Insiders' Hedging for Jump Diffusion Processes with Applications to Index Tracking

The hedging problem for insiders is very important in the financial market.The locally risk minimizing hedging was adopted to solve this problem.Since the market was incomplete,the minimal martingale measure was chosen as the equivalent martingale measure.By the F-S decomposition,the expression of the locally risk minimizing strategy was presented.Finally,the local risk minimization was applied to index tracking and its relationship with tracking error variance (TEV)-minimizing strategy was obtained.

Research on Trajectory Tracking Method of Redundant Manipulator Based on PSO Algorithm Optimization

Aiming at the problem that the trajectory tracking performance of redundant manipulator corresponding to the target position is difficult to optimize,the trajectory tracking method of redundant manipulator based on PSO algorithm optimization is studied.The kinematic diagram of redundant manipulator is created,to derive the equation of motion trajectory of redundant manipulator end.Pseudo inverse Jacobi matrix is used to solve the problem of manipulator redundancy.Based on the tracking ellipse of redundant manipulator,the tracking shape of redundant manipulator is determined with the overall tracking index as the second index,and the optimization method of tracking index is proposed.The redundant manipulator contour is located by active contour model,on this basis,combined with particle swarm optimization algorithm,the point coordinates on the circumference with the relevant joint point as the center and joint length as the radius are selected as the algorithm particles for iteration,and the optimal tracking results of the overall redundant manipulator trajectory are obtained.The experimental results show that under the proposed method,the tracking error of the redundant manipulator is low,and the error jump range is small.It shows that this method has high tracking accuracy and reliability.

Evolutionary Finance： The Case of TEDPIX Tracker Fund Selection

Optimal allocation of financial resources is a critical factor in investment decisions. A proper action in this regard requires the existence of appropriate bases and investing tools and techniques in the capital market. One of these effective methods which is considered as the basis of new investment strategies, in addition to multiple unique features, is called index tracking. By considering the undeniable role of this approach in the future of capital markets, its investigation and implementation have been considered in this research and so the problem of optimal Tehran Exchange Dividend Price Index （TEDPIX） tracker fund selection is studied using a hybrid approach of genetic algorithm and quadratic programming. Neural network was applied to simulate unavailable data. Results illustrate the exactness and acceptable performance of the formed portfolios in several iterations such that achieving similar and even better performance compared to the index is a distinctive characteristic of the proposed algorithm.

Seasonal and inter-annual variations of Arctic cyclones and their linkage with Arctic sea ice and atmospheric teleconnections

The seasonal and inter-annual variations of Arctic cyclone are investigated. An automatic cyclone tracking algorithm developed by University of Reading was applied on the basis of European Center for Medium-range Weather Forecasts（ECMWF） ERA-interim mean sea level pressure field with 6 h interval for 34 a period. The maximum number of the Arctic cyclones is counted in winter, and the minimum is in spring not in summer.About 50% of Arctic cyclones in summer generated from south of 70°N, moving into the Arctic. The number of Arctic cyclones has large inter-annual and seasonal variabilities, but no significant linear trend is detected for the period 1979–2012. The spatial distribution and linear trends of the Arctic cyclones track density show that the cyclone activity extent is the widest in summer with significant increasing trend in CRU（central Russia）subregion, and the largest track density is in winter with decreasing trend in the same subregion. The linear regressions between the cyclone track density and large-scale indices for the same period and pre-period sea ice area indices show that Arctic cyclone activities are closely linked to large-scale atmospheric circulations, such as Arctic Oscillation（AO）, North Atlantic Oscillation（NAO） and Pacific-North American Pattern（PNA）. Moreover,the pre-period sea ice area is significantly associated with the cyclone activities in some regions.

Adaptive projected gradient thresholding methods for constrained l0problems

In this paper, we propose and analyze adaptive projected gradient thresholding(APGT) methods for finding sparse solutions of the underdetermined linear systems with equality and box constraints. The general convergence will be demonstrated, and in addition, the bound of the number of iterations is established in some special cases. Under suitable assumptions, it is proved that any accumulation point of the sequence generated by the APGT methods is a local minimizer of the underdetermined linear system. Moreover, the APGT methods, under certain conditions, can find all s-sparse solutions for accurate measurement cases and guarantee the stability and robustness for flawed measurement cases. Numerical examples are presented to show the accordance with theoretical results in compressed sensing and verify high out-of-sample performance in index tracking.

Comparison of population estimators and indices for monitoring house mice in sorghum crops

House mice(Mus musculus domesticus Schwarz&Schwarz,1943)are monitored in Australia and China to track changes in mouse population densities and forecast their potential damage to cereal crops.The present study compared population indices based on the number of different mice caught and overall trap success from live-trapping with an oil card index(OC)and a tracking index(T)for monitoring mice in sorghum crops immediately before crop maturation.T was measured as the percentage of track board covered with mouse footprints night-1,and OC as the percentage of card removed by mice night-1.The reliability of these abundance indices was quantified by Pearson correlation coefficient with the trappable population size(Ñ),which was estimated by capture-recapture over eight consecutive nights on 175×5 trapping grids,in sorghum crops on two properties on the Darling Downs,Queensland.Because of differences among individual mice in capture probability,Model Mh of program MARK was used to account for such heterogeneity and to estimate the size of each mouse population.The number of individual animals caught was more strongly correlated withÑthan trap success and,therefore,might be a more reliable index;the data suggest that three trapping occasions provide optimal precision for this index.T correlated significantly withÑonly at sites where the canopy of sorghum plants was closed,and its use should,therefore,be restricted to this habitat.OC did not correlate withÑbecause none or very little of the cards was eaten at low to moderate mouse densities.T and the number of animals caught over three trapping nights are recommended for monitoring mice in sorghum crops immediately prior to crop maturation.