type="main"> Short-termism need not breed informational price inefficiency even when generating beauty contests. We demonstrate this claim in a two-period market with persistent liquidity trading and risk-averse, privately informed, short-term investors and find that prices reflect average expectations about fundamentals and liquidity trading. Informed investors engage in “retrospective” learning to reassess inferences (about fundamentals) made during the trading game's early stages. This behavior introduces strategic complementarities in the use of information and can yield two stable equilibria that can be ranked in terms of liquidity, volatility, and informational efficiency. We derive implications that explain market anomalies as well as empirical regularities.
{"title":"The Beauty Contest and Short-Term Trading","authors":"Giovanni Cespa, X. Vives","doi":"10.2139/ssrn.2055031","DOIUrl":"https://doi.org/10.2139/ssrn.2055031","url":null,"abstract":"type=\"main\"> Short-termism need not breed informational price inefficiency even when generating beauty contests. We demonstrate this claim in a two-period market with persistent liquidity trading and risk-averse, privately informed, short-term investors and find that prices reflect average expectations about fundamentals and liquidity trading. Informed investors engage in “retrospective” learning to reassess inferences (about fundamentals) made during the trading game's early stages. This behavior introduces strategic complementarities in the use of information and can yield two stable equilibria that can be ranked in terms of liquidity, volatility, and informational efficiency. We derive implications that explain market anomalies as well as empirical regularities.","PeriodicalId":214104,"journal":{"name":"Econometrics: Applied Econometric Modeling in Financial Economics - Econometrics of Financial Markets eJournal","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117150505","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}
type="main"> We introduce a novel approach to estimating latent oil risk factors and establish their significance in pricing nonoil securities. Our model, which features four factors with simple economic interpretations, is estimated using both derivative prices and oil-related equity returns. The fit is excellent in and out of sample. The extracted oil factors carry significant risk premia, and are significantly related to macroeconomic variables as well as portfolio returns sorted on characteristics and industry. The average nonoil portfolio exhibits a sensitivity to the oil factors amounting to a sixth (in magnitude) of that of the oil industry itself.
{"title":"Estimating Oil Risk Factors Using Information from Equity and Derivatives Markets","authors":"I-Hsuan Ethan Chiang, W. K. Hughen, Jacob S. Sagi","doi":"10.2139/ssrn.2058558","DOIUrl":"https://doi.org/10.2139/ssrn.2058558","url":null,"abstract":"type=\"main\"> We introduce a novel approach to estimating latent oil risk factors and establish their significance in pricing nonoil securities. Our model, which features four factors with simple economic interpretations, is estimated using both derivative prices and oil-related equity returns. The fit is excellent in and out of sample. The extracted oil factors carry significant risk premia, and are significantly related to macroeconomic variables as well as portfolio returns sorted on characteristics and industry. The average nonoil portfolio exhibits a sensitivity to the oil factors amounting to a sixth (in magnitude) of that of the oil industry itself.","PeriodicalId":214104,"journal":{"name":"Econometrics: Applied Econometric Modeling in Financial Economics - Econometrics of Financial Markets eJournal","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124682123","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}
This paper analyzes the relationship between consumer bankruptcy patterns and banks' soft-information. Using a major Canadian bank merger as a source of exogenous variation in local banking conditions, we show that local markets affected by the merger exhibit a relative increase in consumer bankruptcy rates following the merger. We analyze different plausible mechanisms by which the merger might have led to higher bankruptcies and provide evidence consistent with the most plausible mechanism being the disruption of consumer-bank relationships. Markets affected by the merger show a decrease in the branch presence and market share of the merging institutions without overall changes in quantity of credit or loan rates.
