LIBOR market model has played more and more important role in pricing financial assets and managing risk. FX structured deposits driven by LIBOR interest rate also have get more and more application. Therefore, it is very necessary to make theoretic estimation and Monte Carlo simulation for LIBOR interest rate process and its FX structured deposits pricing. In this paper, firstly, on the basic of many existing improved methods for LIBOR market models, combining Heston stochastic volatility into standard market models, we set up a new LIBOR market model. Secondly, by using of Black inverse parameters calibrating methods and Markov chain Monte Carlo simulation, we calibrate and estimate parameters of the new LIBOR market models. Thirdly, we use the improvement LSM to price this FX structured product. Lastly, we make an empirical analysis. The research conclusions are: 1) LIBOR market model with the stochastic volatility process can describe the LIBOR rate very well and display a finer accuracy. 2) The improvement LSM can get the much more precise result.
The microscopic study of market structure is always one of the important research directions, the relevant studies of the degree and the influence of the market power, domestically, however, might be with much importance due to the significant characteristic of concentrated supply of housing by the developers. This paper estimates the price elasticity of demand for 1029 commercial housing project and, of which, the Lerner Index for 494 elastic ones using the micro-level data set from Beijing. Based on the estimated result, the spatial distribution of the degree of monopoly of the housing market in Beijing is derived, and the impact of market power on the housing trading premium is empirically tested. It is revealed that every one percent marginal increase of the market power will result in 0.83% increase of the premium, which is excellent robust over different segmentations of sub-market. Besides, an analysis perspective, based on the concept of elasticity, is provided helping to explain the phenomenon of unwillingness to sell in recent market.
The law on new enterprises tax has been established since January 1, 2008, and it rules unified tax rates for domestic and foreign enterprises in China, which is 25%. Is this specific unified enterprise tax optimal? Therefore, this paper builds a computable general equilibrium model and employs the 2007 national statistical data to try to answer this question and reports the optimal unified tax for manufacturing enterprises (state-owned enterprises, foreign investment enterprises and other private enterprises). Furthermore, this paper compares changes of social welfare, national income, fiscal revenues, and structural changes of employment, wage rates, capital input, capital returns, output and consumption demand, and so on, in the four economic sectors among three specific equilibria (benchmark equilibrium, 25% unified tax rate equilibrium, optimal unified tax rate equilibrium). Finally, this paper does the sensitivity analysis of the optimal unified tax rate for the actual investment foreign enterprise tax rate and the elasticity of substitution in CES utility function.
This paper considers an optimal investment problem for a risk-averse entrepreneur facing business risk to maximize the expectation of total consumption utility through consumption smoothing, real investment, bankruptcy protection and financial investment when the debt and enterprise income tax are given. We derive semi-closed-form solution for capital value, optimal business strategy and bankruptcy threshold in a non-risk-neutral world. In addition, we obtain the expected return, beta coefficient, system risk premium and idiosyncratic risk premium corresponding CAPM. Unlike the classical theory, the idiosyncratic risk premium is strictly positive once the entrepreneur is risk-averse. The conclusions and numeric results show that the risk attitude of the entrepreneur has a significant effect on the value of the capital, optimal capital structure, real investment strategy, bankruptcy threshold, idiosyncratic risk premium and expected return.
The paper established a utility function of containing the surplus risk and shortage risk to find the impacts on the supply chain coordination given different risk preference. By comparing the coordination strategies about return policy and option contracts given the agents being risk-neutrality or risk-averse, it gives the optimal prices of buyback contracts and option contracts and approach the following results: 1) In option contracts, the manufacturer does not need to guess the risk attitude of the retailer. 2) Whatever the risk attitude is, there is a rule that the higher the controlling coefficient is, the better coordination is, the more profit is. 3) Given the risk-averse agents it shows that the profit of the centralized supply chain is not affirmatively higher than the profit of decentralized supply chain. Therefore, with the risk-averse agents various coordinated policies show distinct effects. It also provides important methods for the similar research.
In joint sale promotion of supply chains, the supplier and retailer have a strong incentive of "free riding" due to double moral hazard. It is helpful of the reasonable profit sharing rule to promote active inputs of both parties. By means of Nash bargaining concept, it established mutually incentive model and investigated existence of the optimal linear contract for supply chains joint promotion. It shows that the optimal wholesale price exists on the condition of existence of net cooperative residual and the bargaining powers, on which the allocation of net residual depends, have no impact on the optimal wholesale price. What's more, it points out that the ratio of net cooperative residuals acquired by the two parties is in proportion to the ratio of bargaining power factors.
