For an integrated supply chain with an online direct channel and a traditional retail channel competing with each other, solutions are be identified as to the two channels' ordering policies, product pricing strategies, and optimal product output, when product costs in the two channels are disrupted in different ways. Findings are as follows: 1) For the integrated supply chain, when unanticipated events lead to product cost increase, market size will shrink, and the system profit is harmed. In contrast, when unanticipated events lead to reduced product cost, market size will expand, and system profit increases; 2) Production strategies applicable to normal situations have certain robustness, and should be maintained when product cost disruption caused by unanticipated events is relatively small; 3) When product cost disruption caused by unanticipated events is relatively large, product sales price should be first adjusted, and aligned with the way that product cost is disrupted. Meanwhile, order quantity and product output should also be properly adjusted. That is, order quantity and output need to be reduced when product cost increases; order quantity and output need to be increased when product cost is reduced. In the end, this paper employs numerical examples to testify the findings. Research conclusions help to further enrich and extend the theoretic basis of “supply chain disruption management”, and are helpful for researchers' further study.

Considering time inconsistency and inter-temporal preference of the decision maker who is facing inter-temporal choices, this paper employs hyperbolic discounting to reflect these characteristics in governing inventory replenishment policy under inflation. The authors take the subjective perception of the decision maker and the objective indicator from the capital market into consideration. The decision maker's subjective perception includes confidence towards future value of money and anxiety to return the money, while the objective indicator is represented by the compounded discount rate. The results suggest that over the given planning horizon, with more confidence, inventory policy of larger order quantity and smaller order frequency should be adopted; with more anxiety within a threshold, inventory policy of smaller order quantity and larger order frequency should be adopted, and with more anxiety beyond this threshold, inventory policy keeps unchanged; with a larger discount rate, inventory policy of smaller order quantity and larger order frequency should be adopted.

To strengthen operational process analysis and normalize information requirements description in systemic operations based on information systems, a new operational architecture modeling method is proposed from the perspective of information flow analysis. An operational architecture modeling framework based on information flow analysis is established by referring to American department of defense architecture framework (DoDAF V2.0). Concepts of entities, relationships, attributes and mapping rules are defined. Operational activity model, operational nod model and information alternation model are constructed. Finally, aerial assault operation is taken as an example to demonstrate the modeling process. Simulation results show that operational process analysis is more refined and information requirement descriptions are more visible, normal and clear, which validate the feasibility and validity of the method and models.

This paper proposes that repatriate's knowledge transfer is composed of two dimensions: Explicit knowledge transfer and tacit knowledge transfer. The influencing of repatriate's knowledge transfer on enterprise performance is discussed, and the mediating role of ambidexterity innovation in the above relationships is analyzed. Then, relative assumptions are put forward, and theoretical model is established. Lastly, 156 multinational corporations are selected as study object, and data are collected, bias analysis, descriptive statistic analysis and hierarchical regression analysis are made. The conclusions are got, which are explicit knowledge transfer and tacit knowledge transfer have significant positive effect on exploitative innovation and exploratory innovation, respectively; and explicit knowledge transfer has more effect on exploitative innovation, while tacit knowledge transfer has more effect on exploratory innovation. The findings also indicate that exploitative innovation and exploratory innovation play partial mediation effect on the relationship between explicit knowledge transfer, tacit knowledge transfer and enterprise performance.

This paper introduces the other-regarding preferences coefficients and studies the impact of social preferences on supply chain performance in the price-setting newsvendor setting. It is assumed that the stochastic demand is multiplicative. The manufacturer and retailer play a Stackelberg game. We analyze the impact of the decision-maker's social preferences on the manufacturer's optimal wholesale price, the retailer's optimal retail price and order quantity, the supply chain member's profits and utilities, and the supply chain system's profits and utilities under three different cases that only the retailer, only the manufacturer and both are with social preferences. We show that a manufacturer, as a leader, should find a spiteful retailer, while a retailer, as a follower, should find a manufacturer with generous liability, to improve the entire supply chain. Finally, numerical examples are given to illustrate these results.

