This research examines the impact of local and international market factors on the pricing of stock indexes futures in East Asian countries. The purpose of this paper is to present a study of the significant factors that determine the major stock indexes futures’ prices of Hong Kong, Malaysia, Singapore, South Korea and Taiwan. This study first investigates the relationships between Hang Seng Index Futures, KLCI Futures, SiMSCI Futures, KOSPI Futures, Taiwan Exchange Index Futures and local interest rates, dividend yields, local exchange rates, overnight S&P500 index and a newly constructed index, Asian Tigers Malaysia Index (ATMI). 11 years historical data of stock indexes futures and the economic statistics are studied; 10 years in-sample data are used for testing and developing the pricing models, and 1 year out-of-sample data is used for the purpose of verifying the predicted values of the stock indexes futures. Using simple linear regressions, local interest rates, dividend yields, exchange rates, overnight S&P500 and ATMI are found to have significant impact on these futures contracts. In this research, the next period close is predicted using simple linear regression and non-linear artificial neural network (ANN). An examination of the prediction results using nonlinear autoregressive ANN with exogenous inputs (NARX) shows significant abnormal returns above the passive threshold buy and hold market returns and also above the profits of simple linear regression (SLR). The empirical evidence of this research suggests that economic statistics contain information which can be extracted using a hybrid SLR and NARX trading model to predict futures prices with some degree of confidence for a year forward. This justifies further research and development of pricing models using fundamentally significant economic determinants to predict futures prices.
In emerging markets, technology ventures increasingly rely on new product development (NPD) teams to generate creative ideas and to mold these innovative ideas into streams of new products or services. However, little is known about how behavioral integration (a behavioral team process) and collective efficacy (a motivational team process) jointly facilitate or inhibit team innovation performance in emerging markets—especially in China, the world's largest emerging‐market setting with collectivist and high power distance cultures. Drawing on social cognitive theory and behavioral integration research, this article elucidates the relationships between behavioral integration dimensions (i.e., collaborative behavior, information exchange, and joint decision‐making) and innovation performance and also examines how collective efficacy moderates these relationships in China's NPD teams. Results from a sample of 96 NPD teams in China's technology ventures reveal that information exchange is positively associated with innovation performance. Collaborative behavior positively but marginally influences innovation performance, whereas joint decision‐making does not relate to innovation performance. Moreover, collective efficacy demonstrates an important moderating role. Specifically, both collaborative behavior and joint decision‐making are more positively associated with innovation performance when collective efficacy is higher. In contrast, information exchange is less positively associated with innovation performance when collective efficacy is higher. This study makes important theoretical contributions to the literature on team innovation and behavioral integration in emerging markets by offering a better understanding of how behavioral and motivational team processes jointly shape innovation performance in China's NPD teams. This study also extends social cognitive theory by identifying collective efficacy as a boundary condition for the overall effectiveness of behavioral integration dimensions. In particular, this study highlights the condition under which behavioral integration dimensions facilitate or inhibit NPD team innovation performance in China. 相似文献
This study investigates the moderating effects of a firm's network embeddedness and a partner's transactional specific investments (TSIs) on relationships between the firm's TSIs and its partner's strong- and weak-form opportunism, and compares the efficiency among these moderator variables. The regression results suggest that (1) a firm's TSIs are positively related to partner's opportunism when network embeddedness and the partner's TSIs are relatively low; but (2) a firm's TSIs are negatively related to partner's opportunism when network embeddedness and the partner's TSIs are relatively high. Furthermore (3) network embeddedness is more effective in inhibiting partner's weak-form opportunism than in inhibiting strong-form opportunism resulting from the firm's TSIs. Finally (4) with regard to the relationship between TSIs and weak-form opportunism, the negative moderating effect of network embeddedness is greater than the negative moderating effect of partner's TSIs. This study explains reasons why conflicting views exist about the relationship between TSIs and partner's opportunism, reveals the differences in the moderating effects of network embeddedness and partner's TSIs, and makes new contributions to both transaction cost theory and embeddedness literature. It also provides, for firms involved in TSIs in a buyer–supplier relationship, insightful managerial suggestions about ways to reduce their partner's varying forms of opportunism. 相似文献