多重上市股价异常效应的影响因素——来自中国A、B股证券市场的证据

实证检验了多重上市的股价异常效应及其影响因素。结果表明,多重上市的股价异常效应并非市场过度反应的结果,而与A、B股的市场分割、发行价格与原股票价格的差异、上市前后流动性的变化紧密联系。另外,A股市场多重上市的股价异常效应主要表现在招股公告前,B股市场多重上市的股价异常效应则主要表现在招股公告后。从股东构成、时间因素、散户投资者的损失厌恶心理方面探讨了以上不对称反应模式的原因。     

市场分割下的股价微观行为及其行为金融学解释

以交易量、股价波动率和收益率的自相关性作为流动性、波动性和价格有效性等微观行为指标,实证分析了中国A股和B股市场在微观行为上的差异.结果发现,三个指标在两个市场之间存在显著差异.在B股向境内居民开放前,A股的三个指标都要显著大于B股.而B股开放之后,B股的这些指标都大于开放之前.最后运用行为金融理论中投资者结构对微观行为的影响进行了分析和解释.     

Deep carbon export from a Southern Ocean iron-fertilized diatom bloom

Fertilization of the ocean by adding iron compounds has induced diatom-dominated phytoplankton blooms accompanied by considerable carbon dioxide drawdown in the ocean surface layer. However, because the fate of bloom biomass could not be adequately resolved in these experiments, the timescales of carbon sequestration from the atmosphere are uncertain. Here we report the results of a five-week experiment carried out in the closed core of a vertically coherent, mesoscale eddy of the Antarctic Circumpolar Current, during which we tracked sinking particles from the surface to the deep-sea floor. A large diatom bloom peaked in the fourth week after fertilization. This was followed by mass mortality of several diatom species that formed rapidly sinking, mucilaginous aggregates of entangled cells and chains. Taken together, multiple lines of evidence-although each with important uncertainties-lead us to conclude that at least half the bloom biomass sank far below a depth of 1,000 metres and that a substantial portion is likely to have reached the sea floor. Thus, iron-fertilized diatom blooms may sequester carbon for timescales of centuries in ocean bottom water and for longer in the sediments.     

Amplitude spectroscopy of a solid-state artificial atom

The energy-level structure of a quantum system, which has a fundamental role in its behaviour, can be observed as discrete lines and features in absorption and emission spectra. Conventionally, spectra are measured using frequency spectroscopy, whereby the frequency of a harmonic electromagnetic driving field is tuned into resonance with a particular separation between energy levels. Although this technique has been successfully employed in a variety of physical systems, including natural and artificial atoms and molecules, its application is not universally straightforward and becomes extremely challenging for frequencies in the range of tens to hundreds of gigahertz. Here we introduce a complementary approach, amplitude spectroscopy, whereby a harmonic driving field sweeps an artificial atom through the avoided crossings between energy levels at a fixed frequency. Spectroscopic information is obtained from the amplitude dependence of the system's response, thereby overcoming many of the limitations of a broadband-frequency-based approach. The resulting 'spectroscopy diamonds', the regions in parameter space where transitions between specific pairs of levels can occur, exhibit interference patterns and population inversion that serve to distinguish the atom's spectrum. Amplitude spectroscopy provides a means of manipulating and characterizing systems over an extremely broad bandwidth, using only a single driving frequency that may be orders of magnitude smaller than the energy scales being probed.     

Engineering evolution to study speciation in yeasts

The Saccharomyces 'sensu stricto' yeasts are a group of species that will mate with one another, but interspecific pairings produce sterile hybrids. A retrospective analysis of their genomes revealed that translocations between the chromosomes of these species do not correlate with the group's sequence-based phylogeny (that is, translocations do not drive the process of speciation). However, that analysis was unable to infer what contribution such rearrangements make to reproductive isolation between these organisms. Here, we report experiments that take an interventionist, rather than a retrospective approach to studying speciation, by reconfiguring the Saccharomyces cerevisiae genome so that it is collinear with that of Saccharomyces mikatae. We demonstrate that this imposed genomic collinearity allows the generation of interspecific hybrids that produce a large proportion of spores that are viable, but extensively aneuploid. We obtained similar results in crosses between wild-type S. cerevisiae and the naturally collinear species Saccharomyces paradoxus, but not with non-collinear crosses. This controlled comparison of the effect of chromosomal translocation on species barriers suggests a mechanism for the generation of redundancy in the S. cerevisiae genome.     

Crystal structure of opsin in its G-protein-interacting conformation

Opsin, the ligand-free form of the G-protein-coupled receptor rhodopsin, at low pH adopts a conformationally distinct, active G-protein-binding state known as Ops*. A synthetic peptide derived from the main binding site of the heterotrimeric G protein-the carboxy terminus of the alpha-subunit (GalphaCT)-stabilizes Ops*. Here we present the 3.2 A crystal structure of the bovine Ops*-GalphaCT peptide complex. GalphaCT binds to a site in opsin that is opened by an outward tilt of transmembrane helix (TM) 6, a pairing of TM5 and TM6, and a restructured TM7-helix 8 kink. Contacts along the inner surface of TM5 and TM6 induce an alpha-helical conformation in GalphaCT with a C-terminal reverse turn. Main-chain carbonyl groups in the reverse turn constitute the centre of a hydrogen-bonded network, which links the two receptor regions containing the conserved E(D)RY and NPxxY(x)(5,6)F motifs. On the basis of the Ops*-GalphaCT structure and known conformational changes in Galpha, we discuss signal transfer from the receptor to the G protein nucleotide-binding site.     

Comparative assessment of large-scale data sets of protein-protein interactions

Comprehensive protein protein interaction maps promise to reveal many aspects of the complex regulatory network underlying cellular function. Recently, large-scale approaches have predicted many new protein interactions in yeast. To measure their accuracy and potential as well as to identify biases, strengths and weaknesses, we compare the methods with each other and with a reference set of previously reported protein interactions.