Research articles for the 2019-10-18
A Robust Estimator of the Efficient Frontier
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Convex optimization solutions tend to be unstable, to the point of entirely offsetting the benefits of optimization. For example, in the context of financial applications, it is known that portfolios optimized in-sample often underperform the naïve (equal weights) allocation out-of-sample. This instability can be traced back to two sources: (i) noise in the input variables; and (ii) signal structure that magnifies the estimation errors in the input variables. A first innovation of this paper is to introduce the nested clustered optimization algorithm (NCO), a method that tackles both sources of instability.Over the past 60 years, various approaches have been developed to address these two sources of instability. These approaches are flawed in the sense that different methods may be appropriate for different input variables, and it is unrealistic to expect that one method will dominate all the rest under all circumstances. Accordingly, a second innovation of this paper is to introduce MCOS, a Monte Carlo approach that estimates the allocation error produced by various optimization methods on a particular set of input variables. The result is a precise determination of what method is most robust to a particular case. Thus, rather than relying always on one particular approach, MCOS allows users to apply opportunistically whatever optimization method is best suited in a particular setting.Presentation materials are available at: https://ssrn.com/abstract=3469964
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Convex optimization solutions tend to be unstable, to the point of entirely offsetting the benefits of optimization. For example, in the context of financial applications, it is known that portfolios optimized in-sample often underperform the naïve (equal weights) allocation out-of-sample. This instability can be traced back to two sources: (i) noise in the input variables; and (ii) signal structure that magnifies the estimation errors in the input variables. A first innovation of this paper is to introduce the nested clustered optimization algorithm (NCO), a method that tackles both sources of instability.Over the past 60 years, various approaches have been developed to address these two sources of instability. These approaches are flawed in the sense that different methods may be appropriate for different input variables, and it is unrealistic to expect that one method will dominate all the rest under all circumstances. Accordingly, a second innovation of this paper is to introduce MCOS, a Monte Carlo approach that estimates the allocation error produced by various optimization methods on a particular set of input variables. The result is a precise determination of what method is most robust to a particular case. Thus, rather than relying always on one particular approach, MCOS allows users to apply opportunistically whatever optimization method is best suited in a particular setting.Presentation materials are available at: https://ssrn.com/abstract=3469964
A State Space Framework for the Residual Income Valuation Model of Stock Prices
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We assess the empirical implications of the valuation model for equity prices developed in Ohlson (1995), by accounting for residual income information dynamics. A key assumption of the Ohlson (1995) residual income model stipulates that next period t + 1 residual income is a linear function of current period t residual income and a latent variable referred to as ‘other information’. This ‘other information’, assumed known in the current period t, contains information on next period t+1 abnormal earnings not reflected in current period t abnormal earnings. Previous literature has proxied this ‘other information’ variable with consensus analysts’ forecasts of earnings. In this study, we propose to estimate this latent ‘other information’ variable using a state space framework. Our method obviates the need for analysts’ earnings forecasts. We estimate the valuation model, within the embedded state space framework, using the Kalman filter recursive procedure. We estimate the model across a sample of stocks in the Dow Jones 30 and S&P 500 indices. We compare the model performance to a benchmark two-step regression approach used in previous work. Performance yardsticks indicate that our state space estimation approach shows promise in valuing stocks and predicting next period t+1 residual income relative to the benchmark approach.
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We assess the empirical implications of the valuation model for equity prices developed in Ohlson (1995), by accounting for residual income information dynamics. A key assumption of the Ohlson (1995) residual income model stipulates that next period t + 1 residual income is a linear function of current period t residual income and a latent variable referred to as ‘other information’. This ‘other information’, assumed known in the current period t, contains information on next period t+1 abnormal earnings not reflected in current period t abnormal earnings. Previous literature has proxied this ‘other information’ variable with consensus analysts’ forecasts of earnings. In this study, we propose to estimate this latent ‘other information’ variable using a state space framework. Our method obviates the need for analysts’ earnings forecasts. We estimate the valuation model, within the embedded state space framework, using the Kalman filter recursive procedure. We estimate the model across a sample of stocks in the Dow Jones 30 and S&P 500 indices. We compare the model performance to a benchmark two-step regression approach used in previous work. Performance yardsticks indicate that our state space estimation approach shows promise in valuing stocks and predicting next period t+1 residual income relative to the benchmark approach.
