Search results for "SMILE"

showing 10 items of 44 documents

Cost-effectiveness of zofenopril in patients with left ventricular systolic dysfunction after acute myocardial infarction: a post hoc analysis of SMI…

2013

Claudio Borghi,1 Ettore Ambrosioni,1 Stefano Omboni,2 Arrigo FG Cicero,1 Stefano Bacchelli,1 Daniela Degli Esposti,1 Salvatore Novo,3 Dragos Vinereanu,4 Giuseppe Ambrosio,5 Giorgio Reggiardo,6 Dario Zava7 1Unit of Internal Medicine, Policlinico S Orsola, University of Bologna, Bologna, Italy; 2Italian Institute of Telemedicine, Varese, Italy; 3Division of Cardiology, University of Palermo, Palermo, Italy; 4University and Emergency Hospital, Bucharest, Romania; 5Division of Cardiology, University of Perugia, Perugia, Italy; 6Mediservice, Milano, Italy; 7Istituto Lusofarmaco d'Italia SpA, Peschiera Borromeo, Italy Background: In SMILE-4 (the Survival of Myocardial Infarction Long-term…

Ramiprilmedicine.medical_specialtyCost effectivenessEconomics Econometrics and Finance (miscellaneous)Populationacute myocardial infarctionramiprilchemistry.chemical_compoundInternal medicinePost-hoc analysismedicinezofenoprilMyocardial infarctioneducationcost-effectivenesshealth care economics and organizationsOriginal Researchleft ventricular dysfunctioneducation.field_of_studylcsh:R5-920business.industryHealth Policylcsh:RM1-950acetylsalicylic acidmedicine.diseaseSMILE studycost effectiveness analysis (CEA)Confidence intervalZofenoprilangiotensin-converting enzyme inhibitorsClinicoEconomics and Outcomes Researchlcsh:Therapeutics. PharmacologychemistryCardiologyNumber needed to treatMedical emergencybusinesslcsh:Medicine (General)medicine.drug
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Volatility Transmission Models: A Survey

2005

This study reviews the literature on volatility transmission in order to determine what we have learnt about the different methodologies applied. In particular, GARCH, regime switching and stochastic volatility models are analysed. In addition, this study covers several concrete aspects such as their scope of application, the overlapping problem, the concept of efficiency and asymmetry modelling. Finally, emerging topics and unanswered questions are identified, serving as an agenda for future research.

Scope (project management)Stochastic volatilityOrder (exchange)Financial economicsFinancial models with long-tailed distributions and volatility clusteringAutoregressive conditional heteroskedasticityVolatility swapVolatility smileEconometricsEconomicsImplied volatilitySSRN Electronic Journal
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Another Look at Value and Momentum: Volatility Spillovers

2017

This paper examines volatility interdependencies between value and momentum returns. Using U.S. data over the period 1926-2015, we document persistent periods of low and high volatility spillovers between value and momentum strategies. Moreover, we find that the intensity of the volatility spillovers may change substantially in very short periods of time and that these shifts in spillover intensity can be linked to prominent economic events and financial market turmoil. Our results further demonstrate that value returns increase and momentum returns decrease monotonically with increasing volatility spillovers between the two strategies. Given this linkage between spillover intensity and ret…

Spillover effectFinancial economicsVolatility swapForward volatilityVolatility smileEconometricsEconomicsTrading strategyImplied volatilityVolatility (finance)Volatility risk premiumSSRN Electronic Journal
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Cross-Commodity Spot Price Modeling with Stochastic Volatility and Leverage For Energy Markets

2013

Spot prices in energy markets exhibit special features, such as price spikes, mean reversion, stochastic volatility, inverse leverage effect, and dependencies between the commodities. In this paper a multivariate stochastic volatility model is introduced which captures these features. The second-order structure and stationarity of the model are analyzed in detail. A simulation method for Monte Carlo generation of price paths is introduced and a numerical example is presented.

Statistics and Probability15A04Spot contractSABR volatility model01 natural sciences010104 statistics & probabilityEnergy marketVolatility swap0502 economics and businessEconometricsForward volatilityMean reversionstochastic volatilityleverage0101 mathematicsMathematics050208 financeStochastic volatilityApplied Mathematics05 social sciences91G60subordinator91G20Constant elasticity of variance modelVolatility smileOrnstein-Uhlenbeck process60H3060G1060G51Advances in Applied Probability
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The stabilizing effect of volatility in financial markets

2017

In financial markets, greater volatility is usually considered synonym of greater risk and instability. However, large market downturns and upturns are often preceded by long periods where price returns exhibit only small fluctuations. To investigate this surprising feature, here we propose using the mean first hitting time, i.e. the average time a stock return takes to undergo for the first time a large negative or positive variation, as an indicator of price stability, and relate this to a standard measure of volatility. In an empirical analysis of daily returns for $1071$ stocks traded in the New York Stock Exchange, we find that this measure of stability displays nonmonotonic behavior, …

