Based on the assumption that using all the information from multiple expectiles can improve the efficient of estimators, we propose a weighted composite expectile regression (WCER) estimation for AR models, investigate optimal weights of the resulting WCER estimator and establish its large sample properties. We also discover that the WCER estimators whose weight is data-driven and whose weight are known has the same asymptotic efficient. Simulation studies tell us that our WCER estimator greatly outperforms the least squares estimator in the sense of mean squared-error when the error follows a heavy-tailed or asymmetric distribution. Even if the distribution of the error is unknown, we can obtain a WCER estimator with nice statistical properties just like ones of a maximum likelihood estimator. The empirical analyses on the Hang Seng Index and the standard & Poor's 500 index demonstrate that the proposed WCER is competent in the sense of efficiency.
The skewness risk premium is the skewness risk return which required by investors, and it is measured by the difference between expectation of realized skewness and risk-neutral skewness (implied skewness), which contains abundant information. By using the model-free method in Neuberger, this paper extracts the realized third moment and implied third moment in Taiwan option market through the technique calls variance swap and skewness swap contracts. Then according to the definition of Kozhan, et al, we get the realized skewness and implied skewness. Last, we extract the implied skewness risk premium, which is the difference between the realized skewness and implied skewness. We study the characteristics of the implied skewness risk premium, its information content, predictive power and influence factors. This paper finds that the implied skewness risk premium is significantly different from zero, and it is systematic risk, and it is related with the market risk factor, but it is a new explanatory factor differs from market risk factor. And the implied skewness risk premium contains the tail risk information, but it can not make a precise prediction on segmentation of tail risk. It is more influenced by investor sentiment:when the sentiment of investors is high, the required skewness risk premium is low, and vice versa.
To raise the proportion of direct financing is one of goals of the reform of financial system and development of social financing mechanism in our country. The policy of expanding the scale of social financing was established in 1996. But the goal hasn't been achieved until now. It is the fact that the commercial banks have access of financing from capital market to lead to the expansion of the scale of indirect financing. In this paper, based on the reviews of literatures on direct financing structure and the view of system science, we draw a conclusion of factors that affect the financing structure and set up a system dynamics model of financing structure. And we check the validity of the model by comparing the model results to the real. Finally, we set up a series of simulation to analyse the changes of result under different assumptions and give some advices on how to improve the financing structure.
From the reasonable and illegal channel respectively, the paper puts forward the calculation methods of short-term capital flows. Also it divides the capital flows into five measurable dimensions and raises some thought about measurable dimensions to control the capital flow quality and velocity by referring to reservoir leaching model. This thesis establishes matching relation between economic cycle different nodes and short-term capital inflow, and methods to control short-term capital flow on the basis of the impact which the short-term capital inflow brings the economy a time lag. Finally, this thesis forecasts the level and exceptional conditions of short-term capital flows in China annually, and gives some suggestions to control Chinese short-term capital abnormal flows by making an analysis and statistics to the Chinese data.
Base on the complex networks that showing the relationship between interbank lending, we build a model of bank systems in terms of the bank's balance-sheet. We simulate the process of crisis spreading since depositors withdraw that cause the interbank funding runs and investment assets sell at a discount. Our research show that the interbank lending market structure and loss rate due to bank assets fire sale are the key factors in the risk contagion which caused by liquidity shortage shock. The tight connection between the interbank market suppress the risk spread meanwhile contain the possibility that make the risk expand and exacerbate.
ARMA-GARCH model only takes historical data into consideration when predicting the stock price return, without taking into account the trend information at each belated time point, which, to some degree, influences the model's generalization capability. In this paper, a differential-based ARMAD-GARCH is developed by incorporating approximate differential signal of the belated dependent variable into the traditional ARMA-GARCH model's mean equation, which is used to integrate the stock price trend information and improve the model's discrimination capacity for price's evolution direction. A empirical study, based on different composite index returns, demonstrates that ARMAD-GARCH model is superior to the traditional model in terms of data denosing, trend discrimination and prediction accuracy.
