Using stochastic volatility models to analyse weekly ozone averages in Mexico City

In this paper we make use of some stochastic volatility models to analyse the behaviour of a weekly ozone average measurements series. The models considered here have been used previously in problems related to financial time series. Two models are considered and their parameters are estimated using a Bayesian approach based on Markov chain Monte Carlo (MCMC) methods. Both models are applied to the data provided by the monitoring network of the Metropolitan Area of Mexico City. The selection of the best model for that specific data set is performed using the Deviance Information Criterion and the Conditional Predictive Ordinate method.

Modelos de volatilidade estocástica em séries financeiras: uma aplicação para o IBOVESPA

Neste artigo apresentamos uma análise Bayesiana para o modelo de volatilidade estocástica (SV) e uma forma generalizada deste, cujo objetivo é estimar a volatilidade de séries temporais financeiras. Considerando alguns casos especiais dos modelos SV usamos algoritmos de Monte Carlo em Cadeias de Markov e o software WinBugs para obter sumários a posteriori para as diferentes formas de modelos SV. Introduzimos algumas técnicas Bayesianas de discriminação para a escolha do melhor modelo a ser usado para estimar as volatilidades e fazer previsões de séries financeiras. Um exemplo empírico de aplicação da metodologia é introduzido com a série financeira do IBOVESPA.

An overview of the Amazonian Aerosol Characterization Experiment 2008 (AMAZE-08)

The Amazon Basin provides an excellent environment for studying the sources, transformations, and properties of natural aerosol particles and the resulting links between biological processes and climate. With this framework in mind, the Amazonian Aerosol Characterization Experiment (AMAZE-08), carried out from 7 February to 14 March 2008 during the wet season in the central Amazon Basin, sought to understand the formation, transformations, and cloud-forming properties of fine-and coarse-mode biogenic aerosol particles, especially as related to their effects on cloud activation and regional climate. Special foci included (1) the production mechanisms of secondary organic components at a pristine continental site, including the factors regulating their temporal variability, and (2) predicting and understanding the cloud-forming properties of biogenic particles at such a site. In this overview paper, the field site and the instrumentation employed during the campaign are introduced. Observations and findings are reported, including the large-scale context for the campaign, especially as provided by satellite observations. New findings presented include: (i) a particle number-diameter distribution from 10 nm to 10 mu m that is representative of the pristine tropical rain forest and recommended for model use; (ii) the absence of substantial quantities of primary biological particles in the submicron mode as evidenced by mass spectral characterization; (iii) the large-scale production of secondary organic material; (iv) insights into the chemical and physical properties of the particles as revealed by thermodenuder-induced changes in the particle number-diameter distributions and mass spectra; and (v) comparisons of ground-based predictions and satellite-based observations of hydrometeor phase in clouds. A main finding of AMAZE-08 is the dominance of secondary organic material as particle components. The results presented here provide mechanistic insight and quantitative parameters that can serve to increase the accuracy of models of the formation, transformations, and cloud-forming properties of biogenic natural aerosol particles, especially as related to their effects on cloud activation and regional climate.

A hybrid commodity price-forecasting model applied to the sugar-alcohol sector

Accurate price forecasting for agricultural commodities can have significant decision-making implications for suppliers, especially those of biofuels, where the agriculture and energy sectors intersect. Environmental pressures and high oil prices affect demand for biofuels and have reignited the discussion about effects on food prices. Suppliers in the sugar-alcohol sector need to decide the ideal proportion of ethanol and sugar to optimise their financial strategy. Prices can be affected by exogenous factors, such as exchange rates and interest rates, as well as non-observable variables like the convenience yield, which is related to supply shortages. The literature generally uses two approaches: artificial neural networks (ANNs), which are recognised as being in the forefront of exogenous-variable analysis, and stochastic models such as the Kalman filter, which is able to account for non-observable variables. This article proposes a hybrid model for forecasting the prices of agricultural commodities that is built upon both approaches and is applied to forecast the price of sugar. The Kalman filter considers the structure of the stochastic process that describes the evolution of prices. Neural networks allow variables that can impact asset prices in an indirect, nonlinear way, what cannot be incorporated easily into traditional econometric models.

