This study investigates the pricing efficiency of FTSE/ATHEX-20 index futures contracts and examines whether arbitrage profits exist in the Greek market. By comparing ex-post mispricing with round-trip total transaction costs faced by different groups of market participants, the empirical investigation suggests that profitable arbitrage opportunities are likely to be common in the Athens Exchange. The current paper also documents and tests the factors that determine the occurrence and the magnitude of the arbitrage opportunities in the Greek futures market. The findings suggest that variables, such as futures maturity, dividends, volatility, liquidity and short-selling restrictions, explain effectively the cash-futures mispricing.
{"title":"Mispricing in Stock Index Futures Markets – the Case of Greece","authors":"Athanasios P. Fassas","doi":"10.2139/ssrn.1873949","DOIUrl":"https://doi.org/10.2139/ssrn.1873949","url":null,"abstract":"This study investigates the pricing efficiency of FTSE/ATHEX-20 index futures contracts and examines whether arbitrage profits exist in the Greek market. By comparing ex-post mispricing with round-trip total transaction costs faced by different groups of market participants, the empirical investigation suggests that profitable arbitrage opportunities are likely to be common in the Athens Exchange. The current paper also documents and tests the factors that determine the occurrence and the magnitude of the arbitrage opportunities in the Greek futures market. The findings suggest that variables, such as futures maturity, dividends, volatility, liquidity and short-selling restrictions, explain effectively the cash-futures mispricing.","PeriodicalId":366327,"journal":{"name":"ERN: Other Econometrics: Applied Econometric Modeling in Financial Economics (Topic)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131626979","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}
Pub Date : 2010-01-20DOI: 10.1111/j.1467-629X.2010.00374.x
Carole Comerton-Forde, D. Gallagher, J. Lai, T. Walter
This study examines whether the abnormal performance of active Australian small-cap equity fund managers is associated with broker recommendations. Our evidence supports the investment value of broker recommendations, showing significant abnormal returns (ARs) both pre- and post-broker recommendations. We find that when a factor-mimicking portfolio based on broker recommendations is added to a Carhart (1997) model, annual alphas are reduced by 48 basis points. Using transaction-level data, buy trades following broker recommendations earn significant cumulative ARs of 1.56 per cent after 60 days. Overall, we find that broker recommendations account for an economically significant component of alphas.
{"title":"Broker Recommendations and Australian Small‐Cap Equity Fund Management","authors":"Carole Comerton-Forde, D. Gallagher, J. Lai, T. Walter","doi":"10.1111/j.1467-629X.2010.00374.x","DOIUrl":"https://doi.org/10.1111/j.1467-629X.2010.00374.x","url":null,"abstract":"This study examines whether the abnormal performance of active Australian small-cap equity fund managers is associated with broker recommendations. Our evidence supports the investment value of broker recommendations, showing significant abnormal returns (ARs) both pre- and post-broker recommendations. We find that when a factor-mimicking portfolio based on broker recommendations is added to a Carhart (1997) model, annual alphas are reduced by 48 basis points. Using transaction-level data, buy trades following broker recommendations earn significant cumulative ARs of 1.56 per cent after 60 days. Overall, we find that broker recommendations account for an economically significant component of alphas.","PeriodicalId":366327,"journal":{"name":"ERN: Other Econometrics: Applied Econometric Modeling in Financial Economics (Topic)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133451870","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 review summarizes some of the methodology currently available for estimating and evaluating Beta and stochastic discount factor (SDF) models such as time-series regression, cross-sectional regression, Fama-MacBeth procedure, and the generalized method of moments (GMM). The Fama-French and Carhart models are estimated following this review.
