This article uses data provided by the Federal Emergency Management Agency, which implements the NFIP, to estimate the difference between annual premiums and expected costs associated for the program as a whole and for inland and coastal regions. In addition, we examine the role of discounts, cross‐subsidies, and FEMA's method of setting what it considers to be full‐risk rates in explaining the outcomes that we observe.
{"title":"The National Flood Insurance Program: Is it Financially Sound?","authors":"T. Dinan, P. Beider, David Wylie","doi":"10.1111/rmir.12116","DOIUrl":"https://doi.org/10.1111/rmir.12116","url":null,"abstract":"This article uses data provided by the Federal Emergency Management Agency, which implements the NFIP, to estimate the difference between annual premiums and expected costs associated for the program as a whole and for inland and coastal regions. In addition, we examine the role of discounts, cross‐subsidies, and FEMA's method of setting what it considers to be full‐risk rates in explaining the outcomes that we observe.","PeriodicalId":431629,"journal":{"name":"Econometrics: Applied Econometric Modeling in Financial Economics eJournal","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115537453","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 provide empirical evidence of the post-investment performance and survivorship profile of angel-backed companies, filling a long-standing gap within the entrepreneurial finance literature. Using a unique database of 111 angel-backed companies that received angel investments between 2008 and 2012 and at least 3 years of post-investment financial data, we develop an innovative performance metric and show that the performance and the probability of survival of investee companies are positively affected by the presence of angel syndicates and the hands-on involvement of business angels, while they are negatively related to the intensity of angel monitoring and the time structure of equity provision. Our results are robust to several endogeneity tests and provide insights on the multifaceted contributions of angel investors to the performance and survival of new ventures.
{"title":"The Performance of Angel-Backed Companies","authors":"S. Bonini, Vincenzo Capizzi, P. Zocchi","doi":"10.2139/ssrn.3039307","DOIUrl":"https://doi.org/10.2139/ssrn.3039307","url":null,"abstract":"We provide empirical evidence of the post-investment performance and survivorship profile of angel-backed companies, filling a long-standing gap within the entrepreneurial finance literature. Using a unique database of 111 angel-backed companies that received angel investments between 2008 and 2012 and at least 3 years of post-investment financial data, we develop an innovative performance metric and show that the performance and the probability of survival of investee companies are positively affected by the presence of angel syndicates and the hands-on involvement of business angels, while they are negatively related to the intensity of angel monitoring and the time structure of equity provision. Our results are robust to several endogeneity tests and provide insights on the multifaceted contributions of angel investors to the performance and survival of new ventures.","PeriodicalId":431629,"journal":{"name":"Econometrics: Applied Econometric Modeling in Financial Economics eJournal","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121256768","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 parameter estimation (mean, volatility and correlation) for correlated Brownian processes making use of overlapping return observations. In doing so, we derive the minimum variance unbiased estimators within the space of linear (for the mean) and quadratic (for the variance and covariance) combinations of the observations. These estimators weight the observations using the inverse of the (known) correlation structure, for example, the variance estimator is given by: [sum_{i,j=1}^Nrho^{-1}_{ij}(x_i-mu)(x_j-mu)/(N-1)], where [x_i] are the [n]-day overlapping return observations and $mu$ is the estimated mean of the overlapping observations. These estimators (which are shown to be bias corrected versions of the maximum likelihood estimators) are shown to have standard errors that are not materially different from the standard error of the estimators which use non-overlapping, single-day observations. On the other hand, it is demonstrated that na"{i}vely using standard estimators that equally-weight the observations (for example, for the variance estimate: [sum_{i=1}^N(x_i-mu)^2/(N-1)] as would be standard for non-overlapping observations) results in: begin{enumerate} item biased estimates, requiring the replacement of [N-1] with a factor that is very close to [N-n] to remove the bias, and item estimates that are roughly [sqrt{2n/3}] times noisier that estimates coming from the derived minimum variance estimators. end{enumerate} These observations are demonstrated through Monte-Carlo experiments as well as using historical equity index data.
