Price manipulation usually does not contain explicitillegitimate activities (i.e. financial rumour spreading, equity supply or demand squeezing), instead, includes submission and cancellation of limit orders, which appear to be normal trading behaviours. This paper proposes a Hidden Markov Model based system for detecting price manipulation behaviours in the capital markets. This paper starts from a thorough study of three primary types of price manipulation strategies, from which the intrinsic patterns of the manipulation is extracted through features extraction module, composed of wavelet transformation and gradient method. The extracted features are modelled by Hidden Markov Model, where the intentions of the trading are distinguished, quantitated and designated through the hidden states, which generate the variables that can be directly observed from the market. To overcome the non-stationary nature of the financial data, an adaptive mechanism is proposed for adaptively updating the model. Experimental evaluations for the new proposed system are conducted based on real financial data from NASDAQ and London Stock Exchanges as well as the simulated stock prices. Evaluations show that the proposed system stably outperforms the selected bench market models.
This paper uses complex network and co-integration techniques to investigate the major factors which influence CITIC (China International Trust and Investment Corporation) industry indices among 2005.01.05-2015.01.30. The results:In the long run, the industrial association has positive impacts on industry indexes co-movement. In the short term, industries indexes shocked by specific common information have been linked closely. Therefore, improving the information disclosure system and reducing government intervention can reduce stock price irrational co-movement of great significance.
Based on the arbitrage risk and the arbitrage asymmetry, this paper investigates the different rates of return between the portfolios with different idiosyncratic volatilities by estimating the idiosyncratic risk premium. Further, this paper examines the effect of cash dividend payment, stock liquidity and investor sentiment on the idiosyncratic risk premium. The results show that the relationship between the idiosyncratic volatility and the stock return is positive, namely the idiosyncratic risk premium is positive. The results also show that the higher the cash dividend that a company pays, the higher the information transparency and the lower the noise trading risk, the lower the idiosyncratic risk premium. The more optimistic the investors and the higher the unexpected liquidity, the higher the idiosyncratic risk premium.
This paper calculated the 1996-2014 average equity premium in our country, and based on the traditional utility function and generalized expected utility function of asset pricing model in the H-J variance next and relative risk aversion coefficient under the GMM estimation method is verified in our country there is equity premium puzzle, thus is established considering the disaster risk asset pricing model to explain the equity premium puzzle, the conclusions include:1) 1996-2014 average equity premium of 8.64% in our country, and stock returns volatility is bigger; 2) does exist in our country the equity premium puzzle, the generalized expected utility function is only considered unable to reasonably explain our country equity premium puzzle; 3) under the risk aversion coefficient of reasonable time-varying catastrophe model can well explain the equity premium puzzle in our country, especially the stock market bear market time-varying catastrophe model can reflect the disaster impact on the investors investment behavior and the influence of asset price risk premium; 4) because our country stock return volatility and dividend growth rate volatility smaller, this paper verifies the disaster perspective dividend ratio can effectively predict the stock excess returns, provide stability for the investment decisions in the future scientific indicators and research framework.
Considering the financial markets' characteristics of the cross-correlation in the case of nonlinearity and non-normality, this paper mainly quantitative studies the dependency of the CSI 300 futures market and spot market by applying detrend cross-correlation analysis, multifractal asymmetric detrend cross-correlation analysis method and detrend cross-correlation analysis based on the time-delay, which are more in line with the financial market. The results show that there are obvious cross-correlation characteristics between futures and spot markets in China, and the cross-correlation is multifractal; When futures market and spot market have different trends, the two markets shows that the cross-correlation is asymmetric, and the long-range cross-correlation is more significant while the futures market and spot market with downtrends. The direction of transmission of the cross-correlation between the markets is bidirectional, as well as the two market are more sensitive to the information in a short time and response more quickly. When futures market or spot market less lag 5 days respectively, futures market has a greater impact on the spot market. The results will provide a better reference for the nonlinear dependency between markets and the complex mechanism.