{"title":"Econometrics of Asset Pricing: Methodological Review and Empirical Exercise","authors":"Martín Lozano","doi":"10.2139/SSRN.1754762","DOIUrl":"https://doi.org/10.2139/SSRN.1754762","url":null,"abstract":"This review summarizes some of the methodology currently available for estimating and evaluating Beta and stochastic discount factor (SDF) models such as time-series regression, cross-sectional regression, Fama-MacBeth procedure, and the generalized method of moments (GMM). The Fama-French and Carhart models are estimated following this review.","PeriodicalId":366327,"journal":{"name":"ERN: Other Econometrics: Applied Econometric Modeling in Financial Economics (Topic)","volume":"244 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123157560","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}
Using recent advances in the econometrics literature, we disentangle from high frequency observations on the transaction prices of a large sample of NYSE stocks a fundamental component and a microstructure noise component. We then relate these statistical measurements of market microstructure noise to observable characteristics of the underlying stocks and, in particular, to different financial measures of their liquidity. We find that more liquid stocks based on financial characteristics have lower noise and noise-to-signal ratio measured from their high frequency returns. We then examine whether there exists a common, market-wide, factor in high frequency stock-level measurements of noise, and whether that factor is priced in asset returns.
{"title":"High Frequency Market Microstructure Noise Estimates and Liquidity Measures","authors":"Yacine Ait-Sahalia, Jialin Yu","doi":"10.1214/08-AOAS200","DOIUrl":"https://doi.org/10.1214/08-AOAS200","url":null,"abstract":"Using recent advances in the econometrics literature, we disentangle from high frequency observations on the transaction prices of a large sample of NYSE stocks a fundamental component and a microstructure noise component. We then relate these statistical measurements of market microstructure noise to observable characteristics of the underlying stocks and, in particular, to different financial measures of their liquidity. We find that more liquid stocks based on financial characteristics have lower noise and noise-to-signal ratio measured from their high frequency returns. We then examine whether there exists a common, market-wide, factor in high frequency stock-level measurements of noise, and whether that factor is priced in asset returns.","PeriodicalId":366327,"journal":{"name":"ERN: Other Econometrics: Applied Econometric Modeling in Financial Economics (Topic)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128109811","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 use seasonality in stock trading activity associated with summer vacation as a source of exogenous variation to study the relationship between trading volume and expected return. Using data from 51 stock markets, we first confirm a widely held belief that stock turnover is significantly lower during the summer because market participants are on vacation. Interestingly, we find that mean stock return is also lower during the summer for countries with significant declines in trading activity. This relationship is not due to time-varying volatility. Moreover, both large and small investors trade less and the price of trading (bid-ask spread) is higher during the summer. These findings suggest that heterogeneous agent models are essential for a complete understanding of asset prices.
{"title":"Gone Fishin': Seasonality in Trading Activity and Asset Prices","authors":"Harrison G. Hong, Jialin Yu","doi":"10.2139/ssrn.676743","DOIUrl":"https://doi.org/10.2139/ssrn.676743","url":null,"abstract":"We use seasonality in stock trading activity associated with summer vacation as a source of exogenous variation to study the relationship between trading volume and expected return. Using data from 51 stock markets, we first confirm a widely held belief that stock turnover is significantly lower during the summer because market participants are on vacation. Interestingly, we find that mean stock return is also lower during the summer for countries with significant declines in trading activity. This relationship is not due to time-varying volatility. Moreover, both large and small investors trade less and the price of trading (bid-ask spread) is higher during the summer. These findings suggest that heterogeneous agent models are essential for a complete understanding of asset prices.","PeriodicalId":366327,"journal":{"name":"ERN: Other Econometrics: Applied Econometric Modeling in Financial Economics (Topic)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132711369","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 standard ratings-based models for analyzing credit portfolios and pricing credit derivatives, it is assumed that defaults and recoveries are statistically independent. This paper presents evidence that aggregate quarterly default rates and recovery rates are, in fact, negatively correlated. Using Extreme Value Theory techniques, we show that the dependence affects the tail behavior of total credit loss distributions and leads to higher VaR measures.
