Research articles for the 2019-11-01
A Business Cycle Asset Pricing Model
SSRN
An asset pricing model is introduced that captures the market, liquidity, credit, and business cycle risks. The explicit incorporation of economic-phase-switching business cycle risks makes the predicted return volatility equal to the observed return volatility. Therefore, the concerns over excessive volatility and equity premium puzzle become insignificant in the model. The risk-return tradeoff dynamic disequilibrium model builds on the equilibrium CAPM, taken as its steady state. It has no worse explanatory power than that of the Fama-French three-factor model and its variants but significantly better out-of-sample predictive power and ex post S&P 500 portfolio returns over the last 20-year period.
SSRN
An asset pricing model is introduced that captures the market, liquidity, credit, and business cycle risks. The explicit incorporation of economic-phase-switching business cycle risks makes the predicted return volatility equal to the observed return volatility. Therefore, the concerns over excessive volatility and equity premium puzzle become insignificant in the model. The risk-return tradeoff dynamic disequilibrium model builds on the equilibrium CAPM, taken as its steady state. It has no worse explanatory power than that of the Fama-French three-factor model and its variants but significantly better out-of-sample predictive power and ex post S&P 500 portfolio returns over the last 20-year period.
An Improved Method to Predict Assignment of Stocks into Russell Indexes
SSRN
A growing literature uses the Russell 1000/2000 reconstitution event as an identification strategy to investigate corporate finance and asset pricing questions. To implement this identification strategy, researchers need to approximate the ranking variable used to assign stocks to indexes. We develop a procedure that predicts assignment to the Russell 1000/2000 with significant improvements relative to previous approaches. We apply this methodology to extend the tests in Ben-David, Franzoni, and Moussawi (2018).
SSRN
A growing literature uses the Russell 1000/2000 reconstitution event as an identification strategy to investigate corporate finance and asset pricing questions. To implement this identification strategy, researchers need to approximate the ranking variable used to assign stocks to indexes. We develop a procedure that predicts assignment to the Russell 1000/2000 with significant improvements relative to previous approaches. We apply this methodology to extend the tests in Ben-David, Franzoni, and Moussawi (2018).
CACs and Doorknobs
SSRN
Key Points:• Collective Action Clauses (CACs) in sovereign bonds have been a prominent part of European financial architecture debates since 2010. • They have been the go-to policy prescription in response to the financial crisis, and the subject of intense academic study.• CACs can play an important role in a debt crisis; however, the welfare implications of CACs for any given sovereign borrower are not always clear. In particular, they are very sensitive to the availability of alternative restructuring tools, including bankruptcy and debt exchanges.• This can be shown theoretically, and finds support in corporate bond restructuring practice. - The track record of majority rule in corporate debt is much more ambivalent than the consensus in the sovereign world would suggest.• It is important to identify the welfare implications of CACs in context before recommending them.• Pricing studies can help with this task in some, but not all cases. They deliver unambiguous welfare predictions only if borrowing costs are found to be lower with CACs than with other restructuring alternatives. This prediction does not generalize to other settings.• Policymakers would benefit from more research on the ex post effects of CACs and other restructuring techniques in sovereign bonds, and more comparative analysis of the ex post effects of majority voting in corporate debt.
SSRN
Key Points:• Collective Action Clauses (CACs) in sovereign bonds have been a prominent part of European financial architecture debates since 2010. • They have been the go-to policy prescription in response to the financial crisis, and the subject of intense academic study.• CACs can play an important role in a debt crisis; however, the welfare implications of CACs for any given sovereign borrower are not always clear. In particular, they are very sensitive to the availability of alternative restructuring tools, including bankruptcy and debt exchanges.• This can be shown theoretically, and finds support in corporate bond restructuring practice. - The track record of majority rule in corporate debt is much more ambivalent than the consensus in the sovereign world would suggest.• It is important to identify the welfare implications of CACs in context before recommending them.• Pricing studies can help with this task in some, but not all cases. They deliver unambiguous welfare predictions only if borrowing costs are found to be lower with CACs than with other restructuring alternatives. This prediction does not generalize to other settings.• Policymakers would benefit from more research on the ex post effects of CACs and other restructuring techniques in sovereign bonds, and more comparative analysis of the ex post effects of majority voting in corporate debt.
