Macroprudential and Monetary Policy in Brazil
SSRN
We show that countercyclical liquidity policy smooths credit supply cycles, with stronger crisis effects. For identification, we exploit the Brazilian supervisory credit register and liquidity policy changes on reserve requirements, that affected banks differentially and have a monetary and prudential purpose. Liquidity policy strongly attenuates both the credit crunch in bad times and high credit supply in booms. Strong economic effects are twice as large during the crisis easing than during the boom tightening. Finally, in crises, liquidity easing: increase less credit supply by more financially constrained banks; and collateral requirements increase substantially, especially by banks providing higher credit supply.
SSRN
We show that countercyclical liquidity policy smooths credit supply cycles, with stronger crisis effects. For identification, we exploit the Brazilian supervisory credit register and liquidity policy changes on reserve requirements, that affected banks differentially and have a monetary and prudential purpose. Liquidity policy strongly attenuates both the credit crunch in bad times and high credit supply in booms. Strong economic effects are twice as large during the crisis easing than during the boom tightening. Finally, in crises, liquidity easing: increase less credit supply by more financially constrained banks; and collateral requirements increase substantially, especially by banks providing higher credit supply.
Credit Demand vs. Supply Channels: Experimental- and Administrative-Based Evidence
SSRN
This paper identifies and quantifies â??for the first timeâ?? the relative importance of borrower (credit demand) versus bank (supply) balance-sheet channels. We submit fictitious applications (varying households' characteristics) to the major Italian online-mortgage platform. In this way
SSRN
This paper identifies and quantifies â??for the first timeâ?? the relative importance of borrower (credit demand) versus bank (supply) balance-sheet channels. We submit fictitious applications (varying households' characteristics) to the major Italian online-mortgage platform. In this way
Data vs Collateral
SSRN
The use of massive amounts of data by large technology firms (big techs) to assess firms’ creditworthiness could reduce the need for collateral in solving asymmetric information problems in credit markets. Using a unique dataset of more than 2 million Chinese firms that received credit from both an important big tech firm (Ant Group) and traditional commercial banks, this paper investigates how different forms of credit correlate with local economic activity, house prices and firm characteristics. We find that big tech credit does not correlate with local business conditions and house prices when controlling for demand factors, but reacts strongly to changes in firm characteristics, such as transaction volumes and network scores used to calculate firm credit ratings. By contrast, both secured and unsecured bank credit react significantly to local house prices, which incorporate useful information on the environment in which clients operate and on their creditworthiness. This evidence implies that a greater use of big tech credit â€" granted on the basis of machine learning and big data â€" could reduce the importance of collateral in credit markets and potentially weaken the financial accelerator mechanism.
SSRN
The use of massive amounts of data by large technology firms (big techs) to assess firms’ creditworthiness could reduce the need for collateral in solving asymmetric information problems in credit markets. Using a unique dataset of more than 2 million Chinese firms that received credit from both an important big tech firm (Ant Group) and traditional commercial banks, this paper investigates how different forms of credit correlate with local economic activity, house prices and firm characteristics. We find that big tech credit does not correlate with local business conditions and house prices when controlling for demand factors, but reacts strongly to changes in firm characteristics, such as transaction volumes and network scores used to calculate firm credit ratings. By contrast, both secured and unsecured bank credit react significantly to local house prices, which incorporate useful information on the environment in which clients operate and on their creditworthiness. This evidence implies that a greater use of big tech credit â€" granted on the basis of machine learning and big data â€" could reduce the importance of collateral in credit markets and potentially weaken the financial accelerator mechanism.
De-risking of Green Investments through a Green Bond Market: Empirics and a Dynamic Model
SSRN
A substantial increase of green investments is still required to reach the Paris Agreement's emission targets. Yet, capital markets to expedite green investments are generically constrained. Literature has shown that governments could de-risk such investments. Empirical beta pricing and yield estimates reveal some public involvement in the green bond market, especially for long maturity bonds. We provide empirical evidence that Governments and Multilateral organizations can de-risk green investments by supporting the issuance of green bonds in contrast to private green bonds - that show higher yields, volatility and beta prices - and conventional energy bonds, that are more volatile due to oil price variations. Since lower betas also mean lower capital costs, we use these empirical results and run a dynamic model with two types of firms, modeling the economic behavior of innovators (renewable energy firms) and incumbents (fossil fuel firms). The simulations of our model show that de-risked interest rates help to phase in renewable energy firms in the market and avoid a sharp debt increase. However, when the new entrants carry negative pay-offs for a longer time, it might not be sufficient to keep the debt low and to avoid a shake-out in the market. Subsidies and carbon taxation can complement the role of the de-risked interest rate and expedite the energy transition.
SSRN
A substantial increase of green investments is still required to reach the Paris Agreement's emission targets. Yet, capital markets to expedite green investments are generically constrained. Literature has shown that governments could de-risk such investments. Empirical beta pricing and yield estimates reveal some public involvement in the green bond market, especially for long maturity bonds. We provide empirical evidence that Governments and Multilateral organizations can de-risk green investments by supporting the issuance of green bonds in contrast to private green bonds - that show higher yields, volatility and beta prices - and conventional energy bonds, that are more volatile due to oil price variations. Since lower betas also mean lower capital costs, we use these empirical results and run a dynamic model with two types of firms, modeling the economic behavior of innovators (renewable energy firms) and incumbents (fossil fuel firms). The simulations of our model show that de-risked interest rates help to phase in renewable energy firms in the market and avoid a sharp debt increase. However, when the new entrants carry negative pay-offs for a longer time, it might not be sufficient to keep the debt low and to avoid a shake-out in the market. Subsidies and carbon taxation can complement the role of the de-risked interest rate and expedite the energy transition.
Distillation of News Flow into Analysis of Stock Reactions
arXiv
arXiv
The gargantuan plethora of opinions, facts and tweets on financial business offers the opportunity to test and analyze the influence of such text sources on future directions of stocks. It also creates though the necessity to distill via statistical technology the informative elements of this prodigious and indeed colossal data source. Using mixed text sources from professional platforms, blog fora and stock message boards we distill via different lexica sentiment variables. These are employed for an analysis of stock reactions: volatility, volume and returns. An increased sentiment, especially for those with negative prospection, will influence volatility as well as volume. This influence is contingent on the lexical projection and different across Global Industry Classification Standard (GICS) sectors. Based on review articles on 100 S&P 500 constituents for the period of October 20, 2009, to October 13, 2014, we project into BL, MPQA, LM lexica and use the distilled sentiment variables to forecast individual stock indicators in a panel context. Exploiting different lexical projections to test different stock reaction indicators we aim at answering the following research questions: (i) Are the lexica consistent in their analytic ability? (ii) To which degree is there an asymmetric response given the sentiment scales (positive v.s. negative)? (iii) Are the news of high attention firms diffusing faster and result in more timely and efficient stock reaction? (iv) Is there a sector-specific reaction from the distilled sentiment measures? We find there is significant incremental information in the distilled news flow and the sentiment effect is characterized as an asymmetric, attention-specific and sector-specific response of stock reactions.