A Survey of Institutional Investors’ Investment and Management Decisions on Illiquid Assets
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This paper reports the results of a survey of nine Dutch and five Canadian pension funds and fiduciary managers on the investment and management decisions regarding illiquid assets. The six Dutch pension funds in our survey represent total assets under management of EUR 342 billion and the four Canadian pension funds amount to CAD 203 billion. Dutch pension funds invest on average 14% of their portfolio in illiquid assets; for Canadian funds this equals 34%. The main reasons reported most often for investing in illiquid assets are the risk-return trade-off and the diversification benefits. Dutch pension funds generally use asset liability management studies to determine the allocation to illiquid assets, while Canadian pension funds may deviate from target allocations depending on a specified target return for illiquid assets. Pension funds in both countries apply upper limits to the percentage of funds invested in illiquid assets. Most survey participants have liquidity management policies to free up cash if necessary, such as maintaining a cash buffer, using the repo market or securities lending, and applying a specific sequence in which to liquidate positions. Many survey participants perform liquidity stress tests. We have formulated four best practices based on the results of the survey.
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This paper reports the results of a survey of nine Dutch and five Canadian pension funds and fiduciary managers on the investment and management decisions regarding illiquid assets. The six Dutch pension funds in our survey represent total assets under management of EUR 342 billion and the four Canadian pension funds amount to CAD 203 billion. Dutch pension funds invest on average 14% of their portfolio in illiquid assets; for Canadian funds this equals 34%. The main reasons reported most often for investing in illiquid assets are the risk-return trade-off and the diversification benefits. Dutch pension funds generally use asset liability management studies to determine the allocation to illiquid assets, while Canadian pension funds may deviate from target allocations depending on a specified target return for illiquid assets. Pension funds in both countries apply upper limits to the percentage of funds invested in illiquid assets. Most survey participants have liquidity management policies to free up cash if necessary, such as maintaining a cash buffer, using the repo market or securities lending, and applying a specific sequence in which to liquidate positions. Many survey participants perform liquidity stress tests. We have formulated four best practices based on the results of the survey.
Another Look on Choosing Factors: The International Evidence
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Extending Fama and French’s (2018) study to international equity markets, we test nested and non-nested asset pricing models for North America, Europe, Asia (excluding Japan), and Japan. For testing non-nested models, we propose a new simulation methodology using a blocks bootstrap approach. Our approach, which accounts for factor dependencies, results in lower out-of-sample Sharpe ratios across all models and countries than Fama and French’s (2018) pairs bootstrap approach. While we confirm that the six-factor model that combines the market factor and size factor with the small stock spread factors for vlaue, profitability, investment and momentum, produces the highest maximum squared Sharpe ratio in most economies, we do not find such evidence for Asia (excluding Japan). Spanning regressions reveal that size does not matter in any of the international equity markets, whereas value matters in Europe, Asia (excluding Japan), and even in Japan.
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Extending Fama and French’s (2018) study to international equity markets, we test nested and non-nested asset pricing models for North America, Europe, Asia (excluding Japan), and Japan. For testing non-nested models, we propose a new simulation methodology using a blocks bootstrap approach. Our approach, which accounts for factor dependencies, results in lower out-of-sample Sharpe ratios across all models and countries than Fama and French’s (2018) pairs bootstrap approach. While we confirm that the six-factor model that combines the market factor and size factor with the small stock spread factors for vlaue, profitability, investment and momentum, produces the highest maximum squared Sharpe ratio in most economies, we do not find such evidence for Asia (excluding Japan). Spanning regressions reveal that size does not matter in any of the international equity markets, whereas value matters in Europe, Asia (excluding Japan), and even in Japan.
Blockchain: Moving Beyond Bitcoin into a Digitalized World
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Little over a decade has passed since Blockchain gave birth to its prodigy Bitcoin, but Bitcoin despite all the hype (which was referred to as “big bang†by many) failed to become a simple (stable) global crypto-currency for everyday life to enable users worldwide to purchase products/services online, transfer money and conduct business with both individuals and entities within seconds without going through access related issues and financial burden of high transactional costs. Blockchain’s close link to Bitcoin has been rather negative on the revolutionary technology to live its true potential, but now it is time for blockchain to move beyond Bitcoin. Blockchain distributed ledger technology (DLT) can be used in many areas that are traditionally under government control. In fact, numerous tools and applications we are so accustomed to using or seeing around could be decentralized via blockchain to create a paperless digitalized world; as a side goal, this could possibly help reduce global warming as well. Internet, marketing (advertisement), asset management, traffic control, utilities (electric, gas, and water) and social security (retirement benefits) can all be decentralized through blockchain to provide more efficient and unrestricted access to personal and public records. Blockchain possesses immense opportunities and has the capacity to take unimaginable forms in the future, but only if regulators, law makers, central banks and other branches of governments allow it to happen.
