Research articles for the 2019-09-20
A Multivariate Approach for the Simultaneous Modelling of Market Risk and Credit Risk for Cryptocurrencies
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This paper proposes a set of models which can be used to estimate the market risk for a portfolio of crypto-currencies, and simultaneously to estimate also their credit risk using the Zero Price Probability (ZPP) model by Fantazzini et al (2008), which is a methodology to compute the probabilities of default using only market prices. For this purpose, both univariate and multivariate models with different specifications are employed. Two special cases of the ZPP with closed-form formulas in case of normally distributed errors are also developed using recent results from barrier option theory. A backtesting exercise using two datasets of 5 and 15 coins for market risk forecasting and a dataset of 42 coins for credit risk forecasting was performed. The Value-at-Risk and the Expected Shortfall for single coins and for an equally weighted portfolio were calculated and evaluated with several tests. The ZPP approach was used for the estimation of the probability of default/death of the single coins and compared to classical credit scoring models (logit and probit) and to a machine learning algorithm (Random Forest). Our results reveal the superiority of the t-copula/skewed-t GARCH model for market risk, and the ZPP-based models for credit risk.
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This paper proposes a set of models which can be used to estimate the market risk for a portfolio of crypto-currencies, and simultaneously to estimate also their credit risk using the Zero Price Probability (ZPP) model by Fantazzini et al (2008), which is a methodology to compute the probabilities of default using only market prices. For this purpose, both univariate and multivariate models with different specifications are employed. Two special cases of the ZPP with closed-form formulas in case of normally distributed errors are also developed using recent results from barrier option theory. A backtesting exercise using two datasets of 5 and 15 coins for market risk forecasting and a dataset of 42 coins for credit risk forecasting was performed. The Value-at-Risk and the Expected Shortfall for single coins and for an equally weighted portfolio were calculated and evaluated with several tests. The ZPP approach was used for the estimation of the probability of default/death of the single coins and compared to classical credit scoring models (logit and probit) and to a machine learning algorithm (Random Forest). Our results reveal the superiority of the t-copula/skewed-t GARCH model for market risk, and the ZPP-based models for credit risk.
A Sustainable Capital Asset Pricing Model (S-CAPM): Evidence from Green Investing and Sin Stock Exclusion
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I demonstrate how sustainable investing through exclusionary screening and environmental, social and governance (ESG) integration affects asset returns. I develop an asset pricing model with partial segmentation and heterogeneous beliefs. I characterize two exclusion premia generalizing Merton's (1987) premium on neglected stocks and a taste premium that disentangles the link between ESG and financial performance. By constructing an instrument that captures sustainable investors' tastes for green firms, I estimate this model applied to green investing and sin stock exclusion using U.S. data between 2000 and 2018. The model outperforms the four-factor model, and yields a taste and an exclusion effect of 1.5% and 2.5% per year, respectively.
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I demonstrate how sustainable investing through exclusionary screening and environmental, social and governance (ESG) integration affects asset returns. I develop an asset pricing model with partial segmentation and heterogeneous beliefs. I characterize two exclusion premia generalizing Merton's (1987) premium on neglected stocks and a taste premium that disentangles the link between ESG and financial performance. By constructing an instrument that captures sustainable investors' tastes for green firms, I estimate this model applied to green investing and sin stock exclusion using U.S. data between 2000 and 2018. The model outperforms the four-factor model, and yields a taste and an exclusion effect of 1.5% and 2.5% per year, respectively.
Aggregate Investor Sentiment and Stock Return Synchronicity
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We show that the returns of individual stocks become more synchronous with the aggregate market during periods of high investor sentiment. We also document that the effect of sentiment on stock return synchronicity is especially pronounced for small, young, volatile, non-dividend-paying and low-priced stocks. This âdifference in differenceâ suggests that stocks with these characteristics are affected more by sentiment â" consistent with previous studies. Our results support the hypothesis that greater constraints on arbitrage and the prevalence of sentiment-driven demand during periods of high sentiment lead to increased comovement among stocks.