Based on DEA-Malmquist index, considered the element of energy, the paper decomposed the output growth of the three leading industries in Fujian province into two part: the growth of total factor productivity and the growth effects of input factors. The study found, after having considered the element of energy, during the years 2002-2009: 1) The average growth rate of the output of the three leading industries was 21.48%, mainly depended on the growth of input factors; 2) The growth of total factor productivity led outputs growth 7.48 percentage points every year, with the contribution of 2.98 percentage points of technological progress, and technical efficiency improvement contributed 4.5 percentage points. The growth of input factors contribution to outputs growth was 14 percentage points; 3) The growth of input factors was dominant in the economic growth, under that condition, the development of the three leading industries in Fujian province showed a declining trend. Therefore, the paper argues that in order to maintain the rapid development of the three leading industries, we should make further improvement of the total factor productivity, including technological progress and technical efficiency improvement.
In real projects, the trade-off between the project cost and the completion time, and the uncertainty of the environment are both considerable aspects for managers. Due to the complex uncertain environment with coexisted randomness and fuzziness, a type of time-cost trade-off model based on the philosophy of dependent-chance programming is presented. In the proposed model, the environmental uncertainty of the project is described via fuzzy random variable. A searching method integrating the technique of fuzzy random simulation and genetic algorithm is designed to search the quasi-optimal schedule under some decision-making criterion. Some numerical example is given to demonstrate the feasibility of the searching method for solving the proposed model.
Auction is a realizable way of venture capital equity exit. The problems of information asymmetry and the indefinite nature of external environment in venture capital equity auction make it difficult for the outside investors to accurately price the risk corporate equity. Given this, the equity bidding system can be considered as an open system, thus the changing state of outside investors' bidding strategies can be described by stochastic differential equations. On this basis, this paper constructs a venture capital exit equity auction model, then discusses the formation mechanism of the corporate equity clearing price and its influence factors such as the degree of information disclosure, bidder's susceptible extent and so on, and finally analyses the expected revenue of venture capitalist by means of calculus of variations.
This paper, for the first time, defined the three-regime mean reversion, which is used to describe a special mean reversion phenomenon and to explain the non-linear mean reversion and short-term "non-stationary" phenomenon of time series. Threshold autoregressive model (TAR) and regime-switching model (RSM) can be used to model the three-regime mean reversion. As an empirical example, this paper used three-regime threshold autoregressive model to fit the log growth rate of China's trade surplus with the United States and Hong Kong. The empirical results showed that during the past ten years the probability of the above growth rate in high-level mean process (expansion) is over 50%. The average growth rate is lowest in recession and highest in expansion. The properties of the mean reversion process are characterized by a higher constant term in low-level mean process equation but the lower slope coefficient and a lower constant term in high-level mean process equation but the relatively higher slope coefficient. Therefore, the three-regime TAR model can be used to model three-regime mean reversion phenomenon.
Focusing on the ignorance of co-impacts of network externality, other participants and service quality on telecom business price equilibrium, this paper derives the demand curve from consumers' utilities in the market with network externality. Then, establishes a unified analytical framework of telecom network externality, relative market relation, service quality and price, and makes further analysis about model equilibriums. The results show that both network externality and service quality increase the consumers pay and the profits of the operating system. When network externality is weaker, the decision-making simultaneously between service provider and telecom operator means even better services, less expenditures, and higher system profits, while the sequential decision-making means the first-mover advantage for the first decider. When network externality is stronger, service provider makes decision firstly can bring even better services, more expenditures and higher system profits. As a follower, operator can improve its value acquisition of the business, obtain after-mover advantage through service-enhancement.
Forecasting pork consumption is very important to stabilize the pork market. By using Granger causality test to choose significant factors, we forecasted China's pork consumption with ARIMA、VAR and VEC model respectively. Based on a dynamic integration method, we integrated the forecast results of three models above. Finally, empirical results show that the dynamic integration method is more accurate and stable by forecasting China's pork consumption from 2009 to 2011 with the four methods above.