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Little over a decade has passed since Blockchain gave birth to its prodigy Bitcoin, but Bitcoin despite all the hype (which was referred to as “big bang†by many) failed to become a simple (stable) global crypto-currency for everyday life to enable users worldwide to purchase products/services online, transfer money and conduct business with both individuals and entities within seconds without going through access related issues and financial burden of high transactional costs. Blockchain’s close link to Bitcoin has been rather negative on the revolutionary technology to live its true potential, but now it is time for blockchain to move beyond Bitcoin. Blockchain distributed ledger technology (DLT) can be used in many areas that are traditionally under government control. In fact, numerous tools and applications we are so accustomed to using or seeing around could be decentralized via blockchain to create a paperless digitalized world; as a side goal, this could possibly help reduce global warming as well. Internet, marketing (advertisement), asset management, traffic control, utilities (electric, gas, and water) and social security (retirement benefits) can all be decentralized through blockchain to provide more efficient and unrestricted access to personal and public records. Blockchain possesses immense opportunities and has the capacity to take unimaginable forms in the future, but only if regulators, law makers, central banks and other branches of governments allow it to happen.
Buildings' Energy Efficiency and the Probability of Mortgage Default: The Dutch Case
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In this paper, we investigate the relation between buildings' energy efficiency and the probability of mortgage default. To this end, we construct a novel panel dataset by combining Dutch loan-level mortgage information with provisional building energy ratings that are calculated by the Netherlands Enterprise Agency. By employing the Logistic regression and the extended Cox model, we find that buildings' energy efficiency is associated with lower likelihood of mortgage default. The results hold for a battery of robustness checks. Additional findings indicate that credit risk varies with the degree of energy efficiency.
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In this paper, we investigate the relation between buildings' energy efficiency and the probability of mortgage default. To this end, we construct a novel panel dataset by combining Dutch loan-level mortgage information with provisional building energy ratings that are calculated by the Netherlands Enterprise Agency. By employing the Logistic regression and the extended Cox model, we find that buildings' energy efficiency is associated with lower likelihood of mortgage default. The results hold for a battery of robustness checks. Additional findings indicate that credit risk varies with the degree of energy efficiency.
Financial Misconduct and Changes in Employee Satisfaction
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We use Glassdoor data to study the effects of the public announcement of financial misconduct on employees' perceptions of firms and managers. We find a 0.32 standard deviation decline in employees' overall company ratings and 0.14 to 0.40 standard deviation declines in ratings of career opportunity, compensation benefit, senior leadership, work-life balance, culture value, and recommendation. Additional analysis shows that long-term reputation damage is likely to be the main economic channel behind the findings. Moreover, we further assess whether employee ratings are helpful in predicting misconduct. During the years of the misconduct period, employees who are more likely to have private information lowered their ratings. Such employees' ratings help predict misconduct.
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We use Glassdoor data to study the effects of the public announcement of financial misconduct on employees' perceptions of firms and managers. We find a 0.32 standard deviation decline in employees' overall company ratings and 0.14 to 0.40 standard deviation declines in ratings of career opportunity, compensation benefit, senior leadership, work-life balance, culture value, and recommendation. Additional analysis shows that long-term reputation damage is likely to be the main economic channel behind the findings. Moreover, we further assess whether employee ratings are helpful in predicting misconduct. During the years of the misconduct period, employees who are more likely to have private information lowered their ratings. Such employees' ratings help predict misconduct.
How Might Standard Units of Value Be Defined?
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The research question of this article is how should the International Accounting Standards Board establish standard units of value? Economic value is a social construct that has no use if humans do not exist. The ability for humans to sustain themselves in perpetuity on our planet depends upon how well renewable and recyclable resources in each bioregion can support humanity. As each bioregion has different capacities different units of value are required if prices are to be useful for guiding the size and distribution of the global population between regions. As energy is fundamental for modern human wellbeing, and renewable sources vary by regions this provides a basis for creating sustainability indexes in each bioregion to tether bioregional currencies to promote circular economies. The Internet of Things provides a way to collect and calculate indexes automatically to establish a creditable stable and predicable relative index of value for all goods and services to remove the need for money to be a store of value or unit of account. Self-liquidating money would simplify money to only being a medium of exchange that could be created on a decentralised basis by users. Carbon trading and/or taxing could reduce, or be avoided.
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The research question of this article is how should the International Accounting Standards Board establish standard units of value? Economic value is a social construct that has no use if humans do not exist. The ability for humans to sustain themselves in perpetuity on our planet depends upon how well renewable and recyclable resources in each bioregion can support humanity. As each bioregion has different capacities different units of value are required if prices are to be useful for guiding the size and distribution of the global population between regions. As energy is fundamental for modern human wellbeing, and renewable sources vary by regions this provides a basis for creating sustainability indexes in each bioregion to tether bioregional currencies to promote circular economies. The Internet of Things provides a way to collect and calculate indexes automatically to establish a creditable stable and predicable relative index of value for all goods and services to remove the need for money to be a store of value or unit of account. Self-liquidating money would simplify money to only being a medium of exchange that could be created on a decentralised basis by users. Carbon trading and/or taxing could reduce, or be avoided.