Do Investors Rely on Robots? Evidence from an Experimental Study
SSRN
Robo advice has moved its first steps in the Anglo-Saxon countries and is now rapidly gaining market share at a global level. The phenomenon fuelled a growing and still not conclusive institutional debate about potential benefits and risks to financial consumers, based also on investors’ biases and behaviours that online platforms could trigger to the detriment of robo advisees. The present paper provides some insights into attitudes and behaviours that might prevail in a digital environment among young investors, representing the category of users potentially more involved by the development of the automated advice. In detail, the study investigates whether individuals’ propensity to follow the recommendation received from an advisor changes depending on whether the advisor is a human or a robot. The analysis is based on data collected through an ad hoc developed laboratory experiment run in the Cesare Lab of LUISS University with a sample of 180 students. Students were given an initial monetary endowment and were asked to choose between six different portfolios of financial activities; after being profiled through a questionnaire aimed at eliciting their risk tolerance (Grable and Lytton’s Risk Tolerance Quiz; 2003), they received the advice, either from a human advisor or from a robo advisor (i.e. via a computer platform) depending on the treatment they had randomly assigned before entering the experimental session. Then, they were asked again to choose among the six portfolios in order to capture whether the propensity to follow the recommendation depends on its source (human versus robo). Finally, participants were asked to answer several questions eliciting risk preferences, financial literacy (actual and perceived) and digital literacy, serving as control variables when modelling the probability to follow the advice.Our results show that the probability to follow the advice does not depend on the source of the recommendation but rather on the alignment between the self-directed choice made before receiving the advice and the recommendation subsequently received: the propensity to follow the advisor (either human or robo) increases if the advice confirms individual’s own beliefs about her/his investor profile. This result might be explained by referring to individuals’ attitude towards the so called ‘confirmation bias’. However, when the self-directed choice differs from the recommendation received, participants may be more likely to follow the advice given by a human advisor and less likely to follow the advice formulated by an algorithm. Also the gender of the advisor seems to matter: women tend to follow the advice provided by a female advisor more frequently compared to the case of the recommendation given by a male advisor. This work is part of a wider research on FinTech that CONSOB started in 2016, in collaboration with several Italian universities, with the aim of exploring opportunities and risks for investor protection and the financial system as a whole, related to the application of technological innovation to the provision of financial services. In particular, supplementing Lener, Linciano and Soccorso (2019, edited by) and Caratelli et al. (2019), this document widens the field of investigation by referring to a specific target of the population - the so called millennials and post-millennials â€" and using complementary and innovative methods. According to an evidence-based approach, insights from the present study may suggest specific investor protection initiatives, also in terms of financial education activities designed for a clearly-identified segment of the population (the so called millennials and post-millennials, in this case).Evidence from the present work might be extended further with respect to the consumers’ perception of the fairness of algorithms used to provide financial services, the cognitive heuristics and biases underlying decision making process and investments in the digital environment and nudges which may be used to enhance investor protection.
SSRN
Robo advice has moved its first steps in the Anglo-Saxon countries and is now rapidly gaining market share at a global level. The phenomenon fuelled a growing and still not conclusive institutional debate about potential benefits and risks to financial consumers, based also on investors’ biases and behaviours that online platforms could trigger to the detriment of robo advisees. The present paper provides some insights into attitudes and behaviours that might prevail in a digital environment among young investors, representing the category of users potentially more involved by the development of the automated advice. In detail, the study investigates whether individuals’ propensity to follow the recommendation received from an advisor changes depending on whether the advisor is a human or a robot. The analysis is based on data collected through an ad hoc developed laboratory experiment run in the Cesare Lab of LUISS University with a sample of 180 students. Students were given an initial monetary endowment and were asked to choose between six different portfolios of financial activities; after being profiled through a questionnaire aimed at eliciting their risk tolerance (Grable and Lytton’s Risk Tolerance Quiz; 2003), they received the advice, either from a human advisor or from a robo advisor (i.e. via a computer platform) depending on the treatment they had randomly assigned before entering the experimental session. Then, they were asked again to choose among the six portfolios in order to capture whether the propensity to follow the recommendation depends on its source (human versus robo). Finally, participants were asked to answer several questions eliciting risk preferences, financial literacy (actual and perceived) and digital literacy, serving as control variables when modelling the probability to follow the advice.Our results show that the probability to follow the advice does not depend on the source of the recommendation but rather on the alignment between the self-directed choice made before receiving the advice and the recommendation subsequently received: the propensity to follow the advisor (either human or robo) increases if the advice confirms individual’s own beliefs about her/his investor profile. This result might be explained by referring to individuals’ attitude towards the so called ‘confirmation bias’. However, when the self-directed choice differs from the recommendation received, participants may be more likely to follow the advice given by a human advisor and less likely to follow the advice formulated by an algorithm. Also the gender of the advisor seems to matter: women tend to follow the advice provided by a female advisor more frequently compared to the case of the recommendation given by a male advisor. This work is part of a wider research on FinTech that CONSOB started in 2016, in collaboration with several Italian universities, with the aim of exploring opportunities and risks for investor protection and the financial system as a whole, related to the application of technological innovation to the provision of financial services. In particular, supplementing Lener, Linciano and Soccorso (2019, edited by) and Caratelli et al. (2019), this document widens the field of investigation by referring to a specific target of the population - the so called millennials and post-millennials â€" and using complementary and innovative methods. According to an evidence-based approach, insights from the present study may suggest specific investor protection initiatives, also in terms of financial education activities designed for a clearly-identified segment of the population (the so called millennials and post-millennials, in this case).Evidence from the present work might be extended further with respect to the consumers’ perception of the fairness of algorithms used to provide financial services, the cognitive heuristics and biases underlying decision making process and investments in the digital environment and nudges which may be used to enhance investor protection.
Dynamic Indexing and Allocation: Do they Dominate Simple Static Indexing?
SSRN
Andrew Lo in his book, Adaptive Markets, advocates an investment product that he names a “dynamic index.†He has facilitated the operation of a variant of this dynamic indexation, “dynamic allocation,†by founding a company, AlphaSimplex. Another dynamic investment is GMO’s Benchmark Free Allocation fund. We assess the role for dynamic investing with the AlphaSimplex funds and the GMO fund. The dynamic funds have higher expense ratios and turnover than static index funds do. Do the strategies of these funds add value, and if so is dynamic investing magical enough to overcome these hurdles? Do dynamic investments dominate a simple portfolio of static index funds with similar style rebalanced regularly whether risk adjusted or not and with or without differential expenses stripped away? We also clarify the interpretation of the Fama-French multi-factor models, generalize them, and discover the equivalence between the Fama-French and Sharpe (1992) approaches to mutual fund assessment. On average AphaSimplex funds underreturn portfolios of Vanguard index funds with the same style by 2.54 % age points per year. Some of that is because of expense ratios. Gross of expense ratios the average underreturn is 1.51 % age points/year.
