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A b s t r a c t This study aims to apply value-at-risk (VaR) models to evaluate the risk of dry bulk freight rates when there is an asymmetric long-memory volatility process. The VaR estimations as well as expected shortfalls for both short and long trading positions are conducted. We use the Fractionally Integrated GARCH, Hyperbolic GARCH and Fractionally Integrated APARCH models to analyse the performance of the VaR models with the normal, Student-t and skewed Student-t distributions. Empirical results suggest that precise VaR estimates may be obtained from an asymmetric long-memory volatility structure with the skewed Student-t distribution. Moreover, the asymmetric FIAPARCH model outperforms than other models in out-of-sampling forecasting. Therefore, our findings provide a more accurate estimation of VaR for dry bulk freight rates. These results present several potential implications for dry bulk freight market risk quantification and hedging strategies.

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The purpose of this research is to accomplish the ZPETC (Zero Phase Error Tracking Control) Path-Tracking gain-scheduling control design and real-time multi-task flight simulation for the automatic transition of tilt-rotor aircraft.Firstly, we select 20 flight equilibrium points during the automatic transition through the trim operation. For each equilibrium state, we can get a set of Jacobian matrix A, B of the linearized equation by using the numerical linearization method and perform the flight control system design. Due to the highly instability of the system for the period of the dynamic transition maneuver, if we want to stabilize the unstable aircraft and do the desired path tracking for the vertical take off flight, then it is necessary to use the optimal controller and the ZPETC method.In this research, we use the quadratic synthesis method to find an optimal control gain for each flight equilibrium point and then perform the desired VTOL (Vertical Take-Off and Landing) transition path tracking by using ZPETC method. Also we utilize real-time look-up control gain computation from the selected 20 flight equilibrium points to achieve the gain-scheduling control task.