{"title":"The Dependence of Recovery Rates and Defaults","authors":"W. Perraudin, Yen-Ting Hu","doi":"10.2139/ssrn.1961142","DOIUrl":"https://doi.org/10.2139/ssrn.1961142","url":null,"abstract":"In standard ratings-based models for analyzing credit portfolios and pricing credit derivatives, it is assumed that defaults and recoveries are statistically independent. This paper presents evidence that aggregate quarterly default rates and recovery rates are, in fact, negatively correlated. Using Extreme Value Theory techniques, we show that the dependence affects the tail behavior of total credit loss distributions and leads to higher VaR measures.","PeriodicalId":366327,"journal":{"name":"ERN: Other Econometrics: Applied Econometric Modeling in Financial Economics (Topic)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114494920","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}
The maturity of new debt issues predicts excess bond returns. When the share of long-term debt issues in total debt issues is high, future excess bond returns are low. This predictive power comes in two parts. First, inflation, the real short-term rate, and the term spread predict excess bond returns. Second, these same variables explain the long-term share, and together account for much of its own ability to predict excess bond returns. The results are consistent with survey evidence that firms use debt market conditions in an effort to determine the lowest-cost maturity at which to borrow.
{"title":"The Maturity of Debt Issues and Predictable Variation in Bond Returns","authors":"Malcolm P. Baker, R. Greenwood, Jeffrey Wurgler","doi":"10.2139/ssrn.279518","DOIUrl":"https://doi.org/10.2139/ssrn.279518","url":null,"abstract":"The maturity of new debt issues predicts excess bond returns. When the share of long-term debt issues in total debt issues is high, future excess bond returns are low. This predictive power comes in two parts. First, inflation, the real short-term rate, and the term spread predict excess bond returns. Second, these same variables explain the long-term share, and together account for much of its own ability to predict excess bond returns. The results are consistent with survey evidence that firms use debt market conditions in an effort to determine the lowest-cost maturity at which to borrow.","PeriodicalId":366327,"journal":{"name":"ERN: Other Econometrics: Applied Econometric Modeling in Financial Economics (Topic)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128723049","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}
The Terrorism Risk Insurance Act (TRIA) established a public–private partnership between the U.S. federal government, private insurers, and all commercial enterprises operating on U.S. soil. Renewed and modified in January 2015 until December 2020, the TRIA program requires insurers to offer terrorism insurance to their commercial policyholders while providing insurers with free up‐front financial protection up to $100 billion against terrorist attacks in the United States. With the federal government providing a financial safety net, the private insurance sector can offer coverage against an uncertain risk that would otherwise be largely considered uninsurable, thus making terrorism insurance widely available and affordable. TRIA is a successful case of public–private disaster risk financing that has received bipartisan political support. Yet it remains untested for large losses and it is unclear how the market and policymakers will react should another large‐scale insured loss occur. TRIA also raises concerns about the indemnification of individual victims of a terrorist attack (in addition to workers’ compensation).
{"title":"A Successful (Yet Somewhat Untested) Case of Disaster Financing: Terrorism Insurance Under Tria, 2002–2020","authors":"E. Michel-Kerjan, Howard C. Kunreuther","doi":"10.1111/rmir.12094","DOIUrl":"https://doi.org/10.1111/rmir.12094","url":null,"abstract":"The Terrorism Risk Insurance Act (TRIA) established a public–private partnership between the U.S. federal government, private insurers, and all commercial enterprises operating on U.S. soil. Renewed and modified in January 2015 until December 2020, the TRIA program requires insurers to offer terrorism insurance to their commercial policyholders while providing insurers with free up‐front financial protection up to $100 billion against terrorist attacks in the United States. With the federal government providing a financial safety net, the private insurance sector can offer coverage against an uncertain risk that would otherwise be largely considered uninsurable, thus making terrorism insurance widely available and affordable. TRIA is a successful case of public–private disaster risk financing that has received bipartisan political support. Yet it remains untested for large losses and it is unclear how the market and policymakers will react should another large‐scale insured loss occur. TRIA also raises concerns about the indemnification of individual victims of a terrorist attack (in addition to workers’ compensation).","PeriodicalId":366327,"journal":{"name":"ERN: Other Econometrics: Applied Econometric Modeling in Financial Economics (Topic)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134447776","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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