SSRN
Andrew Lo in his book, Adaptive Markets, advocates an investment product that he names a “dynamic index.†He has facilitated the operation of a variant of this dynamic indexation, “dynamic allocation,†by founding a company, AlphaSimplex. Another dynamic investment is GMO’s Benchmark Free Allocation fund. We assess the role for dynamic investing with the AlphaSimplex funds and the GMO fund. The dynamic funds have higher expense ratios and turnover than static index funds do. Do the strategies of these funds add value, and if so is dynamic investing magical enough to overcome these hurdles? Do dynamic investments dominate a simple portfolio of static index funds with similar style rebalanced regularly whether risk adjusted or not and with or without differential expenses stripped away? We also clarify the interpretation of the Fama-French multi-factor models, generalize them, and discover the equivalence between the Fama-French and Sharpe (1992) approaches to mutual fund assessment. On average AphaSimplex funds underreturn portfolios of Vanguard index funds with the same style by 2.54 % age points per year. Some of that is because of expense ratios. Gross of expense ratios the average underreturn is 1.51 % age points/year.
ESG Investing in Fixed Income: It's Time to Cross the Rubicon
SSRN
This research is the companion study of three previous research projects conducted at Amundi that address the issue of ESG (Berg et al., 2014; Bennani et al., 2018; Drei et al., 2019). These studies, which were focused on the stock market, showed that 2014 marks a turning point for ESG screening and the performance of active and passive management in developed equities. Indeed, ESG investing tended to penalize both passive and active investors between 2010 and 2013. Contrastingly, ESG investing has been a source of outperformance since 2014 in Europe and North America. Moreover, it appears that ESG investing and factor investing are increasingly connected. In particular, Bennani et al. (2018) and Drei et al. (2019) concluded that ESG is a new risk factor in the Eurozone. The case of fixed income is particular since it has been little studied by academics and professionals. It is true that implementing an ESG investment policy in the bond market is less obvious than in the stock market. For example, in the case of sovereign bonds using ESG filters may dramatically change the profile of the bond portfolio, particularly in terms of liquidity. In fact, it seems that ESG investors pursue two different goals when they consider equities and bonds. They invest in stocks with good ESG ratings in order to avoid extra-financial longterm risks, whereas they consider that fixed income is the field of impact investing. This explains the high demand for green and social bonds, and this also explains why ESG screening is less widely implemented infixed income markets than in equity markets.The objective of this new study is to explore the impact of ESG investing on asset pricing in the corporate bond market. For that, we apply the methodologies that have been used by Bennani et al. (2018) for testing ESG screening in active and passive management. In particular, we consider the sorted portfolio approach of Fama and French (1992), and the index optimization method that consists in minimizing the active risk with respect to the benchmark while controlling for the ESG excess score. Three investment universes are analyzed: euro-denominated investment grade bonds, dollar-denominated investment grade bonds, and high-yield bonds. Results differ from one universe to another. In the case of EUR IG bonds, we retrieve some common patterns observed by Bennani et al. (2018) in the case of equities. Indeed, from 2010 to 2013, ESG screening has produced a negative alpha, whereas we observe an outperformance since 2014 when we implement ESG scoring in active and passive management. In the case of USD IG bonds, the results are disappointing since ESG screening produces negative alpha for the entire period. Results on high-yield bonds are difficult to interpret since ESG coverage of this market is not satisfactory.We also test how ESG has impacted the cost of corporate debt. Our results show that there is a positive correlation between ESG and credit ratings. This is normal since credit rating agencies also incorporate extra-financial risks in their default risk models. Using the approach developed by Crifo et al. (2017), we propose an integrated credit-ESG model in order to understand the marginal effects of ESG on the cost of capital. We find that there is a negative relationship between ESG scores and yield spreads. The better the ESG rating, the lower the yield spread. For instance, we estimate that the cost of capital difference is equal to 31 bps between a worst-in-class corporate and a best-in-class corporate in the case of EUR IG corporate bonds. In the case of USD IG corporate bonds, the difference is lower but remains significant at 15 bps. Moreover, the impact of ESG is more pronounced for some sectors, for instance Banking and Utility & Energy. These results are important because ESG investing and ESG financing are two sides of the same coin. In order to tackle environmental and social issues, ESG must be a winning bet for both investors and issuers.
SSRN
This research is the companion study of three previous research projects conducted at Amundi that address the issue of ESG (Berg et al., 2014; Bennani et al., 2018; Drei et al., 2019). These studies, which were focused on the stock market, showed that 2014 marks a turning point for ESG screening and the performance of active and passive management in developed equities. Indeed, ESG investing tended to penalize both passive and active investors between 2010 and 2013. Contrastingly, ESG investing has been a source of outperformance since 2014 in Europe and North America. Moreover, it appears that ESG investing and factor investing are increasingly connected. In particular, Bennani et al. (2018) and Drei et al. (2019) concluded that ESG is a new risk factor in the Eurozone. The case of fixed income is particular since it has been little studied by academics and professionals. It is true that implementing an ESG investment policy in the bond market is less obvious than in the stock market. For example, in the case of sovereign bonds using ESG filters may dramatically change the profile of the bond portfolio, particularly in terms of liquidity. In fact, it seems that ESG investors pursue two different goals when they consider equities and bonds. They invest in stocks with good ESG ratings in order to avoid extra-financial longterm risks, whereas they consider that fixed income is the field of impact investing. This explains the high demand for green and social bonds, and this also explains why ESG screening is less widely implemented infixed income markets than in equity markets.The objective of this new study is to explore the impact of ESG investing on asset pricing in the corporate bond market. For that, we apply the methodologies that have been used by Bennani et al. (2018) for testing ESG screening in active and passive management. In particular, we consider the sorted portfolio approach of Fama and French (1992), and the index optimization method that consists in minimizing the active risk with respect to the benchmark while controlling for the ESG excess score. Three investment universes are analyzed: euro-denominated investment grade bonds, dollar-denominated investment grade bonds, and high-yield bonds. Results differ from one universe to another. In the case of EUR IG bonds, we retrieve some common patterns observed by Bennani et al. (2018) in the case of equities. Indeed, from 2010 to 2013, ESG screening has produced a negative alpha, whereas we observe an outperformance since 2014 when we implement ESG scoring in active and passive management. In the case of USD IG bonds, the results are disappointing since ESG screening produces negative alpha for the entire period. Results on high-yield bonds are difficult to interpret since ESG coverage of this market is not satisfactory.We also test how ESG has impacted the cost of corporate debt. Our results show that there is a positive correlation between ESG and credit ratings. This is normal since credit rating agencies also incorporate extra-financial risks in their default risk models. Using the approach developed by Crifo et al. (2017), we propose an integrated credit-ESG model in order to understand the marginal effects of ESG on the cost of capital. We find that there is a negative relationship between ESG scores and yield spreads. The better the ESG rating, the lower the yield spread. For instance, we estimate that the cost of capital difference is equal to 31 bps between a worst-in-class corporate and a best-in-class corporate in the case of EUR IG corporate bonds. In the case of USD IG corporate bonds, the difference is lower but remains significant at 15 bps. Moreover, the impact of ESG is more pronounced for some sectors, for instance Banking and Utility & Energy. These results are important because ESG investing and ESG financing are two sides of the same coin. In order to tackle environmental and social issues, ESG must be a winning bet for both investors and issuers.