Data Defense in Sustainable Investing
SSRN
Alternative data (alt-data) is becoming an increasingly powerful tool that investors can use to incorporate sustainability considerations â€" e.g., environmental, social, and governance (ESG) factors â€" into their decision-making. But alt-data must be used responsibly. Failure to do so can expose investors to novel forms of risk, some of which are fueled by fast-evolving technology, such as advanced machine-learning algorithms. In this paper, we explain and dissect these risks, and discuss how they create a need for investors to play data defense: that is, adopt organizational postures and processes that recognize how data can become a liability, as well as an asset to the organization. We outline the essential elements of strategies for data defense, and explore how investors can analyze their own organizations’ data-related vulnerabilities. Our hope is that these insights serve as encouragement for investors to more responsibly and effectively use alt-data in their future operations â€" both in pursuing sustainability objectives and in general.
SSRN
Alternative data (alt-data) is becoming an increasingly powerful tool that investors can use to incorporate sustainability considerations â€" e.g., environmental, social, and governance (ESG) factors â€" into their decision-making. But alt-data must be used responsibly. Failure to do so can expose investors to novel forms of risk, some of which are fueled by fast-evolving technology, such as advanced machine-learning algorithms. In this paper, we explain and dissect these risks, and discuss how they create a need for investors to play data defense: that is, adopt organizational postures and processes that recognize how data can become a liability, as well as an asset to the organization. We outline the essential elements of strategies for data defense, and explore how investors can analyze their own organizations’ data-related vulnerabilities. Our hope is that these insights serve as encouragement for investors to more responsibly and effectively use alt-data in their future operations â€" both in pursuing sustainability objectives and in general.
Does Green Bonds Placement Create Value For Firms?
SSRN
The goal of this research is to add to the existing corpus of knowledge concerning particular green finance instrument - green bonds. It tries to answer some questions relevant for both scholars and business in order to reinforce the development of green bonds market. One of these questions is whether green bonds issuance cause positive market reaction. Resent activities in global agenda, starting from United Nations Sustainable Goals released in 2015 and endings huge public attention for green issues in 2019 impose additional burden on companies’ competitiveness. Our major hypothesis is that ecological factors affect investors’ decisions whose portfolios and investment declarations are getting to be more aligned with global ecological agenda. The green bonds issuance provide a signal for investors that the issuing firm is involved in sustainable development and hence its stock may be included in the portfolio. The study discovers the significance of the “green†label for the stock market reaction. Alongside, it studies some other features of green bonds, fostering their evolvement and justifying their costs for issuers.
SSRN
The goal of this research is to add to the existing corpus of knowledge concerning particular green finance instrument - green bonds. It tries to answer some questions relevant for both scholars and business in order to reinforce the development of green bonds market. One of these questions is whether green bonds issuance cause positive market reaction. Resent activities in global agenda, starting from United Nations Sustainable Goals released in 2015 and endings huge public attention for green issues in 2019 impose additional burden on companies’ competitiveness. Our major hypothesis is that ecological factors affect investors’ decisions whose portfolios and investment declarations are getting to be more aligned with global ecological agenda. The green bonds issuance provide a signal for investors that the issuing firm is involved in sustainable development and hence its stock may be included in the portfolio. The study discovers the significance of the “green†label for the stock market reaction. Alongside, it studies some other features of green bonds, fostering their evolvement and justifying their costs for issuers.
