Rongda Chen

A generalized voter model with time-decaying memory on a multilayer network

By incorporating a multilayer network and time-decaying memory into the original voter model, we investigate the coupled effects of spatial and temporal accumulation of peer pressure on the consensus. Heterogeneity in peer pressure and the time-decaying mechanism are both shown to be detrimental to the consensus. We find the transition points below which a consensus can always be reached and above which two opposed opinions are more likely to coexist. Our mean-field analysis indicates that the phase transitions in the present model are governed by the cumulative influence of peer pressure and the updating threshold. We find a functional relation between the consensus threshold and the decay rate of the influence of peer is found. As to the pressure. The time required to reach a consensus is governed by the coupling of the memory length and the decay rate. An intermediate decay rate may greatly reduce the time required to reach a consensus.

Coupled effects of local movement and global interaction on contagion

Abstract By incorporating segregated spatial domain and individual-based linkage into the SIS (susceptible–infected–susceptible) model, we propose a generalized epidemic model which can change from the territorial epidemic model to the networked epidemic model. The role of the individual-based linkage between different spatial domains is investigated. As we adjust the timescale parameter τ from 0 to unity, which represents the degree of activation of the individual-based linkage, three regions are found. Within the region of 0 < τ < 0.02 , the epidemic is determined by local movement and is sensitive to the timescale τ . Within the region of 0.02 < τ < 0.5 , the epidemic is insensitive to the timescale τ . Within the region of 0.5 < τ < 1 , the outbreak of the epidemic is determined by the structure of the individual-based linkage. As we keep an eye on the first region, the role of activating the individual-based linkage in the present model is similar to the role of the shortcuts in the two-dimensional small world network. Only activating a small number of the individual-based linkage can prompt the outbreak of the epidemic globally. The role of narrowing segregated spatial domain and reducing mobility in epidemic control is checked. These two measures are found to be conducive to curbing the spread of infectious disease only when the global interaction is suppressed. A log–log relation between the change in the number of infected individuals and the timescale τ is found. By calculating the epidemic threshold and the mean first encounter time, we heuristically analyze the microscopic characteristics of the propagation of the epidemic in the present model.

Self-reinforcing feedback loop in financial markets with coupling of market impact and momentum traders

Abstract By incorporating market impact and momentum traders into an agent-based model, we investigate the conditions for the occurrence of self-reinforcing feedback loops and the coevolutionary mechanism of prices and strategies. For low market impact, the price fluctuations are originally large. The existence of momentum traders has little impact on the change of price fluctuations but destroys the equilibrium between the trend-following and trend-rejecting strategies. The trend-following herd behaviors become dominant. A self-reinforcing feedback loop exists. For high market impact, the existence of momentum traders leads to an increase in price fluctuations. The trend-following strategies of rational individuals are suppressed while the trend-following strategies of momentum traders are promoted. The crowd–anticrowd behaviors become dominant. A negative feedback loop exists. A theoretical analysis indicates that, for low market impact, the majority effect is beneficial for the trend-followers to earn more, which in turn promotes the trend-following strategies. For high market impact, the minority effect causes the trend-followers to suffer great losses, which in turn suppresses the trend-following strategies.

A generalized public goods game with coupling of individual ability and project benefit

Facing a heavy task, any single person can only make a limited contribution and team cooperation is needed. As one enjoys the benefit of the public goods, the potential benefits of the project are not always maximized and may be partly wasted. By incorporating individual ability and project benefit into the original public goods game, we study the coupling effect of the four parameters, the upper limit of individual contribution, the upper limit of individual benefit, the needed project cost and the upper limit of project benefit on the evolution of cooperation. Coevolving with the individual-level group size preferences, an increase in the upper limit of individual benefit promotes cooperation while an increase in the upper limit of individual contribution inhibits cooperation. The coupling of the upper limit of individual contribution and the needed project cost determines the critical point of the upper limit of project benefit, where the equilibrium frequency of cooperators reaches its highest level. Above the critical point, an increase in the upper limit of project benefit inhibits cooperation. The evolution of cooperation is closely related to the preferred group-size distribution. A functional relation between the frequency of cooperators and the dominant group size is found.

