Research articles for the 2021-02-19
A Factor Model of Company Relative Valuation
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Accurate company valuation is the starting point of value investing and corporate decisions. This paper proposes a statistical factor model to generate company valuation comparison across a large universe. The model scales the market value of a company by its book capital to generate a cross-sectionally comparable relative value target, constructs valuation factors by combining several descriptors from a similar category to increase coverage and reduce multicollinearity, and links industry classification and the valuation factors to the company relative value via a cross-sectional contemporaneous regression at each date. Historical analysis on U.S. publicly traded companies shows that the factor model explains a large proportion of the cross-sectional variation of company relative value and experiences little out-of-sample degeneration. The regression residual represents temporary company misvaluation, and can be exploited by both outside investors as attractive investment opportunities and internal management for market timing of corporate decisions.
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Accurate company valuation is the starting point of value investing and corporate decisions. This paper proposes a statistical factor model to generate company valuation comparison across a large universe. The model scales the market value of a company by its book capital to generate a cross-sectionally comparable relative value target, constructs valuation factors by combining several descriptors from a similar category to increase coverage and reduce multicollinearity, and links industry classification and the valuation factors to the company relative value via a cross-sectional contemporaneous regression at each date. Historical analysis on U.S. publicly traded companies shows that the factor model explains a large proportion of the cross-sectional variation of company relative value and experiences little out-of-sample degeneration. The regression residual represents temporary company misvaluation, and can be exploited by both outside investors as attractive investment opportunities and internal management for market timing of corporate decisions.
A General Framework for a Joint Calibration of VIX and VXX Options
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We analyze the VIX futures market with a focus on the exchange-traded notes written on such contracts, in particular, we investigate the VXX notes tracking the short-end part of the futures term structure. Inspired by recent developments in commodity smile modeling, we present a multi-factor stochastic local-volatility model able to jointly calibrate plain vanilla options both on VIX futures and VXX notes. We discuss numerical results on real market data by highlighting the impact of model parameters on implied volatilities.
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We analyze the VIX futures market with a focus on the exchange-traded notes written on such contracts, in particular, we investigate the VXX notes tracking the short-end part of the futures term structure. Inspired by recent developments in commodity smile modeling, we present a multi-factor stochastic local-volatility model able to jointly calibrate plain vanilla options both on VIX futures and VXX notes. We discuss numerical results on real market data by highlighting the impact of model parameters on implied volatilities.
A Simple Solution to the Multi-dimensionality in Option Pricing
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We devise a method to circumvent the complexity that arises from the option multi-dimensionality. That is, we transform the model to make it as simple as the one-dimensional case. Furthermore, the assumption of comonotonicity and other assumptions regarding the structure of the underlying asset become needless.
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We devise a method to circumvent the complexity that arises from the option multi-dimensionality. That is, we transform the model to make it as simple as the one-dimensional case. Furthermore, the assumption of comonotonicity and other assumptions regarding the structure of the underlying asset become needless.
Abnormal Returns and Dispersion in Cybersecurity Exposure
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This paper examines the dispersion in cybersecurity risk across firms. Using new, proprietary data on the Fortune 500 firms, We show that higher productivity firms exhibit abnormal returns. We subsequently document three new facts: (a) higher productivity firms have fewer cybersecurity vulnerabilities, (b) vulnerabilities are highly persistent within-firm, and (c) vulnerabilities are associated with data breaches. Our results suggest that higher productivity firms gain access to more technical human capital resources that are capable of mitigating cybersecurity vulnerabilities.
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This paper examines the dispersion in cybersecurity risk across firms. Using new, proprietary data on the Fortune 500 firms, We show that higher productivity firms exhibit abnormal returns. We subsequently document three new facts: (a) higher productivity firms have fewer cybersecurity vulnerabilities, (b) vulnerabilities are highly persistent within-firm, and (c) vulnerabilities are associated with data breaches. Our results suggest that higher productivity firms gain access to more technical human capital resources that are capable of mitigating cybersecurity vulnerabilities.
Accounting Information and Risk Shifting with Asymmetrically Informed Creditors
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This paper explores the effects of public information (e.g., accounting earnings) in a competitive lending setting where the borrower can engage in risk shifting. If a privately informed "inside" creditor bids against outsider creditors, public information levels the playing field with nontrivial effects on bidding and risk-shifting. A perfect public signal would yield the least efficient outcome: introducing some measurement noise alleviates risk shifting by subjecting the outsider to the winner's curse. However, for pessimistic priors about the borrower, greater precision can alleviate risk shifting, locally. We derive conditions under which greater signal precision lowers the probability of creditor turnover and discuss implications for financial reporting regulations along the business cycle.
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This paper explores the effects of public information (e.g., accounting earnings) in a competitive lending setting where the borrower can engage in risk shifting. If a privately informed "inside" creditor bids against outsider creditors, public information levels the playing field with nontrivial effects on bidding and risk-shifting. A perfect public signal would yield the least efficient outcome: introducing some measurement noise alleviates risk shifting by subjecting the outsider to the winner's curse. However, for pessimistic priors about the borrower, greater precision can alleviate risk shifting, locally. We derive conditions under which greater signal precision lowers the probability of creditor turnover and discuss implications for financial reporting regulations along the business cycle.
Analyst Team Diversity and Analyst Performance
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We examine the impact of informational and social analyst team diversity on forecast performance. We find that informational diversity is associated with less timely forecasts, whilst it is associated with more accurate forecasts. These findings are consistent with the group dynamics literature which indicates that the more diversified the skillsets of individuals the more beneficial their decision-making. Further analysis indicates the benefits of diversity is more pronounced when the forecast firm is more complex, but moderated when the brokerage house has greater access to proprietary information. We also find informational diversity decrease an analyst’s probability of gaining star status, confirming the benefits of a homophilic environment. Overall, our findings suggest that whichever is the greater need, accuracy or timeliness, will govern the choice of whether to build an informationally diverse analyst team.
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We examine the impact of informational and social analyst team diversity on forecast performance. We find that informational diversity is associated with less timely forecasts, whilst it is associated with more accurate forecasts. These findings are consistent with the group dynamics literature which indicates that the more diversified the skillsets of individuals the more beneficial their decision-making. Further analysis indicates the benefits of diversity is more pronounced when the forecast firm is more complex, but moderated when the brokerage house has greater access to proprietary information. We also find informational diversity decrease an analyst’s probability of gaining star status, confirming the benefits of a homophilic environment. Overall, our findings suggest that whichever is the greater need, accuracy or timeliness, will govern the choice of whether to build an informationally diverse analyst team.
Arbitraging Covered Interest Rate Parity Deviations and Bank Lending
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I propose and test a new channel through which bank lending is affected in an emerging markets setting. This channel is that when banks arbitrage covered interest rate parity (CIP) deviations, they need to borrow in a particular currency. In the presence of borrowing frictions, they shift part of the resources used to lend to households and firms to fund their arbitrage activities. I exploit differences the abilities of Peruvian banks to arbitrage CIP deviations to show that banks that have greater ability to arbitrage reduce their lending in the currency they need to fund their CIP arbitrage. This is compensated by lending in a different currency. Therefore, arbitraging CIP deviations lead to changes in the currency composition of lending.
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I propose and test a new channel through which bank lending is affected in an emerging markets setting. This channel is that when banks arbitrage covered interest rate parity (CIP) deviations, they need to borrow in a particular currency. In the presence of borrowing frictions, they shift part of the resources used to lend to households and firms to fund their arbitrage activities. I exploit differences the abilities of Peruvian banks to arbitrage CIP deviations to show that banks that have greater ability to arbitrage reduce their lending in the currency they need to fund their CIP arbitrage. This is compensated by lending in a different currency. Therefore, arbitraging CIP deviations lead to changes in the currency composition of lending.
Are Stock-Market Anomalies Anomalous After All?