Asymmetric information makes the allocation of resources always not the optima in the traditional financial environment, resulting in the traditional investment institutions gradually narrowing their profit margins. Under the background of Internet finance, by introducing e-commerce platforms, we improve the traditional model in which investment institutions provide financing to small and medium-sized enterprises (SMEs) directly, and take into account a new tripartite participate in indirect investment and financing incentive mode. Then, by using principal-agent theory, this paper quantitative study investment revenue-sharing contracts among traditional financial institutions, e-commerce platforms, as well as SMEs. Furthermore, we empirically analyze the impact of the key parameters on the investment income and investment decisions by use of numerical cases. The results show that compared with the traditional financial pattern, when the operation capacity of SMEs is at lower level, the introduction of e-commerce platforms can reduce the threshold for SMEs financing and increase the credit lines; also, the investment efficiency of investment institutions improves while reducing the information rent obtained by SMEs, thereby effectively alleviating the financing difficulty of SMEs which is caused by the information asymmetry between investment institutions and SMEs.
With the assumption that manager stand for the value of all shareholders, this paper builds a theoretical model of the pricing of loan guarantee under the asymmetric information condition. The pricing model indicates that:1) under the mutual information asymmetric conditions, the increase of equity value of guarantor by information manipulation lets guarantors with high probability of insolvency enter the guarantee market and lets guarantors with low probability of insolvency exit the market; 2) under the condition in which debtor is informational inferior, guarantors with high probability of insolvency can not enter the guarantee market but guarantors with low probability of insolvency exit the market; 3) under the condition in which creditor is informational inferior, guarantors with high probability of insolvency enter the guarantee market and guarantors with low probability of insolvency still stay in the market, making the market over credited. Using the data from the listed companies from Chinese stock market, the empirical evidence suggest our theoretical production, revealing that information manipulation by guarantor expands the loan guarantee market and increase the risk of financial system.
The generosity of returns policy is usually a sign of quality that consumers receive in traditional "bricks-and-mortar", where high quality is defined as a low likelihood of product return. Existing literature, based on signaling theory, suggests that money-back guarantees (MBGs) will be utilized by high-quality firms. But nowadays, almost all the e-tailers offer MBGs, that is to say, the story of "clicks-and-mortar" goes not the same way as the traditional "bricks-and-mortar". To understand this phenomenon, we develop a stylized two-segment market setting, to find in which situation MBGs can greatly improve the profit. Our model captures important features of MBGs sales including demand uncertainty, consumer valuation uncertainty, consumer returns and so on. We show that selling with MBGs increases e-tailers' sales and profit. Furthermore, MBGs is the best returns policy for mid-quality e-tailers under certain technical cost and returns hassle. In addition, adding compensation for MBGs returns policy is usually the strategy of low-quality e-tailers to reduce returns rate.
This paper constructs a conditional factor pricing model and accommodates it in the framework of GMM and this yields rich testable hypothesis. The main conclusions can be summarized as below:Our conditional pricing models indeed consider the conditional information in pricing, and conditional information variables which have more predicting power will be more decisive in pricing. Globally speaking though representative investors from different countries will take different views on same conditional information, and their incentives to inter-temporal hedging and dynamic strategy are comparable. Furthermore, conditional information variables in China differ from those countries in their predictability power and direction, while the economy system in China seems to receive less influence from global recessions. In all, we claim conditional information are helpful with describing the risk-premium trade-off in bond returns, and it makes conditional asset pricing a promising endeavor in future researches of financial economics.
Based on a supplier's capital constraint problem, how two competing manufacturers improve the supplier's capital constraint by adopting financial subsidies under uncertain demand was investigated. A two-stage model with two competing manufacturers and a supplier was built. Meanwhile, manufacturers' equilibrium subsidies and equilibrium ordering decisions were provided. Moreover, the impacts of the manufacturer's financial opportunity cost as well as the supplier's capital level on the equilibrium subsidies were characterized. It reveals that, when the financial opportunity cost or the supplier's capital level is lower than a certain threshold value, both manufacturers offer subsidies; when the financial opportunity cost or the supplier's capital level is higher than a certain threshold value, neither manufacturer offers subsidy; otherwise, only one manufacturer offers subsidy. Finally, when the supplier doesn't provide wholesale price discount, the more manufacturers offer subsidies, the more benefits the supplier gains.