Exchange Rate Prediction with Machine Learning and a Smart Carry Trade Portfolio
SSRN
We establish the out-of-sample predictability of monthly exchange rate changes via
SSRN
We establish the out-of-sample predictability of monthly exchange rate changes via
Financing Ventures
SSRN
The relationship between venture capital and growth is examined using an endogenous growth model incorporating dynamic contracts between entrepreneurs and venture capitalists. At each stage of financing, venture capitalists evaluate the viability of startups. If viable, venture capitalists provide funding for the next stage. The success of a project depends on the amount of funding. The model is confronted with stylized facts about venture capital: viz., statistics for each round of funding that concern the success rates, failure rates, investment rates, equity shares, and IPO values. Counterfactual experiments suggest that long-term U.S. growth would drop from 1.8 percent to 1.4-1.5 percent if venture capital were replaced by more traditional methods of finance. Likewise, it would drop from 1.8 percent to 1.62 percent if VC-funded startups in the United States are taxed at the German rate. The welfare losses associated with these declines in long-term growth rates are large.
SSRN
The relationship between venture capital and growth is examined using an endogenous growth model incorporating dynamic contracts between entrepreneurs and venture capitalists. At each stage of financing, venture capitalists evaluate the viability of startups. If viable, venture capitalists provide funding for the next stage. The success of a project depends on the amount of funding. The model is confronted with stylized facts about venture capital: viz., statistics for each round of funding that concern the success rates, failure rates, investment rates, equity shares, and IPO values. Counterfactual experiments suggest that long-term U.S. growth would drop from 1.8 percent to 1.4-1.5 percent if venture capital were replaced by more traditional methods of finance. Likewise, it would drop from 1.8 percent to 1.62 percent if VC-funded startups in the United States are taxed at the German rate. The welfare losses associated with these declines in long-term growth rates are large.
Forward Looking Loan Provisions: Credit Supply and Risk-Taking
SSRN
We show corporate-level real, financial, and (bank) risk-taking effects associated with calculating loan provisions based on expected-rather than incurred-credit losses. For identification, we exploit unique features of a Colombian reform and supervisory, matched loan-level data. Theregulatory change induces a dramatic increase in provisions. Banks tighten all new lending conditions, adversely affecting borrowing-firms, with stronger effects for risky-firms. Moreover, to minimize provisioning, more affected (less-capitalized) banks cut credit supply to risky-firms-SMEs with shorter credit history, less tangible assets or more defaulted loans-but engage in "search-for-yield" within regulatory constraints and increase portfolio concentration, thereby decreasing risk diversification.
SSRN
We show corporate-level real, financial, and (bank) risk-taking effects associated with calculating loan provisions based on expected-rather than incurred-credit losses. For identification, we exploit unique features of a Colombian reform and supervisory, matched loan-level data. Theregulatory change induces a dramatic increase in provisions. Banks tighten all new lending conditions, adversely affecting borrowing-firms, with stronger effects for risky-firms. Moreover, to minimize provisioning, more affected (less-capitalized) banks cut credit supply to risky-firms-SMEs with shorter credit history, less tangible assets or more defaulted loans-but engage in "search-for-yield" within regulatory constraints and increase portfolio concentration, thereby decreasing risk diversification.
Global Liquidity and Impairment of Local Monetary Policy
SSRN
We show that global liquidity limits the effectiveness of local monetary policy on credit markets. The mechanism is via a bank carry trade in international markets when local monetary policy tightens. For identification, we exploit global (VIX, U.S. monetary policy) shocks and loan-level data -the credit and international interbank registers- from a large emerging market, Turkey. Softer global liquidity conditions attenuate the pass-through of local monetary policy tightening on loan rates, especially for banks with more access to international wholesale markets. Effects are also important for other credit margins and for risk-taking, e.g. riskier borrowers in FX loans or defaults.
SSRN
We show that global liquidity limits the effectiveness of local monetary policy on credit markets. The mechanism is via a bank carry trade in international markets when local monetary policy tightens. For identification, we exploit global (VIX, U.S. monetary policy) shocks and loan-level data -the credit and international interbank registers- from a large emerging market, Turkey. Softer global liquidity conditions attenuate the pass-through of local monetary policy tightening on loan rates, especially for banks with more access to international wholesale markets. Effects are also important for other credit margins and for risk-taking, e.g. riskier borrowers in FX loans or defaults.
Information Demand during the COVID-19 Pandemic
SSRN
We investigate whether the extraordinary rise in the participation of retail investors in equity markets during the COVID-19 pandemic, increases the demand for information. Using Google search data for individual stocks, we show that contrary to expectations, investor search for information is substantially lower during the pandemic. Exploiting variation in lockdown policies across U.S. states, we are able to interpret our results in causal terms. We also document that information demand around earnings drops dramatically during the pandemic, consistent with the demand for information being lower. Our results have important consequences for information diffusion, price discovery and market efficiency under extreme uncertainty. We discuss possible explanations for these puzzling results.
SSRN
We investigate whether the extraordinary rise in the participation of retail investors in equity markets during the COVID-19 pandemic, increases the demand for information. Using Google search data for individual stocks, we show that contrary to expectations, investor search for information is substantially lower during the pandemic. Exploiting variation in lockdown policies across U.S. states, we are able to interpret our results in causal terms. We also document that information demand around earnings drops dramatically during the pandemic, consistent with the demand for information being lower. Our results have important consequences for information diffusion, price discovery and market efficiency under extreme uncertainty. We discuss possible explanations for these puzzling results.
Long-Term Institutional Trades and the Cross-Section of Returns
SSRN
I investigate the relation between long-term institutional trades and future returns, and find that the cumulative number of shares purchased in net by financial institutions over the prior ten quarters is negatively related to future returns. A long-short portfolio constructed on this measure earns an annualized average Carhart alpha of 9.9%. Overall, I find that long-term institutional trades contain information about future returns that is not already captured by existing short-term institutional trades measures.
SSRN
I investigate the relation between long-term institutional trades and future returns, and find that the cumulative number of shares purchased in net by financial institutions over the prior ten quarters is negatively related to future returns. A long-short portfolio constructed on this measure earns an annualized average Carhart alpha of 9.9%. Overall, I find that long-term institutional trades contain information about future returns that is not already captured by existing short-term institutional trades measures.
Low Interest Rates, Policy, and the Predictive Content of the Yield Curve
SSRN
Does the yield curve’s ability to predict future output and recessions differ when interest rates are low, as in the current global environment? In this paper we build on recent econometric work by Shi, Phillips, and Hurn that detects changes in the causal impact of the yield curve and relate that to the level of interest rates. We explore the issue using historical data going back to the 19th century for the United States and more recent data for the United Kingdom, Germany, and Japan. This paper is similar in spirit to Ramey and Zubairy (2018), who look at the government spending multiplier in times of low interest rates.
