Equity offerings, stock price crash risk, and the impact of securities regulation: international evidence

We examine whether earnings manipulation around seasoned equity offerings (SEOs) is associated with an increase in the likelihood of a stock price crash post-issue and test whether the enactment of securities regulations attenuate the relation between SEOs and crash risk. Empirical evidence documents that managerial tendency to conceal bad news increases the likelihood of a stock price crash (Jin and Myers, 2006; Hutton, Marcus, and Tehranian, 2009). We test this hypothesis using a sample of firms from 29 EU countries that enacted the Market Abuse Directive (MAD). Consistent with our hypothesis, we find that equity issuers that engage in earnings management experience a significant increase in crash risk post-SEO relative to control groups of non-issuers; this effect is stronger for equity issuers with poor information environments. In addition, our findings show a significant decline in crash risk post-issue after the enactment of MAD that is stronger for firms that actively manage earnings. This decline in post-issue crash risk is more effective in countries with high ex-ante institutional quality and enforcement. These results suggest that the implementation of MAD helps to mitigate managers’ ability to manipulate earnings around SEOs.

Earnings management and stock price crashes post-crossdelisting

We test whether cross-delisted firms from the major U.S. stock exchanges experience an increase in crash risk associated with earnings management. Consistent with our prediction, we find that earnings management have a greater positive impact on stock price crash risk post-cross-delisting when compared to a sample of still cross-listed firms. Moreover, our results suggest that this effect is more pronounced for crossdelisted firms from countries with weaker investor protection and poorer quality of their information environment. We further examine whether managers’ ability to manipulate earnings increases post-cross-delisting around seasoned equity offerings. Our evidence shows that cross-delisted firms that engage in earnings management to inflate reported earnings prior to a seasoned equity offering are more likely to observe a subsequent stock price crash.

Post-operating performance of cross-delisted firms from U.S. stock exchanges

We investigate the long-term performance of cross-delisted firms from U.S. stock markets. Using a sample of foreign firms listed and delisted from U.S. stock exchange markets over 2000-2012, we examine the operating performance and the long-run stock returns performance of firms post-cross-delisting. Our results suggest that cross-delisted firms have less growth opportunities than matched cross-listed firms in the long run. Moreover, firms that cross-delist after the passage of Rule 12h-6 of 2007 exhibit a significant decline in operating performance. In contrast, before the adoption of the Rule 12h-6, cross-delisted firms seem to be affected by the cost of a U.S. listing in the precross -delisting period. In addition, we provide evidence that cross-delisted firms underperform their cross-listed peers; cross-delisted firms experience negative average abnormal returns, especially in the post-delisting period.

A spectrum-driven damage Identification technique : application and validation through the numerical simulation of the Z24 Bridge

The present paper focuses on a damage identification method based on the use of the second order spectral properties of the nodal response processes. The explicit dependence on the frequency content of the outputs power spectral densities makes them suitable for damage detection and localization. The well-known case study of the Z24 Bridge in Switzerland is chosen to apply and further investigate this technique with the aim of validating its reliability. Numerical simulations of the dynamic response of the structure subjected to different types of excitation are carried out to assess the variability of the spectrum-driven method with respect to both type and position of the excitation sources. The simulated data obtained from random vibrations, impulse, ramp and shaking forces, allowed to build the power spectrum matrix from which the main eigenparameters of reference and damage scenarios are extracted. Afterwards, complex eigenvectors and real eigenvalues are properly weighed and combined and a damage index based on the difference between spectral modes is computed to pinpoint the damage. Finally, a group of vibration-based damage identification methods are selected from the literature to compare the results obtained and to evaluate the performance of the spectral index.

Predicting type of delivery by identification of obstetric risk factors through data mining

In Maternity Care, a quick decision has to be made about the most suitable delivery type for the current patient. Guidelines are followed by physicians to support that decision; however, those practice recommendations are limited and underused. In the last years, caesarean delivery has been pursued in over 28% of pregnancies, and other operative techniques regarding specific problems have also been excessively employed. This study identifies obstetric and pregnancy factors that can be used to predict the most appropriate delivery technique, through the induction of data mining models using real data gathered in the perinatal and maternal care unit of Centro Hospitalar of Oporto (CHP). Predicting the type of birth envisions high-quality services, increased safety and effectiveness of specific practices to help guide maternity care decisions and facilitate optimal outcomes in mother and child. In this work was possible to acquire good results, achieving sensitivity and specificity values of 90.11% and 80.05%, respectively, providing the CHP with a model capable of correctly identify caesarean sections and vaginal deliveries.

Combining analytical methodologies for the identification of Aspergillus section Flavi strains isolated from Brazilian agricultural commodities

The use of chemical analysis of microbial components, including proteins, became an important achievement in the 80’s of the last century to the microbial identification. This led a more objective microbial identification scheme, called chemotaxonomy, and the analytical tools used in the field are mainly 1D/2D gel electrophoresis, spectrophotometry, high-performance liquid chromatography, gas chromatography, and combined gas chromatography-mass spectrometry. The Edman degradation reaction was also applied to peptides sequence giving important insights to the microbial identification. The rapid development of these techniques, in association with knowledge generated by DNA sequencing and phylogeny based on rRNA gene and housekeeping genes sequences, boosted the microbial identification to an unparalleled scale. The recent results of mass spectrometry (MS), like Matrix-Assisted Laser Desorption/Ionisation Time-of-Flight (MALDI-TOF), for rapid and reliable microbial identification showed considerable promise. In addition, the technique is rapid, reliable and inexpensive in terms of labour and consumables when compared with other biological techniques. At present, MALDI-TOF MS adds an additional step for polyphasic identification which is essential when there is a paucity of characters or high DNA homologies for delimiting very close related species. The full impact of this approach is now being appreciated when more diverse species are studied in detail and successfully identified. However, even with the best polyphasic system, identification of some taxa remains time-consuming and determining what represents a species remains subjective. The possibilities opened with new and even more robust mass spectrometers combined with sound and reliable databases allow not only the microbial identification based on the proteome fingerprinting but also include de novo specific proteins sequencing as additional step. These approaches are pushing the boundaries in the microbial identification field.