Determination of Atropine Enantiomers in Ophthalmic Solutions by Liquid Chromatography Using a Chiral AGP (R) Column

Many therapeutic agents are commercialized under their racemic form. The enantiomers can show differences in the pharmacokinetic and pharmacodynamic profile. The use of a pure enantiomer in pharmaceutical formulations may result in a better therapeutic index and fewer adverse effects. Atropine, an alkaloid of Atropa belladonna, is a racemic mixture of l-hyoscyamine and d-hyoscyamine. It is widely used to dilate the pupil. To quantify these enantiomers in ophthalmic solutions, an HPLC method was developed and validated using a Chiral AGP (R) column at 20 degrees C. The mobile phase consisted of a buffered phosphate solution (containing 10 mM 1-octanesulfonic acid sodium salt and 7.5 mM triethylamine, adjusted to pH 7.0 with orthophosphoric acid) and acetonitrile (99 + 1, v/v). The flow rate was 0.6 mL/min, with UV detection at 205 nm. In the concentration range of 14.0-26.0 mu g/mL, the method was found to be linear (r > 0.9999), accurate (with recovery of 100.1-100.5%), and precise (RSD system: <= 0.6%; RSD intraday: <= 1.1%; RSD interday: <= 0.9%). The method was specific, and the standard and sample solutions were stable for up to 72 h. The factorial design assures robustness with a variation of +/-10% in the mobile phase components and 2 degrees C of column temperature. The complete validation, including stress testing and factorial design, was studied and is presented in this research.

Quantitative Determination of Dimethylaminoethanol in Cosmetic Formulations by Nuclear Magnetic Resonance Spectroscopy

A nuclear magnetic resonance (NMR) spectroscopic method was validated for the quantitative determination of dimethylaminoethanol (DMAE) in cosmetic formulations. The linearity in the range from 0.5000 to 1.5000 g (DMAE salt/mass maleic acid) presents a correlation coefficient > 0.99 for all DMAE salts. The repeatability (intraday), expressed as relative standard deviation, ranged from 1.08 to 1.44% for samples and 1.31 to 1.88% for raw materials. The detection limit and quantitation limit were 0.0017 and 0.0051 g for DMAE, 0.0018 and 0.0054 g for DMAE bitartrate, and 0.0023 and 0.0071 g for DMAE acetamidobenzoate, respectively. The proposed method is simple, precise, and accurate and can be used in the quality control of raw materials and cosmetic gels containing these compounds as active substances.

Development and Validation of Stability-Indicating HPLC Methods for Quantitative Determination of Pravastatin, Fluvastatin, Atorvastatin, and Rosuvastatin in Pharmaceuticals

High-performance liquid-chromatographic (HPLC) methods were validated for determination of pravastatin sodium (PS), fluvastatin sodium (FVS), atorvastatin calcium (ATC), and rosuvastatin calcium (RC) in pharmaceuticals. Two stability-indicating HPLC methods were developed with a small change (10%) in the composition of the organic modifier in the mobile phase. The HPLC method for each statin was validated using isocratic elution. An RP-18 column was used with mobile phases consisting of methanol-water (60:40, v/v, for PS and RC and 70:30, v/v, for FVS and ATC). The pH of each mobile phase was adjusted to 3.0 with orthophosphoric acid, and the flow rate was 1.0mL/min. Calibration plots showed correlation coefficients (r)0.999, which were calculated by the least square method. The detection limit (DL) and quantitation limit (QL) were 1.22 and 3.08 mu g/mL for PS, 2.02 and 6.12 mu g/mL for FVS, 0.44 and 1.34 mu g/mL for ATC, and 1.55 and 4.70 mu g/mL for RC. Intraday and interday relative standard deviations (RSDs) were 2.0%. The methods were applied successfully for quantitative determination of statins in pharmaceuticals.

Price dispersion and price indexes

The traditional theory of price index numbers is based on the law of one price. But in the real world, we frequently observe the existence of an equilibrium price dispersion instead of one price of equilibrium. This article discusses the effects of price dispersion on two price indexes: the cost of living index and the consumer price index. With price dispersion and consumer searching for the lowest price, these indexes cannot be interpreted as deterministic indicators, but as stochastic indicators, and they can be biased if price dispersion is not taken into account. A measure for the bias of the consumer price index is proposed and the article ends with an estimation of the bias based on data obtained from the consumer price index calculated for the city of Sao Paulo, Brazil, from January 1988 through December 2004. The period analysed is very interesting, because it exhibits different inflationary environments: high levels and high volatility of the rates of inflation with great price dispersion until July 1994 and low and relatively stable rates of inflation with prices less dispersed after August 1994.

Inflation targeting in emerging economies: What do the data say?