Based on the technique of wavelet-NAR neural network, this paper develops a method for forecasting meteorological elements and pricing weather index rainbow options. By using a data set of daily average temperature and rainfall in Sydney from 2000 to 2014, an empirical analysis of the meteorological forecast and weather option pricing is conducted. The results show that the wavelet-NAR neural network model is more accurate for forecasting meteorological time series and pricing weather index rainbow options because the flexible nonlinear dynamic structure of the model can better reflect the meteorological characteristics. This study also finds that the nonlinearity in the formation of the weather option value is determined by five economic effects. Our findings suggest that a scientific weather forecast and weather option pricing as well as a development of weather derivatives can contribute to mining the economic value of weather uncertainty and weakening its impact on weather-sensitive industries.
We present a generalized sentiment asset pricing model under asymmetric information, which shows that the investor sentiment has a systematic and significant impact on the asset price. In the model, sentiment is contrasted with information. The insiders possess valuable information and trade in such a way that the fundamental information is incorporated into prices, the sentiment investors trade on their own sentiments so that the investor sentiment is also factored into prices, and the outsiders occasionally chase sentiment as if it were information, thereby amplifying sentiment shocks and moving the asset price away from fundamental values. Moreover, the proportion of sentiment investors, the information quality and so on could amplify the sentiment shock on the asset price, thus reducing the efficiency of the market.
We propose an integrated bibliometric approach, composed by statistics with network analysis and data mining with text mining, to analyze studies on bank business models, in order to disclose its development in theory and practice. It shows, 1) compared with other industries, studies on bank business models started much later and process with less output, nevertheless it draws more and more attention of scholars in recent years; 2) its research quality is worrying, with publishing distributed in some non-core journals; 3) its content changes dynamically, focusing on risk and innovation recently; 4) there're some distinctions between domestic studies and foreign ones, for instance, securitizing, and internet finance are highlighted at home.
The single and dual channel models under centralized and decentralized cases are formulated in a closed-loop supply chain that comprises a manufacturer, a retailer and a third-party collector. Deriving and computing equilibria, we further analyze channel selection strategies of closed-loop supply chain in different models and discuss the conditions in choosing single or dual sale channel from the perspectives of the chain members and the whole supply chain system. Furthermore, with the benchmark of the equilibrium outcomes in the centralized model, we find that a simple pricing scheme, together with a complementary profit sharing mechanism or a complementary two-part tariff agreement, can coordinate the dual channel closed-loop supply chain. Finally, we conduct some numerical examples to analyze the impacts of key model parameters on the equilibrium results and profits, and further verify the effectiveness of the designed contract in coordinating the dual channel closed-loop supply chain.
This paper studies the coordination mechanism of production decision-making, carbon purification level selection and revenue distribution between a low-carbon-service provider and a carbon-emission-dependent manufacturer under the carbon emissions cap-and-trade market mechanism, where the relationship of the two participants is built on embedded low-carbon service. For analyzing the decision-making behaviors between the low-carbon-service provider and the manufacturer, we design three different contracts to coordinate the optimal decisions of the low-carbon-service provider and the manufacturer:two-part tariff contract, carbon purification revenue sharing contract and carbon purification cost-revenue sharing contract. By analyzing the designed contracts, we find that the two-part tariff contract can make both of them to agree with the service contract, but the total profits of the low-carbon-service provider and the manufacturer cannot achieve the goals of profit maximization; the two participants cannot reach to unanimous decision on the carbon purification revenue sharing contract; whereas in case of the carbon purification cost-revenue sharing contract, when the parameters satisfy certain conditions, both of the low-carbon-service provider and the manufacturer could participate the low-carbon purification activities and achieve the optimal decisions to maximize their total profits. Meanwhile, we analyzed the contracts chosen by the participants in different scenarios, the impact of the key parameters on the optimal decisions and profits of the participants, and the minimum investment and performance level of the service project for the low-carbon-service provider. The results can provide some management insight for enterprise decision.