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We propose a stochastic spanning to evaluate whether anomalies are genuine under factor-model framework. Our approach is nonparametric and does not rely on any assumption of return distribution and investor risk preferences. It depends on the whole distribution of returns, rather than only on the first two moments. Of the anomalies we consider, only a few expand the opportunity set of the risk-averter and have real economic content. Our approach is consistent in identifying genuine anomalies in and out of samples. This is in contrast to mean-variance (MV) spanning tests where anomalies identified in-sample, not out-of-sample.
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We propose a stochastic spanning to evaluate whether anomalies are genuine under factor-model framework. Our approach is nonparametric and does not rely on any assumption of return distribution and investor risk preferences. It depends on the whole distribution of returns, rather than only on the first two moments. Of the anomalies we consider, only a few expand the opportunity set of the risk-averter and have real economic content. Our approach is consistent in identifying genuine anomalies in and out of samples. This is in contrast to mean-variance (MV) spanning tests where anomalies identified in-sample, not out-of-sample.
Board Governance and Investment Sensitivity to Stock Price: International Evidence
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This paper examines the effect of board governance on investment efficiency. I use the staggered enactment of board reforms in 41 countries as a shock to board structure that exogenously improves the quality of board oversight of managers. I find that investmentâ€"Q sensitivity improves by almost half post-reform. This effect is more pronounced for firms that are more exposed to the reforms or when external governance mechanisms are less likely to discipline managers. These findings suggest that increased board oversight strengthens managers’ incentives to make investment decisions that are more in line with their firms’ growth opportunities.
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This paper examines the effect of board governance on investment efficiency. I use the staggered enactment of board reforms in 41 countries as a shock to board structure that exogenously improves the quality of board oversight of managers. I find that investmentâ€"Q sensitivity improves by almost half post-reform. This effect is more pronounced for firms that are more exposed to the reforms or when external governance mechanisms are less likely to discipline managers. These findings suggest that increased board oversight strengthens managers’ incentives to make investment decisions that are more in line with their firms’ growth opportunities.
Central Bank Issued Digital Currencies
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Digital payments are essential to the functioning of a modern economy, yet pose challenges to the prudential supervision of the financial system. At the same time, the use of physical cash persists in most countries due to its ease of use and the perceived or actual advantages of anonymity. A digital currency is seen as a possible solution to the oversight problem and a suitable instrument for modernising trade and exchange through the elimination of physical cash and its attendant production, storage and transport costs as well as its unsuitability for online payments. In this paper, we provide a non-technical overview of the advantages a central bank issued digital currency (CBDC), mechanisms through which such a currency can be implemented and how it might interact with the conventional banking system. The discussion includes but is not limited to distributed ledgers and we briefly consider the examples of three pilot CBDC projects.
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Digital payments are essential to the functioning of a modern economy, yet pose challenges to the prudential supervision of the financial system. At the same time, the use of physical cash persists in most countries due to its ease of use and the perceived or actual advantages of anonymity. A digital currency is seen as a possible solution to the oversight problem and a suitable instrument for modernising trade and exchange through the elimination of physical cash and its attendant production, storage and transport costs as well as its unsuitability for online payments. In this paper, we provide a non-technical overview of the advantages a central bank issued digital currency (CBDC), mechanisms through which such a currency can be implemented and how it might interact with the conventional banking system. The discussion includes but is not limited to distributed ledgers and we briefly consider the examples of three pilot CBDC projects.
Corporate Governance and Corporate Social Responsibility
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We study how corporate governance affects corporate social responsibility (CSR) using the 2013 CSR regulation in India that mandates qualifying firms to spend 2 percent of the pre-tax profits on CSR. Controlling for the endogeneous association of corporate governance and CSR choices, we demonstrate that the formation of CSR committees and appointment of directors with relevant experience (CSR-Directors) increases the compliance to the CSR law by 11 percent. Further, we show that CSR-Directors affect compliance by reducing the cost of compliance. This effect is larger for companies in more competitive industries, companies with higher debt, and companies with no previous history of CSR. Companies with higher CSR compliance gain in value and have increased creditworthiness.
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We study how corporate governance affects corporate social responsibility (CSR) using the 2013 CSR regulation in India that mandates qualifying firms to spend 2 percent of the pre-tax profits on CSR. Controlling for the endogeneous association of corporate governance and CSR choices, we demonstrate that the formation of CSR committees and appointment of directors with relevant experience (CSR-Directors) increases the compliance to the CSR law by 11 percent. Further, we show that CSR-Directors affect compliance by reducing the cost of compliance. This effect is larger for companies in more competitive industries, companies with higher debt, and companies with no previous history of CSR. Companies with higher CSR compliance gain in value and have increased creditworthiness.
Current Corporate Tax Rates: A Ranking of 223 Countries
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This study ranks 223 countries based on their top corporate tax rate. Rates vary from 0-50 percent.
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This study ranks 223 countries based on their top corporate tax rate. Rates vary from 0-50 percent.
Dealer Networks and the Cost of Immediacy
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We show that uninformed corporate bond index trackers pay lower transaction costs when they request immediacy from more central dealers in the network. This centrality discount supports recent network models in which core dealers have a comparative advantage in carrying inventory. Core dealers provide more immediacy and revert deviations from their desired inventory faster. When dealers trade with other dealers, we find a centrality premium consistent with core dealers exploiting their comparative advantage to extract more surplus when bargaining with peripheral dealers. Using trades around index exclusions rule out alternative explanations based on adverse selection, customer bargaining power, and customer clienteles.
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We show that uninformed corporate bond index trackers pay lower transaction costs when they request immediacy from more central dealers in the network. This centrality discount supports recent network models in which core dealers have a comparative advantage in carrying inventory. Core dealers provide more immediacy and revert deviations from their desired inventory faster. When dealers trade with other dealers, we find a centrality premium consistent with core dealers exploiting their comparative advantage to extract more surplus when bargaining with peripheral dealers. Using trades around index exclusions rule out alternative explanations based on adverse selection, customer bargaining power, and customer clienteles.
ESG Incidents and Shareholder Value
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This paper uses novel environmental, social, and governance (ESG) incident news data to study poor ESG practices. I find that firms’ past ESG incident rates predict more incidents, weaker profits, and lower risk-adjusted stock returns. When examining the cause of these abnormal returns, I find analyst forecast errors as well as lower returns around earnings announcements and subsequent incidents. Moreover, incident rates predict stronger abnormal returns in firms with higher short-term ownership, higher valuation uncertainty, and lower investor attention. Overall, these findings suggest that poor ESG practices negatively impact long-term value, which is not fully reflected in stock prices.
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This paper uses novel environmental, social, and governance (ESG) incident news data to study poor ESG practices. I find that firms’ past ESG incident rates predict more incidents, weaker profits, and lower risk-adjusted stock returns. When examining the cause of these abnormal returns, I find analyst forecast errors as well as lower returns around earnings announcements and subsequent incidents. Moreover, incident rates predict stronger abnormal returns in firms with higher short-term ownership, higher valuation uncertainty, and lower investor attention. Overall, these findings suggest that poor ESG practices negatively impact long-term value, which is not fully reflected in stock prices.
Evolution of Price Effects After One-Day of Abnormal Returns in the US Stock Market
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This paper provides a comprehensive analysis of price effects after one-day abnormal returns and their evolution in the US stock market for the case of Dow Jones Index over the period 1890-2018. Using different statistical tests (both parametrical and non-parametrical) as well as additional technics like modified cumulative abnormal returns approach, regression analysis with dummy variables, R/S analysis and a trading simulation approach; four hypotheses were tested, which are (H1): the after one-day of abnormal returns specific price effects (momentum/ contrarian) do appear; (H2): the price effects after one-day of abnormal returns vary in time and evolve; (H3): the price effects after one-day of abnormal returns can be exploited to generate profits from trading; and (H4): the level of persistence in anomalies related data set differs from the normal data set persistence. The results suggest that price effects after one-day abnormal returns during the analyzed period tend to be rather unstable both from the position of their strength and direction (momentum or contrarian effect). Between the 1940s and the 1980s a strong momentum effect after a day of positive abnormal returns was present and it was exploitable for profit. However, after the 1980s this has since disappeared. Nowadays the after one-day of abnormal returns price effects in the US stock market are rather weak and do not generate profit opportunities. The results, therefore, are consistent with the Adaptive Market Hypothesis.
