Research articles for the 2020-02-25
A Model of Industry Tournament Incentives
SSRN
This paper builds on Rosen (1981) and Hvide (2002) to provide a simple framework that elucidates the nature of incentives in the tournaments among top executives in both the external managerial labor market for the top executive positions in other companies and within the executives’ own firm for the top internal position. In doing so, the model provides a formal foundation for the empirical evidence in Kale Reis, and Venkataswaran (2009), Kini and Williams (2012), and Coles, Li, and Wang (2018, 2017) and is suggestive of the nature of tournament incentives among mutual fund managers (Brown, Harlow, and Starks, 1996).
SSRN
This paper builds on Rosen (1981) and Hvide (2002) to provide a simple framework that elucidates the nature of incentives in the tournaments among top executives in both the external managerial labor market for the top executive positions in other companies and within the executives’ own firm for the top internal position. In doing so, the model provides a formal foundation for the empirical evidence in Kale Reis, and Venkataswaran (2009), Kini and Williams (2012), and Coles, Li, and Wang (2018, 2017) and is suggestive of the nature of tournament incentives among mutual fund managers (Brown, Harlow, and Starks, 1996).
A Practical Approach to Social Learning
arXiv
arXiv
Models of social learning feature either binary signals or abstract signal structures often deprived of micro-foundations. Both models are limited when analyzing interim results or performing empirical analysis. We present a method of generating signal structures which are richer than the binary model, yet are tractable enough to perform simulations and empirical analysis. We demonstrate the method's usability by revisiting two classical papers: (1) we discuss the economic significance of unbounded signals Smith and Sorensen (2000); (2) we use experimental data from Anderson and Holt (1997) to perform econometric analysis. Additionally, we provide a necessary and sufficient condition for the occurrence of action cascades.
A Primer on the Financial Crisis in Lebanon: A Historical and Cross-Country Perspective
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The current financial crisis affecting all sectors of the Lebanese economy became visible in a dollar liquidity shortage in the summer of 2019 that has since become acute with a political crisis since 17 October 2019. However, while the crystallization of the crisis is recent, the fragile funding scheme of the economy has developed over a long period of time. In common with previous countries and crises, the balance sheets of each of the government, the banking system, the central bank and the private sector are overextended and mismatched â€" currency and maturity mismatch. Also in common with many previous crises, a fixed exchange rate regime is vulnerable to speculative attack, especially in light of the overvaluation of the real exchange rate that has developed over more than a decade. What is unique to the Lebanon case is that the balance sheets of all 4 sectors of the economy are so exposed to each other through claims and cross-claims. Other countries relied on foreign investors for funding (such as dispersed foreign banks) and were therefore prone to volatile inflows and reversals. In contrast, dedicated non-volatile depositors supported most of Lebanon’s funding for many years until their sudden stop. In this sense, Lebanon has been a victim of its own luck in having a dedicated resident, expatriate, and regional depositor base. This: i) allowed the debt and the imbalances in the balance sheets to build up even further than in previous crises and ii) now complicates the recovery. It complicates the recovery because a sudden stop in the source domestic depositor funding has quickly spread through all balance sheets, contributing to the systemic liquidity freeze and now causing second-round adverse feedback loops to the economy. There is no easy solution. But to arrest this downward spiral, I propose that a key first step in any effective policy response is to separate the government debt problem from the liquidity problem affecting the banking system and real economy. Borrowing from the lessons of the global financial crisis successfully applied by the Federal Reserve and the European Central Bank, external liquidity support (such as collateralized dollar credit lines) should be targeted directly to the banking system to restore depositor confidence and unfreeze the economy. Then the government debt problem, via restructuring and reform should be addressed separately in a democratic political process with citizen (meaning depositor) agreement.
SSRN
The current financial crisis affecting all sectors of the Lebanese economy became visible in a dollar liquidity shortage in the summer of 2019 that has since become acute with a political crisis since 17 October 2019. However, while the crystallization of the crisis is recent, the fragile funding scheme of the economy has developed over a long period of time. In common with previous countries and crises, the balance sheets of each of the government, the banking system, the central bank and the private sector are overextended and mismatched â€" currency and maturity mismatch. Also in common with many previous crises, a fixed exchange rate regime is vulnerable to speculative attack, especially in light of the overvaluation of the real exchange rate that has developed over more than a decade. What is unique to the Lebanon case is that the balance sheets of all 4 sectors of the economy are so exposed to each other through claims and cross-claims. Other countries relied on foreign investors for funding (such as dispersed foreign banks) and were therefore prone to volatile inflows and reversals. In contrast, dedicated non-volatile depositors supported most of Lebanon’s funding for many years until their sudden stop. In this sense, Lebanon has been a victim of its own luck in having a dedicated resident, expatriate, and regional depositor base. This: i) allowed the debt and the imbalances in the balance sheets to build up even further than in previous crises and ii) now complicates the recovery. It complicates the recovery because a sudden stop in the source domestic depositor funding has quickly spread through all balance sheets, contributing to the systemic liquidity freeze and now causing second-round adverse feedback loops to the economy. There is no easy solution. But to arrest this downward spiral, I propose that a key first step in any effective policy response is to separate the government debt problem from the liquidity problem affecting the banking system and real economy. Borrowing from the lessons of the global financial crisis successfully applied by the Federal Reserve and the European Central Bank, external liquidity support (such as collateralized dollar credit lines) should be targeted directly to the banking system to restore depositor confidence and unfreeze the economy. Then the government debt problem, via restructuring and reform should be addressed separately in a democratic political process with citizen (meaning depositor) agreement.
A Study on Impact of NPA’s on Banks Profitability (Case on selected Banks) 1991-2019
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Non-performing Asset is a vital factor in the examination of financial performance of a bank. Non Performing Asset is the key term for the banking corporations. Non Performing Assets show the competence of the performance of the banks. Non Performing Assets means which amount is not received by the bank in return of loans disbursed. Non Performing Assets affect not only the finance institution but the total financial system. Thus a selective study has been done on public sector banks in India to evaluate the effect of Non Performing Assets on the profitability of banks. Banks today are not judged only on the basis of number of branches and volume of deposits but also on the basis of standard of assets. NPAs negatively affect on the profitability, liquidity and solvency of the banks so in this paper we have worked out to find the impact on NPA to primary sector lending impact on the Profitability of the bank.Banks in India have changed a lot over the course of time along with that the system have changed as well. The accounting and managing the accounts have taken a big leap. With these change the risk of default has increased significantly as well, now banks around the globe are exposed to much higher risk then they are in past. This paper show the impact on NPA’s with change in different element as return on asset, net total asset and net profit. Regression analysis of the data show promising result about the analysis this show that with rise in NPA’s there is rise in other factor as well. Banking companies were exposed to different risks while doing there core business, especially while lending loans. Which lead to increase in NPA’s. NPA’s is a huge problem for a developing country like India.
SSRN
Non-performing Asset is a vital factor in the examination of financial performance of a bank. Non Performing Asset is the key term for the banking corporations. Non Performing Assets show the competence of the performance of the banks. Non Performing Assets means which amount is not received by the bank in return of loans disbursed. Non Performing Assets affect not only the finance institution but the total financial system. Thus a selective study has been done on public sector banks in India to evaluate the effect of Non Performing Assets on the profitability of banks. Banks today are not judged only on the basis of number of branches and volume of deposits but also on the basis of standard of assets. NPAs negatively affect on the profitability, liquidity and solvency of the banks so in this paper we have worked out to find the impact on NPA to primary sector lending impact on the Profitability of the bank.Banks in India have changed a lot over the course of time along with that the system have changed as well. The accounting and managing the accounts have taken a big leap. With these change the risk of default has increased significantly as well, now banks around the globe are exposed to much higher risk then they are in past. This paper show the impact on NPA’s with change in different element as return on asset, net total asset and net profit. Regression analysis of the data show promising result about the analysis this show that with rise in NPA’s there is rise in other factor as well. Banking companies were exposed to different risks while doing there core business, especially while lending loans. Which lead to increase in NPA’s. NPA’s is a huge problem for a developing country like India.
