Mohamed Ghaly, Alexandros Kostakis, K. Stathopoulos
Abstract Labor unionization has no causal effect on firm risk. Using a regression discontinuity design to study the impact of labor union elections on option-implied firm risk, we find that unionization per se does not affect investor perceptions about firm price, tail, or variance risk. This finding is robust to studying very short (5-trading day) and long (up to 2-year) windows around the elections. Moreover, there is no unionization effect on firm risk either in subsets of firms facing strong union bargaining power, or with characteristics that prior literature identifies as important determinants of the effect of unionization on firm outcomes.
{"title":"The (Non-) Effect of Labor Unionization on Firm Risk: Evidence From the Options Market","authors":"Mohamed Ghaly, Alexandros Kostakis, K. Stathopoulos","doi":"10.2139/ssrn.3291555","DOIUrl":"https://doi.org/10.2139/ssrn.3291555","url":null,"abstract":"Abstract Labor unionization has no causal effect on firm risk. Using a regression discontinuity design to study the impact of labor union elections on option-implied firm risk, we find that unionization per se does not affect investor perceptions about firm price, tail, or variance risk. This finding is robust to studying very short (5-trading day) and long (up to 2-year) windows around the elections. Moreover, there is no unionization effect on firm risk either in subsets of firms facing strong union bargaining power, or with characteristics that prior literature identifies as important determinants of the effect of unionization on firm outcomes.","PeriodicalId":251522,"journal":{"name":"Risk Management & Analysis in Financial Institutions eJournal","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124651577","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We perform an empirical analysis of trading strategies based on the systematic selling of delta hedged options, aiming at capturing the so-called volatility risk premium. We compare the performance across different strikes and maturities, and perform a breakdown of the drivers of performance. We also examine how such strategies can be combined to extract other premia related to the profile of the volatility surface, e.g. the skew and the term structure. In this first paper we focus on the S&P 500 index over the period 2010–2018.
{"title":"The Volatility Risk Premium: An Empirical Study on the S&P 500 Index","authors":"Ivan Guo, G. Loeper","doi":"10.2139/ssrn.3739933","DOIUrl":"https://doi.org/10.2139/ssrn.3739933","url":null,"abstract":"We perform an empirical analysis of trading strategies based on the systematic selling of delta hedged options, aiming at capturing the so-called volatility risk premium. We compare the performance across different strikes and maturities, and perform a breakdown of the drivers of performance. We also examine how such strategies can be combined to extract other premia related to the profile of the volatility surface, e.g. the skew and the term structure. In this first paper we focus on the S&P 500 index over the period 2010–2018.","PeriodicalId":251522,"journal":{"name":"Risk Management & Analysis in Financial Institutions eJournal","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116297902","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this article we derive the shareholder loss due to a capital requirement associated to a derivatives transaction. This is a result of a transfer of wealth between shareholders and creditors of the firm. The charge required to negate this loss can be regarded as a capital valuation adjustment which we refer to as KVA2. Our approach does not assume a fixed hurdle rate on equity required by shareholders. Instead we derive the economic return on capital for a marginal derivatives trade. We provide two complementary derivations of the valuation adjustment. The first is based on a Merton single-period balance sheet model and the second on continuous time no-arbitrage arguments.
Our resulting KVA expression is similar in structure to those proposed in the literature. We find however that the effective rate on capital that a shareholder should demand in a derivatives transaction is a junior funding rate as opposed to the return on equity. This is a consequence of the fact that the only risk a shareholder faces once a derivatives transaction is fully hedged is the default of the firm itself.
