The rational expectation hypothesis is widely used in finance and macroeconomics. A natural research question comprises investigating whether models that use this hypothesis can fit the data well. Researchers have been developing econometric procedures to test rational expectation models. Johansen and Swensen showed how to test rational expectation restrictions in the case where the data generating process is a cointegrated vector autoregressive model. This study aims to achieve three objectives. The first objective is to extend Johansen and Swensen's framework to the case where the data generating process is a cointegrated vector autoregressive model with abrupt structural change (CVAR-SC). The second goal is to show that the type of rational expectation restrictions analysed in this paper imply co-breaking, as defined by Hendry. Finally, the restrictions on the CVAR-SC parameters implied by the present value model, which is a particular rational expectation model, are analysed and derived, and a test is developed. Two empirical exercises are reported. The first is Engsted's dataset and the second uses the dividend and share prices of an important Brazilian retail bank.
{"title":"Testing Rational Expectations in a Cointegrated VAR with Abrupt Structural Change","authors":"Emerson Fernandes Marçal","doi":"10.2139/ssrn.983423","DOIUrl":"https://doi.org/10.2139/ssrn.983423","url":null,"abstract":"The rational expectation hypothesis is widely used in finance and macroeconomics. A natural research question comprises investigating whether models that use this hypothesis can fit the data well. Researchers have been developing econometric procedures to test rational expectation models. Johansen and Swensen showed how to test rational expectation restrictions in the case where the data generating process is a cointegrated vector autoregressive model. This study aims to achieve three objectives. The first objective is to extend Johansen and Swensen's framework to the case where the data generating process is a cointegrated vector autoregressive model with abrupt structural change (CVAR-SC). The second goal is to show that the type of rational expectation restrictions analysed in this paper imply co-breaking, as defined by Hendry. Finally, the restrictions on the CVAR-SC parameters implied by the present value model, which is a particular rational expectation model, are analysed and derived, and a test is developed. Two empirical exercises are reported. The first is Engsted's dataset and the second uses the dividend and share prices of an important Brazilian retail bank.","PeriodicalId":11485,"journal":{"name":"Econometrics: Applied Econometrics & Modeling eJournal","volume":"10 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2013-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86180536","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 investigates how the conditional quantiles of future returns and volatility of financial assets vary with various measures of ex-post variation in asset prices as well as option-implied volatility. We work in the flexible quantile regression framework and rely on recently developed model-free measures of integrated variance, upside and downside semivariance, and jump variation. Our results for the S&P 500 and WTI Crude Oil futures contracts show that simple linear quantile regressions for returns and heterogenous quantile autoregressions for realized volatility perform very well in capturing the dynamics of the respective conditional distributions, both in absolute terms as well as relative to a couple of well-established benchmark models. The models can therefore serve as useful risk management tools for investors trading the futures contracts themselves or various derivative contracts written on realized volatility.