Identity and Choice Under Risk
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I test a set of predictions that constitute an identity theory of choice under risk using large-scale artefactual field experiments. Men whose identity is primed or threatened invest more in risky opportunities than other men and women. They become overconfident even in pure games of chance with no scope for skill, which is consistent with the motivated-beliefs channel identity theory postulates. The effects are stronger for men who are more likely to commit to male identity â€" older men and men in the Southern US. I show identity theory can contribute to explain negative-expected-value investment by risk-averse agents (e.g., trading individual stocks) and overinvestment in delegated choice under risk (e.g., managerial overinvestment) using simple financial opportunities. Because behaving in line with their identity increases men's utility, departures from expected utility theory are not necessarily suboptimal in this identity theory of choice under risk.
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I test a set of predictions that constitute an identity theory of choice under risk using large-scale artefactual field experiments. Men whose identity is primed or threatened invest more in risky opportunities than other men and women. They become overconfident even in pure games of chance with no scope for skill, which is consistent with the motivated-beliefs channel identity theory postulates. The effects are stronger for men who are more likely to commit to male identity â€" older men and men in the Southern US. I show identity theory can contribute to explain negative-expected-value investment by risk-averse agents (e.g., trading individual stocks) and overinvestment in delegated choice under risk (e.g., managerial overinvestment) using simple financial opportunities. Because behaving in line with their identity increases men's utility, departures from expected utility theory are not necessarily suboptimal in this identity theory of choice under risk.
Machine Learning Asset Allocation (presentation slides)
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Convex optimization solutions tend to be unstable, to the point of entirely offsetting the benefits of optimization. For example, in the context of financial applications, it is known that portfolios optimized in sample often underperform the naïve (equal weights) allocation out of sample.This instability can be traced back to two sources: (1) noise in the input variables; and (2) signal structure that magnifies the estimation errors in the input variables.There is abundant literature discussing noise induced instability. In contrast, signal induced instability is often ignored or misunderstood.We introduce a new optimization method that is robust to signal induced instability.For additional details, see the full paper at : https://ssrn.com/abstract=3469961
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Convex optimization solutions tend to be unstable, to the point of entirely offsetting the benefits of optimization. For example, in the context of financial applications, it is known that portfolios optimized in sample often underperform the naïve (equal weights) allocation out of sample.This instability can be traced back to two sources: (1) noise in the input variables; and (2) signal structure that magnifies the estimation errors in the input variables.There is abundant literature discussing noise induced instability. In contrast, signal induced instability is often ignored or misunderstood.We introduce a new optimization method that is robust to signal induced instability.For additional details, see the full paper at : https://ssrn.com/abstract=3469961
Making Retail Banks Resolvable
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The EU bank resolution framework relies heavily on banks' internal capacity for loss-absorption and recapitalization through the issuance of bail-inable financial instruments (MREL). Meanwhile, the existing collective funding arrangements (resolution and deposit insurance funds) seem inadequate to support other alternatives, such as resolution transfer strategies or administrative liquidation. Based on resolution experience and evidence thus far, such regulatory architecture cannot work effectively on all EU banks regardless of size and business model. Many retail banks â€" both significant and less significant with deposits higher than 40% of their total liabilities and own funds (TLOF) â€" struggle to comply with the existing framework due to their funding model and difficulty to tap capital markets. Ultimately, efforts to improve their resolvability could threaten their viability. In order to improve the resolvability of retail banks, regulators need to enhance resolution transfer strategies which would ultimately reduce MREL requirements. Credible transfer strategies though require credible financing arrangements when a buyer is not readily available. Therefore, resolution funds would need to be able to contribute more than the current 5% TLOF in order to credibly supplement bail-in. Otherwise, regulators should incentivize banks to establish voluntary collective industry funds â€" similar or identical to institutional protection schemes, which would finance transfer-based resolution strategies integrated into the resolution plans. Participation in such voluntary funds would occur in exchange for lower MREL requirements. The use of transfer strategies in conjunction with the establishment of voluntary industry funds would significantly reduce MREL requirements for retail banks.
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The EU bank resolution framework relies heavily on banks' internal capacity for loss-absorption and recapitalization through the issuance of bail-inable financial instruments (MREL). Meanwhile, the existing collective funding arrangements (resolution and deposit insurance funds) seem inadequate to support other alternatives, such as resolution transfer strategies or administrative liquidation. Based on resolution experience and evidence thus far, such regulatory architecture cannot work effectively on all EU banks regardless of size and business model. Many retail banks â€" both significant and less significant with deposits higher than 40% of their total liabilities and own funds (TLOF) â€" struggle to comply with the existing framework due to their funding model and difficulty to tap capital markets. Ultimately, efforts to improve their resolvability could threaten their viability. In order to improve the resolvability of retail banks, regulators need to enhance resolution transfer strategies which would ultimately reduce MREL requirements. Credible transfer strategies though require credible financing arrangements when a buyer is not readily available. Therefore, resolution funds would need to be able to contribute more than the current 5% TLOF in order to credibly supplement bail-in. Otherwise, regulators should incentivize banks to establish voluntary collective industry funds â€" similar or identical to institutional protection schemes, which would finance transfer-based resolution strategies integrated into the resolution plans. Participation in such voluntary funds would occur in exchange for lower MREL requirements. The use of transfer strategies in conjunction with the establishment of voluntary industry funds would significantly reduce MREL requirements for retail banks.