This study investigated how two types of free-riding effects may influence quality disclosure and pricing decision in a dual-channel supply chain, consisting of an upstream manufacturer, which owns an electronic channel, and a downstream retailer. In this paper we incorporated consumer attentiveness, as well as search costs, into a model of quality disclosure, to describe end consumers' surplus of purchase and both channels' demand. Then we derived the channel's optimal pricing strategy and disclosure conditions under two free-riding formats, respectively. And the impact of consumer attentiveness, search costs and product differentiation between two channels on quality disclosure was analyzed, too. We next compared the decisions of the manufacturer and the retailer under two free-riding formats to derive the influence exerted on the point-of-sale terminal free-riding effect. Our results suggest that:when considering free-riding effect, a retailer discloses the quality to consumers if and only if the quality is appropriate and the wholesale price is sufficiently low; a retailer should disclose less quality information as the share of partially informed consumers (informed about one channel but not the other) increases, as consumer search costs increase, or as product differentiation between two channels decreases; the point-of-sale terminal free-riding effect leads to a lower incentive for information revelation; if some conditions are satisfied for consumer attentiveness, more information will be provided than that when the wholesale price free-riding effect is considered only; when the point-of-sale terminal free-riding parameter is sufficiently high, the greater it is, the more incentives a manufacture will have to induce his retailer to disclose information.
Due to the research gap in how to identify competency trap, this study investigates how organizations identify and solve the competency trap by linking performance feedback theory and capability reconfiguration theory. This paper provides an insightful suggestion to understand the microfoundations of the organizational capabilities. Compared to the dominant logic in strategic management areas that competitive advantage comes from managerial foresight, the main theoretical contribution of this paper is to propose a backward-looking and problem-oriented process of capability reconfiguration, which is more consistent with the hypothesis of managerial bounded rationality. In other words, it is goal-driven decision-making process that can be seen as microfoundations of the source of competitive advantage:a reasonable goal-driven search behavior not only can help organizations involve with rent appropriation process as much as possible, but also helps managers to identify when to engage in rent generation process by selecting variation of the organizational routines in order to overcome competency trap.
According to "main manufacturer-supplier" multiagents collaborative innovation patterns of complex products, in the aspect of the main manufacturer's intervention and coordination to suppliers' resources integration, this paper set up the decomposition steps of complex product resource integration based on related theory of project management, selected suppliers' available resources as the research object, and established multi-agent resource integration utility function. Then, considering the incomplete information of resources integration, the paper set up a decision-making model for main manufacturer. The decision-making model was based on the work breakdown structure and useful for the main manufacturer to optimize the resources integration of suppliers. Finally, the study results show that when main manufacturer takes resource integration to suppliers group, value-added utility of suppliers' group resources improves significantly, and multi-agent collaborative innovation efficiency of complex products increases significantly.
Aiming at the new ship price fluctuating mechanism, by analyzing the weight and way of factors that influence the volatility of ship price, this article researched the formation process of new ship price volatility and its interaction system. Firstly, in order to solve the extreme value problem of multivariate data, a uniform sampling method was put forward based on Newton's law of motion and corresponding weight vectors were generated on a unit sphere in the high-dimensional space, then time series were translated into projection sequences through mapping on different weight vectors. Secondly, this paper applied empirical mode decomposition (EMD) to analyze projection sequences and generated stationary series in different measurement scales, which reduced the effects of non-stationary and irregular data. Thirdly, considering the discrete features of random sampling, R-square of intrinsic mode functions (IMFs) was chosen as optimization goal, which was solved on continuous unit sphere by applying genetic algorithm. Finally, through analysis on the multivariate correlation between new ship price and its related factors, a good fitting curve was drawn while the weights of factors were got. The result showed that this method can effectively solve the extreme value problem of multivariate sequence and correlation analysis problem of multiple nonstationary sequences. It considered more associated factors to describe the curve of new shipbuilding price, and provided a new method for the price prediction of ships.
Based on three practical assumptions that incorporate the impact of maritime cabotage legislations on route design, allow the vessels to visit unlimited number of ports in multi-port calling operation, and extend single route to a finite number of routes in the pair of origin-destination ports, a mixed 0-1 linear programming mathematical model is formulated for route design and capacities allocation such that the total costs of single shipping service provider's hub-and-spoke network subject to maritime cabotage legislations are minimized. Subsequently, a Lagrangian decomposition approach which is capable of obtaining high quality solutions in reasonable times is proposed. Finally, the conclusion is reached by numerical experiments that, the total costs will significantly decrease if the relaxed maritime cabotage legislations are applied in coastal countries or single shipping service provider consolidates its vessels capacities.