SSRN
Does the yield curve’s ability to predict future output and recessions differ when interest rates are low, as in the current global environment? In this paper we build on recent econometric work by Shi, Phillips, and Hurn that detects changes in the causal impact of the yield curve and relate that to the level of interest rates. We explore the issue using historical data going back to the 19th century for the United States and more recent data for the United Kingdom, Germany, and Japan. This paper is similar in spirit to Ramey and Zubairy (2018), who look at the government spending multiplier in times of low interest rates.
Macroprudential Policy, Mortgage Cycles and Distributional Effects: Evidence from the UK
SSRN
Macroprudential regulators worldwide have introduced regulations to limit household leverage in light of existing evidence which suggests that high leverage is associated with household distress during crisis. We analyse the distributional effects of such a macroprudential policy on mortgage and house price cycles. For identification, we exploit the universe of UK mortgages and a 15%-limit imposed in 2014 on lenders-not households-for high loan-to-income ratio (LTI) mortgages. Despite some regulatory arbitrage (e.g. increases in LTV and average loan size), more-constrained lenders issue fewer high-LTI mortgages. Partial substitution by less-constrained lenders leads to overall credit
SSRN
Macroprudential regulators worldwide have introduced regulations to limit household leverage in light of existing evidence which suggests that high leverage is associated with household distress during crisis. We analyse the distributional effects of such a macroprudential policy on mortgage and house price cycles. For identification, we exploit the universe of UK mortgages and a 15%-limit imposed in 2014 on lenders-not households-for high loan-to-income ratio (LTI) mortgages. Despite some regulatory arbitrage (e.g. increases in LTV and average loan size), more-constrained lenders issue fewer high-LTI mortgages. Partial substitution by less-constrained lenders leads to overall credit
Market Fragmentation and Contagion
SSRN
We study the transmission of liquidity shocks from one sector of the economy to other sectors in a general equilibrium model with multiple trading venues connected by profit-seeking arbitrageurs. Arbitrageurs effectively provide liquidity to investors by inter-mediating trades between venues. The welfare impact on venue k of a liquidity shock on venue l can go in either direction, depending on whether inter-mediated trades on k behave as complements or substitutes for such trades on l. In addition to this direct effect through the arbitrage network, there is a feedback effect of an adverse shock reducing liquidity and arbitrageur profits, which leads to a lower level of inter-mediation, further reducing liquidity. We illustrate this contagion with examples of high-frequency trading in equity markets, shocks to one tranche of a collateralized debt obligation impacting investors in the other tranches, carry trade crashes, shocks to cross-country bank lending following the global financial crisis, and the bursting of the Japanese bubble in the early 1990s.
SSRN
We study the transmission of liquidity shocks from one sector of the economy to other sectors in a general equilibrium model with multiple trading venues connected by profit-seeking arbitrageurs. Arbitrageurs effectively provide liquidity to investors by inter-mediating trades between venues. The welfare impact on venue k of a liquidity shock on venue l can go in either direction, depending on whether inter-mediated trades on k behave as complements or substitutes for such trades on l. In addition to this direct effect through the arbitrage network, there is a feedback effect of an adverse shock reducing liquidity and arbitrageur profits, which leads to a lower level of inter-mediation, further reducing liquidity. We illustrate this contagion with examples of high-frequency trading in equity markets, shocks to one tranche of a collateralized debt obligation impacting investors in the other tranches, carry trade crashes, shocks to cross-country bank lending following the global financial crisis, and the bursting of the Japanese bubble in the early 1990s.
Measuring and Managing Carbon Risk in Investment Portfolios
SSRN
This article studies the impact of carbon risk on stock pricing. To address this, we consider the seminal approach of Görgen et al. (2019), who proposed estimating the carbon financial risk of equities by their carbon beta. To achieve this, the primary task is to develop a brown-minus-green (or BMG) risk factor, similar to Fama and French (1992). Secondly, we must estimate the carbon beta using a multi-factor model. While Görgen et al. (2019) considered that the carbon beta is constant, we propose a time-varying estimation model to assess the dynamics of the carbon risk. Moreover, we test several specifications of the BMG factor to understand which climate change-related dimensions are priced in by the stock market. In the second part of the article, we focus on the carbon risk management of investment portfolios. First, we analyze how carbon risk impacts the construction of a minimum variance portfolio. As the goal of this portfolio is to reduce unrewarded financial risks of an investment, incorporating the carbon risk into this approach fulfills this objective. Second, we propose a new framework for building enhanced index portfolios with a lower exposure to carbon risk than capitalization-weighted stock indices. Finally, we explore how carbon sensitivities can improve the robustness of factor investing portfolios.
SSRN
This article studies the impact of carbon risk on stock pricing. To address this, we consider the seminal approach of Görgen et al. (2019), who proposed estimating the carbon financial risk of equities by their carbon beta. To achieve this, the primary task is to develop a brown-minus-green (or BMG) risk factor, similar to Fama and French (1992). Secondly, we must estimate the carbon beta using a multi-factor model. While Görgen et al. (2019) considered that the carbon beta is constant, we propose a time-varying estimation model to assess the dynamics of the carbon risk. Moreover, we test several specifications of the BMG factor to understand which climate change-related dimensions are priced in by the stock market. In the second part of the article, we focus on the carbon risk management of investment portfolios. First, we analyze how carbon risk impacts the construction of a minimum variance portfolio. As the goal of this portfolio is to reduce unrewarded financial risks of an investment, incorporating the carbon risk into this approach fulfills this objective. Second, we propose a new framework for building enhanced index portfolios with a lower exposure to carbon risk than capitalization-weighted stock indices. Finally, we explore how carbon sensitivities can improve the robustness of factor investing portfolios.
Media Capture by Banks
SSRN
Do banks exploit lending relationships with media companies to promote favorable news coverage? To test this hypothesis we map the connections between banks and the top newspapers in several European countries and study how they affect news coverage of two important financial issues. First we look at bank earnings announcements and find that newspapers are significantly more likely to cover announcements by their lenders, relative to other banks, when they report profits than when they report losses. Such pro-lender bias applies to both general-interest and financial newspapers, and is stronger for newspapers and banks that are more financially vulnerable. Second, we look at a broader public interest issue: the Eurozone Sovereign Debt Crisis. We find that newspapers connected to banks more exposed to stressed sovereign bonds are more likely to promote a narrative of the crisis favorable to banks and to oppose debt-restructuring measures detrimental to creditors.
SSRN
Do banks exploit lending relationships with media companies to promote favorable news coverage? To test this hypothesis we map the connections between banks and the top newspapers in several European countries and study how they affect news coverage of two important financial issues. First we look at bank earnings announcements and find that newspapers are significantly more likely to cover announcements by their lenders, relative to other banks, when they report profits than when they report losses. Such pro-lender bias applies to both general-interest and financial newspapers, and is stronger for newspapers and banks that are more financially vulnerable. Second, we look at a broader public interest issue: the Eurozone Sovereign Debt Crisis. We find that newspapers connected to banks more exposed to stressed sovereign bonds are more likely to promote a narrative of the crisis favorable to banks and to oppose debt-restructuring measures detrimental to creditors.