In this paper, smoothing approximation to the square-root exact penalty functions is devised for inequality constrained optimization. It is shown that an approximately optimal solution of the smoothed penalty problem is an approximately optimal solution of the original problem. An algorithm based on the new smoothed penalty functions is proposed and shown to be convergent under mild conditions. Three numerical examples show that the algorithm is efficient.

Engineering has and will continue to have a critical impact on healthcare; the application of technology-based techniques to biological problems can be defined to be technobiology-it can be considered to be the complement to biotechnology, an all too encompassing and overused term. If technobiology can be thus defined, then biotechnology can be conversely defined to be the application of biology-based techniques to technical problems; as a consequence, the two complementary terms, together, can cover the increasingly expanding and complex world where technology and biology intersect. In addition to detailing the scope of technobiology, this paper expands on the technobiology approach of service systems engineering to the development of a healthcare service system that is integrated, adaptive and evidence-based; focuses on a range of example applications in regard to the technobiology areas of information, instrumentation, and insertion; underscores, as an example, the collaborative technobiology efforts between the College of Engineering and the Miller School of Medicine at the University of Miami; and concludes with some additional insights.

This paper extends the DSSW model to accommodate rational arbitrageurs, optimistic investors and pessimistic investors. We model the price impact by using daily data and create a new methodology to calculate the optimistic and the pessimistic. The new sentiment indicator has high correlation with the other traditional ones, and as a proxy variable of individual share or financial market on daily, it could distinguish the optimistic and the pessimistic. In the empirical research, we develop a time-series model and a cross-section model respectively to explore the explanatory power of highly frequent investor sentiment to idiosyncratic volatility and capital asset mispricing. The results show that the new sentiment indicator can explain 21.31% of idiosyncratic volatility to individual share on average, and it has a great explanation of 36% to capital asset mispricing.

The lack of surrendering profits to policy holder leads to the development of this paper. For an insurer with promotion budget, both the interests of the insurance company and policy-holder are given a balance. In addition, promotion budget is introduced into the risk management process, which makes cheap reinsurance more fair. This article aims at obtaining the explicit strategy and value function for an investment-reinsurance problem under stochastic interest rates. Applying stochastic control technique, a Hamilton-Jacobi-Bellman (HJB) equation is established. The closed-form solution for the HJB equation and a verification theorem are obtained. At last, some numerical analysises illustrate the impacts of different parameters.

This article prices American-style continuous-installment options in the constant elasticity of variance (CEV) diffusion model where the volatility is a function of the stock price. We derive the semi-closed form formulas for the American continuous-installment options using Kim's integral representation method and then obtain the closed-form solutions by approximating the optimal exercise and stopping boundaries as step functions. We demonstrate the speed-accuracy of our approach for different parameters of the CEV model. Furthermore, the effects on both option price and the optimal boundaries are discussed and the causes of underestimating or overestimating the option prices are analyzed under the classical Black-Scholes-Merton model, in particular, for the case of elasticity coefficient with numerical examples.

The paper focuses on modeling longitudinal customer behavior and develops a dynamic programming (DP) to show how customer transaction database may be used to guide marketing decisions such as pricing and the design of customer reward programs. Dynamic programming is not as a tool to marketing decisions making in this research but rather as a description of consumer behavior. The results show that the method provides a means for evaluating the effectiveness of marketing strategy, for example, customer reward programs. Moreover, the findings from the model estimation indicate that reward program can actually increase the customer's purchase level and stimulate the repeat purchase behavior.

Under some circumstances, the studies on economic growth theory can be translated into the researches on production function which will beneficial for the government to analyze the pattern of economic growth and then make reasonable policies. The commonly used production functions include C-D production function, CES production function, VES production function with different elasticity of substitution. This paper will put forward to a new class of production function which elasticity of substitution σ is a non-linear function of K/L. With this new model, a calculation formula for accurately measure the influence rates of various factors to economic growth will be derived, which is significant for in-depth studies on functions and scientific measurement. The empirical analysis on the influence rates of China's economic growth factors and its good results will be presented in the end of this paper.