A Theory of Liquidity in Private Equity
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We develop a model of private equity in which many empirical patterns arise endogenously. Our model rests solely on two critical features of this market: moral hazard for General partners (GPs) and illiquidity risk for Limited Partners (LPs). The equilibrium fund structure incentivizes GPs with a share in the fund and compensates LPs with an illiquidity premium. GPs may inefficiently accelerate drawdowns to avoid default by LPs on capital commitments. LPs with higher tolerance to illiquidity then realize higher returns. With a secondary market, return persistence decreases at the GP level but persists at the LP level.
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We develop a model of private equity in which many empirical patterns arise endogenously. Our model rests solely on two critical features of this market: moral hazard for General partners (GPs) and illiquidity risk for Limited Partners (LPs). The equilibrium fund structure incentivizes GPs with a share in the fund and compensates LPs with an illiquidity premium. GPs may inefficiently accelerate drawdowns to avoid default by LPs on capital commitments. LPs with higher tolerance to illiquidity then realize higher returns. With a secondary market, return persistence decreases at the GP level but persists at the LP level.
Actively Managed Mean-Variance Portfolios
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I present closed-form analytical solutions to the active mean-variance portfolio management problem relative to a pre-specified benchmark subject to a budget constraint and a beta constraint. The imposition of the beta constraint makes the benchmark relevant to the portfolio problem. I provide an intuitive interpretation of the optimal active portfolio in the general mean-variance case as well as a detailed expression for the optimal weights when returns follow a single-factor model. I show that the value-added of active portfolio management is simply the incremental certainty equivalent return of the active portfolio relative to the certainty equivalent return of the benchmark. I investigate the out-of-sample performance of the optimal active mean-variance portfolio using industry portfolios as well as individual stocks.
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I present closed-form analytical solutions to the active mean-variance portfolio management problem relative to a pre-specified benchmark subject to a budget constraint and a beta constraint. The imposition of the beta constraint makes the benchmark relevant to the portfolio problem. I provide an intuitive interpretation of the optimal active portfolio in the general mean-variance case as well as a detailed expression for the optimal weights when returns follow a single-factor model. I show that the value-added of active portfolio management is simply the incremental certainty equivalent return of the active portfolio relative to the certainty equivalent return of the benchmark. I investigate the out-of-sample performance of the optimal active mean-variance portfolio using industry portfolios as well as individual stocks.
Additive Processes with Bilateral Gamma Marginals
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The Sato process associated with self decomposable laws at unit time is further generalized to an additive process with arbitrary innovation term structures. A second generalization to additive processes consistent with bilateral gamma marginal distributions is also made. The Sato process is a parametric special case of the two generailzations. This feature is exploited in defining calibration starting values. Calibration results are presented for 1255 days of daily data on SPY options. The deterministic innovation variance model makes a median improvement of 15% in root mean square error over the Sato process. The comparable value for the general additive process is 40%. The Sato process relative to the general additive process over prices negative moves and under prices positive ones. The under pricing of negative moves decreases with maturity. On the positive side the over pricing decreases with maturity. For negative moves the overpricing is larger for smaller moves, while for positive moves the underpricing is larger for the larger moves.
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The Sato process associated with self decomposable laws at unit time is further generalized to an additive process with arbitrary innovation term structures. A second generalization to additive processes consistent with bilateral gamma marginal distributions is also made. The Sato process is a parametric special case of the two generailzations. This feature is exploited in defining calibration starting values. Calibration results are presented for 1255 days of daily data on SPY options. The deterministic innovation variance model makes a median improvement of 15% in root mean square error over the Sato process. The comparable value for the general additive process is 40%. The Sato process relative to the general additive process over prices negative moves and under prices positive ones. The under pricing of negative moves decreases with maturity. On the positive side the over pricing decreases with maturity. For negative moves the overpricing is larger for smaller moves, while for positive moves the underpricing is larger for the larger moves.
Attention Utility: Evidence From Individual Investors
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Attention utility is the hedonic pleasure or pain derived purely from paying attention to information. Using data on brokerage account logins by individual investors, we show that individuals devote disproportionate attention to already-known positive information about the performance of individual stocks within their portfolios. This aversion to paying attention to unfavorable information, through its effect on logins, has consequences for trading activity; it reduces trading after recent losses and increases trading after recent gains. Attention utility is distinct from models of belief-based utility and information aversion (in which information not sought is not fully known), and implies that the pleasure and pain of attending to known information may be important for individual behavior.
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Attention utility is the hedonic pleasure or pain derived purely from paying attention to information. Using data on brokerage account logins by individual investors, we show that individuals devote disproportionate attention to already-known positive information about the performance of individual stocks within their portfolios. This aversion to paying attention to unfavorable information, through its effect on logins, has consequences for trading activity; it reduces trading after recent losses and increases trading after recent gains. Attention utility is distinct from models of belief-based utility and information aversion (in which information not sought is not fully known), and implies that the pleasure and pain of attending to known information may be important for individual behavior.
Bank Monitoring and Financial Reporting Quality: The Case of Accounts-Receivable-Based Loans
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Using novel receivable-based-loan data, we study the effect of aging-report loan covenants on borrowers’ accounts receivable reporting quality. Our purpose is to highlight a channel that lenders use to obtain private information and to understand whether lenders’ information acquisition affects the financial reporting quality of borrowers. Compared to receivable-based borrowers without aging-report requirements (control firms), borrowers with such requirements (test firms) increase their receivable reporting quality significantly after loan initiations. The shift in reporting quality is more pronounced when borrowers have weak bargaining power. Our results lend support to the argument that lender information access affects borrowers’ reporting quality.
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Using novel receivable-based-loan data, we study the effect of aging-report loan covenants on borrowers’ accounts receivable reporting quality. Our purpose is to highlight a channel that lenders use to obtain private information and to understand whether lenders’ information acquisition affects the financial reporting quality of borrowers. Compared to receivable-based borrowers without aging-report requirements (control firms), borrowers with such requirements (test firms) increase their receivable reporting quality significantly after loan initiations. The shift in reporting quality is more pronounced when borrowers have weak bargaining power. Our results lend support to the argument that lender information access affects borrowers’ reporting quality.
CECL: Timely Loan Loss Provisioning and Banking Regulation
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We investigate how loan loss models affect banking regulation. We study an incurred loss model (IL) and a current expected credit loss model (CECL). Relative to IL, CECL improves efficiency as it allows for timely intervention to curb inefficient ex post asset-substitution. However, from a real effects perspective, our analysis uncovers a potential cost of CECL: banks respond to timely intervention by originating riskier loans so that timely intervention induces timelier risk-taking. By appropriately tailoring regulatory capital to information about credit losses, the regulator can improve the efficiency of CECL. In particular, we show that regulatory capital under CECL would be looser when early estimates of credit losses are sufficiently precise and/or asset-substitution incentives are not too severe. From a policy perspective, our model therefore calls for better coordination between banking regulators and accounting standard setters.
