A Trend-Switching Financial Time Series Model with Level-Duration Dependence

The financial time series model that can capture the nonlinearity and asymmetry of stochastic process has been paid close attention for a long time. However, it is still open to completely overcome the difficult problem that motivates our researches in this paper. An asymmetric and nonlinear model with the change of local trend depending on local high-low turning point process is first proposed in this paper. As the point process can be decomposed into the two different processes, a high-low level process and an up-down duration process, we then establish the so-called trend-switching model which depends on both level and duration (Trend-LD). The proposed model can predict efficiently the direction and magnitude of the local trend of a time series by incorporating the local high-low turning point information. The numerical results on six indices in world stock markets show that the proposed Trend-LD model is suitable for fitting the market data and able to outperform the traditional random walk model

Rapid synthesis of rGO–MoO₃ hybrids and mechanism of enhancing sensing performance to H₂S

The 2.5 wt% rGO–MoO3 hybrid prepared by an in situ microwave hydrothermal method has excellent sensing properties to ppm-level H2S at 110 °C.</p

Room temperature triethylamine sensing properties of polyaniline–WO₃ nanocomposites with p–n heterojunctions

A smart sensor based on PANI–WO3 nanocomposite loaded on PET thin film not only exhibits high sensitivity and selectivity to triethylamine at room temperature, but also has flexibility, simple fabrication and portable characters.</p

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A smart sensor based on hierarchical polyaniline microspheres loaded on PET film not only exhibits high sensitivity, good selectivity and low detection limit at room temperature, but also has features of flexibility, portability and transparency.</p