Does the supply of shares affect stock price? It is an important problem not only for investors but also for the financial regulators. Stock supply could affect stock price only when there was a downward-sloping demand curves theoretically. Therefore, an empirical test on the elasticity of stock demand curves is necessary. Based on the institutional bidding data in detail during period of IPO book building, our research shows that demand curve is downward-sloping both on primary market and secondary market, which means that supply of shares will have an effect on the stock price. Therefore, the supply and demand of shares should be taken into account when financial regulators making policies and investors making investment decisions.
The credit spread of commercial bank is the difference of yield to maturity between the bank bond and treasury bond. It reflects the credit risk of bank accepted by the investors in the bond market, and is an important reference for bank bonds investment. The term structure premium of T-1 years is measured by the difference of yields with T year maturity and 1 year maturity on the yield curve of bank bonds. The yield to maturity of 1 year of bank bond is measured by the yield to maturity of T years minus the term structure premium of T-1 years. The calculation models of credit spread and default probabilities of commercial banks are established based on term structure premium of yield to maturity. The innovation and characteristics of the paper are as follows. Firstly, the yield to maturity of 1 year of a specific bank bond ry,1 is calculated by the theoretical yield to maturity of T years of a specific bank bond ry,T minus the term structure premium of T-1 years on the yield curve of bank bonds with the same credit rate rp,T-1, solving the problem that the theoretical formula can only calculate the yield to maturity of whole period of T years and unable to calculate the yield to maturity of 1 year, thus unable to determine the credit spread of bank bond. Secondly, the real credit spreads of commercial banks are calculated by comparing the yields to maturity between bank bonds and treasury bonds, which reflects the credit risk of banks accepted by the capital market, and provides foundation for issue pricing and investment decision making of bank bonds. Thirdly, the real credit spread is measured by comparing the yields to maturity of bank bond and treasury bond on the same date, solving the problem that the yields of bank bonds issued on different dates are not comparable. Fourthly, the empirical results are consistent with the credit rating orders of the banks in our country by the Moody's company, which verifies the rationality of the models in the paper. The empirical study shows that the default probabilities of the four biggest state owned banks are the lowest, the default probabilities of the regional city banks are comparative higher, and the default probabilities of other listed banks are mediate.
In this paper we employ a three-regime-switching model, to capture the nonlinear characteristics of the Chinese stock market bubble dynamics, and to test the explanatory power of heterogeneous beliefs for the regime-switching. We find that the bubbles in SHSE can be distinguished into dormant, explosive and collapsing three regimes, and the abnormal trade volume and the excessive return have the significant explanatory power of the regime switching.
In this paper the triangular intuitionistic fuzzy numbers are used to express the change factors of the underlying assets of the option in order to describe the uncertainty of the estimated value of the European option price and the hesitation degree of the investors, the intuitionistic fuzzy binomial tree pricing model is made, and the risk neutral pricing method is used to research the single period European call option pricing problem. The findings of the study are that the European option price expressed by a triangular intuitionistic fuzzy number, which can reflect the certainty degree, negation degree and hesitation degree of the investor on the estimated value of the option price, and then the interval value of European option price is obtained by using the cuts sets operation of the triangular intuitionistic fuzzy numbers. Some numerical examples show that European call option price obtained by the triangular intuitionistic fuzzy number can express more the hesitation degree of the investors than the one obtained by the fuzzy number.
We estimated the efficiencies of the eight cotton-growing provinces (autonomous region) by using data envelopment model (DEA) and employing the data from 1978-2007. And we calculated the subsidy quota on cotton under the conditions of efficiency-priority, fairness priority and giving attention to both in 2007 by using multiple objective optimization method. Moreover, we promoted the model on the considerations of non-reliance on imports, national grain stable safe supply, reasonable income for farmers and subsidy balance among provinces (autonomous region) by improved greedy method. We therefore come to the conclusion that our national actual distribution of cotton-growing subsidy is slanted toward fairness while lacking efficiency. The policy need to intensify the subsidy on main cotton-growing area as Xinjiang and the subsidy on Yangtze River basin cotton-growing area, thereby significantly extending the acreage of cotton-growing area.