SSRN
We investigate how loan loss models affect banking regulation. We study an incurred loss model (IL) and a current expected credit loss model (CECL). Relative to IL, CECL improves efficiency as it allows for timely intervention to curb inefficient ex post asset-substitution. However, from a real effects perspective, our analysis uncovers a potential cost of CECL: banks respond to timely intervention by originating riskier loans so that timely intervention induces timelier risk-taking. By appropriately tailoring regulatory capital to information about credit losses, the regulator can improve the efficiency of CECL. In particular, we show that regulatory capital under CECL would be looser when early estimates of credit losses are sufficiently precise and/or asset-substitution incentives are not too severe. From a policy perspective, our model therefore calls for better coordination between banking regulators and accounting standard setters.
Capturing the Illiquidity Premium
SSRN
This paper studies the restructuring of financial intermediation in the United States since the 2007-09 financial crisis. We show that the largest U.S. life insurers have entered private debt markets as banks refocused on commercial banking, against a backdrop of unconventional monetary policies and tighter bank regulations. Through complex on- and off-balance sheet arrangements, these insurers, many of whom are controlled by private equity firms, are acquiring and deploying vast amounts of annuity capital to capture the illiquidity premium. The new architecture of the financial system features novel forms of lending. That said, life insurers have become more vulnerable to an aggregate shock to the corporate sector.
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This paper studies the restructuring of financial intermediation in the United States since the 2007-09 financial crisis. We show that the largest U.S. life insurers have entered private debt markets as banks refocused on commercial banking, against a backdrop of unconventional monetary policies and tighter bank regulations. Through complex on- and off-balance sheet arrangements, these insurers, many of whom are controlled by private equity firms, are acquiring and deploying vast amounts of annuity capital to capture the illiquidity premium. The new architecture of the financial system features novel forms of lending. That said, life insurers have become more vulnerable to an aggregate shock to the corporate sector.
Cross Currency Valuation and Hedging in the Multiple Curve Framework
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We generalize the results of Bielecki and Rutkowski (2015) on funding and collateralization to a multi-currency framework and link their results with those of Piterbarg (2012), Moreni and Pallavicini (2017), and Fuji et al (2010).In doing this, we provide a complete study of absence of arbitrage in a multi-currency market where, in each single monetary area, multiple interest rates coexist. We first characterize absence of arbitrage in the case without collateral.After that we study collateralization schemes in a very general situation: the cash flows of the contingent claim and those associated to the collateral agreement can be specified in any currency. We study both segregation and rehypothecation and allow for cash and risky collateral in arbitrary currency specifications. Absence of arbitrage and pricing in the presence of collateral are discussed under all possible combinations of conventions.Our work provides a reference for the analysis of wealth dynamics, we also provide valuation formulas that are a useful foundation for cross-currency curve construction techniques. Our framework provides also a solid foundation for the construction of multi-currency simulation models for the generation of exposure profiles in the context of xVA calculations.
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We generalize the results of Bielecki and Rutkowski (2015) on funding and collateralization to a multi-currency framework and link their results with those of Piterbarg (2012), Moreni and Pallavicini (2017), and Fuji et al (2010).In doing this, we provide a complete study of absence of arbitrage in a multi-currency market where, in each single monetary area, multiple interest rates coexist. We first characterize absence of arbitrage in the case without collateral.After that we study collateralization schemes in a very general situation: the cash flows of the contingent claim and those associated to the collateral agreement can be specified in any currency. We study both segregation and rehypothecation and allow for cash and risky collateral in arbitrary currency specifications. Absence of arbitrage and pricing in the presence of collateral are discussed under all possible combinations of conventions.Our work provides a reference for the analysis of wealth dynamics, we also provide valuation formulas that are a useful foundation for cross-currency curve construction techniques. Our framework provides also a solid foundation for the construction of multi-currency simulation models for the generation of exposure profiles in the context of xVA calculations.
Crowded out from the Beginning: Impact of Government Debt on Corporate Financing
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Using hand-collected data on corporate bond and stock offerings, we identify the impact of government debt on corporate financing during World War I. The early twentieth century provides a unique opportunity to identify the impact of government debt on private financing because during this period (1) firms announced the amount they wanted to raise before each security offering and (2) the Treasury issued debt in discrete intervals. We identify the impact of Treasury issues by comparing differences in the amount firms offered to the amount they actually raised when the Treasury was borrowing to when the Treasury was not in the market. We find that long term government bond offerings negatively affect both amount of long-term corporate bonds and dividend paying stocks issued. In contrast, we find no effect of government bond offerings on short term debt issue. Our findings suggest that investors view dividend paying stocks as a close substitute for relatively safe long-term bonds.
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Using hand-collected data on corporate bond and stock offerings, we identify the impact of government debt on corporate financing during World War I. The early twentieth century provides a unique opportunity to identify the impact of government debt on private financing because during this period (1) firms announced the amount they wanted to raise before each security offering and (2) the Treasury issued debt in discrete intervals. We identify the impact of Treasury issues by comparing differences in the amount firms offered to the amount they actually raised when the Treasury was borrowing to when the Treasury was not in the market. We find that long term government bond offerings negatively affect both amount of long-term corporate bonds and dividend paying stocks issued. In contrast, we find no effect of government bond offerings on short term debt issue. Our findings suggest that investors view dividend paying stocks as a close substitute for relatively safe long-term bonds.
Distributions of Historic Market Data -- Relaxation and Correlations
arXiv
arXiv
We investigate relaxation and correlations in a class of mean-reverting models for stochastic variances. We derive closed-form expressions for the correlation functions and leverage for a general form of the stochastic term. We also discuss correlation functions and leverage for three specific models -- multiplicative, Heston (Cox-Ingersoll-Ross) and combined multiplicative-Heston -- whose steady-state probability density functions are Gamma, Inverse Gamma and Beta Prime respectively, the latter two exhibiting "fat" tails. For the Heston model, we apply the eigenvalue analysis of the Fokker-Planck equation to derive the correlation function -- in agreement with the general analysis -- and to identify a series of time scales, which are observable in relaxation of cumulants on approach to the steady state. We test our findings on a very large set of historic financial markets data.
Does Hedge Fund Activism Influence Trade Credit?
SSRN
I find that target firms reduce their reliance on trade credit after the activist interventions by hedge funds. Targets’ supplier firms reduce the extension of trade credit (accounts payable) by 28 per cent relative to control firms post hedge fund activism. Target firms also extend lower trade credit to their customers - trade receivables attenuate by 12 per cent. This impact is on account of supply-side factors concerning both accounts payable and trade receivables. The earlier studies like Li and Xu (2009), Klein and Zur (2011) and Sunder et al. (2014) have documented a negative response of public and private debtholders toward hedge fund activism. The findings also highlight the expropriation concerns raised by the supplier firms. This implies that the repercussions of hedge fund activism extend beyond the formal debtholders like the private and public debtholders.
SSRN
I find that target firms reduce their reliance on trade credit after the activist interventions by hedge funds. Targets’ supplier firms reduce the extension of trade credit (accounts payable) by 28 per cent relative to control firms post hedge fund activism. Target firms also extend lower trade credit to their customers - trade receivables attenuate by 12 per cent. This impact is on account of supply-side factors concerning both accounts payable and trade receivables. The earlier studies like Li and Xu (2009), Klein and Zur (2011) and Sunder et al. (2014) have documented a negative response of public and private debtholders toward hedge fund activism. The findings also highlight the expropriation concerns raised by the supplier firms. This implies that the repercussions of hedge fund activism extend beyond the formal debtholders like the private and public debtholders.