{"title":"KVA as a Transfer of Wealth","authors":"M. Arnsdorf","doi":"10.2139/ssrn.3484997","DOIUrl":"https://doi.org/10.2139/ssrn.3484997","url":null,"abstract":"In this article we derive the shareholder loss due to a capital requirement associated to a derivatives transaction. This is a result of a transfer of wealth between shareholders and creditors of the firm. The charge required to negate this loss can be regarded as a capital valuation adjustment which we refer to as KVA2. Our approach does not assume a fixed hurdle rate on equity required by shareholders. Instead we derive the economic return on capital for a marginal derivatives trade. We provide two complementary derivations of the valuation adjustment. The first is based on a Merton single-period balance sheet model and the second on continuous time no-arbitrage arguments.<br><br>Our resulting KVA expression is similar in structure to those proposed in the literature. We find however that the effective rate on capital that a shareholder should demand in a derivatives transaction is a junior funding rate as opposed to the return on equity. This is a consequence of the fact that the only risk a shareholder faces once a derivatives transaction is fully hedged is the default of the firm itself.","PeriodicalId":251522,"journal":{"name":"Risk Management & Analysis in Financial Institutions eJournal","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114669838","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A dynamic semi-parametric framework is proposed to study time variation in tail fatness of sovereign bond yield changes during the 2010--2012 euro area sovereign debt crisis measured at a high (15-minute) frequency. The framework builds on the Generalized Pareto Distribution (GPD) for modeling peaks over thresholds as in Extreme Value Theory, but casts the model in a conditional framework to allow for time-variation in the tail shape parameters. The score-driven updates used improve the expected Kullback-Leibler divergence between the model and the true data generating process on every step even if the GPD only fits approximately and the model is mis-sepcified, as will be the case in any finite sample. This is confirmed in simulations. Using the model, we find the ECB program had a beneficial impact on extreme upper tail quantiles, leaning against the risk of extremely adverse market outcomes while active.
{"title":"Modeling Extreme Events: Time-Varying Extreme Tail Shape","authors":"B. Schwaab, Xin Zhang, A. Lucas","doi":"10.2139/ssrn.3727897","DOIUrl":"https://doi.org/10.2139/ssrn.3727897","url":null,"abstract":"A dynamic semi-parametric framework is proposed to study time variation in tail fatness of sovereign bond yield changes during the 2010--2012 euro area sovereign debt crisis measured at a high (15-minute) frequency. The framework builds on the Generalized Pareto Distribution (GPD) for modeling peaks over thresholds as in Extreme Value Theory, but casts the model in a conditional framework to allow for time-variation in the tail shape parameters. The score-driven updates used improve the expected Kullback-Leibler divergence between the model and the true data generating process on every step even if the GPD only fits approximately and the model is mis-sepcified, as will be the case in any finite sample. This is confirmed in simulations. Using the model, we find the ECB program had a beneficial impact on extreme upper tail quantiles, leaning against the risk of extremely adverse market outcomes while active.","PeriodicalId":251522,"journal":{"name":"Risk Management & Analysis in Financial Institutions eJournal","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129791705","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We show that structured equity derivatives could cause a significant price dislocation of the underlying stock upon an event of dramatic payoff change. Moreover, one event causes another: the event cascade amplifies the magnitude of the impact. We find that a single event accounts for -6.4% return on the event day, and it increases the probability of a subsequent event by 21.3%. Given the negative price impact, traders try to liquidate ahead of each other, exacerbating the degree of price dislocation. Our results uncover the chain-reaction and (mis)coordination mechanism in complex derivatives markets that could provoke a substantial price shock.
{"title":"Liquidation Cascade and Hedging Front-Running: Evidence from the Structured Equity Product Market","authors":"J. Auh, Wonho Cho","doi":"10.2139/ssrn.3719988","DOIUrl":"https://doi.org/10.2139/ssrn.3719988","url":null,"abstract":"We show that structured equity derivatives could cause a significant price dislocation of the underlying stock upon an event of dramatic payoff change. Moreover, one event causes another: the event cascade amplifies the magnitude of the impact. We find that a single event accounts for -6.4% return on the event day, and it increases the probability of a subsequent event by 21.3%. Given the negative price impact, traders try to liquidate ahead of each other, exacerbating the degree of price dislocation. Our results uncover the chain-reaction and (mis)coordination mechanism in complex derivatives markets that could provoke a substantial price shock.","PeriodicalId":251522,"journal":{"name":"Risk Management & Analysis in Financial Institutions eJournal","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132035243","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We propose to model and forecast realized covariances by estimating reduced form models on 'pre-shrunk' time-series. By adapting established linear and non-linear shrinkage techniques to high-frequency volatility estimates we construct an alternative time-series that is biased, but offers an expected Frobenius norm improvement with respect to the latent covariance matrix. Both parameter estimates and forecasts are based on the pre-shrunk series. We document statistically and economically significant forecast improvements based on statistical loss functions with respect to both the standard and shrunk realized covariance measures, for cross-sectional dimensions ranging from one to over a hundred. The forecasts also lead to improved global minimum variance portfolios, which do not inherently favour either series. The pre-shrunk models compare favourably to alternative measurement-error alleviating techniques.