Steel industry is the pillar industry of China. There exist three types of markets in domestic which are different from other foreign markets: bulk stock electronic market, futures market and spot market. China's steel electronic market is a unique steel market. Its price discovery has been of concern to theorists and industry. Study on price discovery in domestic and abroad steel markets is of great use to the formation of steel pricing power, as well as the smoothy development of domestic steel markets. This paper uses two classical methods which belongs to common factor measurement model to measure the price discovery of three domestic steel markets and two foreign steel futures markets. The results show that: steel electronic market is the leading market in domestic steel markets. The price discovery of steel electronic market is more powerful than SHFE, LME and NCDEX; and abroad steel futures price is still not an effective steel price by now.
This paper numerically analyzed the effectiveness of monetary and fiscal policies, and their associated risks, on growth rate, product volatility, inflation rate, exchange rate, monetary demand and monetary substitution under capital mobility, domestic interest rate, product volatility, foreign interest rate and foreign pricing volatility respectively by using an extended equilibrium in a stochastic dynamic optimal model with capital flows. The research results show that the effective of the monetary policy and fiscal policy change with capital flows, domestic interest rate, foreign interest rate and foreign pricing volatility. Monetary and fiscal policies have significant effects on growth rate, product volatility, inflation rate and exchange rate for lower interest rate, but have no effects on growth rate and product volatility for higher interest rate. The impacts of capital flows on the effects of monetary and fiscal policy in a country with lower product volatility are the same as those in a country with higher product volatility.
This paper extends cross section spatial error components (SEC) models to panel data, we derivate joint tests, marginal tests and conditional tests, and using Monte Carlo simulation experiments, we prove that, when random effect (RE) exists, conditional tests are more effective, while RE does not exists, marginal tests are more effective; the choice of spatial weight matrix is related with whether RE exists, but non-standard weight matrix is more suitable; what's more, greater N or T will make tests more effective. At the same time, we find that when the real data garnering process is panel data SEC model, traditional spatial tests as Moran I, LM-Error and LM-Lag have poor performance.
Adopting a life-cycle perspective, this paper focuses on time compression in construction projects, and builds an agent-based model on revenue-sharing negotiation. We design three experimental scenarios: only owner has fairness preference, only contractor has fairness preference, both owner and contractor have fairness preferences. Our aim is to find how agents' fairness preferences impact feasible region of agreements, results of successful negotiations and efficiency in negotiations. Results are as follows: raising agents' fairness preferences will compress the feasible region. When agents raise their fairness preferences properly, it will lead to a significant compression in construction time. However, when agents pay attention to fairness preferences excessively, it will lead to substantial cost growth and it is not conducive to growth of profit. Agents' different fairness preferences will take different effects on their profits. Appropriate fairness preferences of agents can improve the success rate of negotiations and shorten the negotiation periods.
This paper analyzed how one generator uses the demand information to increase its long term profit and compared how different information structures affect different equilibrium solutions. The problem was formulated as a duopolistic market consisting of firm 1 and firm 2. Firm 2 adjusts its current strategy based on the previous marginal profit and the current demand information, and firm 1 optimizes its behavior after knowing firm 2's strategy information. The results show that, compared with the old information structure where firm 2 only uses the marginal profit of the previous stage, firm 2 will increase profits but firm 1 will decrease profits under the new information structure; the profits under the static Cournot game and the one-step dynamic game will still be higher than the profits of firm 2 but less than the profits of firm 1 under the new information structure. Meanwhile, some other important characteristics were analyzed for the equilibrium solutions under different information structures, and the problems were pointed out which should pay attention to in numerical simulation.