Founder Succession and Firm Performance in the Luxury Industry
SSRN
Top management succession may be a real threat for the long-term profitability of companies, in particular when it involves the founder whose name also identifies their brand and their products. This is extremely important in the luxury sector where loyalty, trust and the image of brands in consumers’ minds may be affected by the succession process, especially when the founder has no direct heir to ensure continuity of the family firm. Through an analysis of three case studies, as well as a questionnaire distributed to active consumers of luxury products, this study aims to understand whether and how a brand can successfully survive after the death of its founder and whether the purchasing behaviour of customers changes after a founder succession takes place. Our findings reveal that the lack of a clear and structured succession plan may significantly threaten the survival of companies. In addition, our evidence indicates that the purchasing intention of luxury consumers is linked more to the bond and the values that they share with the founder than to the quality of the goods purchased. Accordingly, our results provide insights and suggestions concerning the optimal approach to follow when companies with heirless founders are planning a succession and highlights that the success and the survival of such entities is linked to consumers’ perceptions of the extent to which there is continuity and alignment between the values of the founder and those of their successors.
SSRN
Top management succession may be a real threat for the long-term profitability of companies, in particular when it involves the founder whose name also identifies their brand and their products. This is extremely important in the luxury sector where loyalty, trust and the image of brands in consumers’ minds may be affected by the succession process, especially when the founder has no direct heir to ensure continuity of the family firm. Through an analysis of three case studies, as well as a questionnaire distributed to active consumers of luxury products, this study aims to understand whether and how a brand can successfully survive after the death of its founder and whether the purchasing behaviour of customers changes after a founder succession takes place. Our findings reveal that the lack of a clear and structured succession plan may significantly threaten the survival of companies. In addition, our evidence indicates that the purchasing intention of luxury consumers is linked more to the bond and the values that they share with the founder than to the quality of the goods purchased. Accordingly, our results provide insights and suggestions concerning the optimal approach to follow when companies with heirless founders are planning a succession and highlights that the success and the survival of such entities is linked to consumers’ perceptions of the extent to which there is continuity and alignment between the values of the founder and those of their successors.
G-Learner and GIRL: Goal Based Wealth Management with Reinforcement Learning
arXiv
arXiv
We present a reinforcement learning approach to goal based wealth management problems such as optimization of retirement plans or target dated funds. In such problems, an investor seeks to achieve a financial goal by making periodic investments in the portfolio while being employed, and periodically draws from the account when in retirement, in addition to the ability to re-balance the portfolio by selling and buying different assets (e.g. stocks). Instead of relying on a utility of consumption, we present G-Learner: a reinforcement learning algorithm that operates with explicitly defined one-step rewards, does not assume a data generation process, and is suitable for noisy data. Our approach is based on G-learning - a probabilistic extension of the Q-learning method of reinforcement learning.
In this paper, we demonstrate how G-learning, when applied to a quadratic reward and Gaussian reference policy, gives an entropy-regulated Linear Quadratic Regulator (LQR). This critical insight provides a novel and computationally tractable tool for wealth management tasks which scales to high dimensional portfolios. In addition to the solution of the direct problem of G-learning, we also present a new algorithm, GIRL, that extends our goal-based G-learning approach to the setting of Inverse Reinforcement Learning (IRL) where rewards collected by the agent are not observed, and should instead be inferred. We demonstrate that GIRL can successfully learn the reward parameters of a G-Learner agent and thus imitate its behavior. Finally, we discuss potential applications of the G-Learner and GIRL algorithms for wealth management and robo-advising.
How Integrated Are Corporate Bond and Stock Markets?
SSRN
In this paper, I study the degree of market integration between US corporate bonds and stocks of the corresponding issuing firms, accounting for their characteristics. I find that short-selling constraints are essential restrictions to optimal Sharpe ratio portfolios that yield admissible portfolio positions and implied pricing errors within quoted bid-ask spreads. My empirical evidence suggests that markets are more integrated for larger firms, with more liquid corporate bonds and stocks. Similarly, firms that are more leveraged, have a higher asset growth and profitability feature a greater extent of integration between their debt and equity securities.
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In this paper, I study the degree of market integration between US corporate bonds and stocks of the corresponding issuing firms, accounting for their characteristics. I find that short-selling constraints are essential restrictions to optimal Sharpe ratio portfolios that yield admissible portfolio positions and implied pricing errors within quoted bid-ask spreads. My empirical evidence suggests that markets are more integrated for larger firms, with more liquid corporate bonds and stocks. Similarly, firms that are more leveraged, have a higher asset growth and profitability feature a greater extent of integration between their debt and equity securities.
Impact of Earnings Announcements for Dow Jones Index Stocks
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A regression model for analysis of impact of earnings announcements on stock prices has been formulated. An equal-weight portfolio of 29 stocks that constituted DJI in Oct 2019 is considered within the range Jan 1999 â€" Sep 2019. It is found that out-performance around the earnings announcements is the highest when the portfolio is liquidated on the next day after announcements. Short holding periods have the highest average returns. In this case, however, the differences between returns around and outside earnings become statistically insignificant when the top 10% performers are dropped from the portfolio. Earnings surprises for individual DJI constituents are analyzed.
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A regression model for analysis of impact of earnings announcements on stock prices has been formulated. An equal-weight portfolio of 29 stocks that constituted DJI in Oct 2019 is considered within the range Jan 1999 â€" Sep 2019. It is found that out-performance around the earnings announcements is the highest when the portfolio is liquidated on the next day after announcements. Short holding periods have the highest average returns. In this case, however, the differences between returns around and outside earnings become statistically insignificant when the top 10% performers are dropped from the portfolio. Earnings surprises for individual DJI constituents are analyzed.
Informative Option Portfolios in Unscented Kalman Filter Design for Affine Jump Diffusion Models
SSRN
Option pricing models are tools for pricing and hedging derivatives. Good models are complex and the econometrician faces many design decisions when bringing them to the data. I show that strategically constructed low-dimensional filter designs outperform those that try to use all the available option data. I construct Unscented Kalman Filters around option portfolios that aggregate option data, and track changes in risk-neutral volatility and skewness. These low-dimensional filters perform equivalently to or better than standard approaches that treat full option panels. The performance advantage is greatest in empirically relevant settings: in models with strongly skewed jump components that are not driven by Brownian volatility.
SSRN
Option pricing models are tools for pricing and hedging derivatives. Good models are complex and the econometrician faces many design decisions when bringing them to the data. I show that strategically constructed low-dimensional filter designs outperform those that try to use all the available option data. I construct Unscented Kalman Filters around option portfolios that aggregate option data, and track changes in risk-neutral volatility and skewness. These low-dimensional filters perform equivalently to or better than standard approaches that treat full option panels. The performance advantage is greatest in empirically relevant settings: in models with strongly skewed jump components that are not driven by Brownian volatility.
Investable Commodity Premia in China
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We investigate the investability of commodity risk premia in China. Previously documented standard momentum, carry and basis-momentum are not investable due to unique liquidity patterns on the futures curve. However, dynamic rolling and strategic portfolio weights significantly boost the investment capacity of such premia without compromising its statistical and economic significance. Meanwhile, style integration delivers enhanced performance and improved opportunity set. Furthermore, the observed investable premia are robust to execution lags, stop-loss, illiquidity, sub-period specifications, seasonality, transaction costs and offer promising potential for portfolio diversification. Finally, investable commodity premia in China reveal strong predictability on global real economic growth.