Manufacture of multi-product pricing and ordering problem between the supplier and the retailer in a two-stage supply chain is multi-loss of risk decision-making problems, which can establish a bilevel programming model to be solved. This paper first studies a bilevel programming of multi-loss conditional value-at-risk model. For a multi-loss function and the corresponding weight value level, at a given confidence level, we define concept of the loss value does not exceed a given minimum value at risk (VaR) and the corresponding cumulative expected loss value (i.e. the CVaR losses value). Then, we set up a bilevel programming model of the multi-loss conditional value at risk, which the goal of the model is to solve an optimal strategy the minimum CVaR value of this model. This model can be solved more easily through another bilevel programming model to obtain the optimal solution. Finally, a multi-loss conditional value-at-risk model of multi-product pricing and ordering of a two-stage supply chain is presented. Calculated by two kinds of bread product sales data, we obtain a bread manufacturer's optimal wholesale price and optimal repurchase strategy, and retailers the optimal order quantity.
A general-purpose model associated with vertically differentiated two-sided markets is established based on an abstract function. Using the general-purpose model, the paper discusses the features of market equilibriums in both a monopoly and a duopoly markets, and explores strategic effects of price change in the duopoly market. The paper further studies the impact of the parameters of network externality and the variable of quality gap on equilibrium prices and profits under the assumption of uniform distribution of consumer preference. The following conclusions are obtained by using the general-purpose model. Firstly, a monopoly platform can coordinate the price structure of the two sides more effectively than duopoly platforms. Secondly, a positive feedback exists in competition between duopoly platforms. Thirdly, prices have strategic complementary effect in duopoly competition, and this effect is stronger on the downstream side than on the upstream side. Under the assumption of uniform distribution, the paper finds that the low-quality platform should take the strategy of "divide and conquer", while the high-quality platform should exert the strategy of "act according to circumstances".
This article establishes models and gives examples to explain why the effect of traditional bureaucracy broadcasting of agricultural technology extension is getting worse, while the experience broadcasting can effectively meet the farmers' needs of agricultural technology, and the effect of agricultural technology extension is better. The research is helpful for improvement on the service of agricultural technology extension.
One of the key factors to assess reasonable low bid is that how to judge whether a tender's offer is lower than its cost or not. In this paper, firstly, to analyze the optimal bidding strategy of bidder and find that the most optimal strategy is making bidding price equal to its cost by using the game theory. Then to build the probability judgment model of project cost based on bidder sample size by using hypothesis testing theory and bidder sample number under the second-price-sealed auction bidding. So at confidence level, whether one bidder is lower than its cost or not can be judged according to its position in accept region or rejection region. This model not only is used to solve problem that whether an offer is lower its cost, but also enriches bidding evaluation theory.
Based on the analysis of knowledge classification and characteristics in high-tech enterprises innovation networks, a model of expectations of profit is presented, which can determine the optimal time of knowledge transfer. Important factors, such as knowledge absorption capacity, update rate of knowledge in network, discount rate, the time of knowledge transfer, market share, product life cycle, etc are taken into account in the model. The validation of the model is taken by setting these parameters and deriving the optimal time period of knowledge transfer. Simulation results show that the model and the optimal knowledge transfer time are effective and reasonable. A large number of simulated experimental data and comparative analysis with known research results show that this model is more common and realistic than the current works. The presented model is feasible as a basis of decision making of time optimization of knowledge transfer for enterprises.
Traditional airline fleet planning methods could not reflect the robustness of fleet composition. In order to solve this shortcoming for airlines which operated in single-base linear route structure operating mode, this paper regarded minimum aircraft types deployed on single-base airport as objective, with flight pairing fleet assignment cost constraint, flight pairing fleet assignment uniqueness constraint, and least numbers of selected aircraft types constraint, to incorporate robustness into airline fleet planning model. Combining with only one competitive aircraft type in a desired fleet composition, the simulated annealing algorithm was employed to design heuristic algorithm for this proposed model. An empirical example containing 39 flight parings and 6 candidate aircraft types indicates that the fleet composition derived from traditional fleet planning method has three aircraft types while the proposed algorithm has only two. Furthermore, the fleet composition can well adapt to the market fluctuations, so the algorithm is feasible.
With the aggravation of traffic jam traditional logistics network has reached high-point in big cities in China, so the logistics system on the ground will gradually transfer to underground on various layers in the future so as to release the ground space in cities. Based on SMT theory, this paper establishes underground tree logistics network layout model. Because SMT is NP-complete problem, the algorithm optimization capability is the key of research. Plant growth simulation algorithm (PGSA) in this paper is an intelligence optimization algorithm, which takes plant phototropism growth pattern as its heuristic criterion. Through artificial plant growth process in solution space of given logistics node set, we can get the optimal layout of underground logistics network in cities. Through the calculation of STEINLIB lab data announced internationally, PGSA is demonstrated with better accuracy, stability and global searching ability, by comparing the solutions of ant algorithm and simulated annealing algorithm.