{"title":"Pre-Shrinkage: Improved Volatility Forecasting Using Biased Time-Series","authors":"R. Quaedvlieg","doi":"10.2139/ssrn.3716425","DOIUrl":"https://doi.org/10.2139/ssrn.3716425","url":null,"abstract":"We propose to model and forecast realized covariances by estimating reduced form models on 'pre-shrunk' time-series. By adapting established linear and non-linear shrinkage techniques to high-frequency volatility estimates we construct an alternative time-series that is biased, but offers an expected Frobenius norm improvement with respect to the latent covariance matrix. Both parameter estimates and forecasts are based on the pre-shrunk series. We document statistically and economically significant forecast improvements based on statistical loss functions with respect to both the standard and shrunk realized covariance measures, for cross-sectional dimensions ranging from one to over a hundred. The forecasts also lead to improved global minimum variance portfolios, which do not inherently favour either series. The pre-shrunk models compare favourably to alternative measurement-error alleviating techniques.","PeriodicalId":251522,"journal":{"name":"Risk Management & Analysis in Financial Institutions eJournal","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131449509","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Regina Lee, David White, Michael Barton, Jessica Horewitz, Paul Madden, Colleen M. Maker, Rehan Farooq, John Schultz, J. B. Heaton
The Altman Z Score (AZS) does not predict bankruptcy. The false positive rate of the AZS is 98%-99%. The AZS fails as a predictive model because it does not incorporate market evidence bearing on bankruptcy probability, specifically, returns, debt to an approximation of market value of assets, and stock price. In a probit model, AZS is statistically insignificant in the presence of these market variables.
{"title":"The Altman Z Score Does Not Predict Bankruptcy","authors":"Regina Lee, David White, Michael Barton, Jessica Horewitz, Paul Madden, Colleen M. Maker, Rehan Farooq, John Schultz, J. B. Heaton","doi":"10.2139/ssrn.3570149","DOIUrl":"https://doi.org/10.2139/ssrn.3570149","url":null,"abstract":"The Altman Z Score (AZS) does not predict bankruptcy. The false positive rate of the AZS is 98%-99%. The AZS fails as a predictive model because it does not incorporate market evidence bearing on bankruptcy probability, specifically, returns, debt to an approximation of market value of assets, and stock price. In a probit model, AZS is statistically insignificant in the presence of these market variables.","PeriodicalId":251522,"journal":{"name":"Risk Management & Analysis in Financial Institutions eJournal","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128680004","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jørgen Andersen Sveinsson, Stein Frydenberg, Sjur Westgaard, Maurits M. Aaløkken
We investigate the performance of various value-at-risk (VaR) models in the context of the highly volatile Nordic power futures market, examining whether simple averages of models provide better results than the individual models themselves. The individual models used are normally distributed GARCH, t-distributed GARCH, t-distributed GJR–GARCH, a quantile regression using RiskMetrics, a quantile regression using t-distributed GARCH, RiskMetrics with Cornish–Fisher and a filtered historical simulation using t-distributed GARCH. We find that RiskMetrics with Cornish–Fisher and normally distributed GARCH perform worse than the other individual models. The average models generally outperform the individual models at a 5% significance level. The conditional independence test reveals that the models are only partially capable of accounting for the volatility clustering of the Nordic power futures. Investors in the Nordic electricity markets should therefore use several methods and average them to be more confident in their VaR estimates.
