Speculative Trading and Stock Prices: Evidence from Chinese A-B Share Premia

The market dynamics of technology stocks in the late nineties has stimulated a growing body of theories that analyze the joint effects of short-sales constraints and heterogeneous beliefs on stock prices and trading volume. This paper examines implications of these theories using a unique data sample from China, a market with stringent short-sales constraints and perfectly segmented dual-class shares. The identical rights of the dual-class shares allow us to control for stock fundamentals. We find that trading caused by investors' speculative motive can help explain a significant fraction of the price difference between the dual-class shares.

Speculative Trading and Stock Prices: Evidence from Chinese A-B Share Premia

The market dynamics of technology stocks in the late 1990s have stimulated a growing body of theory that analyzes the joint effects of short-sales constraints and heterogeneous beliefs on stock prices and trading volume. This paper examines several implications of these theories using a unique data sample from a market with stringent short-sales constraints and perfectly segmented dual-class shares. The identical rights of the dual-class shares allow us to control for stock fundamentals. We find that trading caused by investors¡¯ speculative motives can help explain a significant fraction of the price difference between the dual-class shares.Speculative bubble, Trading volume

MicroRNA-124 enhances response to radiotherapy in human epidermal growth factor receptor 2-positive breast cancer cells by targeting signal transducer and activator of transcription 3

Aim To determine whether microRNA (miR)-124 enhances the response to radiotherapy in human epidermal growth factor receptor 2 (HER2)-positive breast cancer cells by targeting signal transducer and activator of transcription 3 (Stat3). Methods miR-29b expression was measured in 80 pairs of breast tumor samples and adjacent normal tissues collected between January 2013 and July 2014. Activity changes of 50 canonical signaling pathways upon miR-124 overexpression were determined using Cignal Signal Transduction Reporter Array. Target gene of miR-124 was determined using Targetscan and validated by Western blotting and dual-luciferase assay. Cell death rate was assessed by propidium iodide (PI)/Annexin V staining followed by flow cytometry analysis. Stat3 and miR-124 expression was further measured in 10 relapsed (non-responder) and 10 recurrence- free HER2-positive breast cancer patients. Results MiR-124 expression was down-regulated in HER2 positive breast cancers compared with normal tissues, and was negatively associated with tumor size. MiR-124 overexpression in HER2 positive breast cancer cell line SKBR3 significantly reduced the activity of Stat3 signaling pathway compared with control transfection (P < 0.001). Bioinformatic prediction and function assay suggested that miR-124 directly targeted Stat3, which is a key regulator of HER2 expression. MiR-124 overexpression down-regulated Stat3 and potently enhanced cell death upon irradiation. Consistently, chemical inhibitor of Stat3 also sensitized HER2-positive breast cancer cells to irradiation. Moreover, increased Stat3 expression and reduced miR-124 expression were associated with a poor response to radiotherapy in HER2-positive breast cancers. Conclusions Weak miR-124 expression might enhance Stat3 expression and radiotherapy resistance in HER2-positive breast cancer cells

Noise-injected neural networks show promise for use on small-sample expression data

BACKGROUND: Overfitting the data is a salient issue for classifier design in small-sample settings. This is why selecting a classifier from a constrained family of classifiers, ones that do not possess the potential to too finely partition the feature space, is typically preferable. But overfitting is not merely a consequence of the classifier family; it is highly dependent on the classification rule used to design a classifier from the sample data. Thus, it is possible to consider families that are rather complex but for which there are classification rules that perform well for small samples. Such classification rules can be advantageous because they facilitate satisfactory classification when the class-conditional distributions are not easily separated and the sample is not large. Here we consider neural networks, from the perspectives of classical design based solely on the sample data and from noise-injection-based design. RESULTS: This paper provides an extensive simulation-based comparative study of noise-injected neural-network design. It considers a number of different feature-label models across various small sample sizes using varying amounts of noise injection. Besides comparing noise-injected neural-network design to classical neural-network design, the paper compares it to a number of other classification rules. Our particular interest is with the use of microarray data for expression-based classification for diagnosis and prognosis. To that end, we consider noise-injected neural-network design as it relates to a study of survivability of breast cancer patients. CONCLUSION: The conclusion is that in many instances noise-injected neural network design is superior to the other tested methods, and in almost all cases it does not perform substantially worse than the best of the other methods. Since the amount of noise injected is consequential, the effect of differing amounts of injected noise must be considered

A Rapid, Non-invasive Method for Anatomical Observations of Tadpole Vertebrae in Vivo

The tadpole is a critical stage in the amphibian life cycle and plays an important role during the transition from the aquatic to the terrestrial stage. However, there is a large gap in tadpole research, which represents a vital component of our understanding of the diversity and complexity of the life history traits of amphibians, especially their developmental biology. Some aspects of this gap are due to limited research approaches. To date, X-ray microcomputed tomography (micro-CT) has been widely used to conduct osteology research in adult amphibians and reptiles, but little is known about whether this tool can be applied in tadpole studies. Thus, we compared the results of two methods (the bone-cartilage double-staining technique and micro-CT) to study vertebrae in tadpole specimens. The results revealed no significant difference between the two methods in determining the number of vertebrae, and micro-CT represents a rapid, non-invasive, reliable method of studying tadpole vertebrae. When scanning tadpoles, voltage is the most critical of the scanning parameters (voltage, current and scan time), and moderate scanning parameters are recommended. In addition, micro-CT performed better using specimens stored in 70% ethanol than those preserved in 10% formalin. Finally, we suggest that micro-CT should be more widely applied in herpetological research to increase specimen utilization

Multifunctional photonic integrated circuit for diverse microwave signal generation, transmission and processing

Microwave photonics (MWP) studies the interaction between microwave and optical waves for the generation, transmission and processing of microwave signals (i.e., three key domains), taking advantages of broad bandwidth and low loss offered by modern photonics. Integrated MWP using photonic integrated circuits (PICs) can reach a compact, reliable and green implementation. Most PICs, however, are recently developed to perform one or more functions restricted inside a single domain. In this paper, as highly desired, a multifunctional PIC is proposed to cover the three key domains. The PIC is fabricated on InP platform by monolithically integrating four laser diodes and two modulators. Using the multifunctional PIC, seven fundamental functions across microwave signal generation, transmission and processing are demonstrated experimentally. Outdoor field trials for electromagnetic environment surveillance along an in-service high-speed railway are also performed. The success to such a PIC marks a key step forward for practical and massive MWP implementations.Comment: 17 page

Speculative Trading and Stock Prices: An Analysis of Chinese A-B Share Premia

China’s stock markets, with stringent short-sales constraints, dominance of inexperienced individual investors, a small asset float and heavy share turnover (500% per year despite a high transaction cost), provide a unique opportunity to study non-fundamental components in stock prices. In particular, several dozen Chinese firms offered two classes of shares: class A, which could only be held by domestic investors, and class B, which could only be traded by foreigners. Despite their identical rights, A-share prices were on average 420% higher than the corresponding B shares. By exploring several different model specifications, we find that the turnover rate of A shares is able to explain a large portion of the cross-sectional variation in A-B share premium. Our further analysis of the relationship between asset float and share turnover shows that trading in A-share markets is more likely to be driven by speculation than by liquidity factors. Our results are robust after controlling for the effects of liquidity, discount rates, and differential risk and demand curves by local and foreign investors