Forecasting CSI 300 Volatility: The Role of Persistence, Asymmetry, and Distributional Assumption in Garch Models

This study investigates the daily volatility forecasting for China Securities Index-C300 series from 2002 to 2010 and identifies the source of performance improvements between volatility specification and distributional assumption. Empirical results suggest that CGARCH model achieves the most accurate volatility forecasts. Such evidence, along with the results of sign bias tests, demonstrates that modeling persistence components is more important than specifying asymmetric components for improving volatility forecasts of financial returns. Furthermore, the GARCH models with Gaussian distribution are preferable to those with more sophisticated error distributions.

Financial Repression Approach to the Financing Difficulty of the Small and Medium-Sized Enterprises: Empirical Evidence from China

It is a universal phenomenon of the financing difficulty of the small and medium-sized enterprises, and opinions vary from theory to practice about its causes. With the Grey Prediction GM (1, 1) Model, this paper predicts the monetization ratio and FIR in the next few years properly. With the theory of financial repression and financial deepening, this paper focuses on the performance of the financial repression in China and its influences on the financing of the small and medium-sized enterprises. The paper argues that the financial repression in China should be responsible for the financing difficulty of the small and medium-sized enterprises. The paper concludes that accelerating the process of the reform of interest rates and promoting the efficiency of the financial market system etc. Are the ways to overcome the difficulty.

The Volatility of Stock Return in GEM Broad

The GEM [Growth Enterprises Market] board has been run for two years. It has been playing an very important role in the capital market of our country. This paper we use the class of ARCH model for analysis of the stock return in GEM board. We find that it has strong volatility and the volatility lasts a long time. In the end, we provide some recommendations on GEM future development.

Efficiency Test in Chinese Plastic Futures Market

In order to test the efficiency of Chinese plastic futures market, we firstly use variance ratio under random walk model to test the price sequences of LLDPE and PVC, which shows that this market is of week form efficiency. Then an assistant method, JJ Cointegration test is completed, which shows that the market is efficient in the short run concerning the price discovery function. The two methods make it clear that Chinese plastic futures market is in weak form efficiency in the short term, and the price discovery functions well.

Nonlinear VaR Model of Options Portfolio under Multivariate Mixture of Normals Distributions

The paper proposes a kind of nonlinear VaR model of options portfolio under heavy-tailed market risk factors. The paper depicts heavy-tailed market risk factors using multivariate mixture of normals distribution, and derives the moment generating function that reflects the change in options portfolio value. Moreover, to make use of the relationship between characteristic function and moment generating function, the paper develops Fourier-Inversion method and adaptive Simpson rule with iterative algorithm of numerical integration into nonlinear VaR model of options portfolio, and calculates the VaR values of portfolio. Numerical results show that the VaR values using Fourier-Inversion method is slight difference from the VaR values using Monte Carlo simulation method. However, the calculation speed using Fourier-Inversion method is obviously quicker than the speed using Monte Carlo simulation method.

Nonlinear VaR Model of FX Options Portfolio Based on Importance Sampling Technique

To overcome the difficulty in estimating low probability, the paper proposes that importance sampling technique is developed upto non-linear VaR model of FX option portfolio. Producing more samples in corresponding region by changing expectation vector and covariance matrix of distribution of market factors returns, this makes the state not be rare event simulation. Accordingly, this decreases calculating effort in Monte Carlo simulation. Moreover, the loss probability of portfolio is estimated precisely. Precise estimation of loss probability of portfolio is a prerequisite to calculating VaR, which is a percentile of the loss distribution. The simulation result shows the algorithm has more much effectiveness of computational efficiency than the standard Monte Carlo simulation, and can lead to large variance reductions when estimating the loss probability of portfolio.