Cope with complex architectural spaces in large passenger transfer hub, pedestrian-oriented signage system in hubs has a positive role in improving the service level of transfer and encouraging travelers to choose public transport. Based on the complexity features and requirements of hub management function, the design of pedestrian-oriented signage system essentially can be summarized as complex decision problems. Aiming at this problem, this paper develops a multi-objective optimization model. The improved particle swarm algorithm based on distance (DISMOPSO) is used to solve the model. In the project of Shanghai South Railway Station pedestrian-oriented sign system design, the mathematical model and the algorithm are used to verify their logical and effectiveness. The empirical results show that optimization models and algorithms can provide reference and help in the design of pedestrian-oriented signage system in large passenger hub.
As compared with sea/ocean shipping, small ships are deployed in river shipping, and ship capacities are limited. This paper investigates a capacitated hub port location problem in river shipping, and a mixed-integer nonlinear programming model is proposed. Different from the transportation discount used in the conventional hub location problems, this paper adopts the flow-based nonlinear cost functions to describe scale economies, leading to a concave optimization problem. In order to simplify our problem, we utilize a piecewise linear function to linearize the objective function. Based on the linearized problem and capacity constraints, a heuristic algorithm with an accelerating technique is proposed to solve our problem. Finally, a case study of the Yangtze River is presented to account for the effectiveness of our model and algorithm.
The assessment of goals satisfiability of emergency response is important for the implement of emergency response. An assessment methodology is proposed to solve the problem that the goals satisfiability is difficult to assess because of uncertainty under the pattern of scenario-response. On the ground of DS evidence theory framework, belief function theory is used to build the goals satisfiability representation model. Basis on this, belief rules are used to reasoning the satisfiability of leaf goals based on scenarios. With different scenarios, different values of leaf goals could be obtained. And then a method for improving traditional OWA operators is put forward in order to compute the weights. Then evidence combination algorithm is used to assess the satisfiability of high-level goals according to the satisfiability of leaf goals, and the conclusion of assessment can provide theoretic foundation for decision makers. Finally, the result of example indicates that the interactive effects of goals satisfiability could be paid attention to and the assessment result of this method is well consistent with the person's subjective intuition.
The influence of security rank on the technology portfolio and configurations of firewall and IDS was researched through game theory by this paper. It shows that the higher the security rank the bigger deterrence to hackers whose intrusion probability would be decreased. The security rank is not always improved when only one of the technology configurations is improved, and it is improved when both of the two technology configurations are coordinated with each other, which illustrates that the higher the security rank the higher requirement of security technology portfolio and configuration. The equilibrium strategy is also compared to the one without considering security rank, and the latter is an extremity of the former, which could not be reached or with no need to get.
Super network which is a special complex network is introduced to model and analyze the network-centric C4ISR structure in this paper. Based on the analyzing of the super network characters of the network-centric C4ISR structure, two modeling methods of the C4ISR structure based on the super network are present, which are based on the idea of "topology" and "time-series" respectively, and then two application assumptions of the C4ISR structure which based on two previous ideas are present respectively, and the simulations to a part of application assumptions are analyzed at last. The super network models and the application assumptions are also valuable to the further study of the system structure.
Organization ability is the critical factor for project task completion, and learning ability is crucial basis for organizational ability formation. Based on meta-network theory and dynamic simulation method, this paper regards organization (people), knowledge and task as complex interactive system of multi-agent and puts forward 2 measurement indexes (knowledge diffusion and task completion), researching the internal mechanism of learning ability of project organization to influence task completion. Finally, taking General Motors (GM) Buick 4S Shop Construction Project Group Organization as a case, this paper further identifies the key knowledge, key agent and key learning phase of project organization through simulation after reasonable confirmation of measurement indexes and optimizes organization learning ability and task assignment. Furthermore, this paper provides effective methodology for research of project organization design, optimization of task assignment and organization learning.
The paper studies a class of online batch ordering problems without knowing purchasing price. It extends the risk aversion hypothesis about the decision-maker in the previous studies and give the batch order policy based on the risk preference. Firstly, the paper builds two risk-reward frameworks about different expectations to help making decision. Furthermore, several on-line batch order strategies based on the risk tolerance and different expectations are designed. Finally, it states the relationship between different risk tolerances, expectations and the batch order policies by the numerical examples. It hopes to provide a new method to solve inventory problems with incomplete information and enrich the present inventory theories.
