Search results for "Volatility"
showing 10 items of 245 documents
Volatility co-movements: a time scale decomposition analysis
2013
In this paper we investigate short-run co-movements before and after the Lehman Brothers’ collapse among the volatility series of US and a number of European countries. The series under investigation (implied and realized volatility) exhibit long-memory and, in order to avoid missspecification errors related to the parameterization of a long memory multivariate model, we rely on wavelet analysis. More specifically, we retrieve the time series of wavelet coefficients for each volatility series for high frequency scales, using the Maximal Overlapping Discrete Wavelet transform and we apply Maximum Likelihood for a factor decomposition of the short-run covariance matrix. The empirical evidence…
Volatility co-movements: a time scale decomposition analysis
2014
In this paper we are interested in detecting contagion from US to European stock market volatilities in the period immediately after the Lehman Brothers’ collapse. The analysis, based on a factor decomposition of the covariance matrix of implied and realized volatilities, is carried for different sub-samples (identified as normal and crisis periods) and across different (high) frequency bands. In particular, the analysis is split in two stages. In the first stage, we retrieve the time series of wavelet coefficients for each volatility series for high frequency scales, using the Maximal Overlapping Discrete Wavelet transform and, in a second stage, we apply Maximum Likelihood for a factor de…
First Study on Nihonium (Nh, Element 113) Chemistry at TASCA
2021
Frontiers in Chemistry 9, 753738 (2021). doi:10.3389/fchem.2021.753738
Low temperature headspace desorption of volatile organic compounds trapped in air sampling solid-supports
2009
Environmental context. The monitoring of volatile organic compounds (VOCs) in air is of great importance for air quality on both local and global scales. The determination of VOCs can be carried out by gas chromatography–mass spectrometry (GC-MS) after active or passive sampling and (high temperature) thermal desorption. An attractive alternative would be to combine GC-MS with headspace (HS) systems as it allows simpler, faster, low temperature desorption. We present here the first report of HS-GC-MS for the determination of VOCs in air sampled using solid supports. Abstract. The use of a headspace (HS) for low temperature desorption of VOCs, previously sorbed from indoor air on solid supp…
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…
Stochastic modeling of Supramax spot and forward freight rates
2015
We conducted an empirical analysis of Supramax spot rates and propose a continuous time process to model the dynamics. The model incorporates features relevant for shipping freight rates, freight rate volatility that varies over time, sudden, big freight rate movements, and short-term, mean-reverting price trends. This suggests some degree of short-term predictability of Supramax spot rates, making shipping different from traditional asset markets, like stocks and currencies, and also most commodity markets. However, this does not imply that arbitrage profits are easily picked up in this market, as, financially speaking, spot freight rates are not traded assets. We instead focus on the rela…
Networks of equities in financial markets
2004
We review the recent approach of correlation based networks of financial equities. We investigate portfolio of stocks at different time horizons, financial indices and volatility time series and we show that meaningful economic information can be extracted from noise dressed correlation matrices. We show that the method can be used to falsify widespread market models by directly comparing the topological properties of networks of real and artificial markets.
Power-law relaxation in a complex system: Omori law after a financial market crash
2003
We study the relaxation dynamics of a financial market just after the occurrence of a crash by investigating the number of times the absolute value of an index return is exceeding a given threshold value. We show that the empirical observation of a power law evolution of the number of events exceeding the selected threshold (a behavior known as the Omori law in geophysics) is consistent with the simultaneous occurrence of (i) a return probability density function characterized by a power law asymptotic behavior and (ii) a power law relaxation decay of its typical scale. Our empirical observation cannot be explained within the framework of simple and widespread stochastic volatility models.
Variety and volatility in financial markets
2000
We study the price dynamics of stocks traded in a financial market by considering the statistical properties both of a single time series and of an ensemble of stocks traded simultaneously. We use the $n$ stocks traded in the New York Stock Exchange to form a statistical ensemble of daily stock returns. For each trading day of our database, we study the ensemble return distribution. We find that a typical ensemble return distribution exists in most of the trading days with the exception of crash and rally days and of the days subsequent to these extreme events. We analyze each ensemble return distribution by extracting its first two central moments. We observe that these moments are fluctua…
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.