In the framework of cooperative games with coalition structure, it studied the problem of profit allocation by introducing lattice structure based on the situation that all the coalitions are not feasible. First, it generalized five properties which Owen value satisfies and then gave the definition of restricted Owen value by two step allocation. It proves that Owen value satisfies some properties, such as additivity, efficiency, symmetric with coalitions, dummy player property and so on. Finally, it gave an example to verify the allocation method in the paper.
In the practical application, abnormal fluctuations of the mean and variance of model are always possible． In this paper, a method based on wavelet coefficients is proposed to estimate the location of breaks in mean function and variance function of nonparametric regression model. The mean function and variance function can be estimated using local linear fitting. The convergence rate of these estimators are derived. The finite sample properties of the estimators are investigated and the impaction of the changes in mean and variance is analysed by comparing sample deviation, mean square error and standard deviations. Finally, we give practical example to estimate changes in a set of stock price data and HANG SENG INDEX using the wavelet method.
This paper considers the discrete-time Geo/G/1 queueing system with delayed D-policy. By using the total probability decomposition technique, we study the transient and equilibrium properties of the queue length from the beginning of the any initial state, obtain both the recursion expressions of the z-transformation of the transient queue length distribution at any time n^{+} and the recursion expressions of the steady state queue length distribution, and then we give the stochastic decomposition of the queue length in equilibrium. The important relations between the steady state queue length distributions at different epochs (n^{-}, n, n^{+}) are discovered. Finally, by numerical examples we discuss the sensitivity of the steady state queue length distribution towards system parameters and illustrate the important value of the expressions of the steady state queue length distribution for calculating conveniently in the system capacity design.
In this paper, the decision-making behavior is introduced into the queuing models, starting from the customer to maximize the interests, the customer optimal balking strategies in the Geom/G/1(ES, MV) has been studied. On the premise of unobservable queue, based on a natural reward-cost structure, the overall profit function about the individual customer and the whole customers are constructed by a method of mean value analysis, then the customer equilibrium balking strategies and socially optimal balking strategies are analyzed and determined within the parameters of different ranges. At last, the conclusion is improved by numerical simulation.
In order to get optimum solution of mission assignment and cannibalization, it puts forward a nonlinear programming model to optimize mission assignment and cannibalization solution, the factors such as mission requirements to equipment subsystem, real condition of equipment system, maintenance resource are considered in the model, the model harmonize the mission, equipment fleet and maintenance resource to the utmost, so it is more practical. It designs the solution algorithm based on particle swarm optimization (PSO), includes algorithm framework, particle representation, initialization, fitness function and update methods. Finally, applies the algorithm to a specific example, analysis shows that the model and algorithm can optimize the mission assignment and cannibalization solution effectively and efficiently, increase the mission success probability, and provide instruction for decision maker in decision-making.
The task of quality of service (QoS) routing is to find a route in the network that satisfies a set of constraints while maintaining high utilization of network resources. It is well-known that this problem is NP-complete. In this paper, a new method of integer linear program model for QoS routing problem was proposed. The idea is to include complicating constraints in the objective function with the "penalty" term, and then obtain the Lagrangian relaxation integer linear problem. For the constraint matrix is totally unimodular, the relaxation can be solved rapidly from a linear program. Updating of Lagrangian multipliers are calculated easily by penalty function method. Numerical computational results indicate that the proposed method is effect.
Features representation and similarity measure are the basic work of time series data mining. Its quality directly influences the results of time series data mining. The orthogonal polynomial regression model is used to represent the multidimensional shape features of time series and the fitting effects of time series are analyzed according to the dimensions of shape features. Part of the features are chosen to describe main shapes and trends of time series. Furthermore, a robustness method with a higher measurement quality based on shape features is proposed to approximately calculate the similarity of time series. The experimental results demonstrate that the similarity measure not only satisfies lower bound and has better tightness and pruning power for time series but also obtains good results of time series data mining such as clustering and classification.
