具有跳扩散模型下永久公司债券的定价和最佳资产结构

综合运用偏微分方程方法和结构化方法,在公司资产价值演化服从跳扩散模型下,研究永久公司债券的定价问题和最佳资产结构问题,获得了公司债券,股东权益和公司总价值的定价表达式和最佳杠杆比率的表达式.     

混合分数布朗运动下永久美式期权的定价

假设标的资产由混合分数布朗运动驱动,利用分数It6公式得到了混合分数布朗运动环境下永久美式期权的Black-Scholes偏微分方程,并通过偏微分方程获得永久美式期权的定价公式.     

具有分数O-U过程的永久美式看跌期权的定价

该文研究具有分数Ornstein-Uhlenbeck过程的永久美式看跌期权的定价问题.首先, 利用分析金融衍生品定价的delta对冲方法和无套利原理, 遵循标准的讨论步骤, 建立了标的资产价格服从分数Ornstein-Uhlenbeck过程的欧式看涨期权和看跌期权的定价公式.然后, 通过求解一个自由边界问题, 对标的资产价格服从分数Ornstein-Uhlenbeck过程的永久美式看跌期权的定价以及实施该期权时的临界标的资产价格给出了显式解.     

On the Optimal Control of a Random Walk with Jumps and Barriers

The modeling and optimal control of a class of random walks (RWs) is investigated in the framework of the Chapman-Kolmogorov (CK) and Fokker-Planck (FP) equations. This class of RWs includes jumps driven by a compound Poisson process and are subject to different barriers. A control mechanism is investigated that is included in the CK stochastic transition matrix and the purpose of the control is to track a desired discrete probability density function and attain a desired terminal density configuration. Existence and characterization of optimal controls are discussed. The proposed approach allows the derivation of a new FP model that accommodates the presence of the jumps and guarantees conservation of total probability in the case of reflecting barriers, which are modelled by appropriate operators. Results of numerical experiments are presented that successfully validate the proposed control framework.     

Optimal Scaling of Random Walk Metropolis Algorithms with Non-Gaussian Proposals

The asymptotic optimal scaling of random walk Metropolis (RWM) algorithms with Gaussian proposal distributions is well understood for certain specific classes of target distributions. These asymptotic results easily extend to any light tailed proposal distribution with finite fourth moment. However, heavy tailed proposal distributions such as the Cauchy distribution are known to have a number of desirable properties, and in many situations are preferable to light tailed proposal distributions. Therefore we consider the question of scaling for Cauchy distributed proposals for a wide range of independent and identically distributed (iid) product densities. The results are somewhat surprising as to when and when not Cauchy distributed proposals are preferable to Gaussian proposal distributions. This provides motivation for finding proposal distributions which improve on both Gaussian and Cauchy proposals, both for finite dimensional target distributions and asymptotically as the dimension of the target density, d → ∞. Throughout we seek the scaling of the proposal distribution which maximizes the expected squared jumping distance (ESJD).     

具有一般跳幅度分布的跳扩散模型下永久公司债券的定价

在公司资产价值演化服从具有一般跳幅度分布的跳扩散模型下,采用结构化方法研究具有无限到期日公司债券的定价问题,通过微分方程的方法和无套利原理获得了公司债券,股东权益和公司总价值的定价表达式以及最佳违约边界的表达式.     

随机环境下的MTAR模型的几何遍历性

在本文中,提出了随机环境下的MTAR模型的非常返性及其确定的导出序列几何遍历的几个充分条件.     

基于分形B-S定价模型的认购权证价格行为实证分析

针对证券收益率呈现"尖峰厚尾"的分布特征,在分析传统B-S权证定价模型的不足基础上,本文提出了基于分形理论的B-S权证定价模型,并利用分形B-S权证定价模型和传统B-S模型分析认购权证价格变化的行为。实证结果发现,两种模型的理论价格均低估了市场价格,且低估的程度具有显著统计性,其中以分形B-S模型评价结果最接近市场价格,评价绩效好。探讨影响分形B-S权证模型理论价格与市场价格差异的主要因素,结果发现距到期日时间的长短、价内外程度以及流动性在解释价差程度上具有统计的显著性。     

Optimal Advertising and Pricing in a New-Product Adoption Model

A model of new-product adoption is proposed that incorporates price and advertising effects. An optimal control problem that uses the model as its dynamics is solved explicitly to obtain the optimal price and advertising effort over time. The model has a great potential to be used in obtaining solutions and insights in a variety of differential game settings. The authors thank Anshuman Chutani for help with the figures.     

基于跳-分形模型的美式看涨期权定价

假设股票变化过程服从跳一分形布朗运动,根据风险中性定价原理对股票发生跳跃次数的收益求条件期望现值推导出M次离散支付红利的美式看涨期权解析定价方程,并使用外推加速法求出当M趋于无穷时方程的二重、三重正态积分多项式表达,依此计算连续支付红利美式看涨期权价值.数值模拟表明通常仅需二重正态积分多项式能产生精确价值,而在极实值状态下则需三重正态积分多项式才能满足,结合两种多项式可以编出有效数字程序评价支付红利的美式看涨期权.     