{"title":"Parameter Estimation from Overlapping Observations","authors":"Michael A. Clayton","doi":"10.2139/ssrn.2968896","DOIUrl":"https://doi.org/10.2139/ssrn.2968896","url":null,"abstract":"This paper examines parameter estimation (mean, volatility and correlation) for correlated Brownian processes making use of overlapping return observations. In doing so, we derive the minimum variance unbiased estimators within the space of linear (for the mean) and quadratic (for the variance and covariance) combinations of the observations. These estimators weight the observations using the inverse of the (known) correlation structure, for example, the variance estimator is given by: [sum_{i,j=1}^Nrho^{-1}_{ij}(x_i-mu)(x_j-mu)/(N-1)], where [x_i] are the [n]-day overlapping return observations and $mu$ is the estimated mean of the overlapping observations. These estimators (which are shown to be bias corrected versions of the maximum likelihood estimators) are shown to have standard errors that are not materially different from the standard error of the estimators which use non-overlapping, single-day observations. \u0000On the other hand, it is demonstrated that na\"{i}vely using standard estimators that equally-weight the observations (for example, for the variance estimate: [sum_{i=1}^N(x_i-mu)^2/(N-1)] as would be standard for non-overlapping observations) results in: begin{enumerate} \u0000item biased estimates, requiring the replacement of [N-1] with a factor that is very close to [N-n] to remove the bias, and \u0000item estimates that are roughly [sqrt{2n/3}] times noisier that estimates coming from the derived minimum variance estimators. end{enumerate} \u0000These observations are demonstrated through Monte-Carlo experiments as well as using historical equity index data.","PeriodicalId":431629,"journal":{"name":"Econometrics: Applied Econometric Modeling in Financial Economics eJournal","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127319665","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 a maximum-expected utility hedging model with futures where cash and futures returns follow a bivariate skew-normal distribution, such to consider the effect of skewness on the optimal futures demand. Relative to the benchmark of bivariate normality, skewness has a material impact when the agent is significantly risk averse. Pure hedging demand is either greater or smaller than minimum-variance demand, depending on the relative skewness of cash and futures positions. The difference between pure hedging and minimum-variance demand increases with basis risk, i.e. the imperfect correlation between cash and futures returns. When the agent is moderately but not infinitely risk averse, there is room for speculative positions, and the optimal futures demand is driven by both basis risk and the expected return on the futures market.
{"title":"Skewness, Basis Risk, and Optimal Futures Demand","authors":"Massimiliano Barbi, S. Romagnoli","doi":"10.2139/ssrn.2845246","DOIUrl":"https://doi.org/10.2139/ssrn.2845246","url":null,"abstract":"We propose a maximum-expected utility hedging model with futures where cash and futures returns follow a bivariate skew-normal distribution, such to consider the effect of skewness on the optimal futures demand. Relative to the benchmark of bivariate normality, skewness has a material impact when the agent is significantly risk averse. Pure hedging demand is either greater or smaller than minimum-variance demand, depending on the relative skewness of cash and futures positions. The difference between pure hedging and minimum-variance demand increases with basis risk, i.e. the imperfect correlation between cash and futures returns. When the agent is moderately but not infinitely risk averse, there is room for speculative positions, and the optimal futures demand is driven by both basis risk and the expected return on the futures market.","PeriodicalId":431629,"journal":{"name":"Econometrics: Applied Econometric Modeling in Financial Economics eJournal","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124051497","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}
Florida chose not to develop its own marketplace and therefore hosts the federally facilitated marketplace. While the state may have had an opportunity to define rating areas, it defaulted to the county level, which is the level at which agents and carriers are licensed to conduct business. This resulted in 67 rating areas, which is significantly more than most other states. South Carolina has 46 rating areas, and Texas has 26. All other states have fewer than 20.
