Search results for "Volatility"

showing 5 items of 245 documents

Does corn market uncertainty impact the US ethanol prices?

2018

The growing interest in biofuel as a green energy source has intensified the linkages between corn and ethanol markets, especially in the United States that represents the largest producing and exporting country for ethanol in the world. In this study, we examine the effect of corn market uncertainty on the price changes of US ethanol applying a set of GARCH-jump models. We find that the US ethanol price changes react positively to the corn market volatility shocks after controlling for the effect of oil price uncertainty. In addition, we document that the impact of corn price volatility on the US ethanol prices appears to be asymmetric. Specifically, only the positive corn market volatilit…

ta520maissiNaturgeografietanoliNatural resource economics020209 energyoil price volatility02 engineering and technologyöljyvolatility shockshintakehitysvolatiliteetti0202 electrical engineering electronic engineering information engineeringEconomicsbiopolttoaineetWaste Management and Disposalta512corn price uncertaintyhealth care economics and organizationsGARCH–jump modelRenewable Energy Sustainability and the EnvironmentMarket uncertaintybusiness.industryasymmetry; corn price uncertainty; GARCH-jump model; oil price volatility; US ethanol market; volatility shocksfood and beveragesForestrybiofuelsRenewable energyPhysical GeographyBiofuelasymmetriahinnatbusinessUS ethanol marketAgronomy and Crop ScienceasymmetryGlobal Change Biology Bioenergy
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Testing explosive bubbles with time-varying volatility: the case of Spanish public debt

2023

In this paper the dynamics of the Spanish public debt-GDP ratio is analysed during the period 1850–2021. We use recent procedures to test for explosive bubbles in the presence under time- varying volatility (Harvey et al., 2016; Harvey et al., 2019, 2020; Kurozumi et al., 2022) in order to test the explosive behavior of Spanish public debt over this long period. We extend previous analysis of Esteve and Prats (2022) where assume constant unconditional volatility in the underlying error process.

time-varying volatilityHG Financeexplosive autoregressionrational bubblepublic debtJ Political ScienceUNESCO::CIENCIAS ECONÓMICASHJ Public Financeright-tailed unit root testingFinance
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A New Perspective on the Relationship between Trading Variables and Volatility in Futures Markets

2017

In this paper, we study the relationship between trading-related variables and volatility in futures markets, from a new unifying perspective, which is based on the separation of open and closed positions. Volatility in stock index futures markets (Standard & Poor’s 500, DAX 30 and Nikkei 225) is related to the flow of contracts entered into the markets and the flow of contracts that are closed out. In general, the daily changes in the number of open and closed positions are both positively correlated with volatility. Additionally, there is a stronger positive relationship between the number of open (respectively, closed) positions and contemporaneous volatility on those days when t…

trading volumelcsh:HB71-74volatilityopen interesttrading volumeopen and closed positionsvolatilitylcsh:Economics as a scienceopen interestlcsh:Businesslcsh:HF5001-6182open and closed positions
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Volatility risk premia and financial connectedness

2014

In this paper we use the Diebold Yilmaz (2009 and 2012) methodology to construct an index of connectedness among five European stock markets: France, Germany, UK, Switzerland and the Netherlands, by using volatility risk premia. The volatility risk premium, which is a proxy of risk aversion, is measured by the difference between the implied volatility and expected realized volatility of the stock market for next month. While Diebold and Yilmaz focus is on the forecast error variance decomposition of stock returns or range based volatilities employing a stationary VAR in levels, we account for the (locally) long memory stationary properties of the levels of volatility risk premia series. The…

volatility risk premium long memory FIVAR financial connectednessjel:C32jel:C38jel:G13jel:C58
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MODELING OF VOLATILITY IN THE ROMANIAN CAPITAL MARKET

2012

This paper aims to analyze the volatility of capital market in Romania by selecting a portfolio of representative indices (BET BET_FI and RASDAQ_C). In this respect, we want to identify the most appropriate model to estimate volatility by using modern econometric tools and useful GARCH models respectively. The study results highlight that EGARCH(1,1) model has managed to eliminate all traces of statistically significant autocorrelation and ARCH effects from the residuals from daily series, giving an accurate image of the Romanian capital market volatility.

volatility GARCH models autocorrelation normal distributionStudies in Business and Economics
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