{"title":"Semiparametric Conditional Quantile Models for Financial Returns and Realized Volatility","authors":"Filip Žikeš, Jozef Baruník","doi":"10.2139/ssrn.2313047","DOIUrl":"https://doi.org/10.2139/ssrn.2313047","url":null,"abstract":"This paper investigates how the conditional quantiles of future returns and volatility of financial assets vary with various measures of ex-post variation in asset prices as well as option-implied volatility. We work in the flexible quantile regression framework and rely on recently developed model-free measures of integrated variance, upside and downside semivariance, and jump variation. Our results for the S&P 500 and WTI Crude Oil futures contracts show that simple linear quantile regressions for returns and heterogenous quantile autoregressions for realized volatility perform very well in capturing the dynamics of the respective conditional distributions, both in absolute terms as well as relative to a couple of well-established benchmark models. The models can therefore serve as useful risk management tools for investors trading the futures contracts themselves or various derivative contracts written on realized volatility.","PeriodicalId":11485,"journal":{"name":"Econometrics: Applied Econometrics & Modeling eJournal","volume":"19 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2013-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75391976","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}
On the afternoon of May 6, 2010 Dow Jones Industrial Average (DJIA) plunged about 1000 points (about 9%) in a matter of minutes before rebounding almost as quickly. This was the biggest one day point decline on an intraday basis in the DJIA's history. An almost similar dramatic change in intraday volatility was observed on April 4, 2000 when DJIA dropped by 4.8%. These historical events present very compelling argument for the need of robust econometrics models which can forecast intraday asset volatility. There are numerous models available in the finance literature to model financial asset volatility. Various Autoregressive Conditional Heteroskedastic (ARCH) time series models are widely used for modelling daily (end of day) volatility of the financial assets. The family of basic GARCH models work well for modelling daily volatility but they are proven to be not as efficient for intraday volatility. The last two decades has seen some research augmenting the GARCH family of models to forecast intraday volatility, the Multiplicative Component GARCH (MCGARCH) model of Engle & Sokalska (2012) is the most recent of them. MCGARCH models the conditional variance as the multiplicative product of daily, diurnal, and stochastic intraday volatility of the financial asset. In this paper we use MCGARCH model to forecast intraday volatility of Australia's S&P/ASX-50 stock market, we also use the model to forecast the intraday Value at Risk. As the model requires a daily volatility component, we test a GARCH based estimate and a Realized Variance based estimate of daily volatility component.
{"title":"Intraday Volatility Forecast in Australian Equity Market","authors":"Abhay K. Singh, D. Allen, R. Powell","doi":"10.2139/ssrn.2308787","DOIUrl":"https://doi.org/10.2139/ssrn.2308787","url":null,"abstract":"On the afternoon of May 6, 2010 Dow Jones Industrial Average (DJIA) plunged about 1000 points (about 9%) in a matter of minutes before rebounding almost as quickly. This was the biggest one day point decline on an intraday basis in the DJIA's history. An almost similar dramatic change in intraday volatility was observed on April 4, 2000 when DJIA dropped by 4.8%. These historical events present very compelling argument for the need of robust econometrics models which can forecast intraday asset volatility. There are numerous models available in the finance literature to model financial asset volatility. Various Autoregressive Conditional Heteroskedastic (ARCH) time series models are widely used for modelling daily (end of day) volatility of the financial assets. The family of basic GARCH models work well for modelling daily volatility but they are proven to be not as efficient for intraday volatility. The last two decades has seen some research augmenting the GARCH family of models to forecast intraday volatility, the Multiplicative Component GARCH (MCGARCH) model of Engle & Sokalska (2012) is the most recent of them. MCGARCH models the conditional variance as the multiplicative product of daily, diurnal, and stochastic intraday volatility of the financial asset. In this paper we use MCGARCH model to forecast intraday volatility of Australia's S&P/ASX-50 stock market, we also use the model to forecast the intraday Value at Risk. As the model requires a daily volatility component, we test a GARCH based estimate and a Realized Variance based estimate of daily volatility component.","PeriodicalId":11485,"journal":{"name":"Econometrics: Applied Econometrics & Modeling eJournal","volume":"73 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2013-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90573309","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}
Abstract Are structural reforms growth enhancing? Is the effectiveness of reforms constrained by a country's distance from the technology frontier or by its institutional environment? This paper takes a new and comprehensive look at these questions by employing a novel data set that includes several kinds of real (trade, agriculture, and networks) and financial (domestic finance, banking, securities, and capital account) reforms for an extensive list of developed and developing countries, going back to the early 1970s. First-pass evidence based on growth breaks analysis and on panel growth regressions suggests that on average, both real and financial sector reforms are positively associated with higher growth. However, on several occasions, botched reforms resulted in growth disasters. More important, the positive reform-growth relationship is shown to be highly heterogeneous and to be influenced by a country's constraints on the authority of the executive power and by its distance from the technology fro...