Peer Pressure, CSR Spending, and Long-Term Financial Performance
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This study investigates the role of peer pressure on banks’ Corporate Social Responsibility (CSR) activities and the long-term impacts of their CSR spending on financial performance. We find that a bank’s CSR expenditure increases with that of its peer-banks. However, there is no association between a bank’s CSR expenditure and that of banks of its non-peer group. Additional analysis suggests that a bank’s CSR spending increases not only the current profitability but also its future profitability. This study establishes the evidence of the peer pressure on CSR spending, and the value of CSR in terms of short- and long-term benefits.
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This study investigates the role of peer pressure on banks’ Corporate Social Responsibility (CSR) activities and the long-term impacts of their CSR spending on financial performance. We find that a bank’s CSR expenditure increases with that of its peer-banks. However, there is no association between a bank’s CSR expenditure and that of banks of its non-peer group. Additional analysis suggests that a bank’s CSR spending increases not only the current profitability but also its future profitability. This study establishes the evidence of the peer pressure on CSR spending, and the value of CSR in terms of short- and long-term benefits.
Prognosemodelle für Länderrisiken: Logit- und Deep Learning-Methoden im Vergleich (Forecasting Sovereign Ratings with Logit Regression and Deep Learning: Quo vadis, Italia?)
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German Abstract: Die vorliegende Untersuchung beschäftigt sich mit den Einflussfaktoren auf das Rating von Staaten sowie auf die Zuordnung eines Investmentgrade-Status. Es werden ein Ordered Logit-Modell, ein Logit-Modell sowie ein Deep Learning-Modell konzipiert, die zur Prognose von zukünftigen Bonitätsentwicklungen verwendet werden können. Ferner eignen sich die Modelle zur Analyse unterschiedlicher politischer und wirt-schaftlicher (Stress-)Szenarien. Für Italien wird eine bedingte Vorhersage gewagt.English Abstract: This study explores the factors driving sovereign ratings. An Ordered Logit-Model, a Logit-Model and a Deep Learning-Model are estimated/trained in order to forecast sovereign ratings. A conditional forecast for Italy is worked out in detail.
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German Abstract: Die vorliegende Untersuchung beschäftigt sich mit den Einflussfaktoren auf das Rating von Staaten sowie auf die Zuordnung eines Investmentgrade-Status. Es werden ein Ordered Logit-Modell, ein Logit-Modell sowie ein Deep Learning-Modell konzipiert, die zur Prognose von zukünftigen Bonitätsentwicklungen verwendet werden können. Ferner eignen sich die Modelle zur Analyse unterschiedlicher politischer und wirt-schaftlicher (Stress-)Szenarien. Für Italien wird eine bedingte Vorhersage gewagt.English Abstract: This study explores the factors driving sovereign ratings. An Ordered Logit-Model, a Logit-Model and a Deep Learning-Model are estimated/trained in order to forecast sovereign ratings. A conditional forecast for Italy is worked out in detail.
Real Effects of Disclosure Regulation: Evidence from U.S. Import Competition
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This paper investigates the impact of disclosure regulation on import competition. Using the segment disclosure regulation (SFAS 131) as a plausibly exogenous shock to the supply of mandatory information about U.S. product markets, I uncover an increase in U.S. import competition at the industry level. Consistent with foreign competition, the effect is more pronounced in industries with high labor intensity and in industries of low competition, where foreign firms have a greater incentive to compete with U.S. firms. Consistent with learning from disclosures, the effect is stronger in industries with high demand uncertainty and in industries of high trade policy uncertainty, where learning to reduce uncertainty is more beneficial. In addition, I provide evidence that the effect on import competition spills over to U.S. firms that are not directly affected by the regulation.
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This paper investigates the impact of disclosure regulation on import competition. Using the segment disclosure regulation (SFAS 131) as a plausibly exogenous shock to the supply of mandatory information about U.S. product markets, I uncover an increase in U.S. import competition at the industry level. Consistent with foreign competition, the effect is more pronounced in industries with high labor intensity and in industries of low competition, where foreign firms have a greater incentive to compete with U.S. firms. Consistent with learning from disclosures, the effect is stronger in industries with high demand uncertainty and in industries of high trade policy uncertainty, where learning to reduce uncertainty is more beneficial. In addition, I provide evidence that the effect on import competition spills over to U.S. firms that are not directly affected by the regulation.
