ARIMA Modeling With Intervention to Forecast and Analyze Chinese Stock Prices

In this study, we demonstrate the usefulness of ARIMA‐Intervention time series analysis as both an analytical and forecast tool. The data base for this study is from the PACAP‐CCER China Database developed by the Pacific‐Basin Capital Markets (PACAP) Research Center at the University of Rhode Island (USA) and the SINOFIN Information Service Inc, affiliated with the China Center for Economic Research (CCER) of Peking University (China). These data are recent and not fully explored in any published study. The forecasting analysis indicates the usefulness of the developed model in explaining the rapid decline in the values of the price index of Shanghai A shares during the world economic debacle stating in China in 2008. Explanation of the fit of the model is described using the latest development in statistical validation methods. We note that the use of a simpler technique although parsimonious will not explain the variation properly in predicting daily Chinese stock prices. Furthermore, we infer that the daily stock price index contains an autoregressive component; hence, one can predict stock return

An investigation of the intention to share files over P2P Networks

In this research we take a comprehensive view of file-sharing over peer-to-peer (P2P) networks in order to develop a model of the intention to share files. P2P file-sharing once consisted largely of music files which, when downloaded, were an infringement of copyrights. For this reason models of file-sharing intentions often included factors and constructs representing ethical concerns. However, these models did not produce a broad agreement about whether or not those ethical concerns had significant effects on intentions. Furthermore, files now shared over P2P networks represent a significant portion of both legitimate and non-infringing files. The model we propose applies to P2P file-sharing of all files, regardless of media type, and regardless of whether they are shared legally or illegally. Lastly we present the factors from the model that were suggested to be significant from an initial pilot study

Evaluating the Role of Income in National Software Piracy

Our study investigates the proper role of income in predicting national software piracy rates. We run regressions isolating various measures of income, including GDP per capita and median household income and variations thereof, to predict national software piracy rates. Then we also run multivariate regressions incorporating GDP and other non-income predictors such as corruption in a manner consistent with previous studies. This topic is of importance due to the multi-billion dollar losses incurred globally each year due to pirating. Our results show that a square root version of median household income is the best measure of national income and consistent with what economic theory predicts.

Using Business Intelligence for Operational Decision-Making in Call Centers

This paper proposes an operational business intelligence system to help achieve operational excellence in insurance call centers. We apply a decision tree based solution to collected data using a sliding window approach. Our solution provides two distinct advantages to call center managers. First, the decision trees allow managers to recognize key factors and the role they play in determining service levels. Second, our sliding window approach allows managers to see the effects on service levels of resource reallocation. Collected data from a large U.S. insurance company is analyzed. Initial results provide good insight into factors affecting this firm’s call center service levels

Association Between Asian Equity Markets and Western Markets: Evidence from the Indexes of Equity Markets

This research examined the time series characteristics of stock price indices for Hong Kong, Tokyo, New York (NYSE) and London (FTSE) equity markets or stock exchanges during the period of 1991 to 2012. Specifically, we calculate the rate of return and the volatility of return for all the markets and estimate the serial correlation and co-movement of the four markets. We find that the average rate of return varies dramatically for the four equity markets and across time. Further, we find that stock prices are positively serially correlated in general. In the multivariate regressions, we find that there is little evidence to show that either the rate of return in certain markets universally affects the rate of return in other equity markets. It suggests that the four markets are co-integrated but not universally across time and with each other in pairwise dimensions. Lastly, we studied and made conclusions concerning the mean and variation in the volatility of the rates of return in the four equity markets studied

Contemporary Usage of CASE Tools in U. S. Colleges and Universities

CASE tools have been incorporated into Information Systems curriculums for years. Curriculum guidelines in both disciplines call for the use of CASE tools. This paper describes the findings of a study of U.S. college and university information technology programs to determine in which classes CASE was taught, the extent to which the tools were being used, the degree of coverage of tools\u27 functional aspects, and reasons why some academics were not using CASE. The results, which confirm continued CASE usage in academia in accordance with the guidelines, present implications for both the quality of the tools as perceived by academics, as well as their continued use. We note that, at present, there is no academic consensus on choice of a CASE tool, and that the drawing features of CASE tools seem to be used more heavily than other more complex and powerful capabilities. Based on the survey results we conclude that schools should reevaluate their teaching curricula and model curriculum guidelines to justify the importance of teaching and using CASE tools

Operational Business Intelligence: Applying Decision Trees to Call Centers

In this paper we propose a decision tree based approach to modeling service levels in insurance call center operations. Our approach allows call center managers to determine which factors they control have the greatest impact on service levels (ex. handle time, average hold time, etc.). We also propose a sliding window to allow managers to interpret the effects changes in resource allocations have on service levels. To test our solution we analyze data collected from a large U.S. insurance company. The initial results provide good insight into factors affecting service levels

Evidence on the seasonality of stock market prices of firms traded on organized markets

Studies of capital market efficiency are important because they infer that there are predictable properties of the time series of prices of traded securities on organized markets. The weak form of the efficient markets hypothesis is put in dispute by the results of this study. Furthermore, this study of individual securities prices of US traded securities corroborates previous findings of studies of stock market indexes both in the USA and for foreign stock exchanges that seasonality is present in the times of securities prices. © 2005 Taylor & Francis Group Ltd