{"title":"Which Reforms Work and Under What Institutional Environment: Evidence from a New Dataset on Structural Reforms","authors":"M. Onorato, A. Prati, C. Papageorgiou","doi":"10.2139/ssrn.1635231","DOIUrl":"https://doi.org/10.2139/ssrn.1635231","url":null,"abstract":"Abstract Are structural reforms growth enhancing? Is the effectiveness of reforms constrained by a country's distance from the technology frontier or by its institutional environment? This paper takes a new and comprehensive look at these questions by employing a novel data set that includes several kinds of real (trade, agriculture, and networks) and financial (domestic finance, banking, securities, and capital account) reforms for an extensive list of developed and developing countries, going back to the early 1970s. First-pass evidence based on growth breaks analysis and on panel growth regressions suggests that on average, both real and financial sector reforms are positively associated with higher growth. However, on several occasions, botched reforms resulted in growth disasters. More important, the positive reform-growth relationship is shown to be highly heterogeneous and to be influenced by a country's constraints on the authority of the executive power and by its distance from the technology fro...","PeriodicalId":11485,"journal":{"name":"Econometrics: Applied Econometrics & Modeling eJournal","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2013-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89669867","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}
Many recent modelling advances in finance topics ranging from the pricing of volatility-based derivative products to asset management are predicated on the importance of jumps, or discontinuous movements in asset returns. In light of this, a number of recent papers have addressed volatility predictability, some from the perspective of the usefulness of jumps in forecasting volatility. Key papers in this area include Andersen, Bollerslev, Diebold and Labys (2003), Corsi (2004), Andersen, Bollerslev and Diebold (2007), Corsi, Pirino and Reno (2008), Barndorff, Kinnebrock, and Shephard (2010), Patton and Shephard (2011), and the references cited therein. In this paper, we review the extant literature and then present new empirical evidence on the predictive content of realized measures of jump power variations (including upside and downside risk, jump asymmetry, and truncated jump variables), constructed using instantaneous returns, i.e., |r_{t}|^{q}, 0≤q≤6, in the spirit of Ding, Granger and Engle (1993) and Ding and Granger (1996). Our prediction experiments use high frequency price returns constructed using SP and our empirical implementation involves estimating linear and nonlinear heterogeneous autoregressive realized volatility (HAR-RV) type models. We find that past "large" jump power variations help less in the prediction of future realized volatility, than past "small" jump power variations. Additionally, we find evidence that past realized signed jump power variations, which have not previously been examined in this literature, are strongly correlated with future volatility, and that past downside jump variations matter in prediction. Finally, incorporation of downside and upside jump power variations does improve predictability, albeit to a limited extent.
从基于波动率的衍生产品定价到资产管理，金融领域的许多最新建模进展都是基于资产回报的跳跃或不连续变动的重要性。鉴于此，最近的一些论文讨论了波动性的可预测性，其中一些是从预测波动性时跳跃的有用性的角度出发的。该领域的主要论文包括Andersen, Bollerslev, Diebold and Labys (2003)， Corsi (2004)， Andersen, Bollerslev and Diebold (2007)， Corsi, Pirino and Reno (2008)， Barndorff, Kinnebrock, and Shephard (2010)， Patton and Shephard(2011)及其引用的参考文献。本文借鉴Ding、Granger和Engle(1993)和Ding和Granger(1996)的精神，利用瞬时收益，即|r_{t}|^{q}， 0≤q≤6，对跳跃力量变化的实现测度(包括上行和下行风险、跳跃不对称和截断的跳跃变量)的预测内容进行了回顾，并提出了新的经验证据。我们的预测实验使用使用SP构建的高频价格回报，我们的经验实现涉及估计线性和非线性异构自回归实现波动率(HAR-RV)类型模型。我们发现，与过去的“小”跳跃功率变化相比，过去的“大”跳跃功率变化对未来实现波动率的预测帮助较小。此外，我们发现有证据表明，过去已实现的签名跳跃功率变化与未来波动率密切相关，过去的下行跳跃变化在预测中很重要。最后，结合下行和上行跳跃力量的变化确实提高了可预测性，尽管在有限的程度上。
{"title":"Empirical Evidence on the Importance of Aggregation, Asymmetry, and Jumps for Volatility Prediction","authors":"D. Duong, Norman R. Swanson","doi":"10.2139/ssrn.2300605","DOIUrl":"https://doi.org/10.2139/ssrn.2300605","url":null,"abstract":"Many recent modelling advances in finance topics ranging from the pricing of volatility-based derivative products to asset management are predicated on the importance of jumps, or discontinuous movements in asset returns. In light of this, a number of recent papers have addressed volatility predictability, some from the perspective of the usefulness of jumps in forecasting volatility. Key papers in this area include Andersen, Bollerslev, Diebold and Labys (2003), Corsi (2004), Andersen, Bollerslev and Diebold (2007), Corsi, Pirino and Reno (2008), Barndorff, Kinnebrock, and Shephard (2010), Patton and Shephard (2011), and the references cited therein. In this paper, we review the extant literature and then present new