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We investigate the investability of commodity risk premia in China. Previously documented standard momentum, carry and basis-momentum are not investable due to unique liquidity patterns on the futures curve. However, dynamic rolling and strategic portfolio weights significantly boost the investment capacity of such premia without compromising its statistical and economic significance. Meanwhile, style integration delivers enhanced performance and improved opportunity set. Furthermore, the observed investable premia are robust to execution lags, stop-loss, illiquidity, sub-period specifications, seasonality, transaction costs and offer promising potential for portfolio diversification. Finally, investable commodity premia in China reveal strong predictability on global real economic growth.
Investor Sentiment and the Pricing of Characteristics-Based Factors
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Using portfolios that are formed by directly sorting stocks based on their exposure to characteristics-based factors, earlier studies find that these beta-sorted portfolios have very large ex post factor beta spreads. However, the return spreads between high- and low-beta firms are typically tiny and insignificant. This study examines the time variation in the pricing of a large set of characteristics-based factors. Our evidence shows a striking two-regime pattern for most of the factor-beta-sorted portfolios: high-beta portfolios earn significantly higher returns than low-beta portfolios following high-sentiment periods, whereas the exact opposite occurs following low-sentiment periods. Remarkably, this two-regime pattern is completely reversed when macro-related factors, such as consumption growth and TFP growth, are used. The evidence based on mutual fund and hedge fund returns also confirms this two-regime pattern. Our findings suggest that the exposure to most of these characteristics-based factors is likely to be a proxy for the level of mispricing, rather than risk, especially during high-sentiment periods.
SSRN
Using portfolios that are formed by directly sorting stocks based on their exposure to characteristics-based factors, earlier studies find that these beta-sorted portfolios have very large ex post factor beta spreads. However, the return spreads between high- and low-beta firms are typically tiny and insignificant. This study examines the time variation in the pricing of a large set of characteristics-based factors. Our evidence shows a striking two-regime pattern for most of the factor-beta-sorted portfolios: high-beta portfolios earn significantly higher returns than low-beta portfolios following high-sentiment periods, whereas the exact opposite occurs following low-sentiment periods. Remarkably, this two-regime pattern is completely reversed when macro-related factors, such as consumption growth and TFP growth, are used. The evidence based on mutual fund and hedge fund returns also confirms this two-regime pattern. Our findings suggest that the exposure to most of these characteristics-based factors is likely to be a proxy for the level of mispricing, rather than risk, especially during high-sentiment periods.
Liquidity Fluctuations in Over-the-Counter Markets
SSRN
This paper presents a model of opaque secondary markets. Investors meet over-the-counter to trade heterogeneous assets under asymmetric information. An endogenous composition effect emerges whereby high liquidity alters the quality of the pool of sellers and decreases future liquidity. With impatient investors, cyclical equilibria arise: Price and volume oscillate without any fundamental shock. With patient investors, the equilibrium is driven instead by a resale effect: Liquidity depends primarily on investors' expectations about future liquidity, and multiple steady states coexist. In each case, equilibrium liquidity is driven by the opaqueness about asset quality and trade history typical of over-the-counter markets.
SSRN
This paper presents a model of opaque secondary markets. Investors meet over-the-counter to trade heterogeneous assets under asymmetric information. An endogenous composition effect emerges whereby high liquidity alters the quality of the pool of sellers and decreases future liquidity. With impatient investors, cyclical equilibria arise: Price and volume oscillate without any fundamental shock. With patient investors, the equilibrium is driven instead by a resale effect: Liquidity depends primarily on investors' expectations about future liquidity, and multiple steady states coexist. In each case, equilibrium liquidity is driven by the opaqueness about asset quality and trade history typical of over-the-counter markets.
Measuring Stressed Default Risk
SSRN
A stressed version of distance to default (DTD) is proposed to measure stressed default risk, which is a DTD conditioning on that the bad economic state would persist during the horizon under consideration. We establish the importance of the stressed DTD for measuring stressed default risk both on the firm and aggregate level, using corporate default data during the 2007-2009 crisis, credit derivative prices, and credit rating data.
SSRN
A stressed version of distance to default (DTD) is proposed to measure stressed default risk, which is a DTD conditioning on that the bad economic state would persist during the horizon under consideration. We establish the importance of the stressed DTD for measuring stressed default risk both on the firm and aggregate level, using corporate default data during the 2007-2009 crisis, credit derivative prices, and credit rating data.
Numerical method for model-free pricing of exotic derivatives using rough path signatures
arXiv
arXiv
We estimate prices of exotic options in a discrete-time model-free setting when the trader has access to market prices of a rich enough class of exotic and vanilla options. This is achieved by estimating an unobservable quantity called "implied expected signature" from such market prices, which are used to price other exotic derivatives. The implied expected signature is an object that characterises the market dynamics.
On the Fast Track: Information Acquisition Costs and Information Production
SSRN
Using the introduction of high-speed rail (HSR) as an exogenous shock to costs of information acquisition, we show that reductions in information-acquisition costs lead to (i) a significant increase in information production, evidenced by a higher frequency of analysts visiting portfolio firms, and (ii) improvement in output quality, manifested in higher forecast accuracy and better recommendations. Increases in the difficulty in visiting a firm without HSR and in the importance of soft information lead to these effects becoming more pronounced. Importantly, more information production is also associated with improved price efficiency. We corroborate these findings using a large-scale survey of financial analysts. Finally, both the empirical and survey results highlight the importance of soft information in analysts’ unique-information production.
SSRN
Using the introduction of high-speed rail (HSR) as an exogenous shock to costs of information acquisition, we show that reductions in information-acquisition costs lead to (i) a significant increase in information production, evidenced by a higher frequency of analysts visiting portfolio firms, and (ii) improvement in output quality, manifested in higher forecast accuracy and better recommendations. Increases in the difficulty in visiting a firm without HSR and in the importance of soft information lead to these effects becoming more pronounced. Importantly, more information production is also associated with improved price efficiency. We corroborate these findings using a large-scale survey of financial analysts. Finally, both the empirical and survey results highlight the importance of soft information in analysts’ unique-information production.
Price mediated contagion through capital ratio requirements
arXiv
arXiv
We develop a framework for price-mediated contagion in financial systems where banks are forced to liquidate assets to satisfy a risk-weight based capital adequacy requirement. In constructing this modeling framework, we introduce a two-tier pricing structure: the volume weighted average price that is obtained by any bank liquidating assets and the terminal mark-to-market price used to account for all assets held at the end of the clearing process. We consider the case of multiple illiquid assets and develop conditions for the existence and uniqueness of clearing prices. We provide a closed-form representation for the sensitivity of these clearing prices to the system parameters, and use this result to quantify: (1) the cost of regulation, in stress scenarios, faced by the system as a whole and the individual banks, and (2) the value of providing bailouts and bail-ins to consider when such notions are financially advisable. Numerical case studies are provided to study the application of this model to data.
Product Market Competition and the Value of Diversification
SSRN
I examine how industry concentration affects the value of diversification and explore the strategic value of agency problems for conglomerates that operate mainly in concentrated industries (concentrated conglomerates). I find that concentrated conglomerates have higher diversification values. Consistent with agency theories, agency problems, on average, cause greater diversification discount. In contrast, agency problems in concentrated conglomerates create strategic advantage and lead to higher valuations consistent with the notion that these conglomerates can credibly commit to their industries. Using tariff reductions as competitive shocks, I show that concentrated conglomerates experience significant valuation decline and respond aggressively to threats in less-competitive industries.