Don’t Take Their Word For It: The Misclassification of Bond Mutual Funds
SSRN
We provide evidence that mutual fund managers misclassify their holdings, and that these misclassifications have a real and significant impact on investor capital flows. In particular, we provide the first systematic study of bond funds’ reported asset profiles to Morningstar against their actual portfolios. Many funds report more investment grade assets than are actually held in their portfolios, making these funds appear significantly less risky. This results in pervasive misclassifications across the universe of US fixed income mutual funds by Morningstar, who relies on these reported holdings. The problem is widespread- resulting in about 30% of funds being misclassified with safer profiles, when compared against their actual, publicly reported holdings. “Misclassified funds†â€" i.e., those that hold risky bonds, but claim to hold safer bondsâ€" outperform the actual low-risk funds in their peer groups. “Misclassified funds†therefore receive higher Morningstar Ratings (significantly more Morningstar Stars) and higher investor flows due to this perceived outperformance. However, when we correctly classify them based on their actual risk, these funds are mediocre performers. Misreporting is stronger following several quarters of large negative returns, and it is strong at the fund family level. We report those families that have the highest percentage of misreported funds in the sample.
SSRN
We provide evidence that mutual fund managers misclassify their holdings, and that these misclassifications have a real and significant impact on investor capital flows. In particular, we provide the first systematic study of bond funds’ reported asset profiles to Morningstar against their actual portfolios. Many funds report more investment grade assets than are actually held in their portfolios, making these funds appear significantly less risky. This results in pervasive misclassifications across the universe of US fixed income mutual funds by Morningstar, who relies on these reported holdings. The problem is widespread- resulting in about 30% of funds being misclassified with safer profiles, when compared against their actual, publicly reported holdings. “Misclassified funds†â€" i.e., those that hold risky bonds, but claim to hold safer bondsâ€" outperform the actual low-risk funds in their peer groups. “Misclassified funds†therefore receive higher Morningstar Ratings (significantly more Morningstar Stars) and higher investor flows due to this perceived outperformance. However, when we correctly classify them based on their actual risk, these funds are mediocre performers. Misreporting is stronger following several quarters of large negative returns, and it is strong at the fund family level. We report those families that have the highest percentage of misreported funds in the sample.
Dynamic Information Aggregation and Welfare
SSRN
In a market with a safe rate and a risky asset that pays a continuous dividend stream depending on a latent state of the economy, several agents make consumption and investment decisions based on public information â€" prices and dividends â€" and private signals. We obtain the equilibrium in closed form, assuming that each investor has constant absolute risk aversion. Equilibrium prices do not reveal all the private signals, but lead to the same estimate of the state of the economy that one would hypothetically obtain from the knowledge of all private signals. Accurate information leads to low volatility, ostensibly improving market efficiency. But it also reduces each agent's consumption through a decrease in the price of risk. Overall, the equilibrium reaches perfect informational efficiency at the expense of agents' welfare.
SSRN
In a market with a safe rate and a risky asset that pays a continuous dividend stream depending on a latent state of the economy, several agents make consumption and investment decisions based on public information â€" prices and dividends â€" and private signals. We obtain the equilibrium in closed form, assuming that each investor has constant absolute risk aversion. Equilibrium prices do not reveal all the private signals, but lead to the same estimate of the state of the economy that one would hypothetically obtain from the knowledge of all private signals. Accurate information leads to low volatility, ostensibly improving market efficiency. But it also reduces each agent's consumption through a decrease in the price of risk. Overall, the equilibrium reaches perfect informational efficiency at the expense of agents' welfare.
Familiarity Breeds Short-Termism
SSRN
Investors exhibit a robust and systematic pattern of shortening their holding period in a stock on which they execute multiple round trip trades. On average, the holding period shortens by 11% with each additional round trip. I show this tendency to be short-termed is associated with reinforcement learning. Investors are more likely to shorten the holding period after a round trip where they could have realized a better return had they sold earlier. Investors become short-termed as they become more familiar with trading a stock.
SSRN
Investors exhibit a robust and systematic pattern of shortening their holding period in a stock on which they execute multiple round trip trades. On average, the holding period shortens by 11% with each additional round trip. I show this tendency to be short-termed is associated with reinforcement learning. Investors are more likely to shorten the holding period after a round trip where they could have realized a better return had they sold earlier. Investors become short-termed as they become more familiar with trading a stock.
