Volume 5, Issue 1

This paper examines the relationship between stock market (KSE-100), money market (M2 and 180 days T-bill rate), and foreign exchange market (ER: PKR/USD) in Pakistan by using monthly data covering the period from 2000:M1 to 2015:M12. The study investigates long-run equilibrium relationship between these three financial markets by employing Johansen and Juselius[1] cointegration tests. Long-run and short-run causality relationship between stock market and other macroeconomic variables is also established by employing vector error correction model (VECM) and pairwise granger causality tests. The results of multivariate cointegration test (trace test) indicate a one cointegrating vector, and the significant normalized cointegrating coefficients are evident of long run equilibrium relationship between all the selected variables. Negative and significant ECT (− 1) for all variables during full sample period witness the presence of long-run causality connection among variables, while during the military regime and democratic regime, significant difference of long-run causal connections are identified across the regimes. Moreover, the results of granger causality test also indicate that there are significant variations in the causality relationship among variables across the regimes. Therefore, it is essential for forecasting, planning and policy making to consider the importance of political governance system while analyzing the historical cointegration among financial market and make the necessary adjustments accordingly.

This paper studies the optimal consumption-investment strategy with Heston’s stochastic volatility (SV) model under hyperbolic absolute risk aversion (HARA) utility criterion. The financial market is composed of a risk-less asset and a risky asset, whose price process is supposed to be driven by Heston’s SV model. The risky preference of the individual is assumed to satisfy HARA utility, which recovers power utility, exponential utility and logarithm utility as special cases. HARA utility is of general framework in the utility theory and is seldom studied in the existing literatures. Legendre transform-dual technique along with stochastic dynamic programming principle is presented to deal with our problem and the closed-form solution to the optimal consumption-investment strategy is successfully obtained. Finally, some special cases are derived in detail.

After the reform and opening, the economic relationship between China and the world is strengthened heavily. Theoretically, international factors have impact on the domestic general price level through a set of channels. This paper employed a sample including monthly data of five representative indicators, to explore the influence of international factors on Chinese price level. The empirical results showed that there is an obvious lag for Chinese CPI reacting to international shocks, while the PPI reacts immediately. The impact of international factors on Chinese CPI and PPI usually lasts 12 months at least and they always exhibit a different transmission mechanism for international shocks. Besides, a further study revealed that some structure-breakpoints in the influence mechanism of international factors exist, and great changes of the impact direction and significance for different factors have taken place in the subsample periods.

It’s well-known that change-point problem is an important part of model statistical analysis. Most of the existing methods are not robust to criteria of the evaluation of change-point problem. In this article, we consider “mean-shift” problem in change-point studies. A quantile test of single quantile is proposed based on saddlepoint approximation method. In order to utilize the information at different quantile of the sequence, we further construct a “composite quantile test” to calculate the probability of every location of the sequence to be a change-point. The location of change-point can be pinpointed rather than estimated within a interval. The proposed tests make no assumptions about the functional forms of the sequence distribution and work sensitively on both large and small size samples, the case of change-point in the tails, and multiple change-points situation. The good performances of the tests are confirmed by simulations and real data analysis. The saddlepoint approximation based distribution of the test statistic that is developed in the paper is of independent interest and appealing. This finding may be of independent interest to the readers in this research area.

This paper proposed the optimized three-stage strategy of orderly management of file stream in network printing workflow. In first stage the customer preflight was added to the conventional prepress preflight, which set quick-type, general-type, stable-type and comprehensive-type preflight scheme for customers by investigating the possibility of occurrence of errors of various preflight entries and customer relevancy. Based on four types of preflight schemes, four customer preflight applications were created by using Pitstop Pro and Connector You. Customers can select one of the appropriate applications for quick preflight before delivering to reduce the probability of returning the files back for correction when errors occur in preflight. Second stage is printing enterprise prepress preflight, which proposed the concept of the prepress preflight tolerance. In addition, according to the different requirements of printing technology and quality, this paper established the prepress preflight scheme based on the printing enterprises’ tolerance for preflight error. Third stage is to manage the optimized sorting of prepress file stream. To achieve it, the SPT rule and the 0-1 programming model were adopted, time spend of preflight, printing process and post-press finishing was also taken into account. Moreover, Enfocus Switch software was applied to establish automated network printing workflow and complete the file stream sorting. Finally, the result of simulation analysis of the optimized strategy shows that the optimized three-stage strategy can effectively shorten the file processing time.

The establishment of the China Pilot Free Trade Zone (FTZ) has significantly promoted international trade, financial development, and economic growth. Building international financial centers (IFCs) satisfies the demand for FTZs to facilitate financial development, as well as promoting economic growth. Thus, successfully predicting the next IFC in China under the FTZ framework is an important issue. In this study, we applied grey relational analysis combined with entropy method to predict potential IFCs among seven FTZ cities. According to the results, our interesting findings include: 1) the “total stock turnover”, “total value of imports and exports”, and “Foreign Direct Investment (FDI)” are key indicators for determining future IFCs; 2) among seven cities, Shenzhen and Tianjin are highly likely to become the next IFCs, while Shanghai is already an IFC.