Regulatory Arbitrage and Cross-Border Syndicated Loans
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This paper investigates how international regulatory and institutional differences affect lending in the cross-border syndicated loan market. Lending provided through a foreign subsidiary is subject to subsidiary-country regulation and institutional arrangements. Multinational banks’ choices between loan origination through the parent bank or through a foreign subsidiary provide information about these banks’ preferences to operate in countries with varying regulations and institutions. Our results indicate that international banks have a tendency to switch loan origination towards countries with less stringent bank regulation and supervision consistent with regulatory arbitrage, but that they prefer to originate loans in countries with higher-quality institutions related to financial market monitoring, creditor rights, and the speed of contract enforcement.
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This paper investigates how international regulatory and institutional differences affect lending in the cross-border syndicated loan market. Lending provided through a foreign subsidiary is subject to subsidiary-country regulation and institutional arrangements. Multinational banks’ choices between loan origination through the parent bank or through a foreign subsidiary provide information about these banks’ preferences to operate in countries with varying regulations and institutions. Our results indicate that international banks have a tendency to switch loan origination towards countries with less stringent bank regulation and supervision consistent with regulatory arbitrage, but that they prefer to originate loans in countries with higher-quality institutions related to financial market monitoring, creditor rights, and the speed of contract enforcement.
Responsible Investing: The ESG-Efficient Frontier
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We propose a theory in which each stock’s environmental, social, and governance (ESG) score plays two roles: 1) providing information about firm fundamentals and 2) affecting investor preferences. The solution to the investor’s portfolio problem is characterized by an ESG-efficient frontier, showing the highest attainable Sharpe ratio for each ESG level. The corresponding portfolios satisfy four-fund separation. Equilibrium asset prices are determined by an ESG-adjusted capital asset pricing model, showing when ESG increases or lowers the required return. Combining several large data sets, we compute the empirical ESG-efficient frontier and show the costs and benefits of responsible investing. Finally, we test our theory’s predictions using commercial ESG measures, governance, sin stocks, and carbon emissions.
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We propose a theory in which each stock’s environmental, social, and governance (ESG) score plays two roles: 1) providing information about firm fundamentals and 2) affecting investor preferences. The solution to the investor’s portfolio problem is characterized by an ESG-efficient frontier, showing the highest attainable Sharpe ratio for each ESG level. The corresponding portfolios satisfy four-fund separation. Equilibrium asset prices are determined by an ESG-adjusted capital asset pricing model, showing when ESG increases or lowers the required return. Combining several large data sets, we compute the empirical ESG-efficient frontier and show the costs and benefits of responsible investing. Finally, we test our theory’s predictions using commercial ESG measures, governance, sin stocks, and carbon emissions.
Self-Help Groups (SHGs) Model for accelerating Grid Connected Rooftop Solar PV (GC-RSPV) in the Residential Sector of India
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The Government of India (GoI) set an ambitious target to provide uninterrupted energy access across all sectors of the economy 2022. In this context, it’s a commitment to deploy 40GW of GC-RSPV by 2022 in the residential sector is facing multiple challenges, which is hindering the progress of market penetration on a large scale. The existing business models failed to deploy at scale due to limited support from loss-making discoms, lack of coordination between institutions, perception of residential consumers about GC-RSPV technology and access to consumer finance, etc made target unachievable. Hence, there is a need for a suitable business model, which is complemented a top-down approach with bottom-up initiatives along with the involvement of various stakeholders. Therefore, this study proposes a SHGs model to accelerate GC-RSPV at scale. This model is a viable strategy since it is mainstreamed in the financial landscape and this program is the world's largest social mobilization initiative supported by various stakeholders such as NGOs, governments, and banks. This model will yield good results if the discussed assumptions are fulfilled. Further, adopting a technology push strategy with regulations rather than a market pull strategy will help higher market penetration. As a result, this business model has the potential to enhance women entrepreneurship, energy access among rural communities where grid connectivity is a problem and help to achieve other developmental goals.
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The Government of India (GoI) set an ambitious target to provide uninterrupted energy access across all sectors of the economy 2022. In this context, it’s a commitment to deploy 40GW of GC-RSPV by 2022 in the residential sector is facing multiple challenges, which is hindering the progress of market penetration on a large scale. The existing business models failed to deploy at scale due to limited support from loss-making discoms, lack of coordination between institutions, perception of residential consumers about GC-RSPV technology and access to consumer finance, etc made target unachievable. Hence, there is a need for a suitable business model, which is complemented a top-down approach with bottom-up initiatives along with the involvement of various stakeholders. Therefore, this study proposes a SHGs model to accelerate GC-RSPV at scale. This model is a viable strategy since it is mainstreamed in the financial landscape and this program is the world's largest social mobilization initiative supported by various stakeholders such as NGOs, governments, and banks. This model will yield good results if the discussed assumptions are fulfilled. Further, adopting a technology push strategy with regulations rather than a market pull strategy will help higher market penetration. As a result, this business model has the potential to enhance women entrepreneurship, energy access among rural communities where grid connectivity is a problem and help to achieve other developmental goals.