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We show that the returns of individual stocks become more synchronous with the aggregate market during periods of high investor sentiment. We also document that the effect of sentiment on stock return synchronicity is especially pronounced for small, young, volatile, non-dividend-paying and low-priced stocks. This âdifference in differenceâ suggests that stocks with these characteristics are affected more by sentiment â" consistent with previous studies. Our results support the hypothesis that greater constraints on arbitrage and the prevalence of sentiment-driven demand during periods of high sentiment lead to increased comovement among stocks.
Are Social Media Analysts Disrupting the Information Content of Sell-Side Analystsâ Reports?
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We examine the impact of âsocial media analysts,â individuals posting equity research online via social media investment platforms, on the value-relevance of the forecasts of professional sell-side equity analysts. Using data from Seeking Alpha, we find that the market reaction to a sell-side analyst forecast is substantially reduced when preceded by the report of a social media analyst. We find that this effect is more pronounced when the social media analyst has greater expertise and when the investor base consists of more retail investors. Additional analyses reveal that social media analyst reports pre-empt the information content of sell-side analyst forecasts when the tenor of the report is consistent (i.e., either positive or negative) with that of the sell-side analyst. Finally, we find no evidence that social media analyst research is associated with inefficient noise trading following the release of sell-side analyst forecasts. Collectively, our results suggest that equity research posted online by social media analysts is disrupting the information content of sell-side equity research. Our findings thus have important implications for understanding how social media is influencing the evolving role of information intermediaries in capital markets.
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We examine the impact of âsocial media analysts,â individuals posting equity research online via social media investment platforms, on the value-relevance of the forecasts of professional sell-side equity analysts. Using data from Seeking Alpha, we find that the market reaction to a sell-side analyst forecast is substantially reduced when preceded by the report of a social media analyst. We find that this effect is more pronounced when the social media analyst has greater expertise and when the investor base consists of more retail investors. Additional analyses reveal that social media analyst reports pre-empt the information content of sell-side analyst forecasts when the tenor of the report is consistent (i.e., either positive or negative) with that of the sell-side analyst. Finally, we find no evidence that social media analyst research is associated with inefficient noise trading following the release of sell-side analyst forecasts. Collectively, our results suggest that equity research posted online by social media analysts is disrupting the information content of sell-side equity research. Our findings thus have important implications for understanding how social media is influencing the evolving role of information intermediaries in capital markets.
Deep Learning, Jumps, and Volatility Bursts
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We develop a new method that detects jumps nonparametrically in financial time series and significantly outperforms the current benchmark on simulated data. We use a long short-term memory (LSTM) neural network that is trained on data generated by a process that experiences both jumps and volatility bursts. As a result, the network learns how to disentangle the two. Then it is applied to out-of-sample simulated data and delivers results that considerably differ from the benchmark: we obtain fewer spurious detection and identify a larger number of true jumps. The method is used on real data afterwards.
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We develop a new method that detects jumps nonparametrically in financial time series and significantly outperforms the current benchmark on simulated data. We use a long short-term memory (LSTM) neural network that is trained on data generated by a process that experiences both jumps and volatility bursts. As a result, the network learns how to disentangle the two. Then it is applied to out-of-sample simulated data and delivers results that considerably differ from the benchmark: we obtain fewer spurious detection and identify a larger number of true jumps. The method is used on real data afterwards.
Equity Crowdfunding Portals Should Join and Enhance the Crowd by Providing Venture Formation Resources
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Several leading venture capital (VC) law firms share their formation-related resources online. These resources are for high-growth ventures forming as Delaware corporations and using equity to recruit, motivate, compensate, and retain employees. While different law firms provide these materials, the resources are quite similar. Many of the resources used by VC-backed companies are well suited for Regulation Crowdfunding (Regulation CF) issuers. This is because the typical Regulation CF issuer is also a new, high-growth, Delaware corporation with four or five employees. Thus, like VC-backed companies, Regulation CF companies should benefit from providing equity to employees, making that equity subject to vesting, and taking advantage of a two-tier stock structure (i.e., by issuing relatively inexpensive common stock to employees and more expensive preferred stock to outside investors). The established VC ecosystem has demonstrated that sharing formation-related resources reflecting these best practices helps its stakeholders. It is time for equity crowdfunding portals to provide similar formation-related resources to Regulation CF issuers and to even require usage. Alternatively, an equity crowdfunding association could develop and maintain such resources. Funding portals could then select which resources to require their issuers to use. Regardless, by having issuers to use a set of formation-related resources, funding portals could ensure best practices are followed, reduce transaction costs, and accelerate growth and the creation of wealth without practicing law. Given many Regulation CF companies lack the cash and expertise, they should value these formation-related resources even more than the VC-backed companies do.