One of the core issues of mergers & acquisitions (M&A) of Chinese automobile industry is how to promote sustainable innovation capability effectively. This paper combines system dynamics with the strategic map, builds system dynamics model, and simulates and analyzes main variable. It shows that reasonable post-merger integration model can enhance sustainable innovation capability, perfect mechanism of cooperative efforts of industry and university and research institute is the key to raise the level of cooperative efforts, share of self-owned brands and sustainable innovation capability can promote each other, and market concentration can not directly enhance sustainable innovation capability. Only the mutual coordination and integration of the main factors can enhance the sustainable innovation capability effectively.
For the adverse selection caused by the concealment of raw materials' green degree in supply chain's purchasing phase, taking the initial stage of green market development as research background, the design of incentive mechanism by the manufacture was studied. The validities of two second-best contracts, the lump-sum transfer contract and the linear shared-saving contract, were discussed respectively. The prerequisites for the implementation of two linear shared-saving contracts, the fixed contract and the flexible contract, were proposed. The influences of certain correlative factors on members' profits were analyzed. By improving the flexible contract, the non-linear coordination contract was given based on the Nash bargaining model. The results indicate that, the linear shared-saving contracts are effective to the type screening and the high-validity motivation, and the non-linear coordination contract achieves the Pareto-improvement of members' profits as well as the optimization of overall profit. The conclusion is instructive to the operation of green supply chain.
The fact that local governments rely heavily on land finance has fostered the emergence of "land lease price champion" in many cities across the country through land auctions and land auctions are most likely to cause excessive land auction premium. This paper focuses on residential and commercial land lease transactions in Beijing for a period from 2003 to 2010 and studies the driving forces of the observed land auction premium using hedonic pricing methodology. Results show that land use purpose, floor-to-site ratio, location, the type of land bidder and distance to city center significantly impact the land auction premium. Comparing with private real estate companies, state-owned real estate firms exert more impact on land auction premium. Another finding is that part of the stimulus package released in 2009 to cope with the economic crisis has been directed to land market through state-owned real estate firms that pushes up the land prices.
This paper has improved the basic method to measure the domestic technological contents of export products. By using data in the input-output table and the export trade data on the SITC REV.2 level, it counts the whole technological contents, the domestic technological contents and the index of the domestic technological contents of export products in several years of East Asian economic bodies like China, Japan, Korea and Indonesia. The result shows that China's export products' domestic technological content is going through an upward trend since middle 90s, 20th century. Also, the short term impact of China's entrance into WTO on China's export products' domestic technological contents is greater than long term impact. Though Japan ranks the top in East Asian on domestic technological contents, its downward trend is obvious in recent years. The Korea's export products' domestic technological contents raises greatly and convergence to Japan. Indonesia failed in improving its export products' domestic technological contents. Finally, in combination of the evolution trend of export products' domestic technological contents in China and other three East Asian countries, the article proposed some relevant policy recommendations under the background of further opening up and involving in regional economic integration in East Asia.
Aiming at the problem that the traditional wholesale price contract cannot coordinate the supply chain, the paper studies the effects that inequity aversion has on coordination of supply chain by wholesale price contract with uncertain demand. Based on inequity aversion retailer assumption, a mathematical model is formulated which takes into considerations advantageous inequity aversion and disadvantageous inequity aversion. The results show that the wholesale price contract can improve the profit of the whole chain and better coordinate the supply chain in advantageous inequity aversion case, which enrich the theory of the wholesale price contract and facilitate its application in real life. In the last part of this paper, a numerical example is used to prove the findings.
In order to improve the accuracy of customer churn prediction at individual level, an E-commerce customer churn prediction model combined with individual activity called H-ULSSVM was established. Firstly, it used heuristic algorithm which integrated into geographic factors to calculate the optimal threshold and obtain the degree of individual activity, identify the correctly identified customers and incorrectly identified customers. On this basis, considering a large number of impact factors exist in E-commerce customer churn prediction, a rough equivalence class reduction method was proposed to extract important index. The correctly identified customers were sent to learn and train in unbalanced least squares support vector machine, and then used the classifier to judge the status of the incorrectly identified customers. The empirical study on B2C E-commerce platform shows that this model has better efficiency and accuracy than others.
