Market reactions for targets of M&A rumours—evidence from China

This paper investigates investors’ reactions to takeover rumours in China’s stock markets from 2004 to 2014. While we find prerumour price run-ups (abnormal returns) for merger and acquisition (M&A) targets, the pre-rumour market overreaction is significantly positive only for target firms that are state-owned enterprises (SOEs). There are no significant abnormal returns for M&A rumour targets over a 41-day event window (20, þ20). Nonetheless, capital market reactions to true rumours are higher than reactions to false rumours, indicating that investors can typically distinguish between them. Finally, we document that while firms with higher institutional ownership have a higher probability of being the subject of false M&A rumours, rumoured targets with higher institutional ownership experience lower market reactions

Evolutionary Multiobjective Optimization Driven by Generative Adversarial Networks (GANs)

Recently, increasing works have proposed to drive evolutionary algorithms using machine learning models. Usually, the performance of such model based evolutionary algorithms is highly dependent on the training qualities of the adopted models. Since it usually requires a certain amount of data (i.e. the candidate solutions generated by the algorithms) for model training, the performance deteriorates rapidly with the increase of the problem scales, due to the curse of dimensionality. To address this issue, we propose a multi-objective evolutionary algorithm driven by the generative adversarial networks (GANs). At each generation of the proposed algorithm, the parent solutions are first classified into real and fake samples to train the GANs; then the offspring solutions are sampled by the trained GANs. Thanks to the powerful generative ability of the GANs, our proposed algorithm is capable of generating promising offspring solutions in high-dimensional decision space with limited training data. The proposed algorithm is tested on 10 benchmark problems with up to 200 decision variables. Experimental results on these test problems demonstrate the effectiveness of the proposed algorithm

Unusual stability of a one-parameter family of dissipative solitons due to spectral filtering and nonlinearity saturation

International audienceThe stability of a one-parameter family of dissipative solitons seen in the cubic-quintic complex Ginzburg-Landau equation is studied. It is found that an unusually strong stability occurs for solitons controlled by the spectral filtering and nonlinearity saturation simultaneously, consistently with the linear stability analysis and confirmed by large-perturbation numerical simulations. Two universal types of bifurcations in the spectrum structure are demonstrated

Debt capacity, debt choice, and underinvestment problem: Evidence from China

This study investigates how short-term debt and debt capacity help firms to make efficient financing decisions and reduce underinvestment problem. The sample includes Chinese nonfinancial firms listed on the Shanghai and Shenzhen Stock Exchanges over the period 2007 to 2017. The findings indicate that short-term debt is positively related to leverage. The results also indicate that growth positively influences leverage. The results further show that short-term debt enhances the positive impact of growth on leverage. These findings reveal that short-term debt makes firms financially flexible, and allows them to obtain more cost-effective debt by repricing and renegotiation of debt contracts in the presence of valuable growth opportunities. Furthermore, the results illustrate that debt capacity is positively associated with leverage, suggesting that debt capacity helps firms to have an easy access to the credit market and reduce liquidity risk. Overall, the findings remain consistent across different types of firms (state-owned [S.O.E.] and non-state-owned enterprises [N.S.O.E.]) and by considering alternative proxy of growth

Evaluation of the Princeton Ocean Model Using South China Sea Monsoon Experiment (SCSMEX) Data

The Princeton Ocean Model (POM) has been implemented in the South China Sea for hindcast of circulation and thermohaline structure. A two-step technique is used to initialize POM with temperature, salinity, and velocity for 1 April 1998 and integrate it from 1 April 1998 with synoptic surface forcing for 3 months with and without data assimilation. Hydrographic and current data acquired from the South China Sea Monsoon Experiment (SCSMEX) from April through June 1998 are used to verify, and to assimilate into, POM. The mean SCSMEX data (Apr–Jun 1998) are about 0.58°C warmer than the mean climatological data above the 50-m depth, and slightly cooler than the mean climatological data below the 50-m depth, and are fresher than the climatological data at all depths and with the maximum bias (0.2–0.25 ppt) at 75-m depth. POM without data assimilation has the capability to predict the circulation pattern and the temperature field reasonably well, but has no capability to predict the salinity field. The model errors have Gaussian-type distri bution for temperature hindcast, and non-Gaussian distribution for salinity hindcast with six to eight times more frequencies of occurrence on the negative side than on the positive side. Data assimilation enhances the model capability for ocean hindcast, if even only conductivity–temperature–depth (CTD) data are assimilated. When the model is reinitialized using the assimilated data at the end of a month (30 Apr; 31 May 1998) and the model is run for a month without data assimilation (hindcast capability test), the model errors for both temperature and salinity hindcast are greatly reduced, and they have Gaussian-type distributions for both temperature and salinity hindcast. Hence, POM gains capability in salinity hindcast when CTD data are assimilated.Office of Naval ResearchNaval Oceanographic OfficeNaval Postgraduate Schoo

Biomolecular network querying: a promising approach in systems biology

The rapid accumulation of various network-related data from multiple species and conditions (e.g. disease versus normal) provides unprecedented opportunities to study the function and evolution of biological systems. Comparison of biomolecular networks between species or conditions is a promising approach to understanding the essential mechanisms used by living organisms. Computationally, the basic goal of this network comparison or 'querying' is to uncover identical or similar subnetworks by mapping the queried network (e.g. a pathway or functional module) to another network or network database. Such comparative analysis may reveal biologically or clinically important pathways or regulatory networks. In particular, we argue that user-friendly tools for network querying will greatly enhance our ability to study the fundamental properties of biomolecular networks at a system-wide level

Resonant radiation emitted by solitary waves via cascading in quadratic media

We present a systematic investigation of the resonant radiation emitted by localized soliton-like wave-packets supported by second-harmonic generation in the cascading regime. We emphasize a general mechanism which allows for the resonant radiation to grow without the need for higher-order dispersion, primarily driven by the second-harmonic component, while radiation is also shed around the fundamental-frequency component through parametric down-conversion processes. The ubiquity of such a mechanism is revealed with reference to different localized waves such as bright solitons (both fundamental and second-order), Akhmediev breathers, and dark solitons. A simple phase matching condition is put forward to account for the frequencies radiated around such solitons, which agrees well with numerical simulations performed against changes of material parameters (say, phase mismatch, dispersion ratio). The results provide explicit understanding of the mechanism of soliton radiation in quadratic nonlinear media