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Several leading venture capital (VC) law firms share their formation-related resources online. These resources are for high-growth ventures forming as Delaware corporations and using equity to recruit, motivate, compensate, and retain employees. While different law firms provide these materials, the resources are quite similar. Many of the resources used by VC-backed companies are well suited for Regulation Crowdfunding (Regulation CF) issuers. This is because the typical Regulation CF issuer is also a new, high-growth, Delaware corporation with four or five employees. Thus, like VC-backed companies, Regulation CF companies should benefit from providing equity to employees, making that equity subject to vesting, and taking advantage of a two-tier stock structure (i.e., by issuing relatively inexpensive common stock to employees and more expensive preferred stock to outside investors). The established VC ecosystem has demonstrated that sharing formation-related resources reflecting these best practices helps its stakeholders. It is time for equity crowdfunding portals to provide similar formation-related resources to Regulation CF issuers and to even require usage. Alternatively, an equity crowdfunding association could develop and maintain such resources. Funding portals could then select which resources to require their issuers to use. Regardless, by having issuers to use a set of formation-related resources, funding portals could ensure best practices are followed, reduce transaction costs, and accelerate growth and the creation of wealth without practicing law. Given many Regulation CF companies lack the cash and expertise, they should value these formation-related resources even more than the VC-backed companies do.
Free Market on the Freeway
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his paper studies a trading mechanism allowing autonomous cars to change lanes on a freeway in congested traffic. When no room is available on the adjacent lane, the mechanism enable a car to change lanes if it pays a small fee to the car occupying the space it is moving into, compensating it for slowing down. We model the impact of this mechanism as a market for speed, which is free in the sense that it can be implemented by peer-to-peer technology without the intervention of the freeway operator. The term market is warranted by the simultaneous presence of multiple lane buyers and lane sellers. We use the term freeway to emphasize that we are not modeling toll-lanes. We develop conditions that the price system should satisfy. The presence of uncertainty in traffic density as well as price makes us model them as the solution of a system of stochastic partial differential equations. We simulate our model and perform sensitivity analysis on the parameters and initial conditions.
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his paper studies a trading mechanism allowing autonomous cars to change lanes on a freeway in congested traffic. When no room is available on the adjacent lane, the mechanism enable a car to change lanes if it pays a small fee to the car occupying the space it is moving into, compensating it for slowing down. We model the impact of this mechanism as a market for speed, which is free in the sense that it can be implemented by peer-to-peer technology without the intervention of the freeway operator. The term market is warranted by the simultaneous presence of multiple lane buyers and lane sellers. We use the term freeway to emphasize that we are not modeling toll-lanes. We develop conditions that the price system should satisfy. The presence of uncertainty in traffic density as well as price makes us model them as the solution of a system of stochastic partial differential equations. We simulate our model and perform sensitivity analysis on the parameters and initial conditions.
Generalized Euler Equation Errors for Discrete Time Dynamic Portfolio Choice Models
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The solution to dynamic portfolio choice models can be formulated in terms of a value function by the Bellman principle of optimality, which reduces the multi-period optimal policy choice problem to a sequence of one-period maximization problems. For two adjacent periods, economists compute the error of numerically obtained policies by measuring how much these policies violate the intertemporal first order conditions for the optimal policy choice problem â" so-called Euler equation errors. In this short note, we derive generalized Euler equation errors for the solution to a broad class of discrete time dynamic portfolio choice models where the policies are continuous choice variables. Our key precondition is that the gradient of the value function with respect to the state variables can be approximated. This is, for example, the case when a global polynomial basis or B-spline basis functions are used for the approximation of the value function within the discrete time dynamic programming approach. We apply our theoretical results to exemplary, representative dynamic portfolio choice models.