{"title":"Consumer Bankruptcy and Soft Information","authors":"Jason Allen, H. E. Damar, David Martínez-Miera","doi":"10.2139/ssrn.2021218","DOIUrl":"https://doi.org/10.2139/ssrn.2021218","url":null,"abstract":"This paper analyzes the relationship between consumer bankruptcy patterns and banks' soft-information. Using a major Canadian bank merger as a source of exogenous variation in local banking conditions, we show that local markets affected by the merger exhibit a relative increase in consumer bankruptcy rates following the merger. We analyze different plausible mechanisms by which the merger might have led to higher bankruptcies and provide evidence consistent with the most plausible mechanism being the disruption of consumer-bank relationships. Markets affected by the merger show a decrease in the branch presence and market share of the merging institutions without overall changes in quantity of credit or loan rates.","PeriodicalId":214104,"journal":{"name":"Econometrics: Applied Econometric Modeling in Financial Economics - Econometrics of Financial Markets eJournal","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133312873","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}
This paper examines the relative importance of liquidity level and liquidity risk for the cross-section of stock returns. A portfolio analysis is implemented to make inferences about the pricing ability of liquidity as a characteristic or as a risk. I find that the ratio of absolute returns-to-volume, the Amihud liquidity measure, is able to explain more variance in stock returns than a battery of liquidity risk measures. My results suggest that trading cost and frictions impact financial markets more than the systemic components of liquidity.
{"title":"Liquidity and Liquidity Risk in the Cross-Section of Stock Returns","authors":"Volodymyr Vovchak","doi":"10.2139/ssrn.2078295","DOIUrl":"https://doi.org/10.2139/ssrn.2078295","url":null,"abstract":"This paper examines the relative importance of liquidity level and liquidity risk for the cross-section of stock returns. A portfolio analysis is implemented to make inferences about the pricing ability of liquidity as a characteristic or as a risk. I find that the ratio of absolute returns-to-volume, the Amihud liquidity measure, is able to explain more variance in stock returns than a battery of liquidity risk measures. My results suggest that trading cost and frictions impact financial markets more than the systemic components of liquidity.","PeriodicalId":214104,"journal":{"name":"Econometrics: Applied Econometric Modeling in Financial Economics - Econometrics of Financial Markets eJournal","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132250225","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 asset prices behave very differently on days when important macroeconomic news is scheduled for announcement. In addition to significantly higher average returns for risky assets on announcement days, return patterns are much easier to reconcile with standard asset pricing theories, both cross-sectionally and over time. On such days, stock market beta is strongly related to average returns. This positive relation holds for individual stocks, for various test portfolios, and even for bonds and currencies, suggesting that beta is after all an important measure of systematic risk. Furthermore, a robust risk–return trade-off exists on announcement days. Expected variance is positively related to future aggregated quarterly announcement day returns, but not to aggregated non-announcement day returns. We explore the implications of our findings in the context of various asset pricing models.
{"title":"Asset Pricing: A Tale of Two Days","authors":"Pavel Savor, Mungo Ivor Wilson","doi":"10.2139/ssrn.2024422","DOIUrl":"https://doi.org/10.2139/ssrn.2024422","url":null,"abstract":"We show that asset prices behave very differently on days when important macroeconomic news is scheduled for announcement. In addition to significantly higher average returns for risky assets on announcement days, return patterns are much easier to reconcile with standard asset pricing theories, both cross-sectionally and over time. On such days, stock market beta is strongly related to average returns. This positive relation holds for individual stocks, for various test portfolios, and even for bonds and currencies, suggesting that beta is after all an important measure of systematic risk. Furthermore, a robust risk–return trade-off exists on announcement days. Expected variance is positively related to future aggregated quarterly announcement day returns, but not to aggregated non-announcement day returns. We explore the implications of our findings in the context of various asset pricing models.","PeriodicalId":214104,"journal":{"name":"Econometrics: Applied Econometric Modeling in Financial Economics - Econometrics of Financial Markets eJournal","volume":"93 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131890629","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 first study mean–variance efficient portfolios when there are no trading constraints and show that optimal strategies perform poorly in bear markets. We then assume that investors use a stochastic benchmark (linked to the market) as a reference portfolio. We derive mean–variance efficient portfolios when investors aim to achieve a given correlation (or a given dependence structure) with this benchmark. We also provide upper bounds on Sharpe ratios and show how these bounds can be useful for fraud detection. For example, it is shown that under some conditions it is not possible for investment funds to display a negative correlation with the financial market and to have a positive Sharpe ratio. All the results are illustrated in a Black–Scholes market.