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This paper provides a comprehensive analysis of price effects after one-day abnormal returns and their evolution in the US stock market for the case of Dow Jones Index over the period 1890-2018. Using different statistical tests (both parametrical and non-parametrical) as well as additional technics like modified cumulative abnormal returns approach, regression analysis with dummy variables, R/S analysis and a trading simulation approach; four hypotheses were tested, which are (H1): the after one-day of abnormal returns specific price effects (momentum/ contrarian) do appear; (H2): the price effects after one-day of abnormal returns vary in time and evolve; (H3): the price effects after one-day of abnormal returns can be exploited to generate profits from trading; and (H4): the level of persistence in anomalies related data set differs from the normal data set persistence. The results suggest that price effects after one-day abnormal returns during the analyzed period tend to be rather unstable both from the position of their strength and direction (momentum or contrarian effect). Between the 1940s and the 1980s a strong momentum effect after a day of positive abnormal returns was present and it was exploitable for profit. However, after the 1980s this has since disappeared. Nowadays the after one-day of abnormal returns price effects in the US stock market are rather weak and do not generate profit opportunities. The results, therefore, are consistent with the Adaptive Market Hypothesis.
Financial Covenants, Firm Financing, and Investment
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Firms reduce investment to avoid costly violations of financial covenants, most of which are based on earnings. Empirically, I show that a 25% drop in earnings implies a 15% decrease in investment for the median listed US firm due to the reduced distance to the covenant threshold. To quantify this precautionary effect of covenants in the aggregate, I incorporate earnings covenants into a heterogeneous firm model with a financial sector. Firms in the model are uncertain about the bank’s reaction to a covenant breach and therefore reduce debt issuance and investment when approaching the covenant threshold. In the model, covenants reduce aggregate investment by 14% relative to a benchmark economy without limits on borrowing, where the precautionary effect of covenants accounts for most of the decrease.
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Firms reduce investment to avoid costly violations of financial covenants, most of which are based on earnings. Empirically, I show that a 25% drop in earnings implies a 15% decrease in investment for the median listed US firm due to the reduced distance to the covenant threshold. To quantify this precautionary effect of covenants in the aggregate, I incorporate earnings covenants into a heterogeneous firm model with a financial sector. Firms in the model are uncertain about the bank’s reaction to a covenant breach and therefore reduce debt issuance and investment when approaching the covenant threshold. In the model, covenants reduce aggregate investment by 14% relative to a benchmark economy without limits on borrowing, where the precautionary effect of covenants accounts for most of the decrease.
Financial Crisis, Trust, and Religious Intensity
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An extant literature rooted in Iannaconne’s club-theoretic approach, advances a social insurance channel via which financial crises lead to increases in religious intensity defined to include religious affiliation and participation. Since variation in religious intensity has implications for; savings behavior, the incidence of religiously motivated terrorism, and the fraction of total resources allocated to religious practice, this social insurance channel implies that the socioeconomic effects of financial crises extends beyond the effects suggested by traditional channels. However, the absence of a demand for supernaturalism in the club-theoretic approach, -- despite the widely held view that religiosity reflects a fundamental demand for supernaturalism -- raises doubt about the adequacy if not validity of the social insurance channel. In light of the foregoing, we deploy an alternative theoretical framework which explicitly incorporates a demand for supernaturalism and implies a relative trust channel in which financial crises affect religious intensity by altering laypeople’s trust in religious organizations relative to their trust in secular institutions. Using responses to survey questions from the General Social Survey for the years 2006, 2008, and 2010, and the yield spread between Baa corporate bonds and ten-year US government bonds as a proxy for financial crisis, we assess the empirical validity of the relative trust channel by deploying Zellner’s SUR approach to test the joint hypothesis that the 2007-2009 financial crisis induced changes in religious participation and affiliation in the US and that it did so by affecting relative trust. Overall, our results confirm the existence of the relative trust channel.
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An extant literature rooted in Iannaconne’s club-theoretic approach, advances a social insurance channel via which financial crises lead to increases in religious intensity defined to include religious affiliation and participation. Since variation in religious intensity has implications for; savings behavior, the incidence of religiously motivated terrorism, and the fraction of total resources allocated to religious practice, this social insurance channel implies that the socioeconomic effects of financial crises extends beyond the effects suggested by traditional channels. However, the absence of a demand for supernaturalism in the club-theoretic approach, -- despite the widely held view that religiosity reflects a fundamental demand for supernaturalism -- raises doubt about the adequacy if not validity of the social insurance channel. In light of the foregoing, we deploy an alternative theoretical framework which explicitly incorporates a demand for supernaturalism and implies a relative trust channel in which financial crises affect religious intensity by altering laypeople’s trust in religious organizations relative to their trust in secular institutions. Using responses to survey questions from the General Social Survey for the years 2006, 2008, and 2010, and the yield spread between Baa corporate bonds and ten-year US government bonds as a proxy for financial crisis, we assess the empirical validity of the relative trust channel by deploying Zellner’s SUR approach to test the joint hypothesis that the 2007-2009 financial crisis induced changes in religious participation and affiliation in the US and that it did so by affecting relative trust. Overall, our results confirm the existence of the relative trust channel.
Fiscal Transparency or Fiscal Illusion? Housing and Credit Market Responses to Fiscal Monitoring
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Nongovernmental stakeholders, including taxpayers and investors of government bonds, have an interest in government financial information. Fiscal transparency entails both access to and understandability of government information. Analyses of a government borrower’s financial information, often facilitated by market intermediaries, directly affect investor return on the bond market. In contrast, taxpayers may lack the incentive or capacity to comprehend government financial data prepared based on complex accounting rules. State fiscal monitoring programs compile and analyze local government financial data to track fiscal stress. This paper examines how housing and municipal bond markets respond to the New York monitoring program implemented in 2013, which uses existing, account-level local government financial data to assign simple labels signifying local government insolvency. Housing prices decreased following significant fiscal stress designations, but not statistically significantly following the other more modest stress labels. In contrast, the bond market priced in government financial information even before the state monitoring.
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Nongovernmental stakeholders, including taxpayers and investors of government bonds, have an interest in government financial information. Fiscal transparency entails both access to and understandability of government information. Analyses of a government borrower’s financial information, often facilitated by market intermediaries, directly affect investor return on the bond market. In contrast, taxpayers may lack the incentive or capacity to comprehend government financial data prepared based on complex accounting rules. State fiscal monitoring programs compile and analyze local government financial data to track fiscal stress. This paper examines how housing and municipal bond markets respond to the New York monitoring program implemented in 2013, which uses existing, account-level local government financial data to assign simple labels signifying local government insolvency. Housing prices decreased following significant fiscal stress designations, but not statistically significantly following the other more modest stress labels. In contrast, the bond market priced in government financial information even before the state monitoring.
Forecasting Earnings Using k-Nearest Neighbor Matching
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We use the k-nearest neighbors (i.e., k-NN) algorithm to forecast a firm’s annual earnings by matching its recent trend in annual earnings to historical earnings sequences of “neighbor†firms. Our forecasts are more accurate than forecasts obtained from the random walk, the regression model developed by Hou, van Dijk and Zhang (2012), other regression models and the matching approach described in Blouin, Core and Guay (2010). The k-NN model is superior to these alternative models both when analysts’ forecasts are available and when they are not. Further, for firm-years with I/B/E/S earnings data available, the accuracy of k-NN forecasts of I/B/E/S earnings is similar to the accuracy of analysts’ forecasts. The k-NN model is also superior to a random forest classifier that we use to choose the best model ex-ante. Finally, we find that our forecasts of earnings changes have a positive association with future stock returns.