A novel decision-making method based on evidential reasoning is proposed for solving the two-sided matching problem with uncertain information under multiple states in this paper. Firstly, the discernment frame of evidence is constructed for two-sided matching. Secondly, the preference ordinal values given by two-sided decision-makers are transformed into rank belief degrees. On this basis, and with two-sided satisfaction as the goal, two-sided rank belief degrees are taken as pieces of evidence, and satisfaction degrees of two-sided matching are obtained through evidence fusion. Then, a decision-making model based on satisfaction degrees is constructed in order to obtain the matching solution. Finally, an illustrative example demonstrates the application of the proposed approach.

Combat modeling is an important area of military operations. System of system counterworkis an important mode of information-based war which is a mode of “network centered” instead of “platform centered” and “capability oriented” instead of “function oriented”. Under the conditions ofinformationization, the combat model must therefore address these challenges by properly representingthe networked efficient based on mutual relations among combat entities. The implementation processof combat system of systems capability is analyzed which is the result of complex interactions betweenthe entities in four domains through a sequence of action processes. The combat network model ofcombat system of systems is described which reflects the fundamental structure of combat system ofsystems. The entity with three types of functions and five types of relations in the combat network isanalyzed. The capability loop is defined and the evaluation index of combat network of combat systemof systems is proposed based on the capability loop analysis. Finally, an example is used to illustratethe methodology.

The whole process of aluminum cycle consists of four stages: Production of alumina andprimary aluminum, fabrication and manufacture of aluminum products, use of aluminum final products, and recycling of obsolete aluminum products. Aluminum cycle in China in 2011 was analyzed usingalumium flow diagram, and the following indices were obtained: The resource self-support ratio ofalumina, aluminum and the whole aluminum industry were 53.18%, 95.58% and 54.85%, respectively;self-produced and net imported aluminum scrap use ratios of the aluminum industry were 4.68% and7.98%, respectively. Aluminum cycles and aluminum flow indices in China of the year 1990, 1995, 2000, 2005 and 2008–2010 were also analyzed. It was found that from 1990 to 2011, imported Al-containingresources increased and imported bauxite has increased significantly since 2005. Resources self-supportratio of aluminum industry changed gradually from fully self-support to depencdent on the imports ofraw materials. Self-produced auminum scrap use ratio presented downtrend basically and the importedaluminum scrap use ratio was greater than self-produced aluminum scrap use ratio after 1995.

Richards model is a nonlinear curve with four parameters. Usually, the estimation of parameters in Richard model is complicated; and there is little literature on the gray prediction in Richards model is found. Facing these problems, this paper presents a algorithm consisting of the following steps: First, replacing approximately the original data with an arithmetic sequence to rapidly estimate the four parameters of Richards model; then, using them as the initial values to fit the original data by nonlinear least squares, the optimized parameters of Richards model are obtained. The algorithm along with “Kernel” and “IAGO” principles are used for the prediction of grey Richards model. The results from the experiments show that the above algorithms have good practicability and research value.

In recent years, it has been a hot pot to explore the effectiveness of basic medical insurance. However, due to different sample characteristics, time series length, models and so on used by authors, there exists big difference among relevant papers. In this paper, we try to apply meta regression analysis (MRA, a prevalent statistic literature review method) to explore its influence on family expenditure, and 90 sample observations were extracted from 49 important literatures. We find: 1) All the index construction, sample characteristic, model selection, control factors will influence the conclusions of medical insurance effectiveness; 2) The implement of basic medical insurance will increase household consumption other than the new rural cooperative systems; 3) The implement of basic health insurance-has not really reduce family's medical expense. Thus, we induce that adverse selection exists in China's medical insurance.