To investigate the effects of competition strategies and decision rationality on airlines' price competition, the airlines' dynamic price competition model based on different competition strategies and heterogeneous players is established by using the theory of bifurcation of dynamical systems, and the existence and stability of equilibrium points of this model are discussed. The complex dynamics of this model in different market parameters are shown though numerical simulation. The simulation results show that in order to investigate the stability of economic systems with realistic significance, it needs a new judgment theorem which combined traditional theorem with individual rationality. And the competition strategies of airlines have an obvious impact on the complexity of price competition and competition performance. Finally, the chaos state of airlines' dynamic price competition model is controlled by the delayed feedback control method.
This paper addressed a multi-supplier multi-affected area multi-relief and multi-vehicle emergency vehicles location, path selection and relief allocation problem. Considering the inherent trade-off between disaster forecast accuracy and logistics cost efficiency, a multi-objective stochastic programming model was proposed. The features were: the demand and availability of relief-allocation path were stochastic, and there were coverage limits for relief suppliers to cover affected areas. The multi-objective programming model was transformed into a single-objective programming model by the use of a weighted Bayes risk; and the proposed model was transformed into an optimal stopping problem by designing a decision rule. The model was solved by using Xpress. Numerical results indicate the velocity and accuracy of the model and software, and demonstrate the superiority of two-stage stochastic programming and disaster scenario information updates respectively.
This paper studies the mode choice problem considering the peak travel chain in a day. The transportation system comprises a subway parallel to a bottleneck-constrained highway between a residential area and a working place. Commuters can get their destinations by either auto or transit only; besides these two modes, they can drive to the bottleneck, park there and then take subway to the destination. Based on the bottleneck theory, a hierarchical Logit model is used to describe commuters' mode choice behaviors, and then mode choice equilibrium equations under elastic demand are constructed. Furthermore, optimal fare and parking fee strategies under four mechanisms are discussed. It is shown that when transit and park-and-ride place are operated by government and the working area parking lot belongs to a private enterprise, lower fares and higher parking fees in working area can effectively encourage parking interchanging, increase public transit trip contribution rate and maximize the system's total net benefit. Numerical results also support the current differentiation parking charge policy in Beijing.
The online routing problem of two vehicles to an emergency scene is considered. In grid transportation network, some of the edges may be suddenly blocked and the blockage will not be observed until reaching an endpoint of the blocked edge. The goal is to minimize the arrival time of the first vehicle with at most k blockages. An online strategy named Row-first and Line-first is presented and the competitive ratio is analyzed, and the ratio is proved to be tight. The optimization of the online strategy in some situations is also proved.
Many literatures proposed effective solutions to multi-faults diagnosis as the combination of standard single faults. However, ignoring interrelation among single faults is to impair its efficiency, especially for complex products. To overcome these disadvantages, two-stage clustering frame was proposed by using KFCM-F algorithm and kernel-based cluster validity index KVK. The simulation results validate the effectiveness of this frame to find latent interrelation among single faults and reduce the number of fault pattern for improving diagnostic efficiency.
To establish practical failure prediction model and facilitate its applications, this paper proposed a failure prediction Bayesian network (FPBN) modeling method based on the failure mode, effects and criticality analysis (FMECA). According to the useful failure relationships embedded in the FMECA unit, the FPBN network construction and the probability parameter computation algorithms were discussed to build the corresponding FPBN unit model. Then, the FPBN unit model of each part in the complex equipment was connected with each other to establish the integrated FPBN model of the whole system. At last, based on the FMECA knowledge of a head up display (HUD), the practical FPBN case of the electronic part was built for the actual failure prediction tasks. The case analysis results show that, the FMECA knowledge embedded FPBN model, which has the advantages of uncertainty representation and quantitative analysis, can perform effectively in the failure prediction of complex equipments.