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We use the k-nearest neighbors (i.e., k-NN) algorithm to forecast a firm’s annual earnings by matching its recent trend in annual earnings to historical earnings sequences of “neighbor†firms. Our forecasts are more accurate than forecasts obtained from the random walk, the regression model developed by Hou, van Dijk and Zhang (2012), other regression models and the matching approach described in Blouin, Core and Guay (2010). The k-NN model is superior to these alternative models both when analysts’ forecasts are available and when they are not. Further, for firm-years with I/B/E/S earnings data available, the accuracy of k-NN forecasts of I/B/E/S earnings is similar to the accuracy of analysts’ forecasts. The k-NN model is also superior to a random forest classifier that we use to choose the best model ex-ante. Finally, we find that our forecasts of earnings changes have a positive association with future stock returns.
Frequent Batch Auctions Under Liquidity Constraints
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We exploit European regulatory interventions to investigate the effects of sub-second periodic auctions on market quality under dark trading restrictions. The restrictions are linked to an observable increase in periodic auctions and an economically meaningful loss of liquidity. While periodic auctions ameliorate illiquidity, their effects are significantly less than those of the restrictions; therefore, the combined effects of periodic auctions’ increases and the restrictions are general declines in liquidity and informational efficiency. However, consistent with theory, periodic auctions are linked to reductions in adverse selection costs, thereby underscoring their potential to address latency arbitrage and the technological arms race.
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We exploit European regulatory interventions to investigate the effects of sub-second periodic auctions on market quality under dark trading restrictions. The restrictions are linked to an observable increase in periodic auctions and an economically meaningful loss of liquidity. While periodic auctions ameliorate illiquidity, their effects are significantly less than those of the restrictions; therefore, the combined effects of periodic auctions’ increases and the restrictions are general declines in liquidity and informational efficiency. However, consistent with theory, periodic auctions are linked to reductions in adverse selection costs, thereby underscoring their potential to address latency arbitrage and the technological arms race.
How Does Leasing Affect Leverage
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Leasing's impact on leverage remains an open debate in the literature. Some argue that leasing and secured debt are substitutes, while others argue that leasing can preserve secured debt capacity and facilitate greater borrowing. I exploit a Moody's accounting policy change that unexpectedly made leasing less costly from a credit ratings perspective and resulted in an economically meaningful increase in leasing. Alongside this uptick in leasing, I find that secured debt decreased on average. I also find that leasing has a non-negative impact on secured debt capacity. While leasing preserves secured debt capacity across the sample of firms, only high investment opportunity firms use their secured debt capacity to increase secured borrowing. Firms with low investment opportunities, lacking reason to increase aggregate financing, substitute out secured debt when leases increase.
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Leasing's impact on leverage remains an open debate in the literature. Some argue that leasing and secured debt are substitutes, while others argue that leasing can preserve secured debt capacity and facilitate greater borrowing. I exploit a Moody's accounting policy change that unexpectedly made leasing less costly from a credit ratings perspective and resulted in an economically meaningful increase in leasing. Alongside this uptick in leasing, I find that secured debt decreased on average. I also find that leasing has a non-negative impact on secured debt capacity. While leasing preserves secured debt capacity across the sample of firms, only high investment opportunity firms use their secured debt capacity to increase secured borrowing. Firms with low investment opportunities, lacking reason to increase aggregate financing, substitute out secured debt when leases increase.
Informational Friction, Economic Uncertainty and CDS-Bond Basis
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We study how macroeconomic uncertainty (EU) manifests into the cross-sectional variations of the credit default swap (CDS)-bond bases. We develop a structural model in which common EU induces informational friction affecting the pricing in the bond and CDS markets. Higher EU will lead to a larger cross-sectional divergence in the bases. Furthermore, the difference between the two markets' exposure to EU measured by the EU betas can predict cross-sectional variations in the bases, which is confirmed in our empirical study. We also study the practical implication of EU as a new basis determinant in the context of the basis arbitrage.
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We study how macroeconomic uncertainty (EU) manifests into the cross-sectional variations of the credit default swap (CDS)-bond bases. We develop a structural model in which common EU induces informational friction affecting the pricing in the bond and CDS markets. Higher EU will lead to a larger cross-sectional divergence in the bases. Furthermore, the difference between the two markets' exposure to EU measured by the EU betas can predict cross-sectional variations in the bases, which is confirmed in our empirical study. We also study the practical implication of EU as a new basis determinant in the context of the basis arbitrage.
Inter-Firm Relationships and the Special Role of Common Banks
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Using a novel dataset that combines information on customer-supplier trade relationships with information on firm-bank lending relationships, we show that common banks that lend to firms at both ends of a trade link strengthen such trade relationships. We use bank mergers that exogenously generate variations in common bank relationships to establish causality and show that common bank relationships between customers and suppliers increase key trade relationships by 40.4%. We argue that common banks bridge information gaps between trading partners and mitigate hold-up problems. Consistent with this hypothesis, we show that firms with a higher share of trading partners with whom they also share common banks invest more in relationship specific assets. The role of common bank is greater for more opaque supply chains and when the common bank is more informed. Lastly, we show that common banks played a central role in facilitating provision of trade credit by suppliers during the Great Recession. Overall, our findings show the unique role of banks in driving inter-firm growth.
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Using a novel dataset that combines information on customer-supplier trade relationships with information on firm-bank lending relationships, we show that common banks that lend to firms at both ends of a trade link strengthen such trade relationships. We use bank mergers that exogenously generate variations in common bank relationships to establish causality and show that common bank relationships between customers and suppliers increase key trade relationships by 40.4%. We argue that common banks bridge information gaps between trading partners and mitigate hold-up problems. Consistent with this hypothesis, we show that firms with a higher share of trading partners with whom they also share common banks invest more in relationship specific assets. The role of common bank is greater for more opaque supply chains and when the common bank is more informed. Lastly, we show that common banks played a central role in facilitating provision of trade credit by suppliers during the Great Recession. Overall, our findings show the unique role of banks in driving inter-firm growth.
Late-career Unemployment Shocks, Pension Outcomes and Unemployment Insurance
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In response to unemployment shocks, older workers deplete their 401(k)s, particularly after the waiving of the early withdrawal penalty on unemployment-motivated withdrawals at age 55. This paper shows that Unemployment Insurance (UI) keeps older workers from depleting their 401(k) assets following job losses. UI also incentivizes older unemployed workers to delay claiming their Social Security (SS) benefits beyond the earliest age of eligibility, 62. Overall, UI enhances the retirement income of the individuals having a history of late-career layoffs by helping them preserve their 401(k) assets, the return on these assets and opt for a higher stream of SS benefits
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In response to unemployment shocks, older workers deplete their 401(k)s, particularly after the waiving of the early withdrawal penalty on unemployment-motivated withdrawals at age 55. This paper shows that Unemployment Insurance (UI) keeps older workers from depleting their 401(k) assets following job losses. UI also incentivizes older unemployed workers to delay claiming their Social Security (SS) benefits beyond the earliest age of eligibility, 62. Overall, UI enhances the retirement income of the individuals having a history of late-career layoffs by helping them preserve their 401(k) assets, the return on these assets and opt for a higher stream of SS benefits
Lenders’ Culture and the Pricing of US Public Corruption in Corporate Loans
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We investigate how the cultural heritage of the CEOs of banks acting as lead lenders in the US syndicated loan market shapes the relationship between public corruption and the cost of bank loans. We find strong evidence that banks led by CEOs originating from higher uncertainty avoidance societies penalize less sharply, in terms of the cost of bank loans, the presence of high local public corruption in the state of the borrowing firms. We find some similar evidence for banks led by CEOs that trace their origins to more individualistic societies. These results are robust to several tests that address concerns such as the matching between borrowing firms from states with high corruption and the cultural heritage of bank CEOs, omitted variable issues, endogeneity, and after controlling for several CEO and bank characteristics. These findings are consistent with the view that certain cultural heritage traits prompt tolerance for the risks of corruption and show that the pricing of institutional quality in corporate loans is conditional on banks led by CEOs with such traits.