In terms of the modeling needs of low-carbon manufacturing process for ceramic enterprises, the modeling method based on fuzzy Petri nets is introduced according to its basic principle and advantages that can grasp the continuity of the serving states and the impact of discrete states on continuous processes. Based on the analysis of the energy carbon-flow of the ceramic enterprises, the energy carbon-flow model of production process for ceramics is established based on generalized fuzzy Petri nets, and its formal definition and the rules explanation are given. Finally, taking firing system as an example, the model is used in ceramic enterprises to describe the dynamic behavior of energy carbon-flow and lay a theoretical foundation for low-carbon development.
It screens the input and output indicators of the total factor productivity of Chinese regional construction industry with the method of added value. On this basis, it uses the super-efficiency DEA method to analyze the Malmquist productivity index of construction industry in 31 Chinese provinces from 2006 to 2009. Finally, it identifies the key factors affecting the productivity of China's construction industry, with the method of analysis of variance. With the effective combination of the above three methods, we successfully achieve the objective study in three aspects, that is, the measurement model for productivity, the selection of indicators and the identification of factors, so as to shape a more scientific structure for studying the change of productivity. It finds that the main reason for the steady increase in total factor productivity is technological progress and the improvement in the scale efficiency is just a kind of short-term behavior which is not the key issue. And one key issue to be solved is the improvement of pure technology efficiency. Three indicators, "science and technology investment", "human capital of construction industry", "economy level", exert a great influence on the improvement of the productivity of Chinese regional construction industry.
It would be more easily to process the image of street scene by recognizing every building facet first. In this paper, a novelty method which recognizes every building facet by analyzing feature line segment of buildings with technique of system engineering is proposed. Beginning, the feature line segments extracted from the area of buildings are accumulated with the mathematics' model which deduced by the relation of horizontal lines between the real world and image. Then the result of feature accumulation is refined by a new method. At last, each building facet could be recognized by dynamic programming because the building facet recognition by analyzing feature line segments has been proved to comply with the optimality principle. The experiment shows that our method could recognize building facet exactly in many complex environments and need less time in the fields of building facet recognition.
The heating steam is an important secondary energy, so it is of great significance to predict the required steam load in the future hours, which is important for the thermal power plant to provide users with high quality heat load securely and economically. Steam load time series proves to be with chaos characteristics. According to Takens theorem, delay time and embedding dimension are calculated respectively using C-C method and Cao method, and the steam load time series is reconstructed in phase space, and then the steam load forecasting model is established using least squares support vector machine (LSSVM). A SA_WPSO algorithm (improved particle swarm optimization (PSO) with simulated annealing algorithm (SA)) is proposed to implement the optimization of LSSVM parameters. The simulation results show that the method can achieve good prediction results.
The management policy taken by government could have some influence on the activity of subjects in water resource conflict. Taking this into account will provide some reference for the solution of water resource conflict in the Zhanghe River Basin. In view of this, cellular automata method is used to describe the activity of group members and the process of water recourse conflict is simulated. Meanwhile, based on the social attribute of human beings and group environment, i.e., the policy, the transformation of conflict group's state is designed. What's more, C# is used to realize the simulation. The results show that management measures are effective to solve trans-boundary water resource conflict. The government should raise the policy implementation degree of conflict agents to alleviate local water conflicts.
As a complex logistics node, the container terminal is affected by many uncertainties. In order to make terminal operating plan implemented smoothly and improve its robustness, a scheduling strategy for berth and quay cranes based on robust and reactive policy is proposed, focusing on how to increase the plan robustness through the real-time scheduling of berth and quay cranes when the uncertainties occurs. The real-time scheduling strategy includes the berth real-time scheduling and the quay cranes real-time scheduling. The former adopts the ASAP strategy. The latter adopts MAS technology, makes full use of quay cranes, and designs a real-time scheduling model for quay cranes based on CNP. The simulation tests show that this real-time scheduling strategy can achieve more stable plan than that just considering the berth real-time scheduling.
Wind speed modeling and prediction is important for utility of wind power. Since the wind speed data are non-normally distributed and have highly variable nature, it is very difficult to predict the wind speed accurately by applying statistical approaches. This paper predicts the wind speed using the Mycielski approach which is similar to a high order Markov chian approach. To improve the prediction accuracy, the wind speed states are redefined in a smaller region. Then, the Mycielski algorithm searches the longest suffix string at the end of the data sequence which had repeated at least once in the history of the sequence. The simulation examples and the F-test values of the comparsion results show that the prediction performance of the proposed approach is improved significantly.