In order to deal with uncertain information in process of purchasing the combat aircrafts, the theory of preference programming is first introduced into procurement effectiveness model. An index system is proposed, which is based on procurement effectiveness evaluation for combat aircrafts, and the interval is using to present the uncertainty of the index data and the preferences. The best alternative is obtained by solving multi-criteria decision problem with a RICH approach. Considering ordinal information about alternatives in some attributes, the mixed integer linear programming is used to present it. The mixed integer linear programming is combined with preference programming methods by linear inequalities. Last, the model is verified by using an example under uncertainty.
This paper mainly deals with the analysis on mechanism modeling of GM(1,N) grey differential equations, based on the structure and characteristics of time series. By the numerical integration method a new algorithm of GM(1,N) forecasting model based on Simpson formula is proposed. Using the method of average relative error, we take empirical analysis on some time series models, and then find that the new algorithm has more accurate fitting precision than the original one. And the validity of the new algorithm is verified for some time series. The new algorithm is worth to be tried on establishing GM(1,N) forecasting model. And the reasonable application of GM(1,N) forecasting model has a practical significance.
In order to deal with the problem that the redistribution rule of real networks always lies between global shared rule and nearest neighbor shared rule or between even shared rule and extremely heterogeneous rule, a novel cascading failure model of complex networks is proposed. It can tune the load redistribution range and the distribution heterogeneity of extra load. Numerical simulation and analytic results show that the model can achieve better robustness against cascading failure than previous model by adjusting the redistribution range and heterogeneity.
Accompanying repair is an important maintenance support form; optimally scheduling maintenance task will improve the efficiency for accompanying repair, and increase the combat efficiency for combat unit. In the paper, maintenance task scheduling heuristics in accompanying repair were researched with discrete event simulation methods. First, accompanying repair and maintenance task scheduling heuristics were presented. Next, simulation model of accompanying repair for equipment minimal combat unit was established. At last, maintenance task scheduling heuristics were evaluated, and influential factors, such as MTBF (mean time between fault), mission duration, preemption, priority updating methods, were analyzed through the simulation model. The simulation results show that it is better to prioritize the important maintenance task and allow preemption; when maintenance task emerging rate is high "MFCFS (modified first come first serve)" is better; when maintenance task emerging rate is low the "MSMPT (modified shortest mean process time)" is better; and it is reliable of "MEETOC (modified estimated earliest time to complete)".
Course of action development is the key step of operation planning, consider the conflict and resource restriction, this paper establishes a model of course of action development based sequential game theory and resolve by translate it into matrix game model. An example is given for illustration of the model and it's solution method, compared with the model that not consider the rivalry between the two sides of war, the result of this model is more suitable for the rivalry situation.
A simulation model combining immune and genetic algorithm is proposed to solve multi-machine multi-task crane scheduling in job shop. Simulation model represents the crane characteristics of natural working environments where spatial abstraction is based on the locations between work stations and cranes in the same span. During scheduling process, multi-machine multi-task confliction is settled considering spatial constraints with available crane task priorities. Crane scheduling is evaluated by simulation model, while optimization is iterated with immune and genetic algorithm. Crane scheduling in a major span of a steelmaking factory is made to validate the simulation model, and compare between feasible schemes is given. The result shows efficiency and feasibility in industry.
The features of terms in technology domain were analyzed, and a model of automatic term extraction for technology domain was proposed considering linguistic and statistical characteristics. The model consisted pre-processing, string extension and term filtering. The relationship between threshold selection and evaluating indicators was studied by experiment, and the validity of the model proposed was verified. Experimental results show that the rate of extraction has been raised more than 2 times as well as the receivable precise rate and recall rate.
