Comparison principles applied to obstacle problems with penalties

Penalty methods form a well known technique to embed elliptic variational inequality problems into a family of variational equations (cf. [6], [13], [17]). Using the specific inverse monotonicity properties of these problems L _∞-bounds for the convergence can be derived by means of comparison solutions. Lagrange duality is applied to estimate parameters involved.

For piecewise linear finite elements applied on weakly acute triangulations in combination with mass lumping the inverse monotonicity of the obstacle problems can be transferred to its discretization. This forms the base of similar error estimations in the maximum norm for the penalty method applied to the discrete problem.

The technique of comparison solutions combined with the uniform boundedness of the Lagrange multipliers leads to decoupled convergence estimations with respect to the discretization and penalization parameters.     

The Lévy Swap Market Model

Models driven by Lévy processes are attractive since they allow for better statistical fitting than classical diffusion models. The dynamics of the forward swap rate process is derived in a semimartingale setting and a Lévy swap market model is introduced. In order to guarantee positive rates, the swap rates are modelled as ordinary exponentials. The model starts with the most distant rate, which is driven by a non‐homogeneous Lévy process. Via backward induction the remaining swap rates are constructed such that they become martingales under the corresponding forward swap measures. Finally it is shown how swaptions can be priced using bilateral Laplace transforms.     

Hybrid Lévy Models: Design and Computational Aspects

ABSTRACT

A hybrid model is a model, where two markets are studied jointly such that stochastic dependence can be taken into account. Such a dependence is well known for equity and interest rate markets on which we focus here. Other pairs can be considered in a similar way. Two different versions of a hybrid approach are developed. Independent time-inhomogeneous Lévy processes are used as the drivers of the dynamics of interest rates and equity. In both versions, the dynamics of the interest rate side is described by an equation for the instantaneous forward rate. Dependence between the markets is generated by introducing the driver of the interest rate market as an additional term into the dynamics of equity in the first version. The second version starts with the equity dynamics and uses a corresponding construction for the interest rate side. Dependence can be quantified in both cases by a single parameter. Numerically efficient valuation formulas for interest rate and equity derivatives are developed. Using market quotes for liquidly traded assets we show that the hybrid approach can be successfully calibrated.     

American Options in the Heston Model with Stochastic Interest Rate and Its Generalizations

Abstract

We consider the Heston model with the stochastic interest rate of Cox–Ingersoll–Ross (CIR) type and more general models with stochastic volatility and interest rates depending on two CIR-factors; the price, volatility and interest rate may correlate. Time-derivative and infinitesimal generator of the process for factors that determine the dynamics of the interest rate and/or volatility are discretized. The result is a sequence of embedded perpetual options arising in the time discretization of a Markov-modulated Lévy model. Options in this sequence are solved using an iteration method based on the Wiener–Hopf factorization. Typical shapes of the early exercise boundary are shown, and good agreement of option prices with prices calculated with the Longstaff–Schwartz method and Medvedev–Scaillet asymptotic method is demonstrated.     

The learning rate of l 2-coefficient regularized classification with strong loss

In the present paper, we give an investigation on the learning rate of l2-coefficient regularized classification with strong loss and the data dependent kernel functional spaces. The results show that the learning rate is influenced by the strong convexity.     

基于ARFIMA-HYGARCH-M-VaR模型的亚洲汇率市场均值和波动过程的双长期记忆性测度研究

作为金融传导机制的一个重要成分,汇率在金融危机的传播中发挥着重要作用.因此本文以亚洲汇率市场的汇率作为研究样本,通过引入skt分布来刻画残差的分布,构建了ARFIMA-HYGARCH-M-VaR模型来测度汇率风险值,并与skt分布下的GARCH及FIGARCH模型的VaR进行失败率回测检验与动态分位数测试.研究结果表明:在不同显著性水平下,skt分布下的各种模型基本都有较好的风险测度能力,且ARFIMA-HYGARCH-M模型的VaR风险测度更加精确与稳定.本研究为我国及亚洲其他国家汇率市场的风险测度与风险管理提供了一定的理论借鉴和方法基础.     

基于股价服从对数正态分布的凯利投资策略

基于集中投资策略的思想,把股票价格服从对数正态分布与凯利优化模型相结合,使其能更好地运用于股票投资实践中,推导出投资者个股投资的资产配置比例与投资者对个股投资收益率和标准差预测值之间的数学关系,从而实现最快财富增长速率的目标.     

中国农业科技进步贡献率的测度及原因分析 ——基于CD生产函数

基于柯布-道格拉斯生产函数,采用1985-2011年农业相关数据测算我国农业全要素增长贡献率,最终测算我国农业科技进步贡献率,并分析我国农业科技进步贡献率长期较低的深层次原因,针对这些原因,提出相应解决之策,以提高我国农业科技进步对农业生产的贡献程度,促进我国传统农业快速转向现代农业.     

用非精确的平行割线法求解奇异问题

奇异方程经常出现在很多实际非线性问题中,如反应扩散系统等.因此,研究奇异非线性方程的求解具有十分重要的意义.平行割线法是一种经典的求解非线性方程的迭代方法,它收敛阶较高,计算量较少.但在解决实际问题时,一方面,抽象出的数学模型与实际问题总是存在着一定的偏差,另外,在数据的计算中难免存在着一定的计算误差,所以研究用非精确的平行割线法求解非线性奇异问题具有很重要的现实意义,使得求解奇异问题具有更高的实用性和可行性.采用在平行割线法的迭代公式中加入摄动项的方法,构造出新的加速迭代格式,证明了新的迭代格式的收敛性,给出了收敛速率,得到了误差估计.