While quantitative investment management has been extensively investigated and many models built in order to provide investment suggestions through quantitative analysis, the combination of quantitative and qualitative analysis is relatively unexplored. The objective of this study is to construct a quantitative stock selection model based on the standard model built by Hsu et al. (2011) which could improve the stability of descriptor and factor structures and the combinability of quantitative and qualitative analysis. The research focuses on the structure of effective factors and descriptors when faced with different types of market trends. Furthermore, we test the performance of a Market Trend-Based Alpha Model (MTB alpha model) and compare with the standard alpha model. The strategy of portfolio construction is a TAIEX enhanced index fund. We find the enhanced index portfolio constructed by the MTB model produces an information ratio of 0.72, which is much higher than the standard model ratio of 0.41. This finding suggests that a MTB model could not only improve performance but also make the descriptor and factor structures more stable and much more easily for managers¡¦ adjusting.

Three-Dimensional (3D) integration of circuits based on die and wafer stacking using through-silicon-via is a critical technology in enabling "more-than-Moore", i.e. functional integration of devices beyond pure scaling ("more Moore"). In particular, the scaling from multi-core to many-core architecture is an excellent candidate for such integration. 3D systems design follows is a challenging and a complex design process involving integration of heterogeneous technologies. It is also expensive to prototype because the 3D industrial ecosystem is not yet complete and ready for low-cost mass production. Networks-on-Chip (NoCs) efficiently facilitates the communication of massively integrated cores on 3D many-core architecture. In this thesis scalability and performance issues of NoCs are explored in terms of architecture, organization and functionality of many-core systems. First, we evaluate on-chip network performance in massively integrated many-core architecture when network size grows. We propose link and channel models to analyze the network traffic and hence the performance. We develop a NoC simulation framework to evaluate the performance of a deflection routing network as the architecture scales up to 1000 cores. We propose and perform comparative analysis of 3D processor-memory model configurations in scalable many-core architectures. Second, we investigate how the deflection routing NoCs can be designed to maximize the benefit of the fast TSVs through clock pumping techniques. We propose multi-rate models for inter-layer communication. We quantify the performance benefit through cycle-accurate simulations for various configurations of 3D architectures. Finally, the complexity of massively integrated many-core architecture by itself brings a multitude of design challenges such as high-cost of prototyping, increasing complexity of the technology, irregularity of the communication network, and lack of reliable simulation models. We formulate a zero-load average distance model that accurately predicts the performance of deflection routing networks in the absence of data flow by capturing the average distance of a packet with spatial and temporal probability distributions of traffic. The thesis research goals are to explore the design space of vertical integration for many-core applications, and to provide solutions to 3D technology challenges through architectural innovations. We believe the research findings presented in the thesis work contribute in addressing few of the many challenges to the field of combined research in many-core architectural design and 3D integration technology. / <p>QC 20151221</p>

This study constructs a quantitative stock selection model across multiple sectors with the application of the Bayesian method. It employees factors from the Taiwan stock market which could explain stock returns. Under this structure, each sector that has different significant factors is allowed to be imported into sub models. The factors are calculated into alpha scores and used to do stock selection. Therefore, the demonstration of both intra and inter-sector alpha scores into sector-specific integration alpha scores is an important concept in this study. Furthermore, an enhanced index fund is built based on the model and related to the benchmark to illustrate the power of this model. Once the contents of a portfolio are decided, this model could provide stock selection criterion based on the predictive power of stock return. Finally, the results demonstrate that this model is practical and flexible for local stock portfolio analysis.

<p> Variational calculations for hypernuclei and their corresponding nuclear cores have been performed with phenornenological effective Ʌ -N and N-N interactions. Effects of deformation and Majorana exchange on the Ʌ binding energies have been studied. The influence of density dependence in both the Ʌ-N and N-N force has been investigated . The three-body ɅNN interaction has also been considered qualitatively. All these effects help to reduce the Ʌ binding energies in hypernuclei. </p> <p> In addition to the variational calculations, the rigid alpha model has been used to determine the Ʌ binding energy in (5 Ʌ - He). A comparison of the methods is given. </p> Finally, excited states of some hypernuclei have been calculated using the variational ground state equilibrium size. </p> / Thesis / Doctor of Philosophy (PhD)