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The solution to dynamic portfolio choice models can be formulated in terms of a value function by the Bellman principle of optimality, which reduces the multi-period optimal policy choice problem to a sequence of one-period maximization problems. For two adjacent periods, economists compute the error of numerically obtained policies by measuring how much these policies violate the intertemporal first order conditions for the optimal policy choice problem â" so-called Euler equation errors. In this short note, we derive generalized Euler equation errors for the solution to a broad class of discrete time dynamic portfolio choice models where the policies are continuous choice variables. Our key precondition is that the gradient of the value function with respect to the state variables can be approximated. This is, for example, the case when a global polynomial basis or B-spline basis functions are used for the approximation of the value function within the discrete time dynamic programming approach. We apply our theoretical results to exemplary, representative dynamic portfolio choice models.
How Does Financial Leverage Affect Financial Risk? An Empirical Study in Sri Lanka
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Having debt or preferred stock capital is an important decision made by firms because the return on equity, in general, is expected to be higher with debt. Nevertheless, the costs associated with leverage tend to outweigh the benefits when the leverage increases beyond an optimal level. Thus, excessive leverage may create an uncertainty about a firmâs existence. However, straight forward guidelines on what constitutes the optimal level of leverage remain largely missing. Therefore, this study examines how financial leverage affects financial risk based on the data collected over ten years ranging from 2006 to 2015 regarding fifteen companies in Hotels and Travels, and Chemicals and Pharmaceuticals industries listed in the Colombo Stock Exchange. The findings revealed that financial leverage positively correlate with financial risk. However, firm size negatively affects the financial risk. Importantly, Hotels and Travels firms have a higher financial risk compared to Chemicals and Pharmaceuticals firms. Hence, financial leverage and firm size can be considered as determinants of financial risk. The findings imply that firms having a higher financial risk can avoid its risk by altering the capital structure when the market condition is favourable. Firms are, however, least able to do so during a decline in the industry.
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Having debt or preferred stock capital is an important decision made by firms because the return on equity, in general, is expected to be higher with debt. Nevertheless, the costs associated with leverage tend to outweigh the benefits when the leverage increases beyond an optimal level. Thus, excessive leverage may create an uncertainty about a firmâs existence. However, straight forward guidelines on what constitutes the optimal level of leverage remain largely missing. Therefore, this study examines how financial leverage affects financial risk based on the data collected over ten years ranging from 2006 to 2015 regarding fifteen companies in Hotels and Travels, and Chemicals and Pharmaceuticals industries listed in the Colombo Stock Exchange. The findings revealed that financial leverage positively correlate with financial risk. However, firm size negatively affects the financial risk. Importantly, Hotels and Travels firms have a higher financial risk compared to Chemicals and Pharmaceuticals firms. Hence, financial leverage and firm size can be considered as determinants of financial risk. The findings imply that firms having a higher financial risk can avoid its risk by altering the capital structure when the market condition is favourable. Firms are, however, least able to do so during a decline in the industry.
New Tax Issues Arising from Derivatives Regulatory Reform
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This article addresses current (as of June 2010) and anticipated U.S. federal income tax issues arising from the clearing of swaps through regulated central counterparties. It makes suggestions for changes to the law in order to address those issues. It is believed that the article inspired the enactment of section 1256(b)(2)(B) of the Internal Revenue Code, which was enacted as section 1601 of the Dodd-Frank Wall Street Reform and Consumer Protection Act.The article examines an array of new U.S. federal income tax questions that arose as a result of changes in market practice and the legal rules governing credit default swaps and other over-the-counter derivative financial instruments (âswapsâ). The first tax question addressed by the article is whether the clearing of swaps on regulated clearinghouses and/or the trading of swaps on regulated exchanges causes such swaps to become âsection 1256 contractsâ required to be marked to market on an annual basis, or should do so. Gain or loss from a section 1256 contract generally is treated for U.S. federal income tax purposes as 60 percent long-term capital gain/loss and 40 percent short-term capital gain/loss, which would be disadvantageous for many taxpayers but advantageous for others. The article then turns to the question of how a large initial payment on a swap â" a fact pattern that is common for credit default and other swaps that have âstandardizedâ coupons, whether or not they are cleared through a regulated clearinghouse â" should be taxed, and in particular whether under current (as of June 2010) law such a payment can give rise to a debt obligation between the parties. Part I of the article provides a brief overview of what a credit default swap is, the manner in which parties transact in swaps in the over-the-counter market, the tax treatment of notional principal contracts and options, respectively, and the basics of section 1256 treatment. Part I is intended as background for readers not already familiar with those instruments or tax rules. Part II of the article describes in broad strokes the proposals pending in Congress as of June 2010 to require clearing and/or exchange-trading of swaps (subsequently enacted by Dodd-Frank), and the manner in which credit default swaps were being cleared on ICE Trust U.S. and the Chicago Mercantile Exchange, the two U.S. clearinghouses for such swaps. Part II also discusses how the initial premium on a standard coupon credit default swap is priced. Part III then considers the section 1256 issue, and Part IV discusses the issues arising from large initial payments on standardized swaps, whether or not they are cleared or traded.The article recommends several possible legislative solutions to the section 1256 issue, and regulatory guidance with respect to the deemed loan issue.
