Yingchao Zou

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For the modeling of complex and nonlinear crude oil price dynamics and movement, wavelet analysis can decompose the time series and produce multiple economically meaningful decomposition structures based on different assumptions of wavelet families and decomposition scale. However, the determination of the optimal model specification will critically affect(More)
As a typical nonlinear and dynamic system, the crude oil price movement is difficult to predict and its accurate forecasting remains the subject of intense research activity. Recent empirical evidence suggests that the multiscale data characteristics in the price movement are another important stylized fact. The incorporation of mixture of data(More)
In this paper, we propose a new entropy-optimized bivariate empirical mode decomposition (BEMD)-based model for estimating portfolio value at risk (PVaR). It reveals and analyzes different components of the price fluctuation. These components are decomposed and distinguished by their different behavioral patterns and fluctuation range, by the BEMD model.(More)
The electricity market has experienced an increasing level of deregulation and reform over the years. There is an increasing level of electricity price fluctuation, uncertainty, and risk exposure in the marketplace. Traditional risk measurement models based on the homogeneous and efficient market assumption no longer suffice, facing the increasing level of(More)
With the electricity market reform in recent decades, the electricity price volatility brings more uncertainty and greater risks. This paper proposes a novel risk measurement approach Based on the EMD algorithm to estimate Value at Risk (VaR) in the electricity market. The EMD algorithm is used to decompose the time series into several intrinsic mode(More)
With the accelerating level of global integration, the volatilities across exchange markets are co-moving with higher level of fluctuation as well as more complicated dynamic inter correlations, which are key to the deeper understanding and proper measurement of risk. Thus, we propose the multivariate wavelet based Value at Risk estimation algorithm to(More)
This paper proposes a modified grey wave forecasting method for time series with irregular fluctuation ranges. This method uses quantile to define the contour lines and forecast future values based on contour time sequences decided by qualified unequal-interval contour lines. For the empirical analysis, this paper uses monthly prices of two metals - nickel(More)
The fractal characteristic of the electricity market has attracted significant research attention in recent years. And the heterogeneous microstructure analysis of the fractal behaviors represent a natural step forward to the understanding and modeling of the complex electricity price behaviors. In this paper, we introduce the Empirical Mode Decomposition(More)