Monetary Policy Surprises and Exchange Rate Behavior
SSRN
Central banks unexpectedly tightening policy rates often observe the exchange value
SSRN
Central banks unexpectedly tightening policy rates often observe the exchange value
No-Arbitrage Priors, Drifting Volatilities, and the Term Structure of Interest Rates
SSRN
We derive a Bayesian prior from a no-arbitrage affine term structure model and use it to estimate the coefficients of a vector autoregression of a panel of government bond yields, specifying a common time-varying volatility for the disturbances. Results based on US data show that this method improves the precision of both point and density forecasts of the term structure of government bond yields, compared to a fully fledged term structure model with time-varying volatility and to a no-change random walk forecast. Further analysis reveals that the approach might work better than an exact term structure model because it relaxes the requirements that yields obey a strict factor structure and that the factors follow a Markov process. Instead, the cross-equation no-arbitrage restrictions on the factor loadings play a marginal role in producing forecasting gains.
SSRN
We derive a Bayesian prior from a no-arbitrage affine term structure model and use it to estimate the coefficients of a vector autoregression of a panel of government bond yields, specifying a common time-varying volatility for the disturbances. Results based on US data show that this method improves the precision of both point and density forecasts of the term structure of government bond yields, compared to a fully fledged term structure model with time-varying volatility and to a no-change random walk forecast. Further analysis reveals that the approach might work better than an exact term structure model because it relaxes the requirements that yields obey a strict factor structure and that the factors follow a Markov process. Instead, the cross-equation no-arbitrage restrictions on the factor loadings play a marginal role in producing forecasting gains.
Outside Investor Access to Top Management: Market Monitoring vs. Stock Price Manipulation
SSRN
This paper studies the role of voluntary disclosure in crowding out independent research about firm value. In the model, when inside firm owners make it easier for outside investors to obtain inexpensive biased information from the manager, then investors rely less on costly unbiased research. Managers are tempted to manipulate the firm stock price more, as a result, but investors are better informed because they anticipate manager manipulation. An increase in stock-price informativeness therefore has to be traded off against an increase in resources wasted on manipulation. It is shown that, surprisingly, firm owners grant investors more access to managers that manipulate more strongly. An implication is that the firm cost of capital is negatively related to manager manipulation.
SSRN
This paper studies the role of voluntary disclosure in crowding out independent research about firm value. In the model, when inside firm owners make it easier for outside investors to obtain inexpensive biased information from the manager, then investors rely less on costly unbiased research. Managers are tempted to manipulate the firm stock price more, as a result, but investors are better informed because they anticipate manager manipulation. An increase in stock-price informativeness therefore has to be traded off against an increase in resources wasted on manipulation. It is shown that, surprisingly, firm owners grant investors more access to managers that manipulate more strongly. An implication is that the firm cost of capital is negatively related to manager manipulation.
Portfolio Inventory Risk of Liquidity Providers: Frictions and Market Fragility
SSRN
We investigate, for today’s limit order book equity markets, how trading, liquidity provision, and the overall market quality in one security are influenced by the inventory risk exposure of liquidity providers to other securities in their portfolios. We show that the trading of these voluntary liquidity providers is strongly conditioned by the risk of their correlated risk exposures in other stocks as predicted by Ho and Stoll (1983). Further, our results are consistent with large and correlated portfolio inventories not only worsening different measures of market quality â€" including bid-ask spreads and pricing errors â€" but also increasing the number and likelihood of extreme price movements and transitory jumps in stock returns. We accordingly highlight a significant but often overlooked source of market frictions, contagion, and fragility.
SSRN
We investigate, for today’s limit order book equity markets, how trading, liquidity provision, and the overall market quality in one security are influenced by the inventory risk exposure of liquidity providers to other securities in their portfolios. We show that the trading of these voluntary liquidity providers is strongly conditioned by the risk of their correlated risk exposures in other stocks as predicted by Ho and Stoll (1983). Further, our results are consistent with large and correlated portfolio inventories not only worsening different measures of market quality â€" including bid-ask spreads and pricing errors â€" but also increasing the number and likelihood of extreme price movements and transitory jumps in stock returns. We accordingly highlight a significant but often overlooked source of market frictions, contagion, and fragility.
Production and Financial Networks in Interplay: Crisis Evidence from Supplier-Customer and Credit Registers
SSRN
We show that bank shocks originating in the financial sector propagate upstream and downstream along the production network and triple the impact of direct bank shocks. Our identification relies on the universe of both supplier-customer transactions and bank loans in Spain, a standard operationalization of credit-supply shocks during the 2008-09 global crisis, and the proposed theoretical framework. The impact on real effects is strong, and similarly so, when considering: (i) direct bank shocks to firms versus first-order interim contagion; (ii) first-order versus higher-order network effects; (iii) downstream versus upstream propagation; (iv) firm-specific versus economy-wide shocks. Market concentration amplifies these effects.
SSRN
We show that bank shocks originating in the financial sector propagate upstream and downstream along the production network and triple the impact of direct bank shocks. Our identification relies on the universe of both supplier-customer transactions and bank loans in Spain, a standard operationalization of credit-supply shocks during the 2008-09 global crisis, and the proposed theoretical framework. The impact on real effects is strong, and similarly so, when considering: (i) direct bank shocks to firms versus first-order interim contagion; (ii) first-order versus higher-order network effects; (iii) downstream versus upstream propagation; (iv) firm-specific versus economy-wide shocks. Market concentration amplifies these effects.
Prospect Theory and Currency Returns: Empirical Evidence
SSRN
We empirically investigate the role of prospect theory in the foreign exchange
SSRN
We empirically investigate the role of prospect theory in the foreign exchange
Risk-Sharing and the Creation of Systemic Risk
SSRN
We address the paradox that financial innovations aimed at risk-sharing appear to have made the world riskier. Financial innovations facilitate hedging idiosyncratic risks among agents; however, aggregate risks can be hedged only with liquid assets. When risk-sharing is primitive, agents selfhedge and hold more liquid assets; this buffers aggregate risks, resulting in few correlated failures compared to when there is greater risk sharing. We apply this insight to build a model of a clearinghouse to show that as risk-sharing improves, aggregate liquidity falls but correlated failures rise. Public liquidity injections, for example, in the form of a lender-of-last-resort can reduce this systemic risk ex post, but induce lower ex-ante levels of private liquidity, which can in turn aggravate welfare costs from such injections.
SSRN
We address the paradox that financial innovations aimed at risk-sharing appear to have made the world riskier. Financial innovations facilitate hedging idiosyncratic risks among agents; however, aggregate risks can be hedged only with liquid assets. When risk-sharing is primitive, agents selfhedge and hold more liquid assets; this buffers aggregate risks, resulting in few correlated failures compared to when there is greater risk sharing. We apply this insight to build a model of a clearinghouse to show that as risk-sharing improves, aggregate liquidity falls but correlated failures rise. Public liquidity injections, for example, in the form of a lender-of-last-resort can reduce this systemic risk ex post, but induce lower ex-ante levels of private liquidity, which can in turn aggravate welfare costs from such injections.