SSRN
I examine how industry concentration affects the value of diversification and explore the strategic value of agency problems for conglomerates that operate mainly in concentrated industries (concentrated conglomerates). I find that concentrated conglomerates have higher diversification values. Consistent with agency theories, agency problems, on average, cause greater diversification discount. In contrast, agency problems in concentrated conglomerates create strategic advantage and lead to higher valuations consistent with the notion that these conglomerates can credibly commit to their industries. Using tariff reductions as competitive shocks, I show that concentrated conglomerates experience significant valuation decline and respond aggressively to threats in less-competitive industries.
Random horizon principal-agent problem
arXiv
arXiv
We consider a general formulation of the random horizon Principal-Agent problem with a continuous payment and a lump-sum payment at termination. In the European version of the problem, the random horizon is chosen solely by the principal with no other possible action from the agent than exerting effort on the dynamics of the output process. We also consider the American version of the contract, which covers the seminal Sannikov's model, where the agent can also quit by optimally choosing the termination time of the contract. Our main result reduces such non-zero-sum stochastic differential games to appropriate stochastic control problems which may be solved by standard methods of stochastic control theory. This reduction is obtained by following Sannikov's approach, further developed by Cvitanic, Possamai, and Touzi. We first introduce an appropriate class of contracts for which the agent's optimal effort is immediately characterized by the standard verification argument in stochastic control theory. We then show that this class of contracts is dense in an appropriate sense so that the optimization over this restricted family of contracts represents no loss of generality. The result is obtained by using the recent well-posedness result of random horizon second-order backward SDE.
Regulatory Forbearance in the U.S. Insurance Industry: The Effects of Eliminating Capital Requirements
SSRN
This paper documents the long-run effects of an important reform of capital regulation for U.S. insurance companies in 2009. We show that its design effectively eliminates capital requirements for (non-agency) MBS, implying an aggregate capital relief of over $18bn at the time of the reform. By 2015, 40% of all high-yield assets in the overall fixed-income portfolio are MBS investments. This result is primarily driven by insurers' reduced propensity to sell poorly-rated legacy assets. Using a regression discontinuity framework, we can attribute this behavior to capital requirements. We also provide evidence that the insurance industry, driven by large life insurers, crowds out other investors in the new issuance of (high-yield) MBS post reform. Our findings are consistent with the view that the regulation and supervision of the U.S. insurance sector is influenced by short-term industry interests.
SSRN
This paper documents the long-run effects of an important reform of capital regulation for U.S. insurance companies in 2009. We show that its design effectively eliminates capital requirements for (non-agency) MBS, implying an aggregate capital relief of over $18bn at the time of the reform. By 2015, 40% of all high-yield assets in the overall fixed-income portfolio are MBS investments. This result is primarily driven by insurers' reduced propensity to sell poorly-rated legacy assets. Using a regression discontinuity framework, we can attribute this behavior to capital requirements. We also provide evidence that the insurance industry, driven by large life insurers, crowds out other investors in the new issuance of (high-yield) MBS post reform. Our findings are consistent with the view that the regulation and supervision of the U.S. insurance sector is influenced by short-term industry interests.
Smart Beta and Statistical Significance
SSRN
I propose an alternative weighting mechanism for equity mandates based on the statistical significance of the factor loading on the benchmark. Specifically, the weight of each security entering the active portfolio is directly proportional to the t-statistic of the factor loading ($\beta$) with the benchmark. I show that this amounts to overweighting securities with high correlations with the benchmark and vice versa. The t-statistic of market beta within a single-factor model is a monotonic transformation of its correlation with the benchmark. I test the out-of-sample performance of this alternative weighing scheme with industry portfolios as well as individual US stocks. I find that this strategy has higher correlations with the benchmark compared to other popular alternatives, has lower tracking error, unitary exposure to the benchmark, very good Sharpe ratios and substantial ex-post realized returns relative to the underlying benchmark.
SSRN
I propose an alternative weighting mechanism for equity mandates based on the statistical significance of the factor loading on the benchmark. Specifically, the weight of each security entering the active portfolio is directly proportional to the t-statistic of the factor loading ($\beta$) with the benchmark. I show that this amounts to overweighting securities with high correlations with the benchmark and vice versa. The t-statistic of market beta within a single-factor model is a monotonic transformation of its correlation with the benchmark. I test the out-of-sample performance of this alternative weighing scheme with industry portfolios as well as individual US stocks. I find that this strategy has higher correlations with the benchmark compared to other popular alternatives, has lower tracking error, unitary exposure to the benchmark, very good Sharpe ratios and substantial ex-post realized returns relative to the underlying benchmark.
Stress Testing: A Measure of Financial Stability across ASEAN-5
SSRN
A banking operation is at the epicenter of financial intermediation, and there is no perfect substitute for it in capital markets. Because a banking operation revolves around a constant inventory of risks, in the event of a financial or economic crisis, banks therefore get hit as the first line of defense, and then the broader economic activity is adversely affected if the financial turmoil exacerbates. Today, all central banks of ASEAN-5 design and conduct own micro and macro stress tests as a measure of financial stability. The main results of all three stress scenarios (i.e. baseline, adverse, and severely adverse) are not only informative to central banks and regulatory supervisors, but they contribute positively to the policy decision-making process; stress testing results also help bank executives (and risk managers) better manage risks, and academia for research. Stress testing is overly misunderstood and often confused with macroeconomic forecasting and early-warning indicator. Stress testing is not a standalone tool and it does not supplant other tools in the central bank’s arsenal; quite the opposite, stress testing is indispensable when complemented by another analytical method, model, or technique such as value-at-risk (VaR). Even though the five founding members of ASEAN-5 have made remarkable strides since the late 1990s in bringing their respective domestic banking sectors in line with the international standards (i.e. Basel III), they must continue with introducing more structural reforms and stay away from instability-inflicting policies.
SSRN
A banking operation is at the epicenter of financial intermediation, and there is no perfect substitute for it in capital markets. Because a banking operation revolves around a constant inventory of risks, in the event of a financial or economic crisis, banks therefore get hit as the first line of defense, and then the broader economic activity is adversely affected if the financial turmoil exacerbates. Today, all central banks of ASEAN-5 design and conduct own micro and macro stress tests as a measure of financial stability. The main results of all three stress scenarios (i.e. baseline, adverse, and severely adverse) are not only informative to central banks and regulatory supervisors, but they contribute positively to the policy decision-making process; stress testing results also help bank executives (and risk managers) better manage risks, and academia for research. Stress testing is overly misunderstood and often confused with macroeconomic forecasting and early-warning indicator. Stress testing is not a standalone tool and it does not supplant other tools in the central bank’s arsenal; quite the opposite, stress testing is indispensable when complemented by another analytical method, model, or technique such as value-at-risk (VaR). Even though the five founding members of ASEAN-5 have made remarkable strides since the late 1990s in bringing their respective domestic banking sectors in line with the international standards (i.e. Basel III), they must continue with introducing more structural reforms and stay away from instability-inflicting policies.