empirical evidence on the predictive content of realized measures of jump power variations (including upside and downside risk, jump asymmetry, and truncated jump variables), constructed using instantaneous returns, i.e., |r_{t}|^{q}, 0≤q≤6, in the spirit of Ding, Granger and Engle (1993) and Ding and Granger (1996). Our prediction experiments use high frequency price returns constructed using SP and our empirical implementation involves estimating linear and nonlinear heterogeneous autoregressive realized volatility (HAR-RV) type models. We find that past \"large\" jump power variations help less in the prediction of future realized volatility, than past \"small\" jump power variations. Additionally, we find evidence that past realized signed jump power variations, which have not previously been examined in this literature, are strongly correlated with future volatility, and that past downside jump variations matter in prediction. Finally, incorporation of downside and upside jump power variations does improve predictability, albeit to a limited extent.","PeriodicalId":11485,"journal":{"name":"Econometrics: Applied Econometrics & Modeling eJournal","volume":"27 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2013-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87165141","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 investigate the relationship between ex ante total skewness and holding returns on individual equity options. Recent theoretical developments predict a negative relationship between total skewness and average returns, in contrast to the traditional view that only coskewness is priced. We find, consistent with recent theory, that total skewness exhibits a strong negative relationship with average option returns. Differences in average returns for option portfolios sorted on ex ante skewness range from 10% to 50% per week, even after controlling for risk. Our findings suggest that these large premiums compensate intermediaries for bearing unhedgeable risk when accommodating investor demand for lottery-like options.
{"title":"Stock Options as Lotteries","authors":"Brian H. Boyer, Keith Vorkink","doi":"10.2139/ssrn.1787365","DOIUrl":"https://doi.org/10.2139/ssrn.1787365","url":null,"abstract":"type=\"main\"> We investigate the relationship between ex ante total skewness and holding returns on individual equity options. Recent theoretical developments predict a negative relationship between total skewness and average returns, in contrast to the traditional view that only coskewness is priced. We find, consistent with recent theory, that total skewness exhibits a strong negative relationship with average option returns. Differences in average returns for option portfolios sorted on ex ante skewness range from 10% to 50% per week, even after controlling for risk. Our findings suggest that these large premiums compensate intermediaries for bearing unhedgeable risk when accommodating investor demand for lottery-like options.","PeriodicalId":11485,"journal":{"name":"Econometrics: Applied Econometrics & Modeling eJournal","volume":"29 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2013-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86960152","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}
Debra J. Aron, David E. Burnstein, Ana C. Danies, G. Keith
In the parlance of regulatory economics, “pass-through�? refers to the effect of a change in an incremental cost – generally, the effect of a change in a regulated input price – on the retail price of a good or service. In this paper we examine retail long distance telephone service prices in the United States for evidence of pass-through of the switched access fees paid by long distance telephone companies to local exchange carriers. We estimate the degree to which long distance companies pass through to their customers reductions in access rates, and we examine whether mandates imposed by regulators on long distance companies to pass through access fee reductions to customers affect the extent of pass-through. We evaluate annual panel data on intrastate long-distance revenues, access expenses, and minutes of use from 2004 to 2008 in each of the 50 states in the U.S. using a proprietary and detailed data set. We leverage the fact that some states have accompanied access rate reductions with pass-through mandates, and others have not. Using standard multivariate regression techniques we find that the market induces carriers to pass-through most of the reduction in access rates, and that this market-based pass-through is consistent with “full�? (100%) pass-through in the states that have undergone regulatory access reform. We also find that a regulatory mandate on long distance companies to pass through access rate reductions has no statistically significant effect on the magnitude of access fee pass-through, supporting the economic hypothesis that pass-through is driven by incentives for profit maximization and by competitive forces.
