ERN: Time-Series Models (Single) (Topic)最新文献_第4页

Patterns and Pricing of Idiosyncratic Volatility in French Stock Market 法国股票市场特殊波动的模式与定价

ERN: Time-Series Models (Single) (Topic) Pub Date : 2017-05-01 DOI: 10.2139/ssrn.2973142

Zhentao Liu, G. Nartea, Ji (George) Wu

{"title":"Patterns and Pricing of Idiosyncratic Volatility in French Stock Market","authors":"Zhentao Liu, G. Nartea, Ji (George) Wu","doi":"10.2139/ssrn.2973142","DOIUrl":"https://doi.org/10.2139/ssrn.2973142","url":null,"abstract":"Purpose: The current research is to investigate the time series behavior of idiosyncratic volatility (IVOL) and its role in asset pricing in France in a twenty-year testing period. Design/methodology/approach: We test for the presence of trends in aggregate idiosyncratic and market volatility using Bunzel and Vogelsang’s (2005) t-dan test. We follow Bekaert et al. (2012) to test for regime shifts of both aggregate idiosyncratic and market volatilities. And then, we employ portfolio level analysis and cross-sectional univariate Fama-MacBeth regressions to examine the relationship between IVOL and cross-sectional stock returns in French stock market. Findings: First, we find that both idiosyncratic and market volatility do not exhibit long-term trends. Instead, their patterns are consistent with regime switching behavior. Second, though we initially find a strong significant negative IVOL effect in the French stock market which is robust in bi-variate Fama-MacBeth regressions, the negative IVOL effect is becoming marginal significant when we control for SIZE, BM, momentum, and short-term reversal simultaneously. Our new evidence suggests that there is a marginal IVOL effect in the French stock market adding to the increasing number of studies questioning the ubiquity of the negative IVOL puzzle. Originality/value: First, we present the first empirical evidence on examining the trends of both aggregate idiosyncratic and market volatilities, and the pricing role of IVOL in French stock market. We draw an attention for both academia and practitioners on an individual developed stock market. Second, we add new evidence to the mounting results questioning the ubiquity of the IVOL effect. This highlights the importance of country verification of so called anomalies in the US, even in developed markets. Finally, we confirm earlier evidence both aggregate idiosyncratic and market volatilities in the French stock market exhibits regime switching behavior rather than showing a long-term time trends.","PeriodicalId":418701,"journal":{"name":"ERN: Time-Series Models (Single) (Topic)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116922492","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}

引用次数: 0

Now-Casting Building Permits with Google Trends 现在用谷歌趋势铸造建筑许可

ERN: Time-Series Models (Single) (Topic) Pub Date : 2017-02-01 DOI: 10.2139/ssrn.2910165

David Coble, Pablo M. Pincheira

引用次数: 12

Factors Associated with Production Input Difference of a Manufacturing Plant in Sri Lanka: A Case Study 斯里兰卡某制造工厂生产投入差异的相关因素研究

ERN: Time-Series Models (Single) (Topic) Pub Date : 2016-12-08 DOI: 10.2139/ssrn.2910228

K.P.D.Y.M. Thiwanthika, R. Abeygunawardana, R. Munasinghe

{"title":"Factors Associated with Production Input Difference of a Manufacturing Plant in Sri Lanka: A Case Study","authors":"K.P.D.Y.M. Thiwanthika, R. Abeygunawardana, R. Munasinghe","doi":"10.2139/ssrn.2910228","DOIUrl":"https://doi.org/10.2139/ssrn.2910228","url":null,"abstract":"Abstract The supply chain is a system of organizations, peoples, activities, information, and resources involved in moving a product or service from supplier to customer. As the whole supply chain is linked together, any inconsistency in one link can badly affect the overall supply chain. Each organization in the supply chain has its own internal individual supply chains. The internal supply chain is mainly based on the production demand and material supply to the production. Any inconsistency between the demand and the supply, directly affects the status of internal supply chain. Only few studies have been done on internal supply demand variance, and this study is one of the few approaches into this area. The main objective of this study is to identify the factors associated with production input difference of a manufacturing plant. This is an explanatory research, which is done using appropriate sampling methods and Vector Auto regressive (VAR) modeling. Eviews (7.0.0.1) version is used to analyze the data. First of all the data has been checked for stationary property and the related lag length has been selected. Then the VAR modeling techniques has been applied and later the diagnostic tests have been performed on the resulted models. In briefing the results, it is stated that style of the product (Style) does not impact the input variance models or downtime models. Considering input variance models, it is found that downtime at lag 1 does not have any impact on the input variance. Furthermore, the previous day input variance has a significant impact to the next day input variance. The style and previous day downtime influence the demand variance only in special cases. As heteroskedasticity is present in some of the models, exponential & power transformations have been done in order to avoid heteroskedasticity. But the results do not dramatically change due to transformations. Keywords: Factors, Internal Supply Chain, Manufacturing Plant, Vector Auto Regressive","PeriodicalId":418701,"journal":{"name":"ERN: Time-Series Models (Single) (Topic)","volume":"120 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124131326","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}

