semimartingale
- semimartingale的基本解释
-
-
半
- 更多网络例句与semimartingale相关的网络例句 [注：此内容来源于网络，仅供参考]
-
Under the assumptiom that the price procee of risky asset is assumed to be a semimartingale under original probability measure, we prove existence and uniqueness of the locally risk-minimizing strategy.
我们在风险资产的价格过程在原概率测度下为半鞅的假设下，证明了局部风险最小对冲策略的存在性和唯一性。
-
It was proved that under Lipschitz coefficients, the solutions of SDEs driven by Brownian motion or a continuous semimartingale form a stochastic homeomorphism flow.
在方程系数Lipschitz连续的条件下，由Brown运动或连续半鞅驱动的随机微分方程的解形成一随机同胚流。
-
To begin with, we point changes of martingale measures can be replaced by the choice of numeriare, and improve the price process of the replicatable contingent claims is independent of the changes of numeriare, for a market under semimartingale model.
因为跳过程能描述市场中的突发事件对资产价格的影响，从而更符合大量金融统计数据规律。所以，本文在假设资产服从一类跳过程的情况下来讨论期权的定价。
-
The exact expressions of minimal martingale measure and the minimal entropy martingale measure for jump diffusion semimartingale are gained,with the specific changes of intensity and density function processes in these measures.
在跳扩散半鞅模型中，引进了跳的强度过程与跳的概率密度函数过程，研究了测度变换对跳的强度与密度函数过程引起的变化、研究了跳扩散半鞅的最小鞅测度与最小熵鞅测度。
-
In Chapter 3 Firstly, the exponential stability in mean square and almost sure exponential stability for neutral stochstic neural networks with time-varying delay can be discussed by using the linear matrix inequality and the semimartingale convergence theorem; And our sufficient conditions are less conserative; Secondly, by utilizing the fixed point theorem, some sufficient and necessary conditions ensuring the asymp- totic stability in mean square for neutral stochastic neural networks with time-varying delays can be given.
第三章首先，利用线性矩阵不等式方法和半鞅收敛定理，考虑了一类具变时滞中立型随机神经网络的二阶矩指数稳定性和几乎必然指数稳定性，所得到的条件保守性要好；其次，采用不动点方法，给出了具变时滞中立型随机神经网络的二阶矩渐近稳定性的充要条件。
- 加载更多网络例句 (3)
- 更多网络解释与semimartingale相关的网络解释 [注：此内容来源于网络，仅供参考]
-
semimartingale：半
semimajorant 半强函数 | semimartingale 半 | semimean axis 半中轴
-
exponential semimartingale：指数半鞅
指数平滑法:exponential smoothing | 指数半鞅:exponential semimartingale | 指数衰减:exponential decay