{"title":"An Empirical Analysis of Regulator Mandates on the Pass Through of Switched Access Fees for In-State Long-Distance Telecommunications in the U.S.","authors":"Debra J. Aron, David E. Burnstein, Ana C. Danies, G. Keith","doi":"10.2139/ssrn.1674082","DOIUrl":"https://doi.org/10.2139/ssrn.1674082","url":null,"abstract":"In the parlance of regulatory economics, “pass-through�? refers to the effect of a change in an incremental cost – generally, the effect of a change in a regulated input price – on the retail price of a good or service. In this paper we examine retail long distance telephone service prices in the United States for evidence of pass-through of the switched access fees paid by long distance telephone companies to local exchange carriers. We estimate the degree to which long distance companies pass through to their customers reductions in access rates, and we examine whether mandates imposed by regulators on long distance companies to pass through access fee reductions to customers affect the extent of pass-through. We evaluate annual panel data on intrastate long-distance revenues, access expenses, and minutes of use from 2004 to 2008 in each of the 50 states in the U.S. using a proprietary and detailed data set. We leverage the fact that some states have accompanied access rate reductions with pass-through mandates, and others have not. Using standard multivariate regression techniques we find that the market induces carriers to pass-through most of the reduction in access rates, and that this market-based pass-through is consistent with “full�? (100%) pass-through in the states that have undergone regulatory access reform. We also find that a regulatory mandate on long distance companies to pass through access rate reductions has no statistically significant effect on the magnitude of access fee pass-through, supporting the economic hypothesis that pass-through is driven by incentives for profit maximization and by competitive forces.","PeriodicalId":11485,"journal":{"name":"Econometrics: Applied Econometrics & Modeling eJournal","volume":"24 25 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2013-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88704931","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 investigate whether stock price movements can inform operations managers as to where they should focus improvement efforts. We examine how unexpected performance along several dimensions of service quality---on-time performance, long delays and cancellations, lost bags, and denied boardings---impacts contemporaneous stock returns. Prior research suggests that airlines buffer their flight schedules and engage in expensive employee incentive programs to increase the likelihood of on-time arrival. We find that only long delays are penalized by the market, and we identify a number of carrier-specific factors that alter the financial impact of long delays. We find that the penalty a carrier faces for long delays is significantly higher if it operates a high percentage of short-haul or connecting flights, or if its competitors incur fewer long delays in the same time period. Our findings suggest that developing ways to curtail long delays is a useful future research area.