The Long-lasting Effects of Living under Communism on Attitudes towards Financial Markets
SSRN
We analyze the long-term effects of living under communism and its anticapitalist doctrine on households' financial investment decisions and attitudes towards financial markets. Utilizing comprehensive German brokerage data and bank data, we show that, decades after Reunification, East Germans still invest significantly less in the stock market than West Germans. Consistent with communist friends-and-foes propaganda, East Germans are more likely to hold stocks of companies from communist countries (China, Russia, Vietnam) and of state-owned companies, and are unlikely to invest in American companies and the financial industry. Effects are stronger for individuals exposed to "positive emotional tagging", e. g., those living in celebrated showcase cities. Effects reverse for individuals with negative experiences, e.g., environmental pollution, religious oppression, or lack of (Western) TV entertainment. Election years trigger further divergence of East and West Germans. We provide evidence of negative welfare consequences due to less diversified portfolios, higher-fee products, and lower risk-adjusted returns.
SSRN
We analyze the long-term effects of living under communism and its anticapitalist doctrine on households' financial investment decisions and attitudes towards financial markets. Utilizing comprehensive German brokerage data and bank data, we show that, decades after Reunification, East Germans still invest significantly less in the stock market than West Germans. Consistent with communist friends-and-foes propaganda, East Germans are more likely to hold stocks of companies from communist countries (China, Russia, Vietnam) and of state-owned companies, and are unlikely to invest in American companies and the financial industry. Effects are stronger for individuals exposed to "positive emotional tagging", e. g., those living in celebrated showcase cities. Effects reverse for individuals with negative experiences, e.g., environmental pollution, religious oppression, or lack of (Western) TV entertainment. Election years trigger further divergence of East and West Germans. We provide evidence of negative welfare consequences due to less diversified portfolios, higher-fee products, and lower risk-adjusted returns.
The Prevalence and Costs of Financial Misrepresentation
SSRN
We use a comprehensive database of regulatory enforcement actions for financial misrepresentation and apply Receiver Operating Characteristics theory to construct a misrepresentation prediction model. The model performs well both in and out of sample, with an average area under the curve (AUC) of 0.78 in out-of-sample tests. The model’s base case implies that 22.3% of Compustat-listed firms are engaged in financial misrepresentation that is potentially sanctionable by regulators in an average year. The average violation period is 3.1 years, implying that 7.2% of firms initiate new programs of financial misrepresentation each year. Of these, 3.5% eventually are caught and sanctioned. These findings yield numerical estimates of the size of the price distortions imposed by misrepresentation on the shares of both misrepresenting and non-misrepresenting firms, and the size of firms’ ex ante expected costs â€" incorporating both the probability of getting caught and the penalties if caught â€" of engaging in financial misrepresentation.
SSRN
We use a comprehensive database of regulatory enforcement actions for financial misrepresentation and apply Receiver Operating Characteristics theory to construct a misrepresentation prediction model. The model performs well both in and out of sample, with an average area under the curve (AUC) of 0.78 in out-of-sample tests. The model’s base case implies that 22.3% of Compustat-listed firms are engaged in financial misrepresentation that is potentially sanctionable by regulators in an average year. The average violation period is 3.1 years, implying that 7.2% of firms initiate new programs of financial misrepresentation each year. Of these, 3.5% eventually are caught and sanctioned. These findings yield numerical estimates of the size of the price distortions imposed by misrepresentation on the shares of both misrepresenting and non-misrepresenting firms, and the size of firms’ ex ante expected costs â€" incorporating both the probability of getting caught and the penalties if caught â€" of engaging in financial misrepresentation.
The Relations Among Firm Characteristic, Capital Intensity, Institutional Ownership, and Tax Avoidance: Some Evidence From Indonesia
SSRN
Purpose of the study: This study is to determine the effect of profitability, leverage, company size, capital intensity, and institutional ownership simultaneously and partially on tax avoidance in Indonesia.Methodology: This study uses a quantitative approach to the type of descriptive research. The population of this research is property, real estate, and building constructs companies from 2013 - 2017, as many as 63 companies, which listed on the Indonesia Stock Exchange (IDX). While the samples in this study were 31 companies. The data analysis method used is multiple linear regression analysis.Principal Findings: Profitability, leverage, company size, and institutional ownership partially influencing tax avoidance. However, the intensity of capital partly does not affect tax avoidance.Applications of this study: This study suggests that the government makes several efforts to intervene to increase tax literacy on companies, the public, and expand access to higher education, as well as improve the quality of the democratization process to enhance tax compliance in Indonesia.Novelty/Originality of this study: This research brings new evidence on the relationship between profitability, leverage, company size, and institutional ownership on tax avoidance in Indonesia.
SSRN
Purpose of the study: This study is to determine the effect of profitability, leverage, company size, capital intensity, and institutional ownership simultaneously and partially on tax avoidance in Indonesia.Methodology: This study uses a quantitative approach to the type of descriptive research. The population of this research is property, real estate, and building constructs companies from 2013 - 2017, as many as 63 companies, which listed on the Indonesia Stock Exchange (IDX). While the samples in this study were 31 companies. The data analysis method used is multiple linear regression analysis.Principal Findings: Profitability, leverage, company size, and institutional ownership partially influencing tax avoidance. However, the intensity of capital partly does not affect tax avoidance.Applications of this study: This study suggests that the government makes several efforts to intervene to increase tax literacy on companies, the public, and expand access to higher education, as well as improve the quality of the democratization process to enhance tax compliance in Indonesia.Novelty/Originality of this study: This research brings new evidence on the relationship between profitability, leverage, company size, and institutional ownership on tax avoidance in Indonesia.
The Risk-Free Asset Implied by the Market: Medium-Term Bonds instead of Short-Term Bills
SSRN
In empirical tests of the CAPM, the theoretical risk-free asset is typically assumed to be 1-month Treasury bills. This paper examines the implications of a mis-specified risk-free asset, i.e. the possibility that the ‘true’ risk-free asset is a longer-maturity Treasury bond. A simple theoretical derivation leads to the testable prediction that low-beta (high-beta) stocks should then exhibit positive (negative) bond betas. We find strong empirical confirmation for these predictions. The market-implied risk-free asset can be pinpointed at medium-term (5-year) bonds. Concrete implications of this finding are a lower equity risk premium and a less steep security market line.
SSRN
In empirical tests of the CAPM, the theoretical risk-free asset is typically assumed to be 1-month Treasury bills. This paper examines the implications of a mis-specified risk-free asset, i.e. the possibility that the ‘true’ risk-free asset is a longer-maturity Treasury bond. A simple theoretical derivation leads to the testable prediction that low-beta (high-beta) stocks should then exhibit positive (negative) bond betas. We find strong empirical confirmation for these predictions. The market-implied risk-free asset can be pinpointed at medium-term (5-year) bonds. Concrete implications of this finding are a lower equity risk premium and a less steep security market line.
The Stock Market Tips
SSRN
We provide evidence that stock market fluctuations can affect local economic activity through the spending of public firms’ employees on local goods/services. Using a dataset of New York City taxi records, we find that tips paid for taxis taken near a firm’s headquarters after normal work hours are higher on the days its stock returnsâ€"as well as the market’s returnsâ€"are higher. This finding is stronger for firms offering greater stock-based compensation. The number of taxis taken near a firm’s headquarters also increases with its stock returns. The results of placebo tests suggest that these findings are not spurious.
SSRN
We provide evidence that stock market fluctuations can affect local economic activity through the spending of public firms’ employees on local goods/services. Using a dataset of New York City taxi records, we find that tips paid for taxis taken near a firm’s headquarters after normal work hours are higher on the days its stock returnsâ€"as well as the market’s returnsâ€"are higher. This finding is stronger for firms offering greater stock-based compensation. The number of taxis taken near a firm’s headquarters also increases with its stock returns. The results of placebo tests suggest that these findings are not spurious.