Stablecoins: Implications for Monetary Policy, Financial Stability, Market Infrastructure and Payments, and Banking Supervision in the Euro Area
SSRN
This paper summarises the outcome of an analysis of stablecoins undertaken by the ECB Crypto-Assets Task Force. At the time of writing, the stablecoin debate lacks a common taxonomy and unambiguous terminology. This paper applies a definition that distinguishes stablecoins from existing forms of currencies â€" regardless of the technology used â€" and characterises stablecoin arrangements based on the functions they fulfil. This approach emphasises the role of technology-neutral regulation in preventing arbitrage, as well as comprehensive Eurosystem oversight, irrespective of stablecoins’ regulatory status. Against this background, this paper assesses stablecoins’ implications for the euro area based on three scenarios for the uptake of stablecoins: (i) as a crypto-assets accessory function; (ii) as a new payment method; and (iii) as an alternative store of value. While the first scenario is merely the continuation of the current state of the market and, thus far, has not posed concerns for the financial sector and/or central bank tasks, stablecoins of the type envisaged in the second scenario may reach a scale such that financial stability risks can become material, and the safety and efficiency of the payment system may be affected. The third scenario is both the least plausible and the most relevant from a monetary policy perspective. The paper concludes that the Eurosystem relies on appropriate regulation, oversight, and supervision to manage the implications of stablecoins (and the risks that stem from them) on its mandate and tasks under plausible scenarios. The Eurosystem continues monitoring the evolution of the stablecoin market and stands ready to respond to rapid changes in all possible scenarios.
SSRN
This paper summarises the outcome of an analysis of stablecoins undertaken by the ECB Crypto-Assets Task Force. At the time of writing, the stablecoin debate lacks a common taxonomy and unambiguous terminology. This paper applies a definition that distinguishes stablecoins from existing forms of currencies â€" regardless of the technology used â€" and characterises stablecoin arrangements based on the functions they fulfil. This approach emphasises the role of technology-neutral regulation in preventing arbitrage, as well as comprehensive Eurosystem oversight, irrespective of stablecoins’ regulatory status. Against this background, this paper assesses stablecoins’ implications for the euro area based on three scenarios for the uptake of stablecoins: (i) as a crypto-assets accessory function; (ii) as a new payment method; and (iii) as an alternative store of value. While the first scenario is merely the continuation of the current state of the market and, thus far, has not posed concerns for the financial sector and/or central bank tasks, stablecoins of the type envisaged in the second scenario may reach a scale such that financial stability risks can become material, and the safety and efficiency of the payment system may be affected. The third scenario is both the least plausible and the most relevant from a monetary policy perspective. The paper concludes that the Eurosystem relies on appropriate regulation, oversight, and supervision to manage the implications of stablecoins (and the risks that stem from them) on its mandate and tasks under plausible scenarios. The Eurosystem continues monitoring the evolution of the stablecoin market and stands ready to respond to rapid changes in all possible scenarios.
The Determinants of Dividend Payout Ratios of Nigerian Non-Financial Firms
SSRN
Research on dividend payout policy is huge in corporate finance. There is however a consensus that it is still an unresolved area. Emerging market research on payout policy generally lags behind those of industrialized countries. This study investigates the determinants of dividend payout in Nigeria to enrich the developing country perspective on the subject. Post Miller-Modigliani (1961) study, asymmetric information models, agency models, tax model and behavioural models have emerged with insufficient empirical test in Nigeria. This study utilizes panel data regression techniques such as two-stage least squares (2SLS), generalized method of moments (GMM) and GARCH to investigate how firm-specific attributes that underscore information asymmetry, agency, transactions and bankruptcy costs affect payout ratios. The key finding of this study is that dividend is an increasing function of the following firm-specific variables namely: book leverage, short-term debt usage, marginal tax rate, firm size and profitability while the attributes that exert negative influences on payout are market leverage, asset tangibility, earnings volatility, firm uniqueness, financing deficit and age. The results confirm the predictions of trade-off, pecking order and agency models of dividends albeit in varying degrees. The study recommends predictable payout policies in line with investors’ expectations in order to facilitate firms’ continuous access to finance.
SSRN
Research on dividend payout policy is huge in corporate finance. There is however a consensus that it is still an unresolved area. Emerging market research on payout policy generally lags behind those of industrialized countries. This study investigates the determinants of dividend payout in Nigeria to enrich the developing country perspective on the subject. Post Miller-Modigliani (1961) study, asymmetric information models, agency models, tax model and behavioural models have emerged with insufficient empirical test in Nigeria. This study utilizes panel data regression techniques such as two-stage least squares (2SLS), generalized method of moments (GMM) and GARCH to investigate how firm-specific attributes that underscore information asymmetry, agency, transactions and bankruptcy costs affect payout ratios. The key finding of this study is that dividend is an increasing function of the following firm-specific variables namely: book leverage, short-term debt usage, marginal tax rate, firm size and profitability while the attributes that exert negative influences on payout are market leverage, asset tangibility, earnings volatility, firm uniqueness, financing deficit and age. The results confirm the predictions of trade-off, pecking order and agency models of dividends albeit in varying degrees. The study recommends predictable payout policies in line with investors’ expectations in order to facilitate firms’ continuous access to finance.
The Great Depression as a Saving Glut
SSRN
Facing the Great Depression, Keynes blamed the detrimental consequences of precautionary savings on growth (paradox of thrift). Yet, the magnitude, forms and effects of savings accumulation remain unexplored in studies on the international economic crash of the 1930s. Based on new data for 22 countries, we document that the Great Depression was associated with a large international increase in savings institutions' deposits. Banking crises spurred precautionary savings. Panel estimations show a negative conditional correlation between real GDP and deposits in savings institutions when a banking crisis hit. A back-of-the-envelope calculation suggests that the negative effect of precautionary savings on growth was at least as large as the direct effect of the decline in banking activity. The evolution of the saving rate began to reverse as countries left the gold standard.
SSRN
Facing the Great Depression, Keynes blamed the detrimental consequences of precautionary savings on growth (paradox of thrift). Yet, the magnitude, forms and effects of savings accumulation remain unexplored in studies on the international economic crash of the 1930s. Based on new data for 22 countries, we document that the Great Depression was associated with a large international increase in savings institutions' deposits. Banking crises spurred precautionary savings. Panel estimations show a negative conditional correlation between real GDP and deposits in savings institutions when a banking crisis hit. A back-of-the-envelope calculation suggests that the negative effect of precautionary savings on growth was at least as large as the direct effect of the decline in banking activity. The evolution of the saving rate began to reverse as countries left the gold standard.
