Constructing a Multifactor Model for the Shanghai Stock Exchange

ABSTRACT

We examine the validity of five factor models for explaining the time-series and cross-sectional variations in stock returns in the Shanghai Stock Exchange. The factor models include four models proposed by previous literature. Moreover, we propose a four-factor model (comprising market, size, book-to-market, and sales-to-price factors) to explain variations of stock returns in the Shanghai Stock Exchange. The results show that the Shanghai stock market exhibits size, book-to-market, and sales-to-price effects. Both the adjusted coefficient of determination and regression model intercepts indicate that the proposed four-factor model explains variations of stock returns in the Shanghai Stock Exchange more effectively in comparison with other multifactor models.     

Using AHP to evaluate the criteria of auto spare parts industry

Analytic hierarchy process method is applied by surveying auto spare parts suppliers in Taiwan to identify the importance of 7 major criteria and 30 sub-criteria. Quality is the most essential criterion whereas production is the least important criterion identified in this study. Unlike the traditional viewpoints that local auto spare parts makers tend to emphasize on production, quality, service, technological capability, and price are relatively more important. In addition, four of five sub-criteria under the criterion of quality play an important role for the local suppliers to gain competitive advantages. By identifying the most essential criteria and sub-criteria, the performance based on those criteria and sub-criteria should be closely monitored and relentlessly improved under such competitive business environment.     

A fuzzy group decision-making approach in quality function deployment

Quality function deployment (QFD) is comprised of two major group decision-making processes. One is to collect the customer requirements from a group of customers, whereas the other is to determine the relationship between customer requirements and technical measures by a cross-functional team. Generally, different and/or even subjective opinions are quite often in a group decision-making process due to the limitations of experience and impreciseness. Obviously, the importance of each customer requirement and the relationship between customer requirements and technical measures are determined by a group of people with imprecision and vagueness. Under such circumstances, a fuzzy group decision-making approach can be applied in QFD to deal with a group decision-making process when the information is imprecise and fuzzy. Moreover, an example is provided as well as the computational steps to show this fuzzy group decision-making approach can be effectively used in QFD to make decisions with imprecision and vagueness.     

Telehealth services evaluation: a combination of SERVQUAL model and importance-performance analysis

Telehealth services provide a means of monitoring a patient’s vital signs through the use of equipment or mobile devices and have the potential to extend clinical outreach to more patients regardless of geographical locations. However, patient acceptance is essentially important for the success of telehealth implementations. Thus, it is of interest to evaluate patients’ attitudes and perceptions toward the use of telehealth services. This study combines service quality model and importance-performance analysis to evaluate telehealth services provided by a case hospital. The results show that six items belong to major weaknesses, which should be addressed immediately in order to reduce patients’ complaints. In contrast to major weaknesses, there are seven items classified as major strengths, which should be maintained to provide telehealth service excellence in order to establish better and longer relationships with patients in the long-term perspectives.     

Finding behavior patterns and evaluating orderliness of dynamical systems by spanning tree invariants

Identifying the behavior patterns is the main goal for a dynamical system. It provides the useful information in behavior prediction of a dynamical system. On the other hand, measuring the orderliness of a dynamical system improves the prediction of behavior patterns. In this study, substitution sequences are used to model the long-term correlation of a dynamical system and evaluate the degree of randomness, where the degree of homogeneity is evaluated by the spanning tree invariant. The results show that the more contiguous patterns the sequence has, the smaller the value of the spanning tree invariant is. In fact, the spanning tree invariant can be an effective tool to measure the orderliness of sequences by comparing the computed value with the value of one.     

Forced financial information restatements and management turnover: Market discipline and large family shareholders’ intervention in an emerging economy

Using data from Taiwan, this paper investigates the market discipline effects associated with the forced financial information restatement on management turnover, and how family governance intervenes with such market discipline. By integrating legitimacy theory, the institution-based view, and multiple agency perspective, we find that market discipline associated with the forced financial information restatement can be effective to trigger management turnover in an emerging economy. Family ownership strengthens such market discipline by promoting ex-ante management turnover but weakens such market discipline by deterring immediate/ex-post management turnover. On the other hand, family board control weakens market discipline in mitigating families-minority shareholders conflicts by deterring all ex-ante, immediate, and ex-post management turnover. The analysis contributes to our understanding of a firm’s legitimacy as the dominating force in supporting an effective market discipline on management turnover in a weak institutional environment. Families play multiple governance roles to intervene with such market discipline in a weak institutional environment in order to build a management team for their investment safety and maintain a management team for family private benefits of control.     

Applying importance-performance analysis to compare the changes of a convenient store

This study applies importance-performance analysis to examine how the services provided by the convenient store (Hi-Life) located in Asia University have been changed when a competitor of a 7–11 convenient store opens nearby the university. In this case study, the performance for each item in the survey was measured by the average value, while the importance was evaluated by the variance-based methods. With the use of importance- performance analysis, a comparison of provided services at Hi-Life can be evaluated by two four-quadrant matrices to see how the services have been changed when the 7–11 becomes the competitor nearby the university.     

The Empirical Relationship Between Earnings Information and Stock Returns

Abstract:

The objective of this study was to examine, using a vector autoregressive model, whether the difference in earnings growth rates caused different reaction speeds in stock prices. Monthly returns of stocks listed in the Taiwan stock market from May 2003 to April 2013 were used as empirical data in this study. The analytical results showed that the returns of portfolios with higher earnings growth rates significantly led those portfolios with lower earnings growth rates when size, trading volume, institutional ownership ratio, and revenue factors were controlled, respectively. This paper finds that the earnings growth rate is a significant determinant of the lead-lag patterns observed in monthly stock returns.     

Applying repertory grids technique for knowledge elicitation in quality function deployment

The repertory grids technique is applied in quality function deployment to elicit the voice of the customers and to derive the importance for each customer requirement from a group of customers. In addition, the repertory grids technique can be used in the relationship matrix to quantify the numerical relationships between customer requirements and technical measures from a group of team members. An integration of the repertory grids technique and quality function deployment would make quality function deployment systematically to gather customer needs for better product or service planning and to determine the relationships between customer requirements and technical measures since the final analyses rely heavily on the results of this relationship matrix. A case illustration is provided to show the usefulness of applying the repertory grids technique in quality function deployment.     

Using <Emphasis Type="Italic">K</Emphasis>-means method and spectral clustering technique in an outfitter’s value analysis

This study applies K-means method and spectral clustering technique in the customer data analysis of an outfitter in Taipei City, Taiwan. The data set contains transaction records of 551 customers from April 2004 to March 2006. The differences between the two clustering techniques mentioned here are significant. K-means method is more capable of dealing with linear separable input, while spectral clustering technique might have the advantage in non-linear separable input. Thus, it would be of interest to know which clustering technique performs better in a real-world case of evaluating customer value when the type of input space is unknown. By using cluster quality assessment, this study found that spectral clustering technique performs better than K-means method. To summarize the analysis, this study also suggests marketing strategies for each cluster based on the results generated by spectral clustering technique.