Valleys and the Maximum Local Time for Random Walk in Random Environment

Let ξ (n, x) be the local time at x for a recurrent one-dimensional random walk in random environment after n steps, and consider the maximum ξ^*(n) = max _x ξ(n, x). It is known that lim sup is a positive constant a.s. We prove that lim inf is a positive constant a.s. this answers a question of P. Révész [5]. The proof is based on an analysis of the valleys in the environment, defined as the potential wells of record depth. In particular, we show that almost surely, at any time n large enough, the random walker has spent almost all of its lifetime in the two deepest valleys of the environment it has encountered. We also prove a uniform exponential tail bound for the ratio of the expected total occupation time of a valley and the expected local time at its bottom.     

Optimal Scaling for the Pseudo-Marginal Random Walk Metropolis: Insensitivity to the Noise Generating Mechanism

We examine the optimal scaling and the efficiency of the pseudo-marginal random walk Metropolis algorithm using a recently-derived result on the limiting efficiency as the dimension, \(d\rightarrow \infty \). We prove that the optimal scaling for a given target varies by less than 20 % across a wide range of distributions for the noise in the estimate of the target, and that any scaling that is within 20 % of the optimal one will be at least 70 % efficient. We demonstrate that this phenomenon occurs even outside the range of noise distributions for which we rigorously prove it. We then conduct a simulation study on an example with d = 10 where importance sampling is used to estimate the target density; we also examine results available from an existing simulation study with d = 5 and where a particle filter was used. Our key conclusions are found to hold in these examples also.     

基于人工神经网络和随机游走模型的汇率预测

由于金融数据具有随机性特征,使得建模和预测变得极其困难.提出一种组合预测方法,即假定任何金融时序数据由线性和非线性两部分组成,将其中线性部分的数据通过随机游走(RW)模型进行模拟,剩余的非线性残差部分由前馈神经网络(FANN)和诶尔曼神经网络(EANN)协同处理.从实证结果可知,该组合方法相比单独使用RW、FANN或EANN模型有更高的预测精度.     

屏蔽数据情形下几何平均亚式期权定价模型

通常情况下,前人的工作都是连续情形下的结论,假定股票价格部分信息被屏蔽,只在有限的时刻点上股票价格是明确已知的.在此假设之下,尝试考虑几何平均型亚式期权定价问题.利用拟-鞅的方法,建立了分数布朗运动环境下亚式期权定价模型,获得了离散情形几何加权平均亚式期权价格的解析表达式.     

The Local time of Simple Random Walk in Random Environment

Two integral tests are established, which characterize respectively Lévy's upper and lower classes for the local time of Sinai's simple random walk in random environment. The weak convergence of the local time is also studied, and the limiting distribution determined. Our results can be applied to a class of diffusion processes with random potentials which asymptotically behave like Brownian motion.     

A Discrete-Time American Put Option Model with Fuzziness of Stock Prices

To solve a mathematical model for American put option with uncertainty, we utilize two essentials, i.e., a λ-weighting function and a mean value of fuzzy random variables simultaneously. Estimation of randomness and fuzziness as uncertainty should be important when we deal with a reasonable and natural model extended from the original optimization/decision making. Three kinds of mean values by fuzzy measures, which are based on Possibility, Necessity and Credibility, are demonstrated particularly. We consider the optimal expected price of the American put option by dynamic programming under a reasonable assumption. A numerical example is given to illustrate our idea.     

Divergence of a Random Walk Through Deterministic and Random Subsequences

Let {S _n} _n0 be a random walk on the line. We give criteria for the existence of a nonrandom sequence n _i for which respectively We thereby obtain conditions for to be a strong limit point of {S _n} or {S _n /n}. The first of these properties is shown to be equivalent to for some sequence a _i , where T(a) is the exit time from the interval [–a,a]. We also obtain a general equivalence between and for an increasing function fand suitable sequences n _i and a _i. These sorts of properties are of interest in sequential analysis. Known conditions for and (divergence through the whole sequence n) are also simplified.     

两阶段免费增值商业模式中的定价优化与时序研究

免费增值商业模式在信息产品和服务当中被广泛采用。针对企业首先推出免费产品再推出付费产品以充分利用两种产品推出的时间差来提升消费者学习效应、降低消费者使用成本的情形,本文首先建立两阶段模型,求解给定系统参数情况下的付费版产品最优定价问题并给出解析解,然后通过与企业应用单阶段免费增值模式时的利润进行比较,解析地得到企业选择两阶段模式可获得较高利润的条件,最后在数值计算基础上讨论了学习效应强度对企业利润的影响,和优化学习效应强度以拓展两阶段模式适用范围的问题。本文的研究成果为拟采用免费增值商业模式的企业提供了关于产品最优定价和模式选择的决策支持。     

永久经理期权的最优实施策略

利用偏微分方程数值方法研究金融市场上永久经理期权(ESOs)的最优实施策略问题.讨论了两种实施情况,即通常的整体实施情况以及非限制实施情况.在非限制实施情况下,持有者在任意可实施时刻可以实施其持有的任意份ESOs.两种实施情况下的最优实施策略分别对应着一个抛物型变分不等式定解问题的自由边界(最佳实施边界).通过数值分析的方法分别研究了自由边界的性质,比较了两种情况下自由边界的异同及其所对应的金融意义.     

美式债券期权定价熵模型

基于熵定价理论,结合美式期权解析近似求解的G eske-Johnson方法,构建了美式债券期权定价熵模型,给出了标的资产为零息票债券和息票债券的美式期权估值的解析近似计算公式,并展示了具体的算法步骤.