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This article addresses current (as of June 2010) and anticipated U.S. federal income tax issues arising from the clearing of swaps through regulated central counterparties. It makes suggestions for changes to the law in order to address those issues. It is believed that the article inspired the enactment of section 1256(b)(2)(B) of the Internal Revenue Code, which was enacted as section 1601 of the Dodd-Frank Wall Street Reform and Consumer Protection Act.The article examines an array of new U.S. federal income tax questions that arose as a result of changes in market practice and the legal rules governing credit default swaps and other over-the-counter derivative financial instruments (âswapsâ). The first tax question addressed by the article is whether the clearing of swaps on regulated clearinghouses and/or the trading of swaps on regulated exchanges causes such swaps to become âsection 1256 contractsâ required to be marked to market on an annual basis, or should do so. Gain or loss from a section 1256 contract generally is treated for U.S. federal income tax purposes as 60 percent long-term capital gain/loss and 40 percent short-term capital gain/loss, which would be disadvantageous for many taxpayers but advantageous for others. The article then turns to the question of how a large initial payment on a swap â" a fact pattern that is common for credit default and other swaps that have âstandardizedâ coupons, whether or not they are cleared through a regulated clearinghouse â" should be taxed, and in particular whether under current (as of June 2010) law such a payment can give rise to a debt obligation between the parties. Part I of the article provides a brief overview of what a credit default swap is, the manner in which parties transact in swaps in the over-the-counter market, the tax treatment of notional principal contracts and options, respectively, and the basics of section 1256 treatment. Part I is intended as background for readers not already familiar with those instruments or tax rules. Part II of the article describes in broad strokes the proposals pending in Congress as of June 2010 to require clearing and/or exchange-trading of swaps (subsequently enacted by Dodd-Frank), and the manner in which credit default swaps were being cleared on ICE Trust U.S. and the Chicago Mercantile Exchange, the two U.S. clearinghouses for such swaps. Part II also discusses how the initial premium on a standard coupon credit default swap is priced. Part III then considers the section 1256 issue, and Part IV discusses the issues arising from large initial payments on standardized swaps, whether or not they are cleared or traded.The article recommends several possible legislative solutions to the section 1256 issue, and regulatory guidance with respect to the deemed loan issue.
Post-Financial Crisis Regulation and the U.S. Tax Treatment of Bank Capital Securities
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The article discusses the U.S. federal income tax characterization of equity-flavored debt instruments issued by banks in compliance with bank regulatory rules adopted after the financial crisis of the late 2000âs.Banks and other financial institutions must issue financial instruments that qualifyas raising capital in order to satisfy regulatory requirements. Banks also must issue financial instruments that facilitate their resolution if they become financially distressed. A portion, often a large portion, of these instruments may be issued in the legal form of debt. U.S. tax law has certain requirements for a financial instrument with the legal form of debt to be respected as indebtedness for tax purposes. The intersection between these two sets of rules can be vexing, since it is inherent in a capital instrument with the legal form of debt that it is subordinate to protected creditors â" for example, depositors in a bank â" and frequently has deferral or non-payment provisions not wholly consistent with a tax lawyerâs notion of conventional debt.A body of historic tax case law and rulings addresses the classification of legal-form debt issued to satisfy regulatory requirements applicable to banks and other financial institutions. That law typically is deferential to regulatory requirements. The issue discussed by this article is whether that deference extends to the new forms of legal-form debt instruments that banks and their affiliates are issuing pursuant to the bank regulatory rules that have been adopted since the financial crisis of the late 2000âs.The article summarizes bank capital and resolution rules, in lay terms suitable for a tax audience; describes the different types of bank capital and resolution instruments that banks issue; discusses the investor perspective for why the U.S. federal income tax characterization of these instruments matter, including characterization, timing, and other issues; and finally lays out a framework for analyzing whether bank capital and resolution instruments should be treated as debt or equity for U.S. federal income tax purposes. It is believed that this article was the first to discuss debt-equity tax issues with respect to debt instruments issued by banks in compliance with bank regulatory rules adopted after the financial crisis of the late 2000âs.