This article studied the kind of charitable fund allocation problem which is consist of N applicants and an allocator, aiming at maximizing the social welfare and finally designed a corresponding allocation and inspection mechanism when the applicants are all identical. The mechanism stops the lying behavior of applicants effectively based on the dominant incentive compatible constraints. The results show that truth reporting is a Nash equilibrium for each applicant considering that the other applicants report truthfully. The allocation of each applicant relies on the worst type applicant in each report under the optimized allocation situation. Through an example analysis of two applicants, the manipulation of this new mechanism is identified. The research provides a reference for such kind of funding allocation and inspection problem.
This paper proposes a research framework for forecasting audience ratings of seasonal entertainment TV shows based on the TEI@I methodology. Seasonal entertainment shows are emerging in China's television industry in the past three years. The forecast of their audience ratings is fundamental to the optimization of program scheduling and the scientific pricing of advertisements. As supplement to conventional data, the Baidu index and the Sina microblog index have been used in forecasting audience ratings. The resulting linear regression model demonstrates the following conclusions:the ratings of the first episode dictate those of the subsequent episodes; the average ratings are decreasing over the years; ratings tend to peak in winters and on Fridays; the two Internet indices show significant positive correlation with the ratings. Besides linear regression, RBF neural network, and support vector regression are experimented, and the integrated technology are employed. The experiment results show that the utilization of big data on internet make noticeable improvements to the forecasting accuracies, and the integrated technology outperforms in predicting the future trend of ratings.
In order to solve the uncertain decision making problems with information uncertainty and incomplete information, the Dempster-Shafer theory-based intuitionistic trapezoidal fuzzy IOWA (DS-TrIFIOWA) operator is defined. Firstly, the intuitionistic trapezoidal fuzzy numbers and their corresponding algorithms and aggregation operators are introduced. Then, based on Dempster-Shafer theory and intuitionistic trapezoidal fuzzy numbers, taking into account the decision-makers' subjective characteristics, DS-TrIFIOWA operator is defined and some properties on the DS-TrIFIOWA operator are presented. Further, a novel method based on DS-TrIFIOWA operator for decision making under uncertainty is developed. Finally, an illustrative example shows the feasibility and availability of the proposed method.
Although activities of daily living (ADL) is an important indicator of the health status of the elderly, the rigorous quantitative studies of the relationship between it and the residual life has been well studied. According to the panel survey data of the elderly aged from 55 upward from China health and nutrition survey, we constructed a stochastic filtering model to predict the residual life based on ADL. Then, the goodness-of-fit test was carried out to test the model. The result demonstrates that the ADL which is closely related to health status can be well used in residual life prediction when biochemical markers are not available in most cases. It provides a scientific basis for paying attention to the ADL of the elderly which is advocated by population health management and an important reference for determining premiums by life insurance companies through the ADL of the elderly.
System design optimization based on reliability is closely linked with economy. Under the conditions that the life of components follows Weibull distribution and group strategy is applied to preventive maintenance, design cost function, manufacturing cost function and maintenance cost function are presented respectively for a multi-unit system which is composed of identical units. And then, a lifecycle costs optimization model under reliability constraints is given. Reliability design value and group preventive maintenance policy in operation phase are comprehensively analyzed by the model. A decision method of equilibrium area for system design is put forward, which includes balanced lifecycle costs, required design reliability and group preventive maintenance period. Finally, an example analysis of switching systems of a large-scale scientific facility is shown to demonstrate its effectiveness and applicability. In the case, curves between optimal lifecycle costs and required reliability design value are obtained. The curve of optimal lifecycle costs with group preventive maintenance strategy is compared with no group preventive strategy, and the intrinsic relationship of reliability-based design, maintenance strategy and the optimal lifecycle costs are revealed by a utility curve altogether. The proposed decision method is helpful to get a new equilibrium area when key parameters are changed by technological advance. Therefore, it is of great significance for system engineers to carry out reliability-based design optimization by these provided solutions and methods.
