The positive feedback trading phenomenon is significant in Chinese market, and buying-winners effect is much stronger than selling-losers effect. We call it rise-favor asymmetry of positive feedback trading. This paper studies if this rise-favor asymmetry has asset pricing power. This paper constructs reversal factor, positive feedback factor, and rise-favor asymmetry factor based on Fama-French three factor, and uses a sample that spans from Jan 1998 to Oct 2016 and contains daily data of all A shares that become a listed company before 2010 to do empirical tests. The paper finds that, the performance of rise-favor asymmetry factor is quite different from that of positive feedback factor and reversal factor; Although these three factors all have some pricing power individually, the pricing power of positive feedback factor and reversal factor is weak in the multi-factor pricing model, and only rise-favor asymmetry factor can significantly promote the pricing power of multi-factor model; The pricing power of rise-favor asymmetry factor does not result from price-rising chasing behavior, price-dropping chasing behavior, liquidity risk premium, or investor sentiment. In sum, rise-favor asymmetry is a new pricing factor that different from traditional factors, and its pricing power may relate to the market's compensation on the risk of irrational speculation.
This paper attempts to consider and solve the problem for companies to choose the optimal strategic route of green transformation technology investment based on economic fluctuation and their own situation. We apply a real option to conduct scenario analysis on the forecast economic development status and technology and get the optimal investment rules and the optimal choice route of the green transformation technology. The main results are:1) the initial role of carbon trading price is to promote the green transformation of high-energy enterprises; 2) enterprise's financial strength is an another important factor that influences green transition success and route selection for enterprise; 3) the key factors which influence green transition success and route selection for enterprise are the degree of economic prosperity, the height of the investment of the discount rate, and the development level of the green transformation technology. Furthermore, our theoretical model implicates that government should control the stability and prosperity of the economic environment and provide a good carbon trading mechanism and encourage to cultivate high green transformation technology with the high discount rate investment.
This paper extends the unified GARCH-Itô model proposed by Kim and Wang (2016) and introduces a more general method to model volatility with the combination of high-frequency and low-frequency data. The new method embeds a low-frequency GARCH structure into high-frequency volatility in a more flexible way, thus embraces a broader application. Theory and simulation study found good asymptotic property and finite sample performances of the quasi-maximum likelihood estimators proposed. In an empirical study, this new method was used to improve the bulk volume classification (BVC, Easley et al.(2013, 2016)). As a result, market participants' trading intentions were estimated more precisely.
Currently, there exists three kinds of steel trading markets in China:Spot market, futures market and B2B electronic trading market (Abbreviated as e-market). Do they reflect the steel market price common factor well? How about their dynamic evolution in terms of price discovery? These questions become hot point of steel producers, sellers, arbitrageurs, as well as market policy planners. In the light of vector error correction and conditional heteroscedasticity model, and analyzing the effects of past information to multiple dynamic conditional covariance matrix, this paper constructs time-varying information shares model based on two-dimensional and three-dimensional VECM-DCC-GARCH model to study the dynamic performance of steel markets in the long interval price discovery function. Empirical results of the daily data indicate that e-market exhibits greatest ability in incorporating information effecitively before hot roll bars futures established. After hot roll bars futures established, three kinds of steel market all contribute to the price discovery process. Most of the time, spot market leads the price discovery process, followed by the futures market and e-market. The role of e-market in price discovery is somehow considerable, while its role on price discovery evolves follower from dominator. In terms of steel markets in China, trading volume, margin level and liquidity have no obvious directly relationship with price discovery function.
Online portfolio selection is one of the fundamental problems in the field of computational finance. As financial markets are changing rapidly, investors need to dynamically adjust asset positions according to various kinds of information related to the capital market. Online portfolio strategy with side information is studied without probability assumptions on the asset prices. By using the relative entropy function to measure the distance between two portfolios, an online portfolio exponential gradient strategy with side information is proposed, and moreover it is proved a universal portfolio, i.e., its average growth rate is asymptotically the same as that of the best state constant rebalanced portfolio, which is offline. The strategy is tested on actual stock data, and the effect of transaction costs on the strategy is also analyzed, which the results show that this strategy can obtain higher returns.