This paper considers the reinsurance-investment problem for an insurer with dynamic income to balance the profit of insurance company and policy-holders. The insurer's dynamic income is given by a net premium minus a dynamic reward budget item and the net premium is obtained according to the expected premium principle. Applying the stochastic control technique, a Hamilton-Jacobi-Bellman equation is established under stochastic interest rate model and the explicit solution is obtained by maximizing the insurer's power utility of terminal wealth. In addition, the comparison with corresponding results under constant interest rate helps us to understand the role and influence of stochastic interest rates more in-depth.

This paper studies the group consensus problem for second-order multi-agent dynamic systems with time-varying delays, where the agents in a network may reach one more consistent values asymptotically. The fixed network topology is in case of being directed and weakly connected. Based on algebraic graph theory and Lyapunov function approach, we propose some sufficient conditions for reaching group consensus. All the results are presented in the form of linear matrix inequalities(LMIs).A simulation example is provided to demonstrate the effectiveness of the theoretical analysis.

The constant elasticity of substitution production function describes the relationship between production results and production factors in the technological production process. The common production factors include capital and labor. In order to comprehensively reflect the input-output relationship, this paper generalizes the model and adds factors including energy, consumption, and import and export. With respect to estimating the parameters of the model, the paper proposes a high-precision and high-speed nonlinear regression method. The constant elasticity of substitution production function model is mainly used to calculate the contribution rates of economic growth factors, and this paper proposes a scientific and reliable calculating method. The final section of the paper proposes an empirical analysis of the contribution rates of Chinese economic growth factors.

A new method is proposed to solve the multiple criteria decision making with interacting criteria, where the preference information on alternatives in a fuzzy relation given by the decision maker. On the basis of the decision maker's preference information, two types of models—the least squares model, the linear programming model—are constructed to determine the capacities and then to select the most desirable alternative. Finally, a numerical example is used to illustrate the validity and practicality of the proposed method.

Economic development has contributed to the rapid expansion of China's steel industry during the past two decades, which has resulted in numerous problems including increased energy consumption and excessive environmental pollution. This study examines changes in crude steel production, steel scrap consumption, energy consumption, CO₂ emissions and steel stocks per capita from 2000 to 2014. Scenario analysis based on QGT equation is provided to accurately assess China's steel demand. Under three different scenarios, the peak of steel production and the variation trend of energy consumption, CO₂ emissions, steel stocks per capita and steel scrap are analyzed from 2010 to 2030. Based on Chinese situation, the most reasonable variation trend of China's steel production is proposed, which will increase from 626.7 Mt in 2010 to approximately 914 Mt in 2020, then gradually decrease to about 870 Mt in 2030. Steel stocks per capita will increase from 3.8 t/cap in 2010 to 8.09 t/cap in 2020 (the inferior limit of completing industrialization), then reach 11.46 t/cap in 2030 and stabilize. The peaks of energy consumption and CO₂ emissions in steel industry are expected to reach 505.37 Mtce and 1444.1 Mt in 2020, respectively. The scrap ratio is expected to reach 0.36 by 2030, when steel scrap resources will be relatively sufficient. This paper can provide corresponding theoretical basis for the government to make decision-making of macro-control.

Consider a closed-loop supply chain including a manufacturer, a retailer and two third party recyclers as the background. A coordination and optimization model is built by using the downside-risk function, Cournot model and government subsidy excitation function. The effect of risk characteristics, government subsidy and Cournot competition on supply chain is analyzed, and the impact of revenueand-expense sharing contract is studied in the channel, which shows that the contract cannot coordinate and optimize the closed-loop supply chain. Also, risk sharing contract and expense sharing contract are designed, which can offer the desired downside protection to the retailer, provide more profits to the agents, and accomplish channel coordination and optimization. Moreover, an application example is given for testing the effectiveness and feasibility of the contract, and the bound and rule of the contract parameters are given. Finally, by the analysis of numerical simulation and sensitivity of the model based on the contract, the validity and practicability of the model are verified, and the relationship between government subsidy, risk characteristics, competitive characteristics with the supply chain is obtained. This study provides decision support and decision-making reference for the development of remanufacturing industry.