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We investigate how the cultural heritage of the CEOs of banks acting as lead lenders in the US syndicated loan market shapes the relationship between public corruption and the cost of bank loans. We find strong evidence that banks led by CEOs originating from higher uncertainty avoidance societies penalize less sharply, in terms of the cost of bank loans, the presence of high local public corruption in the state of the borrowing firms. We find some similar evidence for banks led by CEOs that trace their origins to more individualistic societies. These results are robust to several tests that address concerns such as the matching between borrowing firms from states with high corruption and the cultural heritage of bank CEOs, omitted variable issues, endogeneity, and after controlling for several CEO and bank characteristics. These findings are consistent with the view that certain cultural heritage traits prompt tolerance for the risks of corruption and show that the pricing of institutional quality in corporate loans is conditional on banks led by CEOs with such traits.
Machine Learning, Market Manipulation and Collusion on Capital Markets: Why the 'Black Box' matters
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This paper offers a novel perspective on the implications of increasingly autonomous and “black box†algorithms, within the ramification of algorithmic trading, for the integrity of capital markets. Artificial intelligence (AI) and particularly its subfield of machine learning (ML) methods have gained immense popularity among the great public and achieved tremendous success in many real-life applications by leading to vast efficiency gains. In the financial trading domain, ML can augment human capabilities in both price prediction, dynamic portfolio optimization, and other financial decision-making tasks. However, thanks to constant progress in the ML technology, the prospect of increasingly capable and autonomous agents to delegate operational tasks and even decision-making is now beyond mere imagination, thus opening up the possibility for approximating (truly) autonomous trading agents anytime soon.Given these spectacular developments, this paper argues that such autonomous algorithmic traders may involve significant risks to market integrity, independent from their human experts, thanks to self-learning capabilities offered by state-of-the-art and innovative ML methods. Using the proprietary trading industry as a case study, we explore emerging threats to the application of established market abuse laws in the event of algorithmic market abuse, by taking an interdisciplinary stance between financial regulation, law & economics, and computational finance. Specifically, our analysis focuses on two emerging market abuse risks by autonomous algorithms: market manipulation and “tacit†collusion. We explore their likelihood to arise on global capital markets and evaluate related social harm as forms of market failures.With these new risks in mind, this paper questions the adequacy of existing regulatory frameworks and enforcement mechanisms, as well as current legal rules on the governance of algorithmic trading, to cope with increasingly autonomous and ubiquitous algorithmic trading systems. It shows how the “black box†nature of specific ML-powered algorithmic trading strategies can subvert existing market abuse laws, which are based upon traditional liability concepts and tests (such as “intent†and “causationâ€). In concluding, by addressing the shortcomings of the present legal framework, we develop a number of guiding principles to assist legal and policy reform in the spirit of promoting and safeguarding market integrity and safety.
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This paper offers a novel perspective on the implications of increasingly autonomous and “black box†algorithms, within the ramification of algorithmic trading, for the integrity of capital markets. Artificial intelligence (AI) and particularly its subfield of machine learning (ML) methods have gained immense popularity among the great public and achieved tremendous success in many real-life applications by leading to vast efficiency gains. In the financial trading domain, ML can augment human capabilities in both price prediction, dynamic portfolio optimization, and other financial decision-making tasks. However, thanks to constant progress in the ML technology, the prospect of increasingly capable and autonomous agents to delegate operational tasks and even decision-making is now beyond mere imagination, thus opening up the possibility for approximating (truly) autonomous trading agents anytime soon.Given these spectacular developments, this paper argues that such autonomous algorithmic traders may involve significant risks to market integrity, independent from their human experts, thanks to self-learning capabilities offered by state-of-the-art and innovative ML methods. Using the proprietary trading industry as a case study, we explore emerging threats to the application of established market abuse laws in the event of algorithmic market abuse, by taking an interdisciplinary stance between financial regulation, law & economics, and computational finance. Specifically, our analysis focuses on two emerging market abuse risks by autonomous algorithms: market manipulation and “tacit†collusion. We explore their likelihood to arise on global capital markets and evaluate related social harm as forms of market failures.With these new risks in mind, this paper questions the adequacy of existing regulatory frameworks and enforcement mechanisms, as well as current legal rules on the governance of algorithmic trading, to cope with increasingly autonomous and ubiquitous algorithmic trading systems. It shows how the “black box†nature of specific ML-powered algorithmic trading strategies can subvert existing market abuse laws, which are based upon traditional liability concepts and tests (such as “intent†and “causationâ€). In concluding, by addressing the shortcomings of the present legal framework, we develop a number of guiding principles to assist legal and policy reform in the spirit of promoting and safeguarding market integrity and safety.
Narrow Framing and Under-Diversification: Empirical Evidence from Chinese Households
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“Narrow framing†is a widely documented behavioral bias that predicts, instead of evaluating all their risk components as a whole, people often evaluate risks in isolation, separately from other risks they are already facing. Using representative survey data from the China Household Finance Survey (CHFS), we estimate the extent of narrow framing among Chinese households, using their portfolio choices. Conditional on stock market participation, we find most Chinese households exhibit significant narrow framing. Based on the obtained estimates, we investigate whether the variation in narrow framing can help to explain households’ diversification decisions cross-sectionally. Our results support the theory that narrow framing negatively predicts the extent of diversification. Most importantly, we argue that narrow framing is an irreplaceable ingredient of understanding households' portfolio choices, even after considering measurement error and a wide set of indicators of under-diversification.
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“Narrow framing†is a widely documented behavioral bias that predicts, instead of evaluating all their risk components as a whole, people often evaluate risks in isolation, separately from other risks they are already facing. Using representative survey data from the China Household Finance Survey (CHFS), we estimate the extent of narrow framing among Chinese households, using their portfolio choices. Conditional on stock market participation, we find most Chinese households exhibit significant narrow framing. Based on the obtained estimates, we investigate whether the variation in narrow framing can help to explain households’ diversification decisions cross-sectionally. Our results support the theory that narrow framing negatively predicts the extent of diversification. Most importantly, we argue that narrow framing is an irreplaceable ingredient of understanding households' portfolio choices, even after considering measurement error and a wide set of indicators of under-diversification.
Order Book Price Impact in the Chinese Soybean Futures Market
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We study the price impact of order flow in the world’s largest soybean meal futures markets. Our intraday results indicate that incoming orders can be used to explain price changes and to significantly predict future price changes. Our results are shown to be robust to various order flow measures, price aggregation approaches and data frequencies. We compare various order flow measures; finding that Order Flow Imbalance (OFI) is a more all-encompassing measure carrying greater information about price change relative to both Trade Imbalance (TI) and volume. Moreover, while both OFI and TI are shown to predict future price changes, this predictability diminishes over longer measure and price change frequency horizons.
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We study the price impact of order flow in the world’s largest soybean meal futures markets. Our intraday results indicate that incoming orders can be used to explain price changes and to significantly predict future price changes. Our results are shown to be robust to various order flow measures, price aggregation approaches and data frequencies. We compare various order flow measures; finding that Order Flow Imbalance (OFI) is a more all-encompassing measure carrying greater information about price change relative to both Trade Imbalance (TI) and volume. Moreover, while both OFI and TI are shown to predict future price changes, this predictability diminishes over longer measure and price change frequency horizons.
Persistence in the Private Debt-to-GDP Ratio: Evidence from 43 OECD Countries
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This paper investigates the degree of persistence of the private debt-to-GDP ratio in 43 OECE countries by estimating the fractional integration parameter of each series. Almost all of them are found to be highly persistent, with orders of integration around or above 1. The only exception is Argentina, where the series appears to be mean-reverting. These results highlight the key importance of macroprudential policy as one of the pillars of macro policy.
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This paper investigates the degree of persistence of the private debt-to-GDP ratio in 43 OECE countries by estimating the fractional integration parameter of each series. Almost all of them are found to be highly persistent, with orders of integration around or above 1. The only exception is Argentina, where the series appears to be mean-reverting. These results highlight the key importance of macroprudential policy as one of the pillars of macro policy.