Fault-tolerant strategy is one of the most important effects on the reliability of embryonics hardware. The best fault-tolerant strategy and array layout could be derived from reliability analysis. The traditional reliability model of embryonics hardware was based only on the layout of the array, all cells in the structure were treated as fixed nodes, and the changes of the cell modules in circuit realization were not considered. In this article, a new model was presented with the configuration memory and the I/O routing switch which would change in different fault-tolerant strategies. According to a case study, the methods and procedures in selecting fault-tolerant strategy were summarized. Lastly, the specific quantitative selection criteria based on the example was obtained, and could be directly used to guide the selection of fault-tolerant strategy.
To solve the problems of the uncertain parameters of LSSVM and the low forecasting precision of single method, the learning algorithm of grey least squares support vector machines combined forecasting model optimized by particle swarm algorithm is proposed. Optimize two parameters of LSSVM model study by particle swarm algorithm's abilities of the fast convergence and whole optimization. It can escape from the blindness of man-made choice. First, the combinational results of initial forecasts are put as the input and the corresponding actual values are put as the output of LSSVM. Then we can get combinational model of the grey and the least squares support vector machine based on particle swarm algorithm by training it. The proposed combinational model can enhance the efficiency and the capability of forecasting. Actual data from 1985 to 2006 of area in Sanjiang plain is taken as the sample data. A combinational model based on PSO-LSSVM and GM(1,1) model is proposed. Predict precision of the model is examined by two ways, and the results show that it is more precise than the other methods.
The development of the information-based weaponry, is constantly promoting the request for testing ability of test range. The setting-up of the architecture of test range is extremely urgent. The standard architecture facilitates the interconnection and cooperation of the systems of system, so as to make the efficiency of the systems be most. Through the researching on the Department of Defense Architecture Framework (DoDAF), and analyzing the need of test range, the designing course of the architecture of test range was proposed, and the details of the steps was explained according to DoDAF architecture design method. This will provide reference to system architecture design of test range and some other fields.
In order to make the ecological compensation for river basin more reasonable and stimulate the water ecological protection initiatives of the upstream region, the water ecological compensation amount allocation method is proposed based on the model of DEA cooperative game with the supposition of cooperation among different areas along the basin. Considering the limitation of classic Shapley value in cooperative game, this value is improved by the weight among different areas confirmed by trapezoidal fuzzy number. Applied to Xin'an River basin, its result indicates that the allocation method adopted in this paper not only made the driving force for ecoloical protection stronger, but also combined the importance of different index such as the water and its benefits in the basin, meanwhile, the water benefits was considered among different areas. Thus, it is more reasonable, and it could provide reference for the ecological compensation amount allocation research of the other basins cross regions.
In order to design the piped hydraulic transportation technique of tube-contained raw material reasonably, mathematical model on the piped hydraulic transportation of tube-contained raw material was established based on the hydraulic characteristics of the piped hydraulic transportation of tube-contained raw material in the paper. The mathematical model was solved by FLOW-3D and simulated values were compared with the experimental values. The results find simulated values and experimental values of the pressure field and flow field on the piped hydraulic transportation of tube-contained raw material are in substantial agreement. These show the mathematical model is right and the solve is feasible by the software. These will provide theoretical reference for the technical application of the technique.
In traditional genetic algorithm (GA), all chroms in the solution space are feasible; and if the new chroms created by genetic operation become infeasible they need to be revised. In cascade reservoirs operation, however, such revising becomes complicated because of the hydraulic and electric connections between time sequences and between reservoirs. Therefore, an advanced GA——adaptive genetic algorithm successive approximation (AGASA)——is proposed in this paper, which can do optimizing within a space including feasible and infeasible schemes, and finally find the optimum by successively altering the space and adaptively changing control parameters. Finally, a simulated example is provided, and the results are compared to those obtained by discrete differential dynamic programming (DDDP) and progressive optimality algorithm (POA) respectively, which indicates the feasibility and validity of AGASA.