In view of development lag has become the core factor to limit the efficiency of housing supply. Inspired by the continuous upgrading of domestic land leverage, we try to verify the mechanism of land leverage and development lag. We first use real option model to establish a more practical double stochastic differential equation and partial equilibrium model shows that when the market expectation is stable, the land development cycle is mainly determined by the land lever (i.e. the ratio of land price to housing price). In the past 2002-2015 years, the panel data regression of 31 provinces in China showed that, after controlling the external factors such as population density effectively, on average, the land leverage increased by 100 percentage points, and the development lag increases 20 percentage points. This conclusion is still stable after the test of the time trend, the impact of exogenous events and the location of the region. Then, the three stage mediating effect is established, and the overall mediating effect is 46% with the promotion of land leverage, the direct cost effect has become the main way to influence housing price compared with the indirect way of development lag. At the same time, there is a similar accelerator effect in land leverage, that is, with the improvement from lower to higher level, the positive spillover effect of land leverage on housing prices is stronger, and the effect is increased by about 80%. The study highlights the importance of structural reforms from the land supply side which implies the importance of effective management of development lag as well as land leverage in the overall policy framework of real estate regulation.
This paper selected the evaluation method of prospect theory as comprehensive evaluation method of evaluating Shanghai housing security policy effect, and then screened the corresponding evaluation index by means of correcting total correlation coefficient and factor analysis, thus laying the theoretical foundation for the scientific evaluation of Shanghai housing security policy effect. After model calculation had been done using the index data from 1998 to 2014, the change law of the comprehensive value estimating housing security policy effect was cleared, and the effects and function of various security housing policy was clarified. However, when compared with the inverted U-shaped development process of social security level, the exploration of multi-level housing security system is found to be relatively fallen behind for Shanghai.
Based on expected utility theory, the paper established a decision model for private sectors under social risks in PPP projects, in which private sectors' decision-making behavior was divided into positive one and negative one. Through discussion analysis, the paper summarized private sectors' social risk decision-making into four scenarios, where the private sectors must choose negative behavior in the case that private sectors fully bear the costs to deal with social risk. To resolve the problem, corresponding compensation mechanisms were put forward to ensure the positive behavior can be determined by private sectors under the four scenarios and improve the social efficiency of the PPP projects. In addition, the influence of long-term and short-term benefits as well as the contract period of PPP projects on social risk decision-making behavior was discussed in the paper. The conclusion can be drawn that the private sectors' attitudes to the long-term and short-term benefits are critical to determine the decision-making behavior. Moreover, partnerships and reasonable risk sharing is the effective approach to determine the positive behavior.
This paper studies a supply chain with one supplier and one buyer and explores the effect of complete inspection, sampling inspection, batch sampling inspection and combination strategy on the product quality control based on newsvendor model considering quality uncertainty and inspection error in decentralized and centralized supply chain. The results show that the increase of defective rate will reduce the retailer to order products, but will increase the order quantities and profits of the retailer under the combination strategy; and it is beneficial for the retailer under the complete inspection strategy in the centralized supply chain. Through comparative analysis of strategies:in the decentralized supply chain, if the defective rate is low, batch sampling strategy is optimal, but the combination strategy will be better with the improvement of the defective rate; in the centralized supply chain, the complete inspection strategy will be better. In addition, the selection of retailer quality control strategy is influenced by many factors, and the optimal strategy is not the same, but these factors will not change the trend of retailers' profits to change with the defective rate.
In the case that promotional local advertising of retailers undermine customer loyalty and reduce brand image. In order to analyze prerequisites that manufacturers carried out collaborative advertising in a cost-sharing form, and impacts of cooperative advertising on consumer demand and supply chain profits. Two competitive supply chains which were consist of single manufacturer and single retailer as the object of this paper. The Nash game model between supply chains and the Stackelberg game model with retailers as leaders were built. Cooperative advertising and non-cooperative advertising games in two sales cycles were compared and analyzed by considering long-term effects of advertising. The results show that prerequisites for manufacturers to cooperate advertising are obviously negative effect of advertising and high commodity substitution rate. When the commodity substitution is not obvious, cooperative advertising can effectively increase demand, on the contrary, the demand is reduced. Cooperative advertising does not improve retailer revenue. However, the incomes of manufacturers and total profits of supply chain are improved when the commodity substitution rate is low. The findings have a certain guiding significance to decision making of supply chain member on the local advertising practice.