Marijuana Liberalization and Public Finance: A Capital Market Perspective on a Public Health Policy
SSRN
Marijuana liberalization has generated heated debates over its potential benefits and costs. However, limited attention has been given to its capital market implications. We provide the first evidence on one cost of liberalizing cannabis imposed by municipal bond investors. Making use of the staggered passage of state legislation, we show that legalization of marijuana for medical use leads to a 7-bps increase in the offering spread, an 11-bps increase in the trading spread, and a 4-bps increase in the gross spread for state bonds. To strengthen the causal inference, we employ two additional identification strategies â€" a test that compares the borrowing costs of adjacent counties across state borders and a test that compares the borrowing cost of two states in which one state passed and the other rejected marijuana laws with narrow margins in ballots. The evidence collectively suggests that municipal bond investors impose higher borrowing costs on local governments in states that have legalized medical marijuana.
SSRN
Marijuana liberalization has generated heated debates over its potential benefits and costs. However, limited attention has been given to its capital market implications. We provide the first evidence on one cost of liberalizing cannabis imposed by municipal bond investors. Making use of the staggered passage of state legislation, we show that legalization of marijuana for medical use leads to a 7-bps increase in the offering spread, an 11-bps increase in the trading spread, and a 4-bps increase in the gross spread for state bonds. To strengthen the causal inference, we employ two additional identification strategies â€" a test that compares the borrowing costs of adjacent counties across state borders and a test that compares the borrowing cost of two states in which one state passed and the other rejected marijuana laws with narrow margins in ballots. The evidence collectively suggests that municipal bond investors impose higher borrowing costs on local governments in states that have legalized medical marijuana.
The Public Blockchain Ecosystem: An Empirical Analysis
SSRN
This paper examines the landscape of public blockchains, focusing on consensus protocols. We propose an empirical framework that takes inspiration from the blockchain trilemma. We construct empirical analogs for each of its three attributes: (i) scale, (ii) security, and (iii) decentralization. Our results establish that Proof-of-Work (PoW) blockchains dominate on decentralization and that this dominance arises from an early-mover's advantage. We also demonstrate that Delegated Proof-of-Stake (DPoS) blockchains dominate on scale and that blockchains using non-standard protocols are most secure. We employ a hierarchical clustering algorithm that selects clusters on the basis of the three attributes. The first level of clustering identifies a set of blockchains that perform well on all three attributes. Within that set, we find further sub-clusters that are differentiated by their performance along the trilemma attributes. These sub-clusters also partition the space of consensus protocols thereby highlighting functional differences across protocols. Finally, we examine the relationship between blockchain usage and our attributes. We find that our attributes explain most of the variation in usage. We document a shift towards DPoS blockchain usage and that scale gains in relevance over time.
SSRN
This paper examines the landscape of public blockchains, focusing on consensus protocols. We propose an empirical framework that takes inspiration from the blockchain trilemma. We construct empirical analogs for each of its three attributes: (i) scale, (ii) security, and (iii) decentralization. Our results establish that Proof-of-Work (PoW) blockchains dominate on decentralization and that this dominance arises from an early-mover's advantage. We also demonstrate that Delegated Proof-of-Stake (DPoS) blockchains dominate on scale and that blockchains using non-standard protocols are most secure. We employ a hierarchical clustering algorithm that selects clusters on the basis of the three attributes. The first level of clustering identifies a set of blockchains that perform well on all three attributes. Within that set, we find further sub-clusters that are differentiated by their performance along the trilemma attributes. These sub-clusters also partition the space of consensus protocols thereby highlighting functional differences across protocols. Finally, we examine the relationship between blockchain usage and our attributes. We find that our attributes explain most of the variation in usage. We document a shift towards DPoS blockchain usage and that scale gains in relevance over time.