The Demand for Crop Insurance Bundled with Micro-Credit
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Access to financial services is challenging for small farmers in developing countries. This paper studies the demand for micro-insurance when it is bundled with micro-credit in the context of rain-fed agriculture. It presents the conditions under which linking micro-insurance with micro-credit can be beneficial for small producers who cannot access agricultural credit due to lack of collateral. The results show that if crop insurance and agricultural loans are bundled, the demand for crop insurance increases with the profitability of the investment made through the agricultural credit, and it decreases with the level of collateral required during the application for credit.
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Access to financial services is challenging for small farmers in developing countries. This paper studies the demand for micro-insurance when it is bundled with micro-credit in the context of rain-fed agriculture. It presents the conditions under which linking micro-insurance with micro-credit can be beneficial for small producers who cannot access agricultural credit due to lack of collateral. The results show that if crop insurance and agricultural loans are bundled, the demand for crop insurance increases with the profitability of the investment made through the agricultural credit, and it decreases with the level of collateral required during the application for credit.
The Equity Volatility-Volume Ratio and Treasury Bond Returns
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We consider stock and bond market prices jointly in a setting where rational investors are unsure if overconfident investors have valid signals. In times of likely shifts in economic states, the probability of receiving informative signals is higher, so trading volume (volatility) is lower (higher). Central banks react only to macroeconomic changes, but their reaction is uncertain. So during periods where macroeconomic state shifts are more likely, long-term bonds command larger risk premia. We confirm these predictions by showing that the equity market volatility-volume ratio significantly predicts monetary policy uncertainty as well as one-year ahead bond returns.
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We consider stock and bond market prices jointly in a setting where rational investors are unsure if overconfident investors have valid signals. In times of likely shifts in economic states, the probability of receiving informative signals is higher, so trading volume (volatility) is lower (higher). Central banks react only to macroeconomic changes, but their reaction is uncertain. So during periods where macroeconomic state shifts are more likely, long-term bonds command larger risk premia. We confirm these predictions by showing that the equity market volatility-volume ratio significantly predicts monetary policy uncertainty as well as one-year ahead bond returns.
The Importance of Being Special: Repo Markets During the Crisis
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We study how the Italian sovereign bond scarcity premia, specialness, in the repo market were affected by the European Central Bank (ECB)'s purchases during the euro area sovereign debt crisis. We propose and calibrate a search-based dynamic model with a central bank acting as a buy-and-hold investor. Consistent with model predictions, ECB purchases drive specialness of targeted securities in combination with short-selling. Special benchmark bonds entail a positive cash premium, but their market liquidity decreases when purchased by the ECB. Short-sellers were more likely to fail-to-deliver very special bonds, while holders of these bonds were less inclined to pledge them as collateral to the ECB liquidity operations.
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We study how the Italian sovereign bond scarcity premia, specialness, in the repo market were affected by the European Central Bank (ECB)'s purchases during the euro area sovereign debt crisis. We propose and calibrate a search-based dynamic model with a central bank acting as a buy-and-hold investor. Consistent with model predictions, ECB purchases drive specialness of targeted securities in combination with short-selling. Special benchmark bonds entail a positive cash premium, but their market liquidity decreases when purchased by the ECB. Short-sellers were more likely to fail-to-deliver very special bonds, while holders of these bonds were less inclined to pledge them as collateral to the ECB liquidity operations.
The Myth of Creditor Sabotage
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Since credit derivatives began to substantially influence financial markets a decade ago, rumors have circulated about so-called “net-short†creditors who seek to damage promising albeit financially distressed companies. A recent episode pitting the hedge fund Aurelius against broadband provider Windstream is widely supposed to be a case in point and has at once fueled calls for law reform and yielded an ostensible effigy of Wall Street predation.This article argues that creditor sabotage is a myth. Net-short strategies work, if at all, by in effect burning money. When therefore an activist creditor shows its cards, as all activists must eventually do, it also reveals an opportunity for others to profit by thwarting the activist’s plans and saving threatened surplus from the ashes. We discuss three sources of liquidity that targeted firms could tap to block a saboteur â€" “net-long†derivatives speculators, the targets’ own investors, and bankruptcy. We conclude that it is exceedingly difficult for creditors to make money hobbling debtors and that there is little reason to believe anyone tries. We then examine the Windstream case and find, consistent with our theory, that the strongest reason for thinking Aurelius aimed at sabotage, namely that everyone says so, is weak indeed. Our analysis suggests that calls for law reform are addressed to a non-existent or at worst self-correcting problem. Precisely for this reason, however, the persistent appeal of the sabotage myth is a lesson in political rhetoric. A story needn’t be true for some to find it useful.