The aim of this paper is to measure the effect of sensational seeking, visual merchandising and collectivism on impulsive buying behavior. Valid sample size for this study was 300 comprising of all age groups. Mall intercept method which is a kind of convenience sampling was used for collecting the data. The data was collected by preselected enumerators. Scale used for this study had established reliabilities. After ascertaining the normality of data a typical multiple steps, procedure was adopted for this study. The conceptual framework tested through Structural equation modeling and was found to be relevant in understanding the impact of predictor variables on impulsive buying behavior. A strong and positive relationship was found between sensational seeking, and no relationships were found between, collectivism and impulsive buying, and visual merchandising and impulsive buying. One of the contributions of this study is that it has explored the relationships of collectivism, and sensational seeking with impulsive buying which have not been explored that extensively.

Monte Carlo simulation is an efficient method to estimate quantile. However, it becomes a serious problem when a huge sample size is required but the memory is insufficient. In this paper, we apply the stream quantile algorithm to Monte Carlo simulation in order to estimate quantile with limited memory. A rigorous theoretical analysis on the properties of the ε_n-approximate quantile is proposed in this paper. We prove that if ε_n=o(n^-1/2), then the ε_n-approximate α-quantile computed by any deterministic stream quantile algorithm is a consistent and asymptotically normal estimator of the true quantile q_α. We suggest setting ε_n=1/(n^1/2 log₁₀n) in practice. Two deterministic stream quantile algorithms, including of GK algorithm and ZW algorithm, are employed to illustrate the performance of the ε_n-approximate quantile. The numerical example shows that the deterministic stream quantile algorithm can provide desired estimator of the true quantile with less memory.

Recent studies of correlations in Chinese stock market have mainly focused on the static correlations in financial time series, and then we pay great attention to investigate their dynamic evolution of correlations. Our paper reports on topology of 41 AH-shares companies traded on Shanghai and Hong Kong Stock Exchange in Chinese stock market. We apply the concept of minimum spanning tree (MST) and hierarchical tree (HT) to analyze and reveal the dynamic evolution of correlations between different market sectors for the period 2008-2014. From these trees, we can detect that significantly industry clustering effects are in the stock network. We measure the linkage of different companies geared to different industrial sectors. We observe the evolution of AH-shares companies in the stock network based on the moving window technique and investigate the correlations by calculating the correlation coefficient distribution, mean correlation coefficient and mean distance of these companies with time. Therefore, through our analysis, we find that companies working in the same branch of production tend to make up cluster. The results present the difference and similarity between different industry sectors in different time periods.

A novel reliability-based approach has been developed for multi-state engine systems. Firstly, the output power of the engine is discretized and modeled as a discrete-state continuoustime Markov random process. Secondly, the multi-state Markov model is established. According to the observed data, the transition intensity is determined. Thirdly, the proposed method is extended to compute the forced outage rate and the expected engine capacity deficiency based on time response. The proposed method can therefore be used for forecasting and monitoring the reliability of the multi-state engine utilizing time-domain response data. It is illustrated that the proposed method is practicable, feasible and gives reasonable prediction which conforms to the engineering practice.

Targeting at methodological limitations in the decision-making of enterprise cloud computing adoption, this paper analyzes the main influence factors affecting enterprise cloud computing, builds up their hierarchical structures, and works out 8 key influence factors affecting cloud computing models, based on the structural model theory in system engineering. A quantitative method is provided for the selection of optimal or recommended enterprise cloud computing models, in terms of the relationship valuations among key influence factors, cloud computing models, and the factor weights for a specific enterprise.