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The article discusses the U.S. federal income tax characterization of equity-flavored debt instruments issued by banks in compliance with bank regulatory rules adopted after the financial crisis of the late 2000âs.Banks and other financial institutions must issue financial instruments that qualifyas raising capital in order to satisfy regulatory requirements. Banks also must issue financial instruments that facilitate their resolution if they become financially distressed. A portion, often a large portion, of these instruments may be issued in the legal form of debt. U.S. tax law has certain requirements for a financial instrument with the legal form of debt to be respected as indebtedness for tax purposes. The intersection between these two sets of rules can be vexing, since it is inherent in a capital instrument with the legal form of debt that it is subordinate to protected creditors â" for example, depositors in a bank â" and frequently has deferral or non-payment provisions not wholly consistent with a tax lawyerâs notion of conventional debt.A body of historic tax case law and rulings addresses the classification of legal-form debt issued to satisfy regulatory requirements applicable to banks and other financial institutions. That law typically is deferential to regulatory requirements. The issue discussed by this article is whether that deference extends to the new forms of legal-form debt instruments that banks and their affiliates are issuing pursuant to the bank regulatory rules that have been adopted since the financial crisis of the late 2000âs.The article summarizes bank capital and resolution rules, in lay terms suitable for a tax audience; describes the different types of bank capital and resolution instruments that banks issue; discusses the investor perspective for why the U.S. federal income tax characterization of these instruments matter, including characterization, timing, and other issues; and finally lays out a framework for analyzing whether bank capital and resolution instruments should be treated as debt or equity for U.S. federal income tax purposes. It is believed that this article was the first to discuss debt-equity tax issues with respect to debt instruments issued by banks in compliance with bank regulatory rules adopted after the financial crisis of the late 2000âs.
Selective Disclosure of Credit Ratings: Evidence from Moody's Rating Changes
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This paper provides suggestive evidence that large shareholders of Moodyâs (affiliated investors) can access Moodyâs rating changes before their public release. Affiliated investors abnormally decrease their holdings of a stock before its downgrade by Moodyâs. This finding is stronger for informationally opaque stocks and active affiliated investors, significant only after affiliated investors become Moodyâs shareholders, and insignificant for rating upgrades that are not expected to impact stock prices. A placebo study finds no abnormal trading by affiliated investors before S&Pâs or Fitchâs downgrades. Additional tests help rule out ability-, selection-, or reverse causality-related explanations for these findings.
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This paper provides suggestive evidence that large shareholders of Moodyâs (affiliated investors) can access Moodyâs rating changes before their public release. Affiliated investors abnormally decrease their holdings of a stock before its downgrade by Moodyâs. This finding is stronger for informationally opaque stocks and active affiliated investors, significant only after affiliated investors become Moodyâs shareholders, and insignificant for rating upgrades that are not expected to impact stock prices. A placebo study finds no abnormal trading by affiliated investors before S&Pâs or Fitchâs downgrades. Additional tests help rule out ability-, selection-, or reverse causality-related explanations for these findings.
Stock Market Volatility & Wealth Inequality
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This paper explores how volatility in stock markets affects wealth inequality. It first presents a stylized two trader example that demonstrates that random trading always leads to a situation of great wealth inequality because at a certain point one of the two traders is no longer wealthy enough to trade. In this example, increased price volatility increases trading profits that accelerates the move to this unequal state. The paper then shows that this same dynamic holds in a multi-agent setting. It presents an agent-based stock market model with a thousand noise traders that are heterogeneous with regards to their wealth. Simulation experiments show that the trading system leads to a highly unequal state as the wealth of more and more traders becomes so low that they have to stop trading. Increasing price volatility accelerates the movement towards this state.