{"title":"Mean-Variance Optimal Portfolios in the Presence of a Benchmark with Applications to Fraud Detection","authors":"C. Bernard, S. Vanduffel","doi":"10.2139/ssrn.2154531","DOIUrl":"https://doi.org/10.2139/ssrn.2154531","url":null,"abstract":"We first study mean–variance efficient portfolios when there are no trading constraints and show that optimal strategies perform poorly in bear markets. We then assume that investors use a stochastic benchmark (linked to the market) as a reference portfolio. We derive mean–variance efficient portfolios when investors aim to achieve a given correlation (or a given dependence structure) with this benchmark. We also provide upper bounds on Sharpe ratios and show how these bounds can be useful for fraud detection. For example, it is shown that under some conditions it is not possible for investment funds to display a negative correlation with the financial market and to have a positive Sharpe ratio. All the results are illustrated in a Black–Scholes market.","PeriodicalId":214104,"journal":{"name":"Econometrics: Applied Econometric Modeling in Financial Economics - Econometrics of Financial Markets eJournal","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134213644","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}
This study examines how the decisions that issuers and their investment banks make about IPO pricing are affected by the value of deals in registration, measured at the aggregate, industry and bank level both as of the filing date and the offering date (in order to identify changes in the IPO pipeline over the issuance process). Examining 1684 IPOs from1998-2007 we find evidence that measure of the IPO pipeline significantly affect pricing decisions. The evidence is mostly consistent with agency-based arguments that investment banks with large and growing pipelines of deals partially adjust prices given market information but also leave more money on the table. While harming issuers, this both helps clear their pipeline of deals, and attracts institutional clientele ensuring the banks can sell their backlog of deals.
{"title":"Deal Flow and the Pricing of IPOs","authors":"Craig G. Dunbar, Kevin K. Boeh","doi":"10.2139/ssrn.2133541","DOIUrl":"https://doi.org/10.2139/ssrn.2133541","url":null,"abstract":"This study examines how the decisions that issuers and their investment banks make about IPO pricing are affected by the value of deals in registration, measured at the aggregate, industry and bank level both as of the filing date and the offering date (in order to identify changes in the IPO pipeline over the issuance process). Examining 1684 IPOs from1998-2007 we find evidence that measure of the IPO pipeline significantly affect pricing decisions. The evidence is mostly consistent with agency-based arguments that investment banks with large and growing pipelines of deals partially adjust prices given market information but also leave more money on the table. While harming issuers, this both helps clear their pipeline of deals, and attracts institutional clientele ensuring the banks can sell their backlog of deals.","PeriodicalId":214104,"journal":{"name":"Econometrics: Applied Econometric Modeling in Financial Economics - Econometrics of Financial Markets eJournal","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130348823","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 an Adaptive Dynamic Nelson–Siegel (ADNS) model to adaptively detect parameter changes and forecast the yield curve. The model is simple yet flexible and can be safely applied to both stationary and nonstationary situations with different sources of parameter changes. For the 3- to 12-months ahead out-of-sample forecasts of the US yield curve from 1998:1 to 2010:9, the ADNS model dominates both the popular reduced-form and affine term structure models; compared to random walk prediction, the ADNS steadily reduces the forecast error measurements by between 20% and 60%. The locally estimated coefficients and the identified stable subsamples over time align with policy changes and the timing of the recent financial crisis.
{"title":"Adaptive Dynamic Nelson-Siegel Term Structure Model with Applications","authors":"Ying Chen, Linlin Niu","doi":"10.2139/ssrn.2025853","DOIUrl":"https://doi.org/10.2139/ssrn.2025853","url":null,"abstract":"We propose an Adaptive Dynamic Nelson–Siegel (ADNS) model to adaptively detect parameter changes and forecast the yield curve. The model is simple yet flexible and can be safely applied to both stationary and nonstationary situations with different sources of parameter changes. For the 3- to 12-months ahead out-of-sample forecasts of the US yield curve from 1998:1 to 2010:9, the ADNS model dominates both the popular reduced-form and affine term structure models; compared to random walk prediction, the ADNS steadily reduces the forecast error measurements by between 20% and 60%. The locally estimated coefficients and the identified stable subsamples over time align with policy changes and the timing of the recent financial crisis.","PeriodicalId":214104,"journal":{"name":"Econometrics: Applied Econometric Modeling in Financial Economics - Econometrics of Financial Markets eJournal","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127487339","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 options' implied and physical measures of riskiness and investigate their performance in predicting future returns on the U.S. equity market. The predictive regressions indicate a positive and significant relation between time-varying riskiness and expected market returns. The significantly positive link between aggregate riskiness and market risk premium remains intact after controlling for the S&P500 index option's implied volatility (VIX), aggregate idiosyncratic volatility, and a large set of macroeconomic and financial variables. We present a theoretical framework that justifies the positive link between aggregate riskiness and equity premium. We also provide alternative explanations for the positive relation by showing that aggregate riskiness is higher during economic downturns characterized by high aggregate risk aversion and high expected returns.