Productivity, Managers’ Social Connections and the Great Recession
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This paper investigates whether managers’ personal connections help corporations to escape the productivity trap. Leveraging the heterogeneity in the severity of the GreatRecession across different sectors, the paper reports that (i) the Great Recession has a negative effect on corporate productivity, (ii) the effect is long-lasting and persistent, supporting a productivity-hysteresis hypothesis, (iii) the value of managers’ personal connections are counter-cyclical and indeed allow corporations to escape the productivity trap primarily via favorable credit conditions, in periods of high information asymmetries and tight credit constraints.
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This paper investigates whether managers’ personal connections help corporations to escape the productivity trap. Leveraging the heterogeneity in the severity of the GreatRecession across different sectors, the paper reports that (i) the Great Recession has a negative effect on corporate productivity, (ii) the effect is long-lasting and persistent, supporting a productivity-hysteresis hypothesis, (iii) the value of managers’ personal connections are counter-cyclical and indeed allow corporations to escape the productivity trap primarily via favorable credit conditions, in periods of high information asymmetries and tight credit constraints.
Regimes, Non-Linearities, and Price Discontinuities in Indian Energy Stocks
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We construct a representative index of largest Indian energy companies listed on the National Stock Exchange (NIFTY 50). We test for presence of regimes, non-linearities, and jumps in the price signal. We benchmark performance against alternative models, including single-regime models and models with no jumps. We then benchmark the quality of regime identification against other indices examined in the literature, such as Nikkei 225 and FTSE 100. Overall, find that our regime-switching model performs well in identifying the regimes in this comparative setting. Based on our model selection criteria, we prefer a regime-augmented model to a model that allows no regime identification. But overall, we prefer a model with jumps and regimes over those that do not allow for jump-diffusion and Markov regime-switching.
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We construct a representative index of largest Indian energy companies listed on the National Stock Exchange (NIFTY 50). We test for presence of regimes, non-linearities, and jumps in the price signal. We benchmark performance against alternative models, including single-regime models and models with no jumps. We then benchmark the quality of regime identification against other indices examined in the literature, such as Nikkei 225 and FTSE 100. Overall, find that our regime-switching model performs well in identifying the regimes in this comparative setting. Based on our model selection criteria, we prefer a regime-augmented model to a model that allows no regime identification. But overall, we prefer a model with jumps and regimes over those that do not allow for jump-diffusion and Markov regime-switching.
Regional Banking Market Structure and Emergency Loans to Small Businesses: Examining the Paycheck Protection Program during the COVID-19 Pandemic
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I examine the effects of banking market structure on small business emergency lending to respond to an economic crisis. In particular, I focus on the role of banking market concentration and the presence of community banks in contributing to the number of loans made to small businesses through the Paycheck Protection Program (PPP) during the COVID-19-induced economic shock. Existing theories expect that small business credit access is reduced by higher banking market concentration and increased by community banks. I also explore how these two market characteristics interplay in regional small business credit markets. Using the U.S. county-level data, I find that greater banking market concentration reduces the number of PPP loans per business, but the negative effect is diminished by a greater presence of community banks. Furthermore, the greater presence of community banks increases the number of PPP loans but only in a highly concentrated credit market.
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I examine the effects of banking market structure on small business emergency lending to respond to an economic crisis. In particular, I focus on the role of banking market concentration and the presence of community banks in contributing to the number of loans made to small businesses through the Paycheck Protection Program (PPP) during the COVID-19-induced economic shock. Existing theories expect that small business credit access is reduced by higher banking market concentration and increased by community banks. I also explore how these two market characteristics interplay in regional small business credit markets. Using the U.S. county-level data, I find that greater banking market concentration reduces the number of PPP loans per business, but the negative effect is diminished by a greater presence of community banks. Furthermore, the greater presence of community banks increases the number of PPP loans but only in a highly concentrated credit market.
Same Same But Different -- Stylized Facts of CTA Sub Strategies
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Using a unique dataset of daily returns of 89 programmes of Commodity Trading Advisors (CTA), we investigate the distributional properties of CTA strategies including trend following, fundamental and contrarian strategies. We find that daily data exhibits strong features of fat-tail, volatility clustering, and long memory in volatility. This is different from previous studies which are often based on monthly data. Our study contributes to the literature of stylized facts of financial markets, it also provides insights to practitioners because the information from monthly data might be misleading.
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Using a unique dataset of daily returns of 89 programmes of Commodity Trading Advisors (CTA), we investigate the distributional properties of CTA strategies including trend following, fundamental and contrarian strategies. We find that daily data exhibits strong features of fat-tail, volatility clustering, and long memory in volatility. This is different from previous studies which are often based on monthly data. Our study contributes to the literature of stylized facts of financial markets, it also provides insights to practitioners because the information from monthly data might be misleading.
Savings and Investment in Indonesia
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The main objective of this paper is to understand domestic savings and investment in Indonesia. The level of savings in Indonesia is relatively high by international standard. However, the savings through banking sector are more dominant than non-banking savings. This leads to the scarcity of long-term savings which are essential for long-term investment, especially in infrastructure, that ultimately benefit growth and development. One of the keys to promote long-term savings is through mandatory savings. At the same time, institutional investors such as insurance companies and pension funds must be encouraged to invest in long-term instruments. The role of financial sector plays a crucial role in providing such instruments. Therefore, policy recommendations must be directed to fiscal policy through tax incentives for stimulating long-term saving and investment; social welfare policy for encouraging contractual saving and developing long-term domestic institutional investors; financial market deregulation for increasing access to financial services and increasing competition among financial service providers; and coordination among sectors
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The main objective of this paper is to understand domestic savings and investment in Indonesia. The level of savings in Indonesia is relatively high by international standard. However, the savings through banking sector are more dominant than non-banking savings. This leads to the scarcity of long-term savings which are essential for long-term investment, especially in infrastructure, that ultimately benefit growth and development. One of the keys to promote long-term savings is through mandatory savings. At the same time, institutional investors such as insurance companies and pension funds must be encouraged to invest in long-term instruments. The role of financial sector plays a crucial role in providing such instruments. Therefore, policy recommendations must be directed to fiscal policy through tax incentives for stimulating long-term saving and investment; social welfare policy for encouraging contractual saving and developing long-term domestic institutional investors; financial market deregulation for increasing access to financial services and increasing competition among financial service providers; and coordination among sectors
Shrinking Boundary of the Invisible Hand
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Since the 1980s, capital allocation efficiency has been deteriorating in the United States. This paper argues that the rise of (superstar) firms and their cash hoarding behavior are reasons. I introduce entrepreneur-manager assignment and corporate risk management into a standard continuous-time heterogeneous agent model with incomplete markets. In this way, Coase (1937)'s firm-(financial) market boundary exists in general equilibrium, and the price mechanism is bounded by corporate internal financing as there is no market to equalize the marginal value of internal resources across firms. Therefore, contrary to conventional wisdom, self-financing (through safe assets) increases misallocation. The scale-related technical change in the 1980s increases the earnings-quality gradient sharply in the right tail, which not only generates a winners-take-most phenomenon but also makes current winners inherently riskier and rely less on external financing. This risk redistribution nature of technical change expands the internal financing region and impairs the capital allocation efficiency. When taken to the data, the model can quantitatively match some important macro-finance trends, and it shows that the area disciplined by the market system has declined about 11.2% during the past forty years.
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Since the 1980s, capital allocation efficiency has been deteriorating in the United States. This paper argues that the rise of (superstar) firms and their cash hoarding behavior are reasons. I introduce entrepreneur-manager assignment and corporate risk management into a standard continuous-time heterogeneous agent model with incomplete markets. In this way, Coase (1937)'s firm-(financial) market boundary exists in general equilibrium, and the price mechanism is bounded by corporate internal financing as there is no market to equalize the marginal value of internal resources across firms. Therefore, contrary to conventional wisdom, self-financing (through safe assets) increases misallocation. The scale-related technical change in the 1980s increases the earnings-quality gradient sharply in the right tail, which not only generates a winners-take-most phenomenon but also makes current winners inherently riskier and rely less on external financing. This risk redistribution nature of technical change expands the internal financing region and impairs the capital allocation efficiency. When taken to the data, the model can quantitatively match some important macro-finance trends, and it shows that the area disciplined by the market system has declined about 11.2% during the past forty years.