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This paper explores how volatility in stock markets affects wealth inequality. It first presents a stylized two trader example that demonstrates that random trading always leads to a situation of great wealth inequality because at a certain point one of the two traders is no longer wealthy enough to trade. In this example, increased price volatility increases trading profits that accelerates the move to this unequal state. The paper then shows that this same dynamic holds in a multi-agent setting. It presents an agent-based stock market model with a thousand noise traders that are heterogeneous with regards to their wealth. Simulation experiments show that the trading system leads to a highly unequal state as the wealth of more and more traders becomes so low that they have to stop trading. Increasing price volatility accelerates the movement towards this state.
The Commodity Futures Risk Premium: 1871 â" 2018
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Using a novel comprehensive database of 230 commodity futures that traded between 1871 and 2018, we document that futures prices have on average been set at a discount to future spot prices by about 5%. The historical risk premium is robust across commodity sectors and varies with the state of the economy, inflation and the level of scarcity. Although the majority of contracts are defunct, most commodities have earned a positive risk premium over their lifespan. We find empirical support for Grayâs conjecture that survival of futures contracts is correlated with the returns earned by investors. Finally, we provide out-of-sample evidence that âfactorâ strategies based on commodity basis and momentum have historically earned positive returns over time but are subject to prolonged drawdowns (crashes) that are not dissimilar to those experienced by the overall market.
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Using a novel comprehensive database of 230 commodity futures that traded between 1871 and 2018, we document that futures prices have on average been set at a discount to future spot prices by about 5%. The historical risk premium is robust across commodity sectors and varies with the state of the economy, inflation and the level of scarcity. Although the majority of contracts are defunct, most commodities have earned a positive risk premium over their lifespan. We find empirical support for Grayâs conjecture that survival of futures contracts is correlated with the returns earned by investors. Finally, we provide out-of-sample evidence that âfactorâ strategies based on commodity basis and momentum have historically earned positive returns over time but are subject to prolonged drawdowns (crashes) that are not dissimilar to those experienced by the overall market.
The First Commodity Futures Index of 1933
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We document the properties of the first commodity futures index, the Dow Jones Commodity Futures Index, and use it as a historical laboratory experiment to study the pricing of commodity futures. Despite the setbacks posed by contract failure and trading suspensions of index constituents, the index earned a risk premium of 3.7% per year between 1933 and 1998. The index exhibits time-varying correlations with equities that are higher around economic downturns, and a correlation with inflation that are positive and exceed those of traditional assets.
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We document the properties of the first commodity futures index, the Dow Jones Commodity Futures Index, and use it as a historical laboratory experiment to study the pricing of commodity futures. Despite the setbacks posed by contract failure and trading suspensions of index constituents, the index earned a risk premium of 3.7% per year between 1933 and 1998. The index exhibits time-varying correlations with equities that are higher around economic downturns, and a correlation with inflation that are positive and exceed those of traditional assets.
The Importance of Being Informed: Forecasting Market Risk Measures for the Russian RTS Index Future Using Online Data and Implied Volatility Over Two Decade
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This paper focuses on the forecasting of market risk measures for the Russian RTS index future, and examines whether augmenting a large class of volatility models with implied volatility and Google Trends data improves the quality of the estimated risk measures. We considered a time sample of daily data from 2006 till 2019, which includes several episodes of large-scale turbulence in the Russian future market. We found that the predictive power of several models did not increase if these two variables were added, but actually decreased. The worst results were obtained when these two variables were added jointly and during periods of high volatility, when parameters estimates became very unstable. Moreover, several models augmented with these variables did not reach numerical convergence. Our empirical evidence shows that, in the case of Russian future markets, T-GARCH models with implied volatility and studentâs t errors are better choices if robust market risk measures are of concern.
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This paper focuses on the forecasting of market risk measures for the Russian RTS index future, and examines whether augmenting a large class of volatility models with implied volatility and Google Trends data improves the quality of the estimated risk measures. We considered a time sample of daily data from 2006 till 2019, which includes several episodes of large-scale turbulence in the Russian future market. We found that the predictive power of several models did not increase if these two variables were added, but actually decreased. The worst results were obtained when these two variables were added jointly and during periods of high volatility, when parameters estimates became very unstable. Moreover, several models augmented with these variables did not reach numerical convergence. Our empirical evidence shows that, in the case of Russian future markets, T-GARCH models with implied volatility and studentâs t errors are better choices if robust market risk measures are of concern.