In a recent thought-provoking paper, Ball and Sheridan [Ball, L., Sheridan, N., 2005. Does inflation targeting matter? In: Bernanke, B.S., Woodford, M. (Eds.), The Inflation-Targeting Debate, University of Chicago Press] show that the available evidence for a group of developed economies does not lend credence to the belief that adopting an inflation targeting regime (IT) was instrumental in bringing inflation and inflation volatility down. Here, we extend Ball and Sheridan`s analysis for a subset of 36 emerging market economies and find that, for them, the story is quite different. Compared to non-targeters, developing countries adopting the IT regime not only experienced greater drops in inflation, but also in growth volatility, thus corroborating the view that the regime`s ""constrained flexibility"" to deal with adverse shocks delivered concrete welfare gains. (c) 2006 Elsevier B.V. All rights reserved.

Microscopic origin of non-Gaussian distributions of financial returns

In this paper we study the possible microscopic origin of heavy-tailed probability density distributions for the price variation of financial instruments. We extend the standard log-normal process to include another random component in the so-called stochastic volatility models. We study these models under an assumption, akin to the Born-Oppenheimer approximation, in which the volatility has already relaxed to its equilibrium distribution and acts as a background to the evolution of the price process. In this approximation, we show that all models of stochastic volatility should exhibit a scaling relation in the time lag of zero-drift modified log-returns. We verify that the Dow-Jones Industrial Average index indeed follows this scaling. We then focus on two popular stochastic volatility models, the Heston and Hull-White models. In particular, we show that in the Hull-White model the resulting probability distribution of log-returns in this approximation corresponds to the Tsallis (t-Student) distribution. The Tsallis parameters are given in terms of the microscopic stochastic volatility model. Finally, we show that the log-returns for 30 years Dow Jones index data is well fitted by a Tsallis distribution, obtaining the relevant parameters. (c) 2007 Elsevier B.V. All rights reserved.

Reliability of electromyographic amplitude values of the upper limb muscles during closed kinetic chain exercises with stable and unstable surfaces

The purpose of the present study was to evaluate the intra and interday reliability of surface electromyographic amplitude values of the scapular girdle muscles and upper limbs during 3 isometric closed kinetic chain exercises, involving upper limbs with the fixed distal segment extremity on stable base of support and on a Swiss ball (relatively unstable). Twenty healthy adults performed the exercises push-up, bench-press and wall-press with different effort levels (80% and 100% maximal load). Subjects performed three maximal voluntary contractions (MVC) in muscular testing position of each muscle to obtain a reference value for root mean square (RMS) normalization. Individuals were instructed to randomly perform three isometric contraction series, in which each exercise lasted 6 s with a 2-min resting-period between series and exercises. Intra and interday reliabilities were calculated through the intraclass correlation coefficient (ICC 2.1), standard error of the measurement (SEM). Results indicated an excellent intraday reliability of electromyographic amplitude values (ICC >= 0.75). The interday reliability of normalized RMS values ranged between good and excellent (ICC 0.52-0.98). Finally, it is suggested that the reliability of normalized electromyographic amplitude values of the analyzed muscles present better values during exercises on a stable surface. However, load levels used during the exercises do not seem to have any influence on variability levels, possibly because the loads were quite similar. (C) 2007 Elsevier Ltd. All rights reserved.

Development of a new stir bar sorptive extraction coating and its application for the determination of six pesticides in sugarcane juice

In this article, a novel polydimethylsiloxane/activated carbon (PDMS-ACB) material is proposed as a new polymeric phase for stir bar sorptive extraction (SBSE). The PDMS-ACB stir bar, assembled using a simple Teflon (R)/glass capillary mold, demonstrated remarkable stability and resistance to organic solvents for more than 150 extractions. The SBSE bar has a diameter of 2.36 mm and a length of 2.2 cm and is prepared to contain 92 mu L of polymer coating. This new PDMS-ACB bar was evaluated for its ability to determine the quantity of pesticides in sugarcane juice samples by performing liquid desorption (LD) in 200 mu L of ethyl acetate and analyzing the solvent through gas chromatography coupled with mass spectrometry (GC-MS). A fractional factorial design was used to evaluate the main parameters involved in the extraction procedure. Then, a central composite design with a star configuration was used to optimize the significant extraction parameters. The method used demonstrated a limit of quantification (LOQ) of 0.5-40 mu g/L, depending on the analyte detected; the amount of recovery varied from 0.18 to 49.50%, and the intraday precision ranged from 0.072 to 8.40%. The method was used in the analysis of real sugarcane juice samples commercially available in local markets.