Socially Responsible Investing Strategies under Pressure: Evidence from COVID-19
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By matching socially responsible (SR) stock indices worldwide with their conventional benchmarks, we study the resilience of SR investment strategies during the COVID-19 crisis. Overall, SR indices exhibited dynamics very similar to their benchmarks. Our sample is composed of 573 SR stock indices from MSCI, STOXX, and FTSE. In the first half of 2020, the average daily return was â€"0.11% for SR indices and their benchmarks, with annualized volatility of 40% for each. SR indices remained very close to their benchmarks during both the “fever period†(Feb. 24-Mar. 20) and the “rebound period†(Mar. 23-May 29). However, financial performances of SR strategies exhibit substantial heterogeneity: SR impact strategies slightly out-performed their benchmarks. In addition, the resilience of SR strategies was a little stronger in countries where and during periods when the number of COVID-19 cases increased.. In robustness checks, we control for public attention to the COVID-19 pandemic, as well as the economic effects of new policies implemented during the crisis, including lockdowns, and fiscal and monetary policy changes. These findings call for a selective investment strategy by SR investors if they expect that their preferences also deliver financial outperformance in times of crisis.
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By matching socially responsible (SR) stock indices worldwide with their conventional benchmarks, we study the resilience of SR investment strategies during the COVID-19 crisis. Overall, SR indices exhibited dynamics very similar to their benchmarks. Our sample is composed of 573 SR stock indices from MSCI, STOXX, and FTSE. In the first half of 2020, the average daily return was â€"0.11% for SR indices and their benchmarks, with annualized volatility of 40% for each. SR indices remained very close to their benchmarks during both the “fever period†(Feb. 24-Mar. 20) and the “rebound period†(Mar. 23-May 29). However, financial performances of SR strategies exhibit substantial heterogeneity: SR impact strategies slightly out-performed their benchmarks. In addition, the resilience of SR strategies was a little stronger in countries where and during periods when the number of COVID-19 cases increased.. In robustness checks, we control for public attention to the COVID-19 pandemic, as well as the economic effects of new policies implemented during the crisis, including lockdowns, and fiscal and monetary policy changes. These findings call for a selective investment strategy by SR investors if they expect that their preferences also deliver financial outperformance in times of crisis.
Spillover Effects of Global Monetary Shocks on Foreign Banks: Evidence From an Emerging Economy
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This paper examines spillover effects of global monetary shocks on lending by foreign banks in an emerging country, South Korea. Foreign banks play a significant role by providing additional domestic credit and foreign currency liquidity and directing international capital flows via the banking sector. Using macroeconomic and banking data for the period of 2000Q1-2016Q2, we present evidence that foreign bank branches in Korea have responded in providing their foreign currency loans with one quarter (3-month) time lag to the changes in monetary policies in their home countries (mainly, the US and the Euro area). This short-run spillover effect of monetary policy shocks from the home countries to foreign banks in Korea seems consistent with our bank-level data analysis. The paper also discusses useful policy implications.
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This paper examines spillover effects of global monetary shocks on lending by foreign banks in an emerging country, South Korea. Foreign banks play a significant role by providing additional domestic credit and foreign currency liquidity and directing international capital flows via the banking sector. Using macroeconomic and banking data for the period of 2000Q1-2016Q2, we present evidence that foreign bank branches in Korea have responded in providing their foreign currency loans with one quarter (3-month) time lag to the changes in monetary policies in their home countries (mainly, the US and the Euro area). This short-run spillover effect of monetary policy shocks from the home countries to foreign banks in Korea seems consistent with our bank-level data analysis. The paper also discusses useful policy implications.
Stock Return Asymmetry in China
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In this paper, we find that the upside asymmetry calculated based on a new distribution-based asymmetry measure proposed by Jiang, Wu, Zhou, and Zhu (2020) is negatively related to average future returns in the cross-section of Chinese stock returns. By contrast, when using a conventional skewness measure, the relationship between asymmetry and average returns is unclear. Furthermore, the asymmetry factor constructed from the new asymmetry measure cannot be explained by the three-factor (CH-3) and four-factor (CH-4) models proposed by Liu, Stambaugh, and Yuan (2019). When augmenting the CH-3 model with our asymmetry factor, the new four-factor model is able to explain 94 anomalies out of a universe of 102 anomalies in the Chinese stock market.
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In this paper, we find that the upside asymmetry calculated based on a new distribution-based asymmetry measure proposed by Jiang, Wu, Zhou, and Zhu (2020) is negatively related to average future returns in the cross-section of Chinese stock returns. By contrast, when using a conventional skewness measure, the relationship between asymmetry and average returns is unclear. Furthermore, the asymmetry factor constructed from the new asymmetry measure cannot be explained by the three-factor (CH-3) and four-factor (CH-4) models proposed by Liu, Stambaugh, and Yuan (2019). When augmenting the CH-3 model with our asymmetry factor, the new four-factor model is able to explain 94 anomalies out of a universe of 102 anomalies in the Chinese stock market.
The Effects of Reputational Sanctions on Culpable Firms: Evidence From China’s Stock Markets
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reputational sanctions are widely used as a regulatory tool to curb corporate misconduct. However, existing literature on its workings and effectiveness is largely limited to developed economies. This paper thus endeavours to examine the case of China, focusing on public criticisms imposed on culpable firms by the two Chinese stock exchanges in Shanghai and Shenzhen. Public criticism is an important yet understudied form of reputational sanction, and thanks to its unique features, presents a very good opportunity to quantitatively measure the scale of reputational damage. This paper constructs a unique dataset of all public criticisms announced by the two Chinese stock exchanges from 2013 to 2018, providing empirical evidence on the stock price effects of reputational sanctions on culpable firms for their corporate misconduct. The paper uses event study and shows significantly negative cumulative abnormal returns around the announcement date of public criticisms, which demonstrate the general effectiveness of reputational sanctions. Further tests, however, suggest that the significant negative market reaction only appears in the firms relying on external financing and those not controlled by state ownership. Importantly, the market reaction is not significant in cases where the firm had already self-exposed misconduct before the announcement of public criticisms by the stock exchange. Cross-sectional regression analysis finds that there are several factors affecting the effectiveness of public criticisms in a statistically significant way, including financing propensity, governance mechanism, and equity nature. Our findings suggest that reputational sanctions function better towards the firms with more reliance on reputational capital. In light of the empirical findings, some policy recommendations are made to improve the effectiveness of reputational sanctions.
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reputational sanctions are widely used as a regulatory tool to curb corporate misconduct. However, existing literature on its workings and effectiveness is largely limited to developed economies. This paper thus endeavours to examine the case of China, focusing on public criticisms imposed on culpable firms by the two Chinese stock exchanges in Shanghai and Shenzhen. Public criticism is an important yet understudied form of reputational sanction, and thanks to its unique features, presents a very good opportunity to quantitatively measure the scale of reputational damage. This paper constructs a unique dataset of all public criticisms announced by the two Chinese stock exchanges from 2013 to 2018, providing empirical evidence on the stock price effects of reputational sanctions on culpable firms for their corporate misconduct. The paper uses event study and shows significantly negative cumulative abnormal returns around the announcement date of public criticisms, which demonstrate the general effectiveness of reputational sanctions. Further tests, however, suggest that the significant negative market reaction only appears in the firms relying on external financing and those not controlled by state ownership. Importantly, the market reaction is not significant in cases where the firm had already self-exposed misconduct before the announcement of public criticisms by the stock exchange. Cross-sectional regression analysis finds that there are several factors affecting the effectiveness of public criticisms in a statistically significant way, including financing propensity, governance mechanism, and equity nature. Our findings suggest that reputational sanctions function better towards the firms with more reliance on reputational capital. In light of the empirical findings, some policy recommendations are made to improve the effectiveness of reputational sanctions.