The Protection Gap in Homeowners Insurance: An Introduction
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In the past few years the insurance community has paid increasing attention to the âprotection gapâ â" the extent to which significant property losses are not covered by insurance. Because insurance plays an important economic and social role in many ways, the protection gap is significant to individuals, firms, the communities in which they reside or operate, and the economy as a whole.In March 2019, the Rutgers Center for Risk and Responsibility at Rutgers Law School held a conference on The Protection Gap in Property Insurance. Academics in law and business, policyholder-side and insurer-side coverage lawyers, regulators, consumer advocates, and other professionals engaged in insurance issues explored protection gaps: what they are, where they occur, what causes them, and how to cure them. This paper provides an orientation to the issues raised at the conference.
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In the past few years the insurance community has paid increasing attention to the âprotection gapâ â" the extent to which significant property losses are not covered by insurance. Because insurance plays an important economic and social role in many ways, the protection gap is significant to individuals, firms, the communities in which they reside or operate, and the economy as a whole.In March 2019, the Rutgers Center for Risk and Responsibility at Rutgers Law School held a conference on The Protection Gap in Property Insurance. Academics in law and business, policyholder-side and insurer-side coverage lawyers, regulators, consumer advocates, and other professionals engaged in insurance issues explored protection gaps: what they are, where they occur, what causes them, and how to cure them. This paper provides an orientation to the issues raised at the conference.
The Role of Media in Mergers and Acquisitions
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Using a novel dataset of news events for 170,000 entities across over 100 countries, we find that media sentiment plays an important role in the market for merger and acquisition. Firms with high media sentiment are more likely to become an acquirer. The effect of media on the likelihood of an acquisition is stronger for cross-border deals, larger firms with fewer financial constraints, and firms with higher market-to-book ratio and more media coverage. Acquirers with high media sentiment experience significantly negative returns post-acquisition, inconsistent with theories of media content as a proxy for new information about fundamental asset values.
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Using a novel dataset of news events for 170,000 entities across over 100 countries, we find that media sentiment plays an important role in the market for merger and acquisition. Firms with high media sentiment are more likely to become an acquirer. The effect of media on the likelihood of an acquisition is stronger for cross-border deals, larger firms with fewer financial constraints, and firms with higher market-to-book ratio and more media coverage. Acquirers with high media sentiment experience significantly negative returns post-acquisition, inconsistent with theories of media content as a proxy for new information about fundamental asset values.
Unemployment, Global Economic Crises and Suicides: Evidence from 21 OECD Countries
SSRN
This study explores age- and gender-specific suicide mortality due to unemployment and economic crises, for 21 OECD countries over the period 1960 to 2011. The findings indicate that a higher unemployment rate leads to an increase in suicides in almost all age groups. Further, using dataset on economic/financial crisis events, results show that, in general, these crises increase suicide rates. However, the evidence also shows that economic crises have no effect on those in the 45 to 64 years age group in terms of suicides. Further, we assessed whether suicide mortality can be attributed to a âcrisis effectâ beyond that of unemployment. For males, we found a significant joint effect between crises and unemployment. Finally, we investigated the possible nonlinear threshold response of suicides to unemployment. We found that suicides among young males (< 45 years) are due to marked increases in unemployment in association with global economic crises.
SSRN
This study explores age- and gender-specific suicide mortality due to unemployment and economic crises, for 21 OECD countries over the period 1960 to 2011. The findings indicate that a higher unemployment rate leads to an increase in suicides in almost all age groups. Further, using dataset on economic/financial crisis events, results show that, in general, these crises increase suicide rates. However, the evidence also shows that economic crises have no effect on those in the 45 to 64 years age group in terms of suicides. Further, we assessed whether suicide mortality can be attributed to a âcrisis effectâ beyond that of unemployment. For males, we found a significant joint effect between crises and unemployment. Finally, we investigated the possible nonlinear threshold response of suicides to unemployment. We found that suicides among young males (< 45 years) are due to marked increases in unemployment in association with global economic crises.