{"title":"ACA Exchange Competitiveness in Florida","authors":"P. Born","doi":"10.1111/rmir.12074","DOIUrl":"https://doi.org/10.1111/rmir.12074","url":null,"abstract":"Florida chose not to develop its own marketplace and therefore hosts the federally facilitated marketplace. While the state may have had an opportunity to define rating areas, it defaulted to the county level, which is the level at which agents and carriers are licensed to conduct business. This resulted in 67 rating areas, which is significantly more than most other states. South Carolina has 46 rating areas, and Texas has 26. All other states have fewer than 20.","PeriodicalId":431629,"journal":{"name":"Econometrics: Applied Econometric Modeling in Financial Economics eJournal","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126001580","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 document significantly lower inflows into female-managed mutual funds than into male-managed funds. This result is obtained with field data and with data from a laboratory experiment. There are no gender differences in performance. Thus, rational statistical discrimination is unlikely to explain the fund flow effect. We conduct an implicit association test and find that subjects with stronger gender bias according to this test invest significantly less into female-managed funds. Our results suggest that gender bias affects investment decisions and thus offer a new explanation for the low fraction of women in the mutual fund industry.
{"title":"Sex Matters: Gender Bias in the Mutual Fund Industry","authors":"Alexandra Niessen-Ruenzi, S. Ruenzi","doi":"10.2139/ssrn.1957317","DOIUrl":"https://doi.org/10.2139/ssrn.1957317","url":null,"abstract":"We document significantly lower inflows into female-managed mutual funds than into male-managed funds. This result is obtained with field data and with data from a laboratory experiment. There are no gender differences in performance. Thus, rational statistical discrimination is unlikely to explain the fund flow effect. We conduct an implicit association test and find that subjects with stronger gender bias according to this test invest significantly less into female-managed funds. Our results suggest that gender bias affects investment decisions and thus offer a new explanation for the low fraction of women in the mutual fund industry.","PeriodicalId":431629,"journal":{"name":"Econometrics: Applied Econometric Modeling in Financial Economics eJournal","volume":"135 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116070220","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 an optimal changepoint approach, we find a structural change in the relation between hedge funds’ stock market exposure and aggregate stock market liquidity that takes place in the period 2000 to 2002. Before the structural break, market betas have no relation to liquidity and only a few style categories of hedge funds show increased market presence when liquidity is low. After the break, the relationship is inverted, pointing towards an increased liquidity timing ability of hedge funds, as users of liquidity. We relate our findings to best execution rules and decimalization in the US stock market that were introduced in that period and impacted aggregate liquidity conditions. Furthermore, the returns to a momentum strategy display a similar structural break and momentum-loading funds constitute a sizeable proportion of hedge funds that manifest a distinct beta-liquidity evolution with a structural break in that period.
{"title":"The Evolving Beta-Liquidity Relationship of Hedge Funds","authors":"Arjen Siegmann, D. Stefanova","doi":"10.2139/ssrn.2023924","DOIUrl":"https://doi.org/10.2139/ssrn.2023924","url":null,"abstract":"Using an optimal changepoint approach, we find a structural change in the relation between hedge funds’ stock market exposure and aggregate stock market liquidity that takes place in the period 2000 to 2002. Before the structural break, market betas have no relation to liquidity and only a few style categories of hedge funds show increased market presence when liquidity is low. After the break, the relationship is inverted, pointing towards an increased liquidity timing ability of hedge funds, as users of liquidity. We relate our findings to best execution rules and decimalization in the US stock market that were introduced in that period and impacted aggregate liquidity conditions. Furthermore, the returns to a momentum strategy display a similar structural break and momentum-loading funds constitute a sizeable proportion of hedge funds that manifest a distinct beta-liquidity evolution with a structural break in that period.","PeriodicalId":431629,"journal":{"name":"Econometrics: Applied Econometric Modeling in Financial Economics eJournal","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117351226","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 “talent crisis” in the insurance industry is well documented. Solutions to this crisis, however, are not plentiful. One of the major challenges faced by the industry is its reputation. We hypothesize that opinions of the industry can be changed through brief but specific education efforts. We test our hypothesis at a major university and find very strong support for our hypothesis.
