Alternative estimation method of earnings growth rate for PEGR strategy

The ambiguous return pattern for the PEGR (the ratio of the stock’s price/earnings to its estimated earnings growth rate) strategy has been documented in literature for the US stock markets. As stock prices and earnings per share (EPS) are objective data, earnings growth rate, however, is estimated by analyst whose method partial explains the PEGR vague return pattern. The purpose of this study is not to deny or substitute analysts’ estimation, but rather, to provide a simple and popular method, log-linear regression model, to forecast the earnings growth rate (G), and examine whether the typical PEGR effect, such as PER (price/earnings ratio) or PBR (price/book ratio) effect, exists by using our alternative estimation method. Our evidence indeed shows that returns on the lowest PEGR portfolio not only dominate over all higher PEGR portfolios, but also beat the market with stochastic dominance (SD) analysis, which is consistent with our prediction. Our results, at least, imply that using the log-linear regression model to construct the PEGR-sorted portfolios can benefit investors and the model is also a good choice for analysts in their forecasting.     

Alternative approaches for the reformulation of economics

Journal of Economic Interaction and Coordination -     

Alternative procedures for macrosociological theorizing

Forty years ago sociology possessed a plethora of broad theories, some untestable and others merely untested. Merton rightly argued that global theorizing could be premature if the middle-range groundwork were not properly accomplished. At the present time sociology possesses a plethora of middle-range theories, and is close to paralyzing fragmentation. This paper argues that the time has come for a return to classical concerns as a complement (not an alternative) to continuing middle-range theorizing. Three strategies for macrosociological theorizing are presented: the divisive, aggregative, and direct. The divisive strategy is largely nonexistent, and Merton argued strongly against the direct, leaving the aggregative as his method of choice. We argue here that the concept of middle-range theory is vague, and it is exceedingly difficult to distinguish middle-range from non-middle-range theories. Out of 27 cells in our table, only 14 are identifiable as middle-range, and 9 are indeterminable. We argue that the aggregative strategy is probably not feasible at this time, but that all three strategies should be used, with an emphasis on the direct.     

Alternative efficiency measures for multiple-output production

This paper has two main purposes. Firstly, we develop various ways of defining efficiency in the case of multiple-output production. Our framework extends a previous model by allowing for nonseparability of inputs and outputs. We also specifically consider the case where some of the outputs are undesirable, such as pollutants. We investigate how these efficiency definitions relate to one another and to other approaches proposed in the literature. Secondly, we examine the behavior of these definitions in two examples of practically relevant size and complexity. One of these involves banking and the other agricultural data. Our main findings can be summarized as follows. For a given efficiency definition, efficiency rankings are found to be informative, despite the considerable uncertainty in the inference on efficiencies. It is, however, important for the researcher to select an efficiency concept appropriate to the particular issue under study, since different efficiency definitions can lead to quite different conclusions.     

Alternative methods for waste paper disposal

The purpose of this paper is to develop an analytic model which can be applied to the disposal of various components of municipal waste. Utilizing data from the City of Philadelphia, this paper examines the generators of used newsprint; the interactions between incineration, landfill, and the beneficial extraction of the caloric content of paper for steam generation: and the feasibility of recycling. The social cost issue is considered in light of present City disposal practices Finally, an attempt is made to derive optimal collection and disposal policies for FY 1976 as functions of various model parameters. The paper concludes that the construction of a steam generation plant is a viable alternative to present disposal practices for a range of processing costs.     

Alternative policy options for combatting a downturn

• ? With limited scope for conventional monetary policy options, central banks and governments may need to turn to alternative approaches to combat slowing global growth and respond to economic shocks.
• ? Our analysis shows that not only do governments in advanced economies have limited room to cut rates but that doing so has proved less effective in boosting growth in recent years. This increases the need to look at alternatives, such as negative interest rates, renewed QE and fiscal stimulus.
• ? While negative interest rates have helped reduce borrowing costs in some economies, the impact on banks has been ambiguous. Also, lowering rates further into negative territory could be hard without incurring significant costs.
• ? QE in the form practised up to now is also likely to be less effective than in the past due to low yields, narrow risk spreads and high asset valuations. So, a deeper downturn might require more radical QE ‐ buying corporate bonds, bank loans and equities ‐ which comes with significant drawbacks.
• ? Some central bankers are starting to acknowledge the limits of monetary action, with the next step being to consider fiscal action as a more effective alternative ‐ as argued recently by the likes of Larry Summers.
• ? In our view, fiscal policy is likely to be especially effective in a climate of weak growth and low rates, with large multiplier effects. Advanced economies have more scope for fiscal stimulus than often recognised and could finance a large public investment programme by issuing ultra‐cheap long‐dated debt

     

应对中美贸易不平衡的政策选择

近年来,中美贸易不平衡问题,引起人们的关注。据中方统计,美国对华贸易逆差始于1993年,为62.7亿美元;到2004年为802.7亿美元。而据美方统计,其对华逆差始于1983年,为3亿美元;2004年为1272.6亿美元。(见表1)在2000年时,中国就取代日本成为美最大的逆差国。     

适应之后的变通——顶好公司的适应之道：传统公司在早期的探索

美国的顶好公司（Foremost）是世界著名的乳制品加工和销售企业。公司的目标是：成为食品行业跨国经营的大公司，并向消费者提供富于营养的乳制品。为此，公司很早就向海外发展。     

Shake-and-bake algorithms for the identification of nonredundant linear inequalities*

Two probabilistic shake-and-bake algorithms are presented to detect nonredundant constraints in a full dimensional system of linear inequalities. The algorithms proceed by generating a random sequence of points on the boundary of a polyhedron, and by searching for a nonredundant constraint in the direction of a random vector from each point in the sequence. The limiting distribution of the sequence of points generated by the algorithms is proven to be uniform on the boundary of the polyhedron.     