{"title":"Can Financial Markets Inform Operational Improvement Efforts? Evidence from the Airline Industry","authors":"Kamalini Ramdas, Jonathan M. Williams, M. Lipson","doi":"10.2139/ssrn.1777250","DOIUrl":"https://doi.org/10.2139/ssrn.1777250","url":null,"abstract":"We investigate whether stock price movements can inform operations managers as to where they should focus improvement efforts. We examine how unexpected performance along several dimensions of service quality---on-time performance, long delays and cancellations, lost bags, and denied boardings---impacts contemporaneous stock returns. Prior research suggests that airlines buffer their flight schedules and engage in expensive employee incentive programs to increase the likelihood of on-time arrival. We find that only long delays are penalized by the market, and we identify a number of carrier-specific factors that alter the financial impact of long delays. We find that the penalty a carrier faces for long delays is significantly higher if it operates a high percentage of short-haul or connecting flights, or if its competitors incur fewer long delays in the same time period. Our findings suggest that developing ways to curtail long delays is a useful future research area.","PeriodicalId":11485,"journal":{"name":"Econometrics: Applied Econometrics & Modeling eJournal","volume":"37 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2013-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85545054","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 analyze the construction of multivariate forecasting densities based on conditional models for each variable, given the other variables; a joint predictive density is obtained by iteratively simulating from the conditional models. This idea has been pursued in the context of missing data imputation, but is new to the field of econometric forecasting. Its main advantage is that only univariate models for the variables in question are needed as inputs. Within a Monte Carlo study we illustrate the flexibility and robustness of this approach especially for the case of model misspecification. We then consider forecasting the bivariate mixed discrete-continuous distribution of returns and order flows on a high frequency level. This distribution can be related to an ex-post concept of market liquidity. A simulation-based forecasting distribution constructed from the conditional models for returns and order flows is found to outperform a vector autoregressive benchmark for several large-cap US stocks.
{"title":"An MCMC Approach to Multivariate Density Forecasting: An Application to Liquidity","authors":"Fabian Krueger, Ingmar Nolte","doi":"10.2139/ssrn.1743707","DOIUrl":"https://doi.org/10.2139/ssrn.1743707","url":null,"abstract":"We analyze the construction of multivariate forecasting densities based on conditional models for each variable, given the other variables; a joint predictive density is obtained by iteratively simulating from the conditional models. This idea has been pursued in the context of missing data imputation, but is new to the field of econometric forecasting. Its main advantage is that only univariate models for the variables in question are needed as inputs. Within a Monte Carlo study we illustrate the flexibility and robustness of this approach especially for the case of model misspecification. We then consider forecasting the bivariate mixed discrete-continuous distribution of returns and order flows on a high frequency level. This distribution can be related to an ex-post concept of market liquidity. A simulation-based forecasting distribution constructed from the conditional models for returns and order flows is found to outperform a vector autoregressive benchmark for several large-cap US stocks.","PeriodicalId":11485,"journal":{"name":"Econometrics: Applied Econometrics & Modeling eJournal","volume":"136 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2013-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86303429","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"> Labor mobility is the flexibility of workers to walk away from an industry in response to better opportunities. I develop a model in which labor flows make bad times worse for shareholders who are left with capital that is less productive. The model shows that firms face greater operating leverage by providing flexibility to mobile workers. I construct an empirical measure of labor mobility consistent with the model and document an economically significant cross-sectional relation between mobility, operating leverage, and stock returns. I find that firms in mobile industries earn returns over 5% higher than those in less mobile industries.
{"title":"Labor Mobility: Implications for Asset Pricing","authors":"Andrés Donangelo","doi":"10.2139/ssrn.1715232","DOIUrl":"https://doi.org/10.2139/ssrn.1715232","url":null,"abstract":"type=\"main\"> Labor mobility is the flexibility of workers to walk away from an industry in response to better opportunities. I develop a model in which labor flows make bad times worse for shareholders who are left with capital that is less productive. The model shows that firms face greater operating leverage by providing flexibility to mobile workers. I construct an empirical measure of labor mobility consistent with the model and document an economically significant cross-sectional relation between mobility, operating leverage, and stock returns. I find that firms in mobile industries earn returns over 5% higher than those in less mobile industries.","PeriodicalId":11485,"journal":{"name":"Econometrics: Applied Econometrics & Modeling eJournal","volume":"14 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2013-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74759684","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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