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This paper proposed a method that combined target state and system error based on the maximum correntropy criterion unscented Kalman filter(MCUKF), namely ASMCUKF, which could solve the problems that the observation noise of sensor was heavy-tailed or had some sudden change in space-air-ground integrated sensor network. Firstly, MCUKF used unscented transformation(UT) to obtain the predicted state estimation and covariance matrix, and then used a non-linear regression model based on MCC to reconstruct the observed information and strengthen the robustness of UKF in heavy-tailed noise. The ASMCUKF algorithm established the state equation and the nonlinear observation equation with systematic errors through the expansion of target state vector, and made the error registration according to the estimated system errors to improve the influence of the system errors on the target state estimation. The simulation results show that the ASMCUKF has a better performance for the state estimation of the communication target than the traditional method in the environment of heavy-tailed non-Gaussian noise. [ABSTRACT FROM AUTHOR]

Applied with autoregressive exogenous model and vector error correction model, this article analyzes the nonperforming-loan rate of a commercial bank based on the house price falling scenario. Nonperforming-loan ratio is used to describe the credit risk and the pressure indicators, including CPI, lending rates, house prices, exchange rates, TED spread and M2, are used to construct the stress testing model of house loan. This article forecasts the fluctuations of nonperforming-loan ratios between the second quarter of 2010 and the first quarter of 2011 under the assumption of the lending rate rising and house prices falling. The results suggest that the nonperforming-loan ratios will rise sharply first, and then slow down to be steady in the stress scenarios. Among all of those factors, house price is the most influential one and its influence lasts the longest. [ABSTRACT FROM AUTHOR]

Compared with the large scale of presale property market in China, researches on the relationship between China's presale and spot real estate prices are far from adequate. By the experiences of research on financial market, this paper adopts VECM model to research price lead-lag relationship between presale and spot housing market in China. By testing both the short-run and long-run Granger casualty relationship, the results indicate that there's a bilateral price lead-lag relationship between Chinese presale and spot property market. The outcomes of VECM models and variance decomposition demonstrate that presale housing market plays a greater role in the property price discovery process in China. [ABSTRACT FROM AUTHOR]

The relationship between futures and spot prices for the China's commodity futures markets displays high and low volatility regimes that often affected by various factors, which greatly impacts the hedging behavior. The Markov regime-switching method was introduced to study the optimal hedging of China's commodity futures markets, and to analyze the hedging with regime-switching. The results show that there are different high and low volatility regimes in the relationship between futures and spot prices, the stability and duration of the high volatility regime are lower than the low volatility regime, and the regimes of the markets are closely related to the changes of basis. Moreover, hedging performance analysis shows that in the single regime models the hedging performance of MGARCH is better than the VECM, the VECM is better than the VAR, and the three models are better than the OLS model. And the hedging performance of the constant and time-varying transition probability Markov models is better than that of single regime models. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to describe the dynamic relationship between futures and spot cotton market in China. Price discovery and volatility spillovers were examined for futures and spot cotton market based on VEC model, Granger causality test, impulse response analysis and BEKK model. The empirical results show that there is a eointegration relation between spot and futures prices of cotton. The futures market is the leader of price discovery in long-term, although bidirectional Granger causality are observed in short run. Meanwhile, the response of futures market is faster than spot market when they received impacts at the same time. Besides, there are strong volatility lagging effects and volatility spillovers in both markets, which in futures market are dominant. [ABSTRACT FROM AUTHOR]

The cross-market interactional mechanism between Chinese and international nonferrous metal prices is investigated from a new perspective. The two-regime threshold vector error correction model (TVECM) with a single threshold cointegrating vector is employed to explore the relationship. The results indicate that the threshold vector error correction model can capture characteristics of the correlation between the futures prices of London Metal Exchange (LME) and Shanghai Futures Exchange (SHFE). There is different adjustment intensity in the different state. When the price of SHFE' copper or LME' aluminum cause the deviation from the equilibrium, the error correction mechanism will promote the price to the equilibrium with strong efforts. There is different observation in the different state. There are more samples when the price of LME' copper or the SHFE' aluminum deviate from the equilibrium. [ABSTRACT FROM AUTHOR]