Adaptive algorithms for maximizing overall stock return

Deciding which stocks to purchase and how to optimally allocate the total investment among them is a nontrivial task for every investor. In this article, we propose two adaptive techniques that would provide an optimal allocation maximizing the return over the investment period. The first approach is the adaptive power method (PM) which is a modification of the proper orthogonal decomposition method. The adaptive PM uses only the currently available information to compute the optimal allocations, yet its long-term solution approaches the dominant eigen solution, even though that solution would require having a priori knowledge of all stocks’ performance. The second approach is derived from the well-known Least Mean Square (LMS) method, where the optimal allocation can be computed by adaptively steering the overall return toward a desired value. The experimental results have indicated promising gains even when the general market trend is downward.     

德邦物流物流的“另类”

德邦创新地推出“卡车航班”业务,用公路货运的价格完成航空快运的业务,这让德邦完成了脱胎换骨的变化     

Alternative conceptual frameworks for the analysis of mobility tables and the log-linear models

This article contrasts two alternative conceptual frameworks for the analysis of mobility tables: the “structure vs. circulation” framework that in the past inspired the construction of “pure” mobility indices, and the “absolute vs. relative mobility” one, more recently proposed by Goldthorpe. Contrary to the beliefs of the past, the former cannot conveniently be expressed by the parameters of the saturated log-linear model. The latter, on the contrary, permits (via the language of odds and odds ratios) the coherent application of log-linear models. Moreover, it does not incur those theoretical difficulties which even the most sophisticated attempts to save the old framework incur (e.g. Sobel et al., 1985). In the third section of the article a contribution to the understanding of the analysis of mobility tables through odds ratios is given and the relation between odds ratios and the interaction parameters of the saturated model is shown.     

Machine learning algorithms for the creation of clinical healthcare enterprise systems

Clinical recommender systems are increasingly becoming popular for improving modern healthcare systems. Enterprise systems are persuasively used for creating effective nurse care plans to provide nurse training, clinical recommendations and clinical quality control. A novel design of a reliable clinical recommender system based on multiple classifier system (MCS) is implemented. A hybrid machine learning (ML) ensemble based on random subspace method and random forest is presented. The performance accuracy and robustness of proposed enterprise architecture are quantitatively estimated to be above 99% and 97%, respectively (above 95% confidence interval). The study then extends to experimental analysis of the clinical recommender system with respect to the noisy data environment. The ranking of items in nurse care plan is demonstrated using machine learning algorithms (MLAs) to overcome the drawback of the traditional association rule method. The promising experimental results are compared against the sate-of-the-art approaches to highlight the advancement in recommendation technology. The proposed recommender system is experimentally validated using five benchmark clinical data to reinforce the research findings.     

电气设备状态维修策略研究

电器设备维修策略逐渐从以时间周期为基础的定期维修制度向以设备状态为基础的状态维修制度过渡,并取得了一定的成效。本文将实施状态维修的关键技术概括为状态监测技术、状态预测技术及状态评估技术并分别阐述了它们的操作过程和意义。     

Creativity strategy selection for the higher education system

As one of the major developing locations that are playing a critical role in determining the national competitive advantage to accomplish the Taiwanese national goal of becoming a Republic of Creativity (ROC) and a kingdom of innovation, Taipei County has started to become a highlighted issue by both researchers and practitioners. Because a higher education system is at the core of generating innovation in a nation, how to prompt the creativity of higher education system in Taipei County has been one of the top concerns for the Taipei County government. Therefore, the aim of this study is to select critical creativity strategies that were developed by the Taipei County government for the higher education system to implement creativity improvement and enhancement. Based on the results, the most effective creativity strategy is Creative Intelligence. The higher education system in Taipei County is encouraged to improve and enhance creativity in accordance with the results so as to enhance the Taiwanese innovation level and fulfill the Taiwanese national goal of efficiency.     

Benchmarking regression algorithms for loss given default modeling

The introduction of the Basel II Accord has had a huge impact on financial institutions, allowing them to build credit risk models for three key risk parameters: PD (probability of default), LGD (loss given default) and EAD (exposure at default). Until recently, credit risk research has focused largely on the estimation and validation of the PD parameter, and much less on LGD modeling. In this first large-scale LGD benchmarking study, various regression techniques for modeling and predicting LGD are investigated. These include one-stage models, such as those built by ordinary least squares regression, beta regression, robust regression, ridge regression, regression splines, neural networks, support vector machines and regression trees, as well as two-stage models which combine multiple techniques. A total of 24 techniques are compared using six real-life loss datasets from major international banks. It is found that much of the variance in LGD remains unexplained, as the average prediction performance of the models in terms of R² ranges from 4% to 43%. Nonetheless, there is a clear trend that non-linear techniques, and in particular support vector machines and neural networks, perform significantly better than more traditional linear techniques. Also, two-stage models built by a combination of linear and non-linear techniques are shown to have a similarly good predictive power, with the added advantage of having a comprehensible linear model component.