Based on the evolutionary game method, influences of the costly second-party punishment mechanism on the equilibrium selection of the public goods game and the cooperative behavior of the population are investigated. The strategy evolution process of the population is described as a multidimensional Markov process. The evolutionary stable states of the system are analyzed based on the limit distribution of the stochastic process. Two kinds of punishments are considered respectively in this paper, namely, first-order punishments that only punish the defectors and second-order punishments that not only punish the defectors but also the cooperators who have not punished the defectors (second-order defection). The study reveals that compared with the first-order punishment, the second-order punishment mechanism can promote the evolution of cooperation within a larger parameter range. The system has critical values of punishment parameters for choosing different equilibrium results. The results are also compared with those of the corresponding deterministic replication dynamic model.
This paper proposes a competition and cooperation relationship model between high-speed rail and air transport based on the two-stage game theory. Firstly, it builds a one dimensional evolutionary game model from the perspective of passengers to calculate the best competition range. Then, it builds a competition and cooperation relationship model between high-speed rail and air transport from the perspective of price based on Cournot game theory. Finally, it uses the Bertrand game theory to apply the model through a distance perspective, and discusses the competition and cooperation between high-speed rail and air transport in order to find a scientific strategy to achieve a win-win situation. The results show that a distance range of 650 km~850 km is the most intense competition area between air transport and high-speed rail. With the increase of transportation distance, the game strategy of air transport changes from cooperation to competition. On the contrary, the strategy of high-speed rail changes from competition to cooperation.
In this paper, we assumed that machines have different energy consumptions or maintenance costs in the context of green manufacturing, and tried to solve the parallel machine scheduling problem under the condition of cost constraints. To minimize the maximum lateness, an integer programming model MIP was established and an improved algorithm for EDD (earliest due date firstly)-MEDD was designed. Then the feasibility of the MEDD algorithm was proved under the condition of cost constraints, and the worst error bound of the algorithm was also analyzed theoretically. By giving an example, we proved the feasibility of the algorithm. And its performance was verified by a large number of random data experiments. For a small scale, the solution of MEDD was compared with the exact solution of MIP. While the exact solution of MIP is too hard to obtain when it comes to a large scale, the optimal value of MLP of the linear programming relaxation model corresponding to MIP was taken as the lower bound to measure the solution of MEDD algorithm. All these results showed a great effectiveness of MEDD algorithm.
This work studies MapReduce model-based parallel machine scheduling. Each job with arbitrary release time and setup time consists of one map task and one reduce task. The map task can be split and processed on several machines simultaneously, while the reduce task has to be processed on a single machine and it cannot be started unless the map task has been completed, and the processing for any task cannot be interrupted. In this paper, we consider the MapReduce scheduling on parallel identical machines, aiming at minimizing the makespan. We formulate the problem as a mixed integer linear programming model, and develop an improved sine cosine algorithm (ISCA) using differential perturbation and dimension-by-dimension Levy perturbation to obtain a near-optimal solution. Computational comparisons between ISCA and genetic algorithm together with the classical SCA algorithm show that the proposed ISCA algorithm outperforms the other two algorithms. Besides, the ISCA is of an average relative deviation of 3.02% from the lower bound of the problem. Numerical computation verifies the effectiveness of the proposed algorithm.
The characteristics of multi-skilled resources and time window constraints on them are the key factors often considered in the field of software development, engineering design, equipment maintenance and so on. In many real projects, the execution of tasks allows to be interrupted. In this paper, an integer programming model is established for this preemptive project scheduling problem with time-window constraints on multi-skilled resources, and a branch and bound method is developed to construct a search tree to find solutions of the problem where each node represents a combination of tasks. To reduce the number of branch nodes, two valid pruning rules are proposed and the node priority rules are designed. For the task combination of each node, a greedy algorithm is employed to verify resource constraints. Using improved PSPLIB in experiments, the results show the effectiveness of dominance strategies, and the comparisons with the CPLEX and the basic heuristic algorithm reveal the efficiency and effectiveness of the proposed method in solving such problem. The solutions can provide support for the actual project scheduling to make better decisions.