{"title":"Performance of Value-at-Risk Averaging in the Nordic Power Futures Market","authors":"Jørgen Andersen Sveinsson, Stein Frydenberg, Sjur Westgaard, Maurits M. Aaløkken","doi":"10.21314/jem.2020.207","DOIUrl":"https://doi.org/10.21314/jem.2020.207","url":null,"abstract":"We investigate the performance of various value-at-risk (VaR) models in the context of the highly volatile Nordic power futures market, examining whether simple averages of models provide better results than the individual models themselves. The individual models used are normally distributed GARCH, t-distributed GARCH, t-distributed GJR–GARCH, a quantile regression using RiskMetrics, a quantile regression using t-distributed GARCH, RiskMetrics with Cornish–Fisher and a filtered historical simulation using t-distributed GARCH. We find that RiskMetrics with Cornish–Fisher and normally distributed GARCH perform worse than the other individual models. The average models generally outperform the individual models at a 5% significance level. The conditional independence test reveals that the models are only partially capable of accounting for the volatility clustering of the Nordic power futures. Investors in the Nordic electricity markets should therefore use several methods and average them to be more confident in their VaR estimates.","PeriodicalId":251522,"journal":{"name":"Risk Management & Analysis in Financial Institutions eJournal","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129556952","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
How do experienced prior loss or gains affect risk-taking? A large literature reports significant but seemingly inconsistent effects of prior outcomes on risk-taking. We resolve these inconsistencies by proposing a similarity based mechanism determining which outcomes are jointly evaluated and state conditions under which we expect no behavioral changes. In line with our theory, we find in a pre-registered experiment, that the less similar a prior decision situation is in task-relevant dimensions, the weaker is the effect of the prior outcomes on the current decision; variation in non-task relevant dimensions will not change the impact of prior outcomes.
{"title":"This Time Is Different: On Similarity and Risk Taking After Experienced Gains and Losses","authors":"Steve Heinke, Adrian Leuenberger, J. Rieskamp","doi":"10.2139/ssrn.3691829","DOIUrl":"https://doi.org/10.2139/ssrn.3691829","url":null,"abstract":"How do experienced prior loss or gains affect risk-taking? A large literature reports significant but seemingly inconsistent effects of prior outcomes on risk-taking. We resolve these inconsistencies by proposing a similarity based mechanism determining which outcomes are jointly evaluated and state conditions under which we expect no behavioral changes. In line with our theory, we find in a pre-registered experiment, that the less similar a prior decision situation is in task-relevant dimensions, the weaker is the effect of the prior outcomes on the current decision; variation in non-task relevant dimensions will not change the impact of prior outcomes.","PeriodicalId":251522,"journal":{"name":"Risk Management & Analysis in Financial Institutions eJournal","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131505847","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We study the anatomy of four widely used institutional trading algorithms representing $675 billion in demand from 961 institutions. Parent orders generate hundreds of child orders which strategically employ price, time-in-force, and display priority rules to navigate the tradeoff between trading and minimizing transaction costs. Child orders incur price impact at the time they are submitted regardless of whether or not they are filled, and even when passively priced. Child orders are grouped in strategic runs that oscillate between the aggressive or passive side of the spread. Child-level price, time-in-force, and display choices aggregate up to parent-level trading costs.
{"title":"The Anatomy of Trading Algorithms","authors":"Tyler Beason, Sunil Wahal","doi":"10.2139/ssrn.3497001","DOIUrl":"https://doi.org/10.2139/ssrn.3497001","url":null,"abstract":"We study the anatomy of four widely used institutional trading algorithms representing $675 billion in demand from 961 institutions. Parent orders generate hundreds of child orders which strategically employ price, time-in-force, and display priority rules to navigate the tradeoff between trading and minimizing transaction costs. Child orders incur price impact at the time they are submitted regardless of whether or not they are filled, and even when passively priced. Child orders are grouped in strategic runs that oscillate between the aggressive or passive side of the spread. Child-level price, time-in-force, and display choices aggregate up to parent-level trading costs.","PeriodicalId":251522,"journal":{"name":"Risk Management & Analysis in Financial Institutions eJournal","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122130305","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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