In seismic data processing, random noise seriously affects the seismic data quality and subsequently the interpretation. This study aims to increase the signal-to-noise ratio by suppressing random noise and improve th...In seismic data processing, random noise seriously affects the seismic data quality and subsequently the interpretation. This study aims to increase the signal-to-noise ratio by suppressing random noise and improve the accuracy of seismic data interpretation without losing useful information. Hence, we propose a structure-oriented polynomial fitting filter. At the core of structure-oriented filtering is the characterization of the structural trend and the realization of nonstationary filtering. First, we analyze the relation of the frequency response between two-dimensional（2D） derivatives and the 2D Hilbert transform. Then, we derive the noniterative seismic local dip operator using the 2D Hilbert transform to obtain the structural trend. Second, we select polynomial fitting as the nonstationary filtering method and expand the application range of the nonstationary polynomial fitting. Finally, we apply variableamplitude polynomial fitting along the direction of the dip to improve the adaptive structureoriented filtering. Model and field seismic data show that the proposed method suppresses the seismic noise while protecting structural information.展开更多
针对障碍期权的定价问题,给出了一种高效的蒙特卡罗(Monte Carlo,MC)模拟方法——基于布朗桥构造路径的随机化拟蒙特卡罗(Brownian bridge path randomization quasi Monte Carlo,BBPR-QMC)方法.首先,用Faure序列代替MC方法中的随机序列...针对障碍期权的定价问题,给出了一种高效的蒙特卡罗(Monte Carlo,MC)模拟方法——基于布朗桥构造路径的随机化拟蒙特卡罗(Brownian bridge path randomization quasi Monte Carlo,BBPR-QMC)方法.首先,用Faure序列代替MC方法中的随机序列,得到了Faure序列的拟蒙特卡罗(quasi Monte Carlo,QMC)模拟方法;其次,应用Moro算法得到了随机化拟蒙特卡罗(randomization quasi Monte Carlo,R-QMC)模拟方法;最后,将QMC方法和R-QMC方法结合,利用布朗桥技术来降低有效维,得到障碍期权定价的BBPR-QMC方法.数值试验表明,与MC方法和R-QMC方法相比较,BBPR-QMC方法模拟的价格与真实价格更接近、收敛速度更快.数值试验证实,BBPR-QMC方法是一种高效求解障碍期权定价的数值方法.展开更多
This paper presents structural approach for the valuation of credit risk. Credit risk arises whenever a borrower is expecting to use future cash flows to pay a current debt. It is closely tied to the potential return ...This paper presents structural approach for the valuation of credit risk. Credit risk arises whenever a borrower is expecting to use future cash flows to pay a current debt. It is closely tied to the potential return of investment, the most notable being that the yields on bonds correlate strongly to their perceived credit risk. Structural approach is based on the volatility of the total value of the firm. The credit risk to this measured in a standard way. The random time of default is defined in an intuition way. The default event is linked to the notion of the firm＇s insolvency. This approach is known to generated low credit spreads for corporate bonds close to maturity. It requires a judicious specification of the default barrier in order to get a good fit to the observed spread curves.展开更多
In this paper, using the kernel weight function, we obtain the parameter estimation of p-norm distribution in semi-parametric regression model, which is effective to decide the distribution of random errors. Under the...In this paper, using the kernel weight function, we obtain the parameter estimation of p-norm distribution in semi-parametric regression model, which is effective to decide the distribution of random errors. Under the assumption that the distribution of observations is unimodal and symmetry, this method can give the estimates of the parametric. Finally, two simulated adjustment problem are constructed to explain this method. The new method presented in this paper shows an effective way of solving the problem; the estimated values are nearer to their theoretical ones than those by least squares adjustment approach.展开更多
基金Research supported by the 863 Program of China(No.2012AA09A20103)the National Natural Science Foundation of China(No.41274119,No.41174080,and No.41004041)
文摘In seismic data processing, random noise seriously affects the seismic data quality and subsequently the interpretation. This study aims to increase the signal-to-noise ratio by suppressing random noise and improve the accuracy of seismic data interpretation without losing useful information. Hence, we propose a structure-oriented polynomial fitting filter. At the core of structure-oriented filtering is the characterization of the structural trend and the realization of nonstationary filtering. First, we analyze the relation of the frequency response between two-dimensional（2D） derivatives and the 2D Hilbert transform. Then, we derive the noniterative seismic local dip operator using the 2D Hilbert transform to obtain the structural trend. Second, we select polynomial fitting as the nonstationary filtering method and expand the application range of the nonstationary polynomial fitting. Finally, we apply variableamplitude polynomial fitting along the direction of the dip to improve the adaptive structureoriented filtering. Model and field seismic data show that the proposed method suppresses the seismic noise while protecting structural information.
文摘针对障碍期权的定价问题,给出了一种高效的蒙特卡罗(Monte Carlo,MC)模拟方法——基于布朗桥构造路径的随机化拟蒙特卡罗(Brownian bridge path randomization quasi Monte Carlo,BBPR-QMC)方法.首先,用Faure序列代替MC方法中的随机序列,得到了Faure序列的拟蒙特卡罗(quasi Monte Carlo,QMC)模拟方法;其次,应用Moro算法得到了随机化拟蒙特卡罗(randomization quasi Monte Carlo,R-QMC)模拟方法;最后,将QMC方法和R-QMC方法结合,利用布朗桥技术来降低有效维,得到障碍期权定价的BBPR-QMC方法.数值试验表明,与MC方法和R-QMC方法相比较,BBPR-QMC方法模拟的价格与真实价格更接近、收敛速度更快.数值试验证实,BBPR-QMC方法是一种高效求解障碍期权定价的数值方法.
文摘This paper presents structural approach for the valuation of credit risk. Credit risk arises whenever a borrower is expecting to use future cash flows to pay a current debt. It is closely tied to the potential return of investment, the most notable being that the yields on bonds correlate strongly to their perceived credit risk. Structural approach is based on the volatility of the total value of the firm. The credit risk to this measured in a standard way. The random time of default is defined in an intuition way. The default event is linked to the notion of the firm＇s insolvency. This approach is known to generated low credit spreads for corporate bonds close to maturity. It requires a judicious specification of the default barrier in order to get a good fit to the observed spread curves.
文摘In this paper, using the kernel weight function, we obtain the parameter estimation of p-norm distribution in semi-parametric regression model, which is effective to decide the distribution of random errors. Under the assumption that the distribution of observations is unimodal and symmetry, this method can give the estimates of the parametric. Finally, two simulated adjustment problem are constructed to explain this method. The new method presented in this paper shows an effective way of solving the problem; the estimated values are nearer to their theoretical ones than those by least squares adjustment approach.