引用次数: 0

Jump-Preserving Varying-Coefficient Models for Nonlinear Time Series 非线性时间序列的保跳变系数模型

ERN: Time-Series Models (Single) (Topic) Pub Date : 2016-12-01 DOI: 10.2139/ssrn.2938472

P. Čížek, C. Koo

引用次数: 2

Time Varying Quantile Lasso 时变分位数套索

ERN: Time-Series Models (Single) (Topic) Pub Date : 2016-11-03 DOI: 10.2139/ssrn.2865608

Lenka Zbonáková, W. Härdle, Weining Wang

{"title":"Time Varying Quantile Lasso","authors":"Lenka Zbonáková, W. Härdle, Weining Wang","doi":"10.2139/ssrn.2865608","DOIUrl":"https://doi.org/10.2139/ssrn.2865608","url":null,"abstract":"In the present chapter we study the dynamics of penalization parameter (lambda ) of the least absolute shrinkage and selection operator (Lasso) method proposed by Tibshirani (J Roy Stat Soc Series B 58:267–288, 1996) and extended into quantile regression context by Li and Zhu (J Comput Graph Stat 17:1–23, 2008). The dynamic behaviour of the parameter (lambda ) can be observed when the model is assumed to vary over time and therefore the fitting is performed with the use of moving windows. The proposal of investigating time series of (lambda ) and its dependency on model characteristics was brought into focus by Hardle et al. (J Econom 192:499–513, 2016), which was a foundation of FinancialRiskMeter. Following the ideas behind the two aforementioned projects, we use the derivation of the formula for the penalization parameter (lambda ) as a result of the optimization problem. This reveals three possible effects driving (lambda ); variance of the error term, correlation structure of the covariates and number of nonzero coefficients of the model. Our aim is to disentangle these three effects and investigate their relationship with the tuning parameter (lambda ), which is conducted by a simulation study. After dealing with the theoretical impact of the three model characteristics on (lambda ), empirical application is performed and the idea of implementing the parameter (lambda ) into a systemic risk measure is presented.","PeriodicalId":418701,"journal":{"name":"ERN: Time-Series Models (Single) (Topic)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130665132","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}

引用次数: 8

Feasible Invertibility Conditions and Maximum Likelihood Estimation for Observation-Driven Models 观测驱动模型的可行可逆性条件和最大似然估计

ERN: Time-Series Models (Single) (Topic) Pub Date : 2016-10-04 DOI: 10.2139/ssrn.2848819

F. Blasques, P. Gorgi, S. J. Koopman, O. Wintenberger

引用次数: 44

Time-Varying Parameter Vector Autoregressions: Specification, Estimation, and an Application 时变参数向量自回归:规范，估计和应用

ERN: Time-Series Models (Single) (Topic) Pub Date : 2016-09-01 DOI: 10.21144/eq1010403

T. Lubik, C. Matthes

引用次数: 43

Forecasting Value-at-Risk Under Temporal and Portfolio Aggregation 时间和组合聚集下的风险价值预测

ERN: Time-Series Models (Single) (Topic) Pub Date : 2015-12-31 DOI: 10.2139/ssrn.2711203

E. Kole, Thijs D. Markwat, A. Opschoor, Dick J. C. van Dijk

引用次数: 10

Relationship of the Change in Implied Volatility with the Underlying Equity Index Return in Thailand 泰国隐含波动率变动与标的股票指数回报之关系

ERN: Time-Series Models (Single) (Topic) Pub Date : 2015-11-01 DOI: 10.2139/ssrn.2791306

Supachok Thakolsri, Yuthana Sethapramote, Komain Jiranyakul

引用次数: 0

Conţinutul Analizei Seriilor De Timp Financiare (The Essentials of the Analysis of Financial Time Series ) Conţinutul analyizei Seriilor De Timp Financiare(金融时间序列分析要点)

ERN: Time-Series Models (Single) (Topic) Pub Date : 2015-10-11 DOI: 10.2139/ssrn.2672628

R. Stefanescu, Ramona Dumitriu

引用次数: 0