Modelling returns volatility: mixed-frequency model based on momentum of predictability

The estimation and prediction of financial asset volatility are important in terms of theoretical and practical applications. Considering that low-frequency and high-frequency information plays an important role in volatility prediction, this article proposes a mixed-frequency model based on the momentum of predictability (MF-MoP). To illustrate the advantages of the proposed model, comparative research is conducted on the prediction accuracy of volatility among the GARCH model, the Realized GARCH model and the MF-MoP model, by the loss function and MCS test. The empirical results show that the MF-MoP model has higher prediction accuracy than the other two models; especially based on skewed-t distribution, the MF-MoP significantly outperforms the competing models. Moreover, the MF-MoP model can improve the forecasting of volatility, regardless of different lookback periods (including 1, 3, 6 and 9 days), different data (including the CSI 300 index, the N225 index and the KS11 index), and realized measures (including RV, RRV and MedRV), indicating that the model is robust

Systemic risk in Chinese financial industries: a vine copula grouped CoVaR approach

This paper investigates systemic risk in Chinese financial industries by constructing a vine copula grouped CoVaR model, which accounts for the fact that various sub-industries are comprised of multiple financial institutions. The backtesting results indicate that the vine copula grouped model performs better in measuring the systemic risk in comparison to the vine copula model, which in turn validates the accuracy and effectiveness of the former. Moreover, the results indicate that banking is a major systemic risk contributor, even though it has a strong ability to resist risk. Additionally, the potential loss faced by the securities industry is big, but its systemic risk contribution is small. These results are of significance to investment decision and risk management

Correlations for the ignition delay times of hydrogen/air mixtures

Correlations for the ignition delay times of hydrogen/air mixtures were developed using the method of High Dimensional Model Representation (HDMR). The hydrogen/air ignition delay times for initial conditions over a wide range of temperatures from 800 to 1600 K, pressures from 0.1 to 100 atm, and equivalence ratios from 0.2 to 10 were first calculated utilizing the full chemical mechanism. Correlations were then developed based on these ignition delay times. Two forms of correlations were constructed: the first one is an overall general model covering the whole range of the initial conditions; while the second one is a piecewise correlation model valid for initial conditions within different sub-domains. The performance of these correlations was studied through comparison with results from the full chemical mechanism as well as experimental data. It was shown that these correlations work well over the whole range of initial conditions and that the accuracy can be significantly improved by using different piecewise correlations for different sub-domains. Therefore, piecewise correlations can be used as an effective replacement for the full mechanism when the prediction of chemical time scale is needed in certain combustion modeling.http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000286389300013&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701Multidisciplinary SciencesSCI(E)6ARTICLE2215-2215

Polar Functions for Anisotropic Gaussian Random Fields

Let X be an (N, d)-anisotropic Gaussian random field. Under some general conditions on X, we establish a relationship between a class of continuous functions satisfying the Lipschitz condition and a class of polar functions of X. We prove upper and lower bounds for the intersection probability for a nonpolar function and X in terms of Hausdorff measure and capacity, respectively. We also determine the Hausdorff and packing dimensions of the times set for a nonpolar function intersecting X. The class of Gaussian random fields that satisfy our conditions includes not only fractional Brownian motion and the Brownian sheet, but also such anisotropic fields as fractional Brownian sheets, solutions to stochastic heat equation driven by space-time white noise, and the operator-scaling Gaussian random field with stationary increments

Design of a rotary reactor for chemical-looping combustion. Part 1: Fundamentals and design methodology

Chemical-looping combustion (CLC) is a novel and promising option for several applications including carbon capture (CC), fuel reforming, H2 generation, etc. Previous studies demonstrated the feasibility of performing CLC in a novel rotary design with micro-channel structures. In the reactor, a solid wheel rotates between the fuel and air streams at the reactor inlet, and depleted air and product streams at exit. The rotary wheel consists of a large number of micro-channels with oxygen carriers (OC) coated on the inner surface of the channel walls. In the CC application, the OC oxidizes the fuel while the channel is in the fuel zone to generate undiluted CO2, and is regenerated while the channel is in the air zone. In this two-part series, the effect of the reactor design parameters is evaluated and its performance with different OCs is compared. In Part 1, the design objectives and criteria are specified and the key parameters controlling the reactor performance are identified. The fundamental effects of the OC characteristics, the design parameters, and the operating conditions are studied. The design procedures are presented on the basis of the relative importance of each parameter, enabling a systematic methodology of selecting the design parameters and the operating conditions with different OCs. Part 2 presents the application of the methodology to the designs with the three commonly used OCs, i.e., nickel, copper, and iron, and compares the simulated performances of the designs