Since the deteriorating effect of the facilities usually appears in the real-world flow shop scheduling, a multiobjective optimization model is built in order to minimize the makespan and the total tardiness simultaneously, where the normal processing time of job on each machine is a linear increasing function of its starting time. Then a decomposition based adaptive multipopulation multiobjective genetic algorithm is proposed to solve it. The proposed algorithm decomposes the multiobjective optimization problem into multiple single objective subproblems, which will be introduced to be solved step by step. According to the distribution of population in the objective space and solution space at each iteration, the current solved subproblems are solved by constructing the subpopulation, respectively. Experimental results on instances show that the proposed algorithm can get better quality and distributed nondominated solution set in solving the proposed problem.
In the present study, an optimization model, which is defined as a problem specified multi-depot vehicle routing problem with time windows (MDVRPTW), is developed for dealing with the large scale routing problem in secondary petroleum product delivery. The MDVRPTW model is subsequently decomposed into two separate sub-problems, and correspondingly a two-stage optimization procedure is proposed. A modified hierarchical clustering algorithm is used to solve demand assigning problem, and an enhanced genetic algorithm is designed to cope with truck allocation problem. For truck allocation, which could be considered as a customer partition problem, a new distance measure named expected saving distance is proposed to comprehensively distinguish the geographical distribution of oil stations with respect to deports. Enhanced genetic operators are also designed based on the new measure to improve the speed, quality, and stability of the convergence of evolutionary processes. Simulated examples are employed to demonstrate the effectiveness and efficiency of the proposed methods.
The Hidden Markov-Bayes networks (HM-Bayes) based precipitation interpolation method has the strong statistic basis and high precision, but it fails to take the full consideration of the impacts of physical geographical elements on precipitation interpolation. Based on the interactions between precipitation processes and land surface features, this paper improved the HM-Bayes based interpolation model by building up the spatial correlations between precipitation and elevation, slope and aspect, and took the monthly precipitation of 32 hydrologic stations of the Wuding River basin in 264 months as the example to test its performance. Results indicate that the root mean square error and relative error of the improved model are 24.25mm/month and 0.24, which decrease by 23.62\% and 33.43\% relative to the original model. Therefore, the improved model is highly accurate and its accuracy increases significantly. In particular, in the areas with big terrain differences and sparse stations, the accuracy improvement is quite obvious. Meanwhile, this model has the advantages of explicit physics meaning, extensive feasibility, high calculation efficiency, and great flexibility, therefore it has great potentials to be extended to the largely terrain different and ungauged basins.
Dam safety evaluation is a complicated and comprehensive evaluation problem involving multiple factors, multiple hierarchies and compound uncertainties. Through the introduction of the cloud model theory specialized in uncertainty problems into dam safety evaluation, the paper makes a research on the ubiquitous uncertainties of dam safety monitoring data, and proposes a multi-hierarchical comprehensive evaluation method for dam safety based on cloud model. By using a group of random numbers with stable tendencies to replace definite fuzzy degrees of membership and utilizing cloud generators to create membership clouds, the approach obtains a comprehensive dam safety evaluation result characterized by numerical features of cloud model and considering uncertainty of monitoring data. It not only gives a reasonable assessment to the state of dam safety, but also shows the credibility of this evaluation result and instabilities for the result created by uncertainties. Compared with the traditional fuzzy synthetic evaluation approach, examples show that the comprehensive dam safety evaluation method based on cloud model proposed in the paper is reasonable, feasible and superior.
Aiming at the uncertainty of attribute values and expert advice during the decision-making allocation process of manned/unmanned combat aerial vehicle cooperative engagement, this paper applied interval-valued intuitionistic fuzzy multiple attribute decision-making (IVIFMADM) method to deal with uncertain data integratedly. Firstly, consistency test for expert advice matrix was carried out, and group decision-making matrix through convergent iteration was generated afterwards. Then, it adopted entropy method to determine the weight value of each attribute, which with higher entropy value would be assigned higher weight value. After that, by using information aggregation operator, it combined modified grey relational analysis as well as weight values to obtain similarity degree between all attribute values and decision-making levels, and the final decision-making level was determined on this basis. Finally, the feasibility and stability of the method was verified by a practical example.