Understanding Machine Learning for Diversified Portfolio Construction by Explainable AI
SSRN
In this paper, we construct a pipeline to investigate heuristic diversification strategies in asset allocation. We use machine learning concepts ("explainable AI") to compare the robustness of different strategies and back out implicit rules for decision making.In a first step, we augment the asset universe (the empirical dataset) with a range of scenarios generated with a block bootstrap from the empirical dataset.Second, we backtest the candidate strategies over a long period of time, checking their performance variability. Third, we use XGBoost as a regression model to connect the difference between the measured performances between two strategies to a pool of statistical features of the portfolio universe tailored to the investigated strategy. Finally, we employ the concept of Shapley values to extract the relationships that the model could identify between the portfolio characteristics and the statistical properties of the asset universe. We test this pipeline for studying risk-parity strategies with a volatility target, and in particular, comparing the machine learning-driven Hierarchical Risk Parity (HRP) to the classical Equal Risk Contribution (ERC) strategy.In the augmented dataset built from a multi-asset investment universe of commodities, equities and fixed income futures, we find that HRP better matches the volatility target, and shows better risk-adjusted performances. Finally, we train XGBoost to learn the difference between the realized Calmar ratios of HRP and ERC and extract explanations.The explanations provide fruitful ex-post indications of the connection between the statistical properties of the universe and the strategy performance in the training set. For example, the model confirms that features addressing the hierarchical properties of the universe are connected to the relative performance of HRP respect to ERC.
SSRN
In this paper, we construct a pipeline to investigate heuristic diversification strategies in asset allocation. We use machine learning concepts ("explainable AI") to compare the robustness of different strategies and back out implicit rules for decision making.In a first step, we augment the asset universe (the empirical dataset) with a range of scenarios generated with a block bootstrap from the empirical dataset.Second, we backtest the candidate strategies over a long period of time, checking their performance variability. Third, we use XGBoost as a regression model to connect the difference between the measured performances between two strategies to a pool of statistical features of the portfolio universe tailored to the investigated strategy. Finally, we employ the concept of Shapley values to extract the relationships that the model could identify between the portfolio characteristics and the statistical properties of the asset universe. We test this pipeline for studying risk-parity strategies with a volatility target, and in particular, comparing the machine learning-driven Hierarchical Risk Parity (HRP) to the classical Equal Risk Contribution (ERC) strategy.In the augmented dataset built from a multi-asset investment universe of commodities, equities and fixed income futures, we find that HRP better matches the volatility target, and shows better risk-adjusted performances. Finally, we train XGBoost to learn the difference between the realized Calmar ratios of HRP and ERC and extract explanations.The explanations provide fruitful ex-post indications of the connection between the statistical properties of the universe and the strategy performance in the training set. For example, the model confirms that features addressing the hierarchical properties of the universe are connected to the relative performance of HRP respect to ERC.
Underwriter Networks, Information Asymmetry, and Seasoned Equity Offerings
SSRN
Using various “centrality†measures from Social Network Analysis (SNA), we analyze, for the first time in the literature, how the location of a lead underwriter in its network of investment banks affects various aspects of seasoned equity offerings (SEOs). We hypothesize that investment banking networks perform an important economic role in the underwriting process for SEOs, namely, that of information dissemination, where the lead underwriter uses its investment banking network to disseminate information about the SEO firm to institutional investors. Consistent with the above information dissemination role, we show that SEOs with more central lead SEO underwriters are associated with a smaller extent of information asymmetry in the equity market. We then develop testable hypotheses based on the information dissemination role of underwriter networks for the relationship between SEO underwriter centrality and various SEO characteristics, which we test in our empirical analysis. Consistent with the above hypotheses, we find that SEOs with more central lead underwriters are associated with less negative announcement effects; smaller offer price revisions; smaller SEO discounts and underpricing; higher immediate post-SEO equity valuations; and greater post-SEO long-run stock returns. We also find that SEOs with more central lead underwriters are associated with greater institutional investor participation. Our instrumental variable (IV) analysis using the industry-average bargaining power of underwriters relative to issuers as the instrument show that the above results are causal. Consistent with greater value creation by more central lead underwriters, we find that more central lead underwriters receive greater compensation as a fraction of total SEO proceeds.
SSRN
Using various “centrality†measures from Social Network Analysis (SNA), we analyze, for the first time in the literature, how the location of a lead underwriter in its network of investment banks affects various aspects of seasoned equity offerings (SEOs). We hypothesize that investment banking networks perform an important economic role in the underwriting process for SEOs, namely, that of information dissemination, where the lead underwriter uses its investment banking network to disseminate information about the SEO firm to institutional investors. Consistent with the above information dissemination role, we show that SEOs with more central lead SEO underwriters are associated with a smaller extent of information asymmetry in the equity market. We then develop testable hypotheses based on the information dissemination role of underwriter networks for the relationship between SEO underwriter centrality and various SEO characteristics, which we test in our empirical analysis. Consistent with the above hypotheses, we find that SEOs with more central lead underwriters are associated with less negative announcement effects; smaller offer price revisions; smaller SEO discounts and underpricing; higher immediate post-SEO equity valuations; and greater post-SEO long-run stock returns. We also find that SEOs with more central lead underwriters are associated with greater institutional investor participation. Our instrumental variable (IV) analysis using the industry-average bargaining power of underwriters relative to issuers as the instrument show that the above results are causal. Consistent with greater value creation by more central lead underwriters, we find that more central lead underwriters receive greater compensation as a fraction of total SEO proceeds.
What Factors Do Influence Islamic Social Reporting (ISR) Disclosure? Evidence from Indonesia
SSRN
This research was aimed to identify factors affecting disclosure quality of Islamic Social Reporting (ISR) disclosure. ISR is an index that measures the level of social disclosure following the sharia principles conveyed by the company in its annual report. To assess corporate social disclosure following Islamic sharia, an index is known as Islamic Social Reporting (ISR). There are four factors believed to influence disclosure ISR quality, i.e. the board of independent commissioners, liquidity, company growth, the age of the company and the size of the company. The data used are secondary data taken from the website of the Indonesia Stock Exchange. The population of this study was the Jakarta Islamic Index company listed in Indonesia Stock Exchange during 2014-2016 period. The samples in this study were taken by using purposive sampling technique to obtain 16 companies. Data analysis techniques used are multiple regression analysis methods. The results showed that liquidity and the size of the firm significantly affect the quality of Islamic social reporting disclosure. While for the board of independent commissioner, company growth and the age of the company has no significant effect on quality of Islamic social reporting disclosure.
SSRN
This research was aimed to identify factors affecting disclosure quality of Islamic Social Reporting (ISR) disclosure. ISR is an index that measures the level of social disclosure following the sharia principles conveyed by the company in its annual report. To assess corporate social disclosure following Islamic sharia, an index is known as Islamic Social Reporting (ISR). There are four factors believed to influence disclosure ISR quality, i.e. the board of independent commissioners, liquidity, company growth, the age of the company and the size of the company. The data used are secondary data taken from the website of the Indonesia Stock Exchange. The population of this study was the Jakarta Islamic Index company listed in Indonesia Stock Exchange during 2014-2016 period. The samples in this study were taken by using purposive sampling technique to obtain 16 companies. Data analysis techniques used are multiple regression analysis methods. The results showed that liquidity and the size of the firm significantly affect the quality of Islamic social reporting disclosure. While for the board of independent commissioner, company growth and the age of the company has no significant effect on quality of Islamic social reporting disclosure.