Proteins on microbial identification: past achievements, present state-of-the-art, and future challenges

The use of chemical analysis of microbial components, including proteins, became an important achievement in the 80’s of the last century to the microbial identification. This led a more objective microbial identification scheme, called chemotaxonomy, and the analytical tools used in the field are mainly 1D/2D gel electrophoresis, spectrophotometry, high-performance liquid chromatography, gas chromatography, and combined gas chromatography-mass spectrometry. The Edman degradation reaction was also applied to peptides sequence giving important insights to the microbial identification. The rapid development of these techniques, in association with knowledge generated by DNA sequencing and phylogeny based on rRNA gene and housekeeping genes sequences, boosted the microbial identification to an unparalleled scale. The recent results of mass spectrometry (MS), like Matrix-Assisted Laser Desorption/Ionisation Time-of-Flight (MALDI-TOF), for rapid and reliable microbial identification showed considerable promise. In addition, the technique is rapid, reliable and inexpensive in terms of labour and consumables when compared with other biological techniques. At present, MALDI-TOF MS adds an additional step for polyphasic identification which is essential when there is a paucity of characters or high DNA homologies for delimiting very close related species. The full impact of this approach is now being appreciated when more diverse species are studied in detail and successfully identified. However, even with the best polyphasic system, identification of some taxa remains time-consuming and determining what represents a species remains subjective. The possibilities opened with new and even more robust mass spectrometers combined with sound and reliable databases allow not only the microbial identification based on the proteome fingerprinting but also include de novo specific proteins sequencing as additional step. These approaches are pushing the boundaries in the microbial identification field.

Use of a polyphasic approach including MALDI-TOF MS for identification of Aspergillus section Flavi strains isolated from food commodities in Brazil

Brazil is one the largest producers and exporters of food commodities in the world. The evaluation of fungi capable of spoilage and the production mycotoxins in these commodities is an important issue that can be of help in bioeconomic development. The present work aimed to identify fungi of the genus Aspergillus section Flavi isolated from different food commodities in Brazil. Thirty-five fungal isolates belonging to the section Flavi were identified and characterised. Different classic phenotypic and genotypic methodologies were used, as well as a novel approach based on proteomic profiles produced by matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry (MALDI-TOF MS). Type or reference strains for each taxonomic group were included in this study. Three isolates that presented discordant identification patterns were further analysed using the internal transcribed spacer (ITS) region and calmodulin gene sequences. The data obtained from the phenotypic and spectral analyses divide the isolates into three groups, corresponding to taxa closely related to Aspergillus flavus, Aspergillus parasiticus, and Aspergillus tamarii. Final polyphasic fungal identification was achieved by joining data from molecular analyses, classical morphology, and biochemical and proteomic profiles generated by MALDI-TOF MS.

Polyphasic identification of a Rhizopus species and a putative novel Gongronella which both degrade the fungicide metalaxyl

Apresentação efetuada na MicroBiotec’15

Identification and energy calibration of hadronically decaying tau leptons with the ATLAS experiment in pp collisions at s√=8 TeV

This paper describes the trigger and offline reconstruction, identification and energy calibration algorithms for hadronic decays of tau leptons employed for the data collected from pp collisions in 2012 with the ATLAS detector at the LHC center-of-mass energy s√ = 8 TeV. The performance of these algorithms is measured in most cases with Z decays to tau leptons using the full 2012 dataset, corresponding to an integrated luminosity of 20.3 fb−1. An uncertainty on the offline reconstructed tau energy scale of 2% to 4%, depending on transverse energy and pseudorapidity, is achieved using two independent methods. The offline tau identification efficiency is measured with a precision of 2.5% for hadronically decaying tau leptons with one associated track, and of 4% for the case of three associated tracks, inclusive in pseudorapidity and for a visible transverse energy greater than 20 GeV. For hadronic tau lepton decays selected by offline algorithms, the tau trigger identification efficiency is measured with a precision of 2% to 8%, depending on the transverse energy. The performance of the tau algorithms, both offline and at the trigger level, is found to be stable with respect to the number of concurrent proton--proton interactions and has supported a variety of physics results using hadronically decaying tau leptons at ATLAS.

Sistema de reposição e de gestão de inventários na rede de lojas de uma empresa de retalho de moda

Dissertação de mestrado integrado em Engenharia e Gestão Industrial

A radiofrequency identification system for the 60 GHz ISM band

Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Eletrónica Médica)

Consumption, wealth, stock and housing returns: evidence from emerging markets

We test the predictive ability of the transitory deviations of consumption from its common trend with aggregate wealth and labour income, cay, for both future equity and housing risk premia in emerging market economies. Using quarterly data for 31 markets, our country-level evidence shows that forecasting power of cay vis-à-vis stock returns is high for Brazil, China, Colombia, Israel, Korea, Latvia and Malaysia. As for housing returns, the empirical evidence suggests that financial and housing assets are perceived as complements in the case of Chile, Russia, South Africa and Thailand, and as substitutes in Argentina, Brazil, Hong Kong, Indonesia, Korea, Malaysia, Mexico and Taiwan. Using a panel econometric framework, we find that the cross-country heterogeneity observed in asset return predictability does not accrue to regional location, but can be attributed to differences in the degree of equity market development and in the level of income.