{"title":"Improving Perceptions of the Insurance Industry: The Influence of Insurance Professionals","authors":"J. Karl, Brenda Wells","doi":"10.1111/rmir.12058","DOIUrl":"https://doi.org/10.1111/rmir.12058","url":null,"abstract":"The “talent crisis” in the insurance industry is well documented. Solutions to this crisis, however, are not plentiful. One of the major challenges faced by the industry is its reputation. We hypothesize that opinions of the industry can be changed through brief but specific education efforts. We test our hypothesis at a major university and find very strong support for our hypothesis.","PeriodicalId":431629,"journal":{"name":"Econometrics: Applied Econometric Modeling in Financial Economics eJournal","volume":"304 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133986402","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}
J. Arismendi, Janis Back, Marcel Prokopczuk, Raphael Paschke, M. Rudolf
Many commodity markets contain a strong seasonal component not only at the price level, but also in volatility. In this paper, the importance of seasonal behavior in the volatility for the pricing of commodity options is analyzed. We propose a seasonally varying long-run mean variance process that is capable of capturing empirically observed patterns. Semi-closed-form option valuation formulas are derived. We then empirically study the impact of the proposed Seasonal Stochastic Volatility Model on the pricing accuracy of natural gas futures options traded at the New York Mercantile Exchange (NYMEX) and corn futures options traded at the Chicago Board of Trade (CBOT). Our results demonstrate that allowing stochastic volatility to fluctuate seasonally significantly reduces pricing errors for these contracts.
{"title":"Seasonal Stochastic Volatility: Implications for the Pricing of Commodity Options","authors":"J. Arismendi, Janis Back, Marcel Prokopczuk, Raphael Paschke, M. Rudolf","doi":"10.2139/ssrn.1879109","DOIUrl":"https://doi.org/10.2139/ssrn.1879109","url":null,"abstract":"Many commodity markets contain a strong seasonal component not only at the price level, but also in volatility. In this paper, the importance of seasonal behavior in the volatility for the pricing of commodity options is analyzed. We propose a seasonally varying long-run mean variance process that is capable of capturing empirically observed patterns. Semi-closed-form option valuation formulas are derived. We then empirically study the impact of the proposed Seasonal Stochastic Volatility Model on the pricing accuracy of natural gas futures options traded at the New York Mercantile Exchange (NYMEX) and corn futures options traded at the Chicago Board of Trade (CBOT). Our results demonstrate that allowing stochastic volatility to fluctuate seasonally significantly reduces pricing errors for these contracts.","PeriodicalId":431629,"journal":{"name":"Econometrics: Applied Econometric Modeling in Financial Economics eJournal","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134320215","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 provides a comprehensive examination of money flows in corporate bond funds which, though less researched, represent an important setting to study investor behavior. Based on a large sample of corporate bond funds over 1991–2014, we first show that flows are sensitive to both fund performance and macro condition, but unlike equity funds, the flow-performance relationship is not convex. Then, we find that investor flows can predict fund performance. More importantly, the predictability cannot be explained by return momentum or price pressure but is subsumed by performance persistence. Finally, an examination of idiosyncratic flows reveals little evidence that fund investors use finer-than-public information.
{"title":"The Behavior of Investor Flows in Corporate Bond Mutual Funds","authors":"Yong Chen, Nan Qin","doi":"10.2139/ssrn.2022059","DOIUrl":"https://doi.org/10.2139/ssrn.2022059","url":null,"abstract":"This paper provides a comprehensive examination of money flows in corporate bond funds which, though less researched, represent an important setting to study investor behavior. Based on a large sample of corporate bond funds over 1991–2014, we first show that flows are sensitive to both fund performance and macro condition, but unlike equity funds, the flow-performance relationship is not convex. Then, we find that investor flows can predict fund performance. More importantly, the predictability cannot be explained by return momentum or price pressure but is subsumed by performance persistence. Finally, an examination of idiosyncratic flows reveals little evidence that fund investors use finer-than-public information.","PeriodicalId":431629,"journal":{"name":"Econometrics: Applied Econometric Modeling in Financial Economics eJournal","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134150739","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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