The Real Effects of Checks and Balances: Policy Uncertainty and Corporate Investment
SSRN
This article explores the economic effects of checks and balances on corporate investment and employment. I use U.S. gubernatorial election results from 1978 to 2010 as a source of exogenous variation in whether the party controls both the executive and the legislative branch (unified government) or not (divided government), which determines its ability to implement its political agenda. I find that both public and private firms respond to the political cycle by reducing investment and hiring when government becomes unified. Investment drops by three to five percent in the year following an election resulting in unified government, while stock returns volatility is three percent higher. The findings support the hypothesis that moving from divided to unified government raises policy uncertainty by increasing the probability of future policy changes. Consistent with a real option channel, the effect is stronger for capital intensive firms with lower asset redeployability.
SSRN
This article explores the economic effects of checks and balances on corporate investment and employment. I use U.S. gubernatorial election results from 1978 to 2010 as a source of exogenous variation in whether the party controls both the executive and the legislative branch (unified government) or not (divided government), which determines its ability to implement its political agenda. I find that both public and private firms respond to the political cycle by reducing investment and hiring when government becomes unified. Investment drops by three to five percent in the year following an election resulting in unified government, while stock returns volatility is three percent higher. The findings support the hypothesis that moving from divided to unified government raises policy uncertainty by increasing the probability of future policy changes. Consistent with a real option channel, the effect is stronger for capital intensive firms with lower asset redeployability.
The evolution and heterogeneity of credit procyclicality in Central and Eastern Europe
RePEC
This paper presents empirical estimates of bank credit procyclicality for a sample of 11 Central and Eastern Europe countries (CEECs) for the period 2000Q1â€"2016Q4. In the first step we estimate a traditional-type panel VAR model and analyse the evolution of credit procyclicality in the CEECs by comparing the impulse response functions for different business cycle periods. The results confirm the existence of credit procyclicality in CEECs and show that procyclicality is higher during boom periods. Furthermore we observe the heterogeneity of credit procyclicality in the different countries in our sample. To explain the cross-country heterogeneity in credit procyclicality we construct an interacted panel VAR model (IPVAR) and analyse whether bank level competition, proxied by the aggregate Lerner index, constitutes a driving force of credit procyclicality. Our findings indicate that bank competition affects credit procyclicality and explains the differences in credit dynamics across CEECs. Specifically we show that the reaction of credit to a GDP shock is on average higher in a less competitive banking market.
RePEC
This paper presents empirical estimates of bank credit procyclicality for a sample of 11 Central and Eastern Europe countries (CEECs) for the period 2000Q1â€"2016Q4. In the first step we estimate a traditional-type panel VAR model and analyse the evolution of credit procyclicality in the CEECs by comparing the impulse response functions for different business cycle periods. The results confirm the existence of credit procyclicality in CEECs and show that procyclicality is higher during boom periods. Furthermore we observe the heterogeneity of credit procyclicality in the different countries in our sample. To explain the cross-country heterogeneity in credit procyclicality we construct an interacted panel VAR model (IPVAR) and analyse whether bank level competition, proxied by the aggregate Lerner index, constitutes a driving force of credit procyclicality. Our findings indicate that bank competition affects credit procyclicality and explains the differences in credit dynamics across CEECs. Specifically we show that the reaction of credit to a GDP shock is on average higher in a less competitive banking market.
Trust and Corporate Innovation
SSRN
This paper examines the relation between the level of societal trust and corporate innovation in the worldwide. Using data on firms located in 72 countries or regions from1992 to 2016, we quantify the country trust level and find strong evidence that firms in countries with a higher level of societal trust have higher R&D investment input. We also find that the impact of societal trust on firms’ innovation behavior is more pronounced in the firms with a higher level of financial constraints and in the countries with a poor intellectual property rights protection. Overall, our results highlight the effect of societal trust in shaping enterprise innovation behavior.
SSRN
This paper examines the relation between the level of societal trust and corporate innovation in the worldwide. Using data on firms located in 72 countries or regions from1992 to 2016, we quantify the country trust level and find strong evidence that firms in countries with a higher level of societal trust have higher R&D investment input. We also find that the impact of societal trust on firms’ innovation behavior is more pronounced in the firms with a higher level of financial constraints and in the countries with a poor intellectual property rights protection. Overall, our results highlight the effect of societal trust in shaping enterprise innovation behavior.