{"title":"A New Approach to Measuring Riskiness in the Equity Market: Implications for the Risk Premium","authors":"Turan G. Bali, Nusret Cakici, Fousseni Chabi-Yo","doi":"10.2139/ssrn.2039078","DOIUrl":"https://doi.org/10.2139/ssrn.2039078","url":null,"abstract":"We propose options' implied and physical measures of riskiness and investigate their performance in predicting future returns on the U.S. equity market. The predictive regressions indicate a positive and significant relation between time-varying riskiness and expected market returns. The significantly positive link between aggregate riskiness and market risk premium remains intact after controlling for the S&P500 index option's implied volatility (VIX), aggregate idiosyncratic volatility, and a large set of macroeconomic and financial variables. We present a theoretical framework that justifies the positive link between aggregate riskiness and equity premium. We also provide alternative explanations for the positive relation by showing that aggregate riskiness is higher during economic downturns characterized by high aggregate risk aversion and high expected returns.","PeriodicalId":214104,"journal":{"name":"Econometrics: Applied Econometric Modeling in Financial Economics - Econometrics of Financial Markets eJournal","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132500088","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}
This paper presents a variety of tests of volatility spillover that are robust to heavy tails generated by large errors or GARCH-type feedback. The tests are couched in a general conditional heteroskedasticity framework with idiosyncratic shocks that are only required to have a finite variance if they are independent. We negligibly trim test equations, or components of the equations, and construct heavy tail robust score and portmanteau statistics. Trimming is either simple based on an indicator function, or smoothed. In particular, we develop the tail-trimmed sample correlation coefficient for robust inference, and prove that its Gaussian limit under the null hypothesis of no spillover has the same standardization irrespective of tail thickness. Further, if spillover occurs within a specified horizon, our test statistics obtain power of one asymptotically. We discuss the choice of trimming portion, including a smoothed p-value over a window of extreme observations. A Monte Carlo study shows our tests provide significant improvements over extant GARCH-based tests of spillover, and we apply the tests to financial returns data. Finally, based on ideas in Patton (2011) we construct a heavy tail robust forecast improvement statistic, which allows us to demonstrate that our spillover test can be used as a model specification pre-test to improve volatility forecasting.
{"title":"Robust Score and Portmanteau Tests of Volatility Spillover","authors":"Mike Aguilar, Jonathan B. Hill","doi":"10.2139/ssrn.2003387","DOIUrl":"https://doi.org/10.2139/ssrn.2003387","url":null,"abstract":"This paper presents a variety of tests of volatility spillover that are robust to heavy tails generated by large errors or GARCH-type feedback. The tests are couched in a general conditional heteroskedasticity framework with idiosyncratic shocks that are only required to have a finite variance if they are independent. We negligibly trim test equations, or components of the equations, and construct heavy tail robust score and portmanteau statistics. Trimming is either simple based on an indicator function, or smoothed. In particular, we develop the tail-trimmed sample correlation coefficient for robust inference, and prove that its Gaussian limit under the null hypothesis of no spillover has the same standardization irrespective of tail thickness. Further, if spillover occurs within a specified horizon, our test statistics obtain power of one asymptotically. We discuss the choice of trimming portion, including a smoothed p-value over a window of extreme observations. A Monte Carlo study shows our tests provide significant improvements over extant GARCH-based tests of spillover, and we apply the tests to financial returns data. Finally, based on ideas in Patton (2011) we construct a heavy tail robust forecast improvement statistic, which allows us to demonstrate that our spillover test can be used as a model specification pre-test to improve volatility forecasting.","PeriodicalId":214104,"journal":{"name":"Econometrics: Applied Econometric Modeling in Financial Economics - Econometrics of Financial Markets eJournal","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123709623","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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