Considering the importance of user-experts knowledge to the product and service innovation, this paper proposes a discovering and analyzing method to study the knowledge of user-experts in enterprises virtual communities based on weighted knowledge network (WKN). First, the knowledge of user-experts, presented as forum posts in virtual communities, was acquired through the method of web content mining, and then the acquired knowledge was processed and integrated into a weighted knowledge network model (WKN). Next, based on the WKN model, the basic knowledge mode, the developing knowledge mode and the core knowledge mode of user-experts were identified by analyzing the weights of nodes and edges, the cliques and components in WKN model. The knowledge modes identified from the methods reveal the structure of knowledge relations. Compared with scattered knowledge points, knowledge modes are better understood and more thoroughly and systematically to study user knowledge in enterprise virtual communities.
Based on the frame of the knowledge production function, the paper introduces geographical proximity and technological proximity together in the spatial econometric model, systematically analyzes the two proximities' interactive effects in the process of knowledge spillover, and realizes an effective combination of the spillover effect in the spatial and the industrial dimensions. Based on the first and the second economic census data in regions all over China, the Bayesian Markov Chain Monte Carlo (MCMC) methods are used to estimate the spatial Durbin model, and the spatial externalities are divided into direct effects and indirect effects, so as to avoid the error of explanations for the model parameter. The empirical results not only confirm the presence of spatial externalities, but also find that specialization economies based on technological proximity promote innovation output effectively, and that spatial spillover effects based on geographical proximity are relatively weak.
Enterprises are continuously falling into fire management because of quality problems emerging endlessly. To improve the situation, this work proposes a quality control decision model based on fuzzy cognitive map and evidence theory. The model includes four typical quality control modes:reactive, preventive, predictive and proactive. Firstly, the four typical quality control modes and decision factors were analyzed; then, the quality control decision model and implementation steps were presented. The decision strategy was studied from four perspectives including quality properties dimension, cost dimension, function accord dimension and organization support dimension. Aiming at solving quality problems scientifically, the decision network was constructed and the most appropriate quality control mode was chosen for actual requirements. In order to construct multi-expert fuzzy cognitive map (FCM), we use multi-expert's knowledge as evidences, the possible value of weight as frame of discernment, and use evidence rule combing to give fusion basic probability assignment. Finally, the proposed method was applied to the bearing groove shape error out of specification limits problems in the bearing enterprises, which proved that the method was effective.
Traditional clustering methods have great limitations when they deal with the clustering problems that involved uncertainties. In order to deal with the uncertainties in clustering analysis, this paper proposes a new clustering analysis approach based on type-2 fuzzy equivalence. It first transfers the linguistic variables into interval type-2 fuzzy sets (IT2FSs), and combines advantages of the linguistic variables and IT2FSs together. Then with the aid of the Jaccard similarity method, a new fuzzy equivalence clustering analysis method with specific algorithm processes based on IT2FSs is proposed. The new method can avoid the information loss in the process of clustering computations. Furthermore, the new method can produce the dynamic clustering results with the change of cluster similarity parameters in a flexible way. Finally, an example of the clustering on mobile phone brands under e-commerce platform is given to demonstrate the feasibility and rationality of the new method.
To enhance the optimization ability of classical shuffled frog leaping algorithm, a quantum inspired shuffled frog leaping algorithm with adaptive grouping is proposed. In this work, the frog swarms are adaptive grouped according to the average value of the objective function of child frog swarms, the frogs are encoded by probability amplitudes of multi-qubits system. The rotation angles of multi-qubits are determined based on the local optimum frog and the global optimal frog, and the multi-qubits rotation gates are employed to update the worst frog in child frog swarms. The experimental results of some benchmark functions optimization show that, although its single step iteration consumes a long time, the optimization ability of the proposed method is two orders higher than the classical frog leaping algorithm. Therefore, grouping strategy and encoding method proposed in this paper can effectively improve the optimization ability of traditional frog leaping algorithm.