The Japanese Banks in the Lasting Low-, Zero- and Negative-Interest Rate Environment
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The bursting of the Japanese bubble economy in the early 1990s put the stage for a lasting lowzero-, and negative-interest rate environment, which fundamentally changed the business environment for the Japanese commercial banks. On the income side, with interest margins becoming increasingly depressed, net interest revenues declined, which forced the banks to expand revenues from fees and commissions. The banks had to cut costs by reducing the number of employees, closing branches and merging into larger banks. The gradual concentration process has most recently cumulated in the relaxation of the monopoly law. With the capital allocation function of banks being undermined, the Japanese economy has become zombified, suffering from anemic growth.
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The bursting of the Japanese bubble economy in the early 1990s put the stage for a lasting lowzero-, and negative-interest rate environment, which fundamentally changed the business environment for the Japanese commercial banks. On the income side, with interest margins becoming increasingly depressed, net interest revenues declined, which forced the banks to expand revenues from fees and commissions. The banks had to cut costs by reducing the number of employees, closing branches and merging into larger banks. The gradual concentration process has most recently cumulated in the relaxation of the monopoly law. With the capital allocation function of banks being undermined, the Japanese economy has become zombified, suffering from anemic growth.
The Mortgage-Cash Premium Puzzle
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We document that in residential real estate transactions, mortgaged homebuyers pay a premium of 12% relative to all-cash buyers on the same property. This difference far exceeds the premium implied by standard transaction frictions and is of economic importance as all-cash purchases account for one-third of U.S. home purchases over our 1980-2017 sample. The 12% mortgage-cash premium estimate obtains under a variety of repeat-sales, instrumental variable, and semi-structural methodologies as well as novel data on backup purchase offers. A model with risk-averse home sellers, calibrated to realistic transaction frictions, implies a premium of only 3%. Explaining the remaining 9% requires sellers to be extremely risk-averse, to believe mortgaged transactions will fail 13 times more often than in the data or, in the event of transaction failure, to incur a utility loss equivalent to a 51% price cut.
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We document that in residential real estate transactions, mortgaged homebuyers pay a premium of 12% relative to all-cash buyers on the same property. This difference far exceeds the premium implied by standard transaction frictions and is of economic importance as all-cash purchases account for one-third of U.S. home purchases over our 1980-2017 sample. The 12% mortgage-cash premium estimate obtains under a variety of repeat-sales, instrumental variable, and semi-structural methodologies as well as novel data on backup purchase offers. A model with risk-averse home sellers, calibrated to realistic transaction frictions, implies a premium of only 3%. Explaining the remaining 9% requires sellers to be extremely risk-averse, to believe mortgaged transactions will fail 13 times more often than in the data or, in the event of transaction failure, to incur a utility loss equivalent to a 51% price cut.
The Propagation of Local Credit Shocks: Evidence from Hurricane Katrina
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A local credit shock, induced by hurricane Katrina, propagated through banks’ internal networks to produce real and credit markets’ effects in distant regions. Driven by abnormal mortgage and housing demand in Katrina-hit areas, financially constrained multi-market banks reallocated resources towards the damaged areas leading to a credit tightening in the undamaged local markets. Depending on their housing supply elasticity, local housing markets in the undamaged regions responded to this credit disruption with a mix of housing prices and housing supply declines. These spillovers depended on undamaged markets’ financial linkages to disaster areas. In the undamaged regions, community banks, being local and unexposed to disaster areas, partially insulated their markets from these spillovers.
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A local credit shock, induced by hurricane Katrina, propagated through banks’ internal networks to produce real and credit markets’ effects in distant regions. Driven by abnormal mortgage and housing demand in Katrina-hit areas, financially constrained multi-market banks reallocated resources towards the damaged areas leading to a credit tightening in the undamaged local markets. Depending on their housing supply elasticity, local housing markets in the undamaged regions responded to this credit disruption with a mix of housing prices and housing supply declines. These spillovers depended on undamaged markets’ financial linkages to disaster areas. In the undamaged regions, community banks, being local and unexposed to disaster areas, partially insulated their markets from these spillovers.
The Role Of State Ownership as a Determinant of Green Bond Issuance
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This study focuses on characteristics of green bond issuers, and more specifically on ownership as a driver of green bond issuance. We test the impact of firm ownership on green bond issuance from a sample of issuers of green and non-green bonds in 18 countries for the 2013â€"2017 period. We find that state ownership is a primary determinant of green bond issuance. Our results also show that the link between state ownership and green bond issuance is stronger in weak institutional frameworks. This confirms the view that the state is a key stakeholder favoring firms’ environmental commitments, such as green bond issuance.
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This study focuses on characteristics of green bond issuers, and more specifically on ownership as a driver of green bond issuance. We test the impact of firm ownership on green bond issuance from a sample of issuers of green and non-green bonds in 18 countries for the 2013â€"2017 period. We find that state ownership is a primary determinant of green bond issuance. Our results also show that the link between state ownership and green bond issuance is stronger in weak institutional frameworks. This confirms the view that the state is a key stakeholder favoring firms’ environmental commitments, such as green bond issuance.
The Role of Peer Events in Corporate Governance: Evidence From Data Breaches
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Economic theory suggests that negative peer events can result in market-wide spillovers which help unaffected firms take real actions to enhance corporate governance. Motivated by the SEC’s concern about cybersecurity, I study the role of peer events in corporate governance using the setting of data breaches. While controlling for firm-specific time-varying unobservable characteristics, I find that peer data breaches are associated with a reduction in future internal control material weaknesses for non-breached firms. The association is robust to a changes analysis and varies cross-sectionally with breach, firm, and board characteristics. Inferences remain consistent when studying IT-related material weaknesses only. Finally, non-breached firms are more likely to have a cybersecurity expert on the top management team after a peer breach. My findings have important implications for mandatory disclosure regulation in general and, in particular, suggest that regulators can help reduce market-wide exposure to cyber risk by facilitating disclosure of cyber incidents.
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Economic theory suggests that negative peer events can result in market-wide spillovers which help unaffected firms take real actions to enhance corporate governance. Motivated by the SEC’s concern about cybersecurity, I study the role of peer events in corporate governance using the setting of data breaches. While controlling for firm-specific time-varying unobservable characteristics, I find that peer data breaches are associated with a reduction in future internal control material weaknesses for non-breached firms. The association is robust to a changes analysis and varies cross-sectionally with breach, firm, and board characteristics. Inferences remain consistent when studying IT-related material weaknesses only. Finally, non-breached firms are more likely to have a cybersecurity expert on the top management team after a peer breach. My findings have important implications for mandatory disclosure regulation in general and, in particular, suggest that regulators can help reduce market-wide exposure to cyber risk by facilitating disclosure of cyber incidents.
When do Regulatory Interventions Work?
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Regulators worldwide have introduced measures such as a fee on high order-to-trade ratio (OTR) to slow down high frequency trading, which existing research shows as having mixed results about its impact on market quality. We study a natural experiment in the Indian stock market where such a fee was introduced twice, with subtle differences in the implementation driven by different motivations. Using a difference-in-difference regression that exploits microstructure features, we find causal evidence of lower aggregate OTR and higher market quality when the fee was used to manage limited exchange infrastructure but little to no change in either OTR or market quality when it was used for a regulatory need to slow down high frequency trading.
SSRN
Regulators worldwide have introduced measures such as a fee on high order-to-trade ratio (OTR) to slow down high frequency trading, which existing research shows as having mixed results about its impact on market quality. We study a natural experiment in the Indian stock market where such a fee was introduced twice, with subtle differences in the implementation driven by different motivations. Using a difference-in-difference regression that exploits microstructure features, we find causal evidence of lower aggregate OTR and higher market quality when the fee was used to manage limited exchange infrastructure but little to no change in either OTR or market quality when it was used for a regulatory need to slow down high frequency trading.