SSRN
Since credit derivatives began to substantially influence financial markets a decade ago, rumors have circulated about so-called “net-short†creditors who seek to damage promising albeit financially distressed companies. A recent episode pitting the hedge fund Aurelius against broadband provider Windstream is widely supposed to be a case in point and has at once fueled calls for law reform and yielded an ostensible effigy of Wall Street predation.This article argues that creditor sabotage is a myth. Net-short strategies work, if at all, by in effect burning money. When therefore an activist creditor shows its cards, as all activists must eventually do, it also reveals an opportunity for others to profit by thwarting the activist’s plans and saving threatened surplus from the ashes. We discuss three sources of liquidity that targeted firms could tap to block a saboteur â€" “net-long†derivatives speculators, the targets’ own investors, and bankruptcy. We conclude that it is exceedingly difficult for creditors to make money hobbling debtors and that there is little reason to believe anyone tries. We then examine the Windstream case and find, consistent with our theory, that the strongest reason for thinking Aurelius aimed at sabotage, namely that everyone says so, is weak indeed. Our analysis suggests that calls for law reform are addressed to a non-existent or at worst self-correcting problem. Precisely for this reason, however, the persistent appeal of the sabotage myth is a lesson in political rhetoric. A story needn’t be true for some to find it useful.
The Psychology of Financial Professionals and Their Clients
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Financial professionals and their clients exhibit a wide collection of behavioral biases that many times result in imperfect judgments and outcomes. Understanding these cognitive and affective factors are important for financial planners and advisors to ensure their clients are receiving the best financial advice and investment information. The authors describe some common psychological biases and offer solutions for overcoming these biases. The paper draws on some themes from the authors’ book Financial Behavior â€" Players, Services, Products, and Markets published by Oxford University Press in 2017.
SSRN
Financial professionals and their clients exhibit a wide collection of behavioral biases that many times result in imperfect judgments and outcomes. Understanding these cognitive and affective factors are important for financial planners and advisors to ensure their clients are receiving the best financial advice and investment information. The authors describe some common psychological biases and offer solutions for overcoming these biases. The paper draws on some themes from the authors’ book Financial Behavior â€" Players, Services, Products, and Markets published by Oxford University Press in 2017.
Valuing Private Equity Strip by Strip
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We propose a new valuation method for private equity investments. First, we construct a cash-flow replicating portfolio for the private investment, using cash-flows on various listed equity and fixed income instruments. The second step values the replicating portfolio using a flexible asset pricing model that accurately prices the systematic risk in listed equity and fixed income instruments of different horizons. The method delivers a measure of the risk-adjusted profit earned on a PE investment, a time series for the expected return on PE fund categories, and a time series for the residual net asset value in a fund. We apply the method to real estate, infrastructure, buyout, and venture capital funds, and find modestly positive average risk-adjusted profits with substantial cross-sectional variation, and declining expected returns in the later part of the sample.
SSRN
We propose a new valuation method for private equity investments. First, we construct a cash-flow replicating portfolio for the private investment, using cash-flows on various listed equity and fixed income instruments. The second step values the replicating portfolio using a flexible asset pricing model that accurately prices the systematic risk in listed equity and fixed income instruments of different horizons. The method delivers a measure of the risk-adjusted profit earned on a PE investment, a time series for the expected return on PE fund categories, and a time series for the residual net asset value in a fund. We apply the method to real estate, infrastructure, buyout, and venture capital funds, and find modestly positive average risk-adjusted profits with substantial cross-sectional variation, and declining expected returns in the later part of the sample.
What is the Real Relationship between Cash Holdings and Stock Returns?
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The literature has provided mixed evidence on the relationship between cash holdings and average stock returns. We empirically verify that the relationship is positive and robust to the adjustment of risk, the construction of cash holdings portfolios, and the weighting scheme of portfolio returns. We further examine a battery of potential channels that can explain the positive relationship. We find that the cash holding effect can be subsumed by accruals-related anomalies and it mainly comes from stocks with low net operating assets. It is stronger among stocks with high limits to arbitrage. Overall, our results indicate that the cash holding effect does not present a new asset-pricing regularity, but that it is a manifestation of existing anomalies closely related to mispricing.
SSRN
The literature has provided mixed evidence on the relationship between cash holdings and average stock returns. We empirically verify that the relationship is positive and robust to the adjustment of risk, the construction of cash holdings portfolios, and the weighting scheme of portfolio returns. We further examine a battery of potential channels that can explain the positive relationship. We find that the cash holding effect can be subsumed by accruals-related anomalies and it mainly comes from stocks with low net operating assets. It is stronger among stocks with high limits to arbitrage. Overall, our results indicate that the cash holding effect does not present a new asset-pricing regularity, but that it is a manifestation of existing anomalies closely related to mispricing.