The Great Lockdown: Pandemic Response Policies and Bank Lending Conditions
SSRN
This study analyses the policy measures taken in the euro area in response to the outbreak and the escalating diffusion of new coronavirus (COVID-19) pandemic. We focus on monetary, microprudential and macroprudential policies designed specifically to support bank lending conditions. For identification, we use proprietary data on participation in central bank liquidity operations, high-frequency reactions to monetary policy announcements, and confidential supervisory information on bank capital requirements. The results show that in the absence of the funding cost relief and capital relief associated with the pandemic response measures, banks' ability to supply credit would have been severely affected. The results also indicate that the coordinated intervention by monetary and prudential authorities amplified the effects of the individual measures in supporting liquidity conditions and helping to sustain the flow of credit to the private sector. Finally, we investigate the potential real effects of the joint pandemic response measures by estimating the adjustment in labour input variables for firms that in the past have been more exposed to similar policies. We find that, in absence of monetary and prudential policies, the pandemic would lead to a significantly larger decline in firms' employment.
SSRN
This study analyses the policy measures taken in the euro area in response to the outbreak and the escalating diffusion of new coronavirus (COVID-19) pandemic. We focus on monetary, microprudential and macroprudential policies designed specifically to support bank lending conditions. For identification, we use proprietary data on participation in central bank liquidity operations, high-frequency reactions to monetary policy announcements, and confidential supervisory information on bank capital requirements. The results show that in the absence of the funding cost relief and capital relief associated with the pandemic response measures, banks' ability to supply credit would have been severely affected. The results also indicate that the coordinated intervention by monetary and prudential authorities amplified the effects of the individual measures in supporting liquidity conditions and helping to sustain the flow of credit to the private sector. Finally, we investigate the potential real effects of the joint pandemic response measures by estimating the adjustment in labour input variables for firms that in the past have been more exposed to similar policies. We find that, in absence of monetary and prudential policies, the pandemic would lead to a significantly larger decline in firms' employment.
The Impact of Financial Education of Managers on Medium and Large Enterprises - a Randomized Controlled Trial in Mozambique
SSRN
This paper studies the impact of a course in "Finance" for top managers of medium and large enterprises in Mozambique through a randomized controlled trial (RCT). Survey data and accounting data provide consistent evidence that managers change firm financial policies in response to finance education. The largest treatment ef- fect is on short-term financial policies related to working capital. Reductions in accounts receivable and inventories generate an increase in cash flows used to finance long-term investments. Those policy changes also improve the performance of the treated firms. Overall, our results suggest that relatively small and low-cost interventions, such as a standard executive education program in finance, can help firms to mitigate financial constraints and potentially affect economic development.
SSRN
This paper studies the impact of a course in "Finance" for top managers of medium and large enterprises in Mozambique through a randomized controlled trial (RCT). Survey data and accounting data provide consistent evidence that managers change firm financial policies in response to finance education. The largest treatment ef- fect is on short-term financial policies related to working capital. Reductions in accounts receivable and inventories generate an increase in cash flows used to finance long-term investments. Those policy changes also improve the performance of the treated firms. Overall, our results suggest that relatively small and low-cost interventions, such as a standard executive education program in finance, can help firms to mitigate financial constraints and potentially affect economic development.
The Nonlinear Relationship between Public Debt and Sovereign Credit Ratings
SSRN
This study investigates the relationship between public debt and sovereign credit ratings, using a wide sample of over 100 advanced, emerging, and developing economies. It finds that: i) higher public debt lowers the probability of being placed in a higher rating category; ii) the negative debt-ratings relationship is nonlinear and depends on the rating grade itself; and iii) the identified nonlinearity explains the differential impact of debt on ratings in advanced economies versus emerging and developing economies (previously suggested in the literature as different relationships). These results hold for both gross and net debt, and are robust to alternative dependent variable definitions, analytical techniques, and empirical specifications.
SSRN
This study investigates the relationship between public debt and sovereign credit ratings, using a wide sample of over 100 advanced, emerging, and developing economies. It finds that: i) higher public debt lowers the probability of being placed in a higher rating category; ii) the negative debt-ratings relationship is nonlinear and depends on the rating grade itself; and iii) the identified nonlinearity explains the differential impact of debt on ratings in advanced economies versus emerging and developing economies (previously suggested in the literature as different relationships). These results hold for both gross and net debt, and are robust to alternative dependent variable definitions, analytical techniques, and empirical specifications.
The Rise of Multiple Institutional Affiliations in Academia
arXiv
arXiv
This study provides the first systematic, international, large-scale evidence on the extent and nature of multiple institutional affiliations on journal publications. Studying more than 13.6M authors and 20.5M articles from 40 countries we document that: In 2019, almost one in three articles was (co-)authored by authors with multiple affiliations and the share of authors with multiple affiliations increased from 6.7% to 11.8% since 1996. The growth of multiple affiliations is prevalent in all disciplines and it is stronger in high impact journals. About 60% of multiple affiliations involve institutions from within the academic sector and international co-affiliations often involve institutions from the United States, Germany and the United Kingdom as well as institutions in neighboring countries. We discuss potential causes and show that the timing of the rise in multiple affiliations can be linked to the introduction of more competitive funding structures such as 'excellence initiatives' in a number of countries. We discuss implications for science and science policy.
The Two Growth Rates of the Economy
arXiv
arXiv
Economic growth is measured as the rate of relative change in gross domestic product (GDP) per capita. Yet, when incomes follow random multiplicative growth, the ensemble-average (GDP per capita) growth rate is higher than the time-average growth rate achieved by each individual in the long run. This mathematical fact is the starting point of ergodicity economics. Using the atypically high ensemble-average growth rate as the principal growth measure creates an incomplete picture. Policymaking would be better informed by reporting both ensemble-average and time-average growth rates. We analyse rigorously these growth rates and describe their evolution in the United States and France over the last fifty years. The difference between the two growth rates gives rise to a natural measure of income inequality, equal to the mean logarithmic deviation. Despite being estimated as the average of individual income growth rates, the time-average growth rate is independent of income mobility.
Unpatented Innovation and Merger Synergies
SSRN
The increasingly service-based U.S. economy places a high reliance on innovation. While there is considerable research on the importance of certain innovative activities such as patents, less attention has been paid to un-patented innovation, about which there is naturally less publicly available information. Our research leverages a unique merger and acquisition database that reveals the fair values of targets’ innovative activities. We show that existing studies underestimate the contribution of innovation by exclusively focusing on patents. Our evidence, for example, shows that approximately three percent of merger synergy value is associated with patented innovation, whereas the less often studied un-patented innovation accounts for twelve percent of synergy gains.
SSRN
The increasingly service-based U.S. economy places a high reliance on innovation. While there is considerable research on the importance of certain innovative activities such as patents, less attention has been paid to un-patented innovation, about which there is naturally less publicly available information. Our research leverages a unique merger and acquisition database that reveals the fair values of targets’ innovative activities. We show that existing studies underestimate the contribution of innovation by exclusively focusing on patents. Our evidence, for example, shows that approximately three percent of merger synergy value is associated with patented innovation, whereas the less often studied un-patented innovation accounts for twelve percent of synergy gains.