With the help of multiple UCAV cooperative task control model, the mathematical model of multiple UUV cooperative task control is made. Variables related to decision are broken into goals, guidelines and programs levels by Analytical Hierarchy Process (AHP), on this basis; the command decision of multiple UUV task assignment is achieved. The correctness of task allocation algorithm is verified by case analysis. Time calculation formulas for a task assignment are given. The changes of overall effectiveness in the process of task allocation are analyzed, the time changes of each sub task allocation time in one task assignment are analyzed, the time changes of the number of tasks and platforms respectively fixed in task allocation are also discussed.

Regional tax burden difference is related to regional sustainable development and social interests balance. Based on the calculation of the tax burden of 31 provinces and cities in 1995-2013, this paper puts forward that the over-statement of GDP is an important reason that causes the deviation of tax share and economic share. By using spatial econometric method, the results show that the economy as a whole is overvalued; investment in fixed assets, the proportion of secondary industry and state-owned economy have positive effects on regional GDP overestimated; per capita income and R&D have significantly negative effects on regional tax growth. Besides, the regional tax burden has spatial autocorrelation characteristic. This paper explains the abnormal difference of regional tax burden from a new perspective.

This paper proposes a financing system consisting of a bank under Mean-Variance criterion and a capital-constrained retailer, where the bank offers an unlimited credit to the retailer. The demand is assumed to be stochastic. The newsvendor is allowed to make an emergency order with a minimum reorder quantity threshold (RQT). It shows that under RQT, the newsvendor has different reorder strategies. The optimal primary order quantity and interest rate are derived, sequentially. Extension under perfectly competitive capital market is given. The mathematic model reveals that RQT and reorder price have significant effect on the optimal strategies.

This paper constructs the relationship between consumption and economic growth by a structure equation model and uses the provincial panel data of 29 provinces (municipalities, autonomous regions) from 1992 to 2010 in China, using maximum likelihood estimation method to analyze empirically the relationship between the consumption and economic growth in China. The result shows that the path coefficients between consumptions and economic growth are all positive, that suggests the consumption has significant positive effects on the economic growth. Also in this paper, it gives a new try to use a structural equation model to research the relationship between consumption and economic growth.

This paper considers a multi-period fuzzy portfolio selection problem maximizing the terminal wealth imposed by risk control, in which the returns of assets are characterized by fuzzy numbers. A fuzzy absolute deviation is originally de ned as the risk control of portfolio. Entropy constraints and borrowing constraints are added in the portfolio selection model. Based on the theories of possibility measures, a new multi-period portfolio optimization model with transaction costs is proposed. And then, the proposed model is transformed into a crisp nonlinear programming problem by using fuzzy programming approach. Because of the transaction costs, the multi-period portfolio selection is the dynamic optimization problem with path dependence. Through changing the cost function into a variable, the multi-period portfolio selection is approximately turned into the dynamic programming. Furthermore, the discrete approximate iteration method is designed to obtain the optimal portfolio strategy. Finally, an example is given to illustrate the behavior of the proposed model and the designed algorithm using real data from the Shanghai Stock Exchange.

Owing to the limited number of inspections during a short run process, it is impossible to get the correct estimate of the population mean and standard deviation during Phase I implementation of control chart. The t control chart proposed recently can overcome this problem. The EWMA t control chart has been proposed to monitor the process mean, but a single EWMA t control chart cannot perform well for small and large shifts simultaneously, which is known as the "inertia problem". The adaptive varying smoothing parameter EWMA (AEWMA) control chart can overcome the inertia problem. In this paper, the AEWMA t control chart for short run process is proposed. The truncated average run length and the probability of trigger a signal are adopted to test the performance of short run AEWMA t chart. Based on the investigation of the joint effect of control chart parameters on the performance of AEWMA t chart, a new optimization algorithm is proposed for statistical design of the AEWMA control chart. Simulations are performed for perfect and imperfect setup conditions, the results show that the AEWMA t control chart performs better than the EWMA t control chart.