US Banking Deregulation and Local Economic Growth: Direct Effects and Externalities
SSRN
This study investigates the effects of banking deregulation on county-level economic growth in the U.S. during the 1970â€"2000 period. Our main contribution to the literature is that we analyze both the direct and external effects of banking deregulation on local economic growth. For the regions South, West and Northeast, we find significantly positive long-run direct effects of intrastate branching deregulation on the expected growth rates of counties in the deregulated state itself, up to several percentage points. We also establish significantly positive long-run external effects on the expected growth rates of counties adjacent to the deregulated state, up to several tenths of percentage points. We do not find such robust effects for interstate banking deregulation.
SSRN
This study investigates the effects of banking deregulation on county-level economic growth in the U.S. during the 1970â€"2000 period. Our main contribution to the literature is that we analyze both the direct and external effects of banking deregulation on local economic growth. For the regions South, West and Northeast, we find significantly positive long-run direct effects of intrastate branching deregulation on the expected growth rates of counties in the deregulated state itself, up to several percentage points. We also establish significantly positive long-run external effects on the expected growth rates of counties adjacent to the deregulated state, up to several tenths of percentage points. We do not find such robust effects for interstate banking deregulation.
Willow Tree Algorithms for Pricing VIX Derivatives Under Stochastic Volatility Models
SSRN
VIX futures and option are the most popular contracts traded in the Chicago Board Options Exchange. The bid-ask spreads of traded VIX derivatives remain to be wide, possibly due to lack of reliable pricing models. In this paper, we consider pricing VIX derivatives under the consistent model approach, which considers joint modeling of the dynamics of S&P index and its instantaneous variance. Under the affine jump-diffusion formulation with stochastic volatility, analytic integral formulas can be derived to price VIX futures and option. However, these integral formulas invariably involve Fourier inversion integrals with cumbersome hyper-geometric functions, thus posing various challenges in numerical evaluation. We propose a unified numerical approach based on the willow tree algorithms to price VIX derivatives under various common types of joint process of the S&P index and its instantaneous variance. Given the analytic form of the characteristic function of the instantaneous variance of the S&P index process in the Fourier domain, we apply the fast Fourier transform algorithm to obtain the transition density function numerically in the real domain. We then construct the willow tree that approximates the dynamics of the instantaneous variance process up to the fourth order moment. Our comprehensive numerical tests performed on the willow tree algorithms demonstrate high level of numerical accuracy, run time efficiency and reliability for pricing VIX futures and both European and American options under the affine model and 3/2-model. We also examine the implied volatility smirks and the term structures of the implied skewness of the model prices of VIX options.
SSRN
VIX futures and option are the most popular contracts traded in the Chicago Board Options Exchange. The bid-ask spreads of traded VIX derivatives remain to be wide, possibly due to lack of reliable pricing models. In this paper, we consider pricing VIX derivatives under the consistent model approach, which considers joint modeling of the dynamics of S&P index and its instantaneous variance. Under the affine jump-diffusion formulation with stochastic volatility, analytic integral formulas can be derived to price VIX futures and option. However, these integral formulas invariably involve Fourier inversion integrals with cumbersome hyper-geometric functions, thus posing various challenges in numerical evaluation. We propose a unified numerical approach based on the willow tree algorithms to price VIX derivatives under various common types of joint process of the S&P index and its instantaneous variance. Given the analytic form of the characteristic function of the instantaneous variance of the S&P index process in the Fourier domain, we apply the fast Fourier transform algorithm to obtain the transition density function numerically in the real domain. We then construct the willow tree that approximates the dynamics of the instantaneous variance process up to the fourth order moment. Our comprehensive numerical tests performed on the willow tree algorithms demonstrate high level of numerical accuracy, run time efficiency and reliability for pricing VIX futures and both European and American options under the affine model and 3/2-model. We also examine the implied volatility smirks and the term structures of the implied skewness of the model prices of VIX options.