The dynamic firepower allocation (DFA) optimization model based on fuzzy chance constrained bilevel programming (FCCBLP) is presented on the basis of analyzing the deficiency of the existing DFA model. Firstly, employing the maximization cost-effectiveness ratio and earliest intercept time respectively as the upper and the lower objective function of the model, and considering the complex constraint condition so as to close to the battlefield environment. Secondly, particle coding scheme with hierarchical structure for multi-constrained bilevel DFA problem is constructed. On this basis, the hierarchical hybrid fuzzy particle swarm optimization (HHFPSO) algorithm is proposed with fuzzy simulation technique, which effectively combines two algorithms:the discrete variable neighborhood PSO algorithm with convergence criterions (DVNPSO-CC) and the PSO algorithm with doubt and repulsion factor (PSO-DR). Finally, computational results show the proposed algorithm has faster convergence speed and stronger global searching ability, which can satisfy the high requirements on the timeliness of the large-scale DFA problem.
Sparse coding algorithm is a popular data representation method. In order to deal with the high nonlinear data, in this paper, a kernel sparse concept coding (KSCC) algorithm is proposed for image representation. Our algorithm performs spectral analysis on nearest neighbor graph and captures the geometric manifold structure of the data. Then the data in the origin feature space is mapped into the high-dimensional feature space and the basis vector in high-dimensional space is obtained using spectral regression. Finally, the samples are individually represented in high-dimensional feature space. Therefore, the proposed algorithm not only effectively handles the nonlinear structure data, but also needs to solve a sparse eigen-problem and two regression problems, which is very simple and effective. The experiments on Yale、ORL and PIE image datasets demonstrate that the accuracy and normalized mutual information of our proposed algorithm are superior to other comparison algorithms.
In order to understand the bigger difference reason between the failure probability spatial distribution by factors projection fitting method in DSFT and relatively accurate result by CSFT, the calculating process of this method is analyzed again to understand the reasons of the imprecision. It is found that the determination of the characteristic functions Pit(t) and Pic(c) of working time t and working temperature c is not accurate. To rebuild these two functions, the new expressions of the characteristic functions were obtained through a series of derivation. Contrast analysis shows that the function linear of the method is the same as the real result, except degree of scaling and translation quantity, so there is still practical significance. c0 and t0 as independent variables to form a group of family function, but because of the lack of constraints, c0 and t0 are still unable to determine the specific numerical value.
In order to further improve the water-transfer efficiencies derived from some existing water-transfer rules, this study aims to develop a new improved pattern of water-transfer rule and figure out a method to determinate the quantity of water transfer for each recipient reservoir. In this proposed rule, water storage conditions of both recipient and donor reservoirs are taken into consideration, and upper-and-lower water-transfer rule curves for each recipient reservoir with one water-transfer rule curve for the donor reservoir are developed to make water-transfer decisions. Given that it can transfer water out from the donor reservoir; if water storage of the recipient reservoir stays below the lower rule curve, namely water shortage is huge, the quantity of water transfer equals to the maximum capacity of water available (full water-transfer state); if the water storage of reservoir stays between the upper-and-lower rule curves, namely water shortage is small, the quantity of water transfer equals to the quantity interpolated linearly within that in the full water-transfer state; otherwise, no water is transferred. Taking the North-line Inter-basin Water Transfer Project located in Liaoning Province in China as an example, a new parallel PSO algorithm is adopted to solve the optimal operation model based on the improved rule. The results show that the proposed rule, with the guarantee of water supply, can significantly reduce water transfer, especially in wet and normal years.
To seek breakthrough point of safety systematics and to improve it, definition and contents about similarity safety systematics were put forward according similar characteristics of safety system. The feasibility and significance of establishing similarity safety systematics were argued through subject attribute and system feature. Subject foundations of similarity safety systematics were described, the concept system, research levels and application fields were constructed. Then, the discipline branches were classified within multi-view, and took comparative safety method as the main research tool of similarity safety systematics. Development direction and related subjects extended from similarity safety systematics were prospected at last. Research shows that, similarity safety systematics provides new thoughts and methods to the research of safety systematics.