For a class of non-affine nonlinear systems with state constraints, input constraint, uncertain parameters and unknown external disturbance, a back-stepping control scheme is proposed based on mean value theorem, nonlinear mapping and prescribed performance bounds (PPB). The non-affine system isfirst transformed into a time-varying system with a linear structure by using the mean value theorem, and the intervals of the time-varying uncertain parameters are calculated. The bounded time-varying parameters and external disturbance are estimated by adaptive algorithms with projection; the estimation error is compensated by employing nonlinear damping technology. To handle the state and input constraints, the nonlinear mapping technique (NMT), hyperbolic tangent function and Nussbaum function are employed. The prescribed performance control method improves the performance of the system. It is proved that the proposed control scheme can guarantee that all signals of the closed-loop system are bounded through the Lyapunov analysis. Simulation results are presented to demonstrate the effectiveness of the proposed control scheme.

Cox's proportional hazard models with time-varying coefficients have much flexibility for modeling the dynamic of covariate effects. Although many variable selection procedures have been developed for Coxs proportional hazard model, the study of such models with time-varying coefficients appears to be limited. The variable selection methods involving nonconvex penalty function, such as the minimax concave penalty (MCP), introduces numerical challenge, but they still have attractive theoretical properties and were indicated that they are worth to be alternatives of other competitive methods. We propose a group MCP method that uses B-spline basis to expand coefficients and maximizes the log partial likelihood with nonconvex penalties on regression coefficients in groups. A fast, iterative group shooting algorithm is carried out for model selection and estimation. Under some appropriate conditions, the simulated example shows that our method performs competitively with the group lasso method. By comparison, the group MCP method and group lasso select the same amount of important covariates, but group MCP method tends to outperform the group lasso method in selection of unimportant covariates.

The rise of Big Data brings the financial innovation opportunities as well as challenges. This paper reviews different fields of big-data-based financial innovations as well as the scientific discoveries and theoretical breakthroughs of risk analysis with respect to these financial innovations. Based on the current research status, several key problems are put forward and their relative solutions are discussed. The three mean aspects are listed as the pricing and risk measuring for data-driven financial innovation products or services; the changes that data-driven financial innovation would bring to finance industry, which involve operation, resources allocation and ecosystem; and questions and solutions of systemic risk management based on Big Data analytics. Finally, predictions towards the hotspots frontier and developing trends for further data-driven financial innovation are proposed.

This paper chooses the monthly real growth rate of industrial added values, which have been released by the China National Bureau of Statistics, as the benchmark indicator. By using the large quantity of collected data, the actual value of indicators is obtained through deflating them by price index. Based on this result, 26 indicators from various areas of the economy are regarded as China's macro economic prosperity indicators via methods such as K-L approach, time difference correlation analysis as well as grading system, which correspond well with the fluctuation of benchmark indicator. Furthermore, this paper analyzes and forecasts the economic growth rate cycle of China by composite index and early warning signal system.

Investors prefer to invest the stocks with high history returns, which results in that the return of the stock with high history maximum return is often lower than that with low history maximum return, i.e., the MAX effect. We show that the MAX effect is also significant in China stock market, that is, there is a significant negative relationship between maximum return and expected return. We then conduct portfolio analysis and Fama-Macbeth cross-sectional regression and find that range of price and turnover rate can explain the MAX effect in a certain extent, idiosyncratic volatility and idiosyncratic skewness cannot explain the negative relationship between maximum return and expected return. Moreover, maximum return explains the idiosyncratic volatility puzzle partially.

The problem of pollution arises along with the rapid development of economic, and it spread from a regional problem to a nationwide one. It has caught the eyes of Chinese government and people that how to develop Chinese economy without harming environment. In this paper, to obtain a win-win solution between economy and environment, optimal results of unit emission penalty mechanism under different industrial GDP growth rates and the growth rates of industrial technical input is given, which applies multi-objective optimization methods based on an economic-ecological model. The results provide factories a way to maximize the benefits, as well as a scientific basis for government to determine the punishment standard and the technical input growth rate.