Statistics and ProbabilityStatistical Finance (q-fin.ST)Stochastic volatilityFinancial economicsQuantitative Finance - Statistical FinanceImplied volatilityCondensed Matter Physics01 natural sciencesVolatility risk premiumSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)010305 fluids & plasmasHeston modelFOS: Economics and businessVolatility swap0103 physical sciencesEconometricsForward volatilityEconomicsVolatility smileVolatility (finance)010306 general physicsStatistical and Nonlinear Physic
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A Multivariate Non-Gaussian Stochastic Volatility Model with Leverage for Energy Markets

2009

Spot prices in energy markets exhibit special features like price spikes, mean-reversion inverse, stochastic volatility, inverse leverage effect and co-integration between the different commodities. In this paper a multivariate stochastic volatility model is introduced which captures these features. Second order structure and stationary issues of the model are analysed. Moreover the implied multivariate forward model is derived. Due to the flexibility of the model stylized facts of the forward curve as contango, backwardation and humps are explained. Moreover, a transformed-based method to price options on the forward is described, where fast and precise algorithms for price computations ca…

Stochastic volatilityConstant elasticity of variance modelNormal backwardationVolatility swapForward volatilityVolatility smileForward priceEconometricsEconomicsImplied volatilitySSRN Electronic Journal
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Firm Size and Volatility Analysis in the Spanish Stock Market

2011

In this article, three strongly related questions are studied. First, volatility spillovers between large and small firms in the Spanish stock market are analyzed by using a conditional CAPM with an asymmetric multivariate GARCH-M covariance structure. Results show that there exist bidirectional volatility spillovers between both types of firms, especially after bad news. Second, the volatility feedback hypothesis explaining the volatility asymmetry feature is investigated. Results show significant evidence for this hypothesis. Finally, the study uncovers that conditional beta coefficient estimates within the used model are insensitive to sign and size asymmetries in the unexpected shock re…

Stochastic volatilityFinancial economicsRisk premiumAutoregressive conditional heteroskedasticityEconomics Econometrics and Finance (miscellaneous)CovarianceImplied volatilityVolatility risk premiumMultivariate garchPrice of riskVolatility swapEconomicsEconometricsForward volatilityVolatility smileCapital asset pricing modelStock marketVolatility (finance)SSRN Electronic Journal
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Univariate and multivariate statistical aspects of equity volatility

2004

We discuss univariate and multivariate statistical properties of volatility time series of equities traded in a financial market. Specifically, (i) we introduce a two-region stochastic volatility model able to well describe the unconditional pdf of volatility in a wide range of values and (ii) we quantify the stability of the results of a correlation-based clustering procedure applied to synchronous time evolution of a set of volatility time series.

Stochastic volatilityFinancial models with long-tailed distributions and volatility clusteringVolatility smileUnivariateEconometricsForward volatilityEconomicsVolatility (finance)Implied volatilitySettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)volatility financial markets econophysics log range correlated processes stochastic processesHeston model
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Option-Implied Volatility Spillovers between Risk Factors in FX Markets and States of the Global Economy

2016

This study employs option price data to back out the implied portfolio volatilities of the dollar and carry trade risk factors of the G-10 currencies. To investigate expected volatility spillover effects between risk factors in FX markets, we extend Grobys (2015) and Diebold and Yilmaz (2009) by constructing expected volatility spillover indices based upon the forecast-error variance decomposition of Vector-Autoregression models employing option-implied portfolio volatilities. Surprisingly, the dollar and carry trade risk factors that are orthogonal in the first moment exhibit strong stochastic interrelations in the second expected moment. Our findings indicate that expected high spillover …

Stochastic volatilitySpillover effectFinancial economicsVolatility swapEconometricsForward volatilityVolatility smileLiberian dollarBusinessImplied volatilityVolatility risk premiumSSRN Electronic Journal
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Open and Closed Positions and Stock Index Futures Volatility

2011

In this paper we analyze the relationship between volatility in index futures markets and the number of open and closed positions. We observe that, although in general both positions are positively correlated with contemporaneous volatility, in the case of S&P 500, only the number of open positions has influence over the volatility. Additionally, we observe a stronger positive relationship on days characterized by extreme movements of these contracting movements dominating the market. Finally, our findings suggest that day-traders are not associated to an increment of volatility, whereas uninformed traders, both opening and closing their positions, have to do with it.

Stock index futuresMonetary economicsOpen interestTrading volumeImplied volatilityVolatility risk premiumVolatilityVolatility swapmental disordersForward volatilityVolatility smileEconomicsVolatility (finance)Futures contractpsychological phenomena and processesSSRN Electronic Journal
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