Some efficiency antinomies can be found by example analysis when most of important DEA models are used. Namely, the higher the evaluation standards is, the larger the efficiency value of a fixed decision-making unit. In order to explore the occurrence causes and solution method of DEA efficiency antinomy, this paper firstly proves that the efficiency antinomy exists when some most important DEA models (including CCR model, BCC model, FG model and ST model) are used by examples. Then, it is explained theoretically that the origin of the DEA efficiency paradox lies in the short-tail phenomenon of data in decision making units, and the method for judging whether there is the short tail phenomenon is provided. At the same time, a revised DEA model is given, which can not only overcome the emergence of DEA efficiency paradox, but also improve the accuracy of efficiency measurement. Finally, a comparative study of the related models is given by using the provincial economic data in China from 2000 to 2014.
With respect to the emergency response problem with uncertain scenario predictions, a beforehand-ongoing two-stage decision making method is proposed considering that the prevention actions adopted beforehand will affect the effects of response actions when the emergency is ongoing. In the method, by calculating the utility of each response action, the most desirable response action concerning each prevention action and each scenario is determined. Then, based on the idea of regret theory, the excessive response matrix and insufficient response matrix for pairwise comparisons of prevention actions are constructed, and then an overall anticipated regret matrix is built for selection the desirable prevention action. Further, the global delight value, global regret value and ranking value of each prevention action is calculated according to the overall anticipated regret matrix. Moreover, the ranking of the prevention actions can be determined, and the desirable prevention action and the response action corresponding to each emergency scenario can be obtained. Finally, a case study is given to illustrate the use of the proposed method.
The idempotent, linear and affine properties of initial sequence operator, zero-starting sequence operators and initial zero-starting sequence operator were systematically studied. The closeness axiom of the grey relational degree was defined mathematically. Mathematical definition and physical significance of positive definiteness, affinity and affine transformation isotonicity were also expounded. Generalized grey relational analysis models and their corresponding improvements were essentially constructed based on the areas between sequence interpolation curves. By introducing distinguishing coefficient, the unified representations of generalized relational analysis models and improved models were given respectively. Furthermore, the parallelism, uniformity, affinity, parallel transformation isotonicity, multiple transformation isotonicity and affine transformation isotonicity properties, as well as the applicability were subsequently researched.
Based on the systematic analysis of the factors which influence the warranty strategy and the business performance, a new regional warranty differential pricing strategy on the basis of operational reliability was proposed. A mathematical model reflecting the quantitative relationship between operational reliability and different geographical regions was established in this study. And then a novel three-dimensional differential pricing system dynamics model that considers the regional differences of operational reliability, inherent reliability growth and warranty period was developed. Finally, the simulation analysis for warranty strategy of an air-conditioning enterprise is presented to verify the applicability and validity of the proposed model. The results show that, it would likely contribute to brand influence increase when the warranty period is extended appropriately to a certain threshold. Moreover, a moderate decline in the price of products with higher operational reliability and increase the price of products with lower operational reliability are effective ways to increase profits.
A joint optimization model of economic production quantity and condition-based maintenance policy is proposed in this paper, considering the situation that the production plan and maintenance schedule share the same machine. Using the random coefficient growth model to describe the degenerated condition, the condition monitoring is carried out when a lot is finished. The observed condition composed of two parts, the actual deterioration condition and the random error, once the condition information observed is equal to or higher than the preventive maintenance level, or the actual condition is equal to the failure level, the machine should be renewed. The cost and the length model in the renewal cycle are proposed, then the expected cost per unit time is modeled based on the renewal reward theory. The optimal condition of preventive maintenance level and production time of one lot can be calculated by minimizing the expected cost per unit time. Numerical examples are presented based on the data collected from a steel mill, the results are consistent with the actual situation.
The interaction of public opinion exists in both the real space and the virtual space. To specifically study the evolution process of public opinion in the two spaces, we first analyzed the characteristics of the evolution of public opinion in different spaces and the link between them in the process of evolution. Then, combined with the improved Hegselmann-Krause (HK) model, the online and offline public opinion evolution model based on the supernetwork was constructed. We also proposed a simulation system framework including initialization module, information propagation and interaction module and synchronization module. According to the direction of synchronization, two kinds of synchronization rate, real space-virtual space and virtual space-real space were proposed. Finally, through simulation experiments, the influence of synchronization ratio and space velocity radio on the evolution of public opinion was discussed.