Discrete credit barrier models

The model introduced in this article is designed to provide a consistent representation for both the real-world and pricing measures for the credit process. We find that good agreement with historical and market data can be achieved across all credit ratings simultaneously. The model is characterized by an underlying stochastic process that takes on values on a discrete lattice and represents credit quality. Rating transitions are associated with barrier crossings and default events are associated with an absorbing state. The stochastic process has state-dependent volatility and jumps which are estimated by using empirical migration and default rates. A risk-neutralizing drift is estimated to consistently match the average spread curves corresponding to all the various ratings.     

Futures and futures options with basis risk: theoretical and empirical perspectives

Under a no-arbitrage assumption, the futures price converges to the spot price at the maturity of the futures contract, where the basis equals zero. Assuming that the basis process follows a modified Brownian bridge process with a zero basis at maturity, we derive the closed-form solutions of futures and futures options with the basis risk under the stochastic interest rate. We make a comparison of the Black model under a stochastic interest rate and our model in an empirical test using the daily data of S&P 500 futures call options. The overall mean errors in terms of index points and percentage are ?4.771 and ?27.83%, respectively, for the Black model and 0.757 and 1.30%, respectively, for our model. This evidence supports the occurrence of basis risk in S&P 500 futures call options.     

A STRUCTURAL RISK‐NEUTRAL MODEL FOR PRICING AND HEDGING POWER DERIVATIVES

We develop a structural risk‐neutral model for energy market modifying along several directions the approach introduced in Aïd et al. In particular, a scarcity function is introduced to allow important deviations of the spot price from the marginal fuel price, producing price spikes. We focus on pricing and hedging electricity derivatives. The hedging instruments are forward contracts on fuels and electricity. The presence of production capacities and electricity demand makes such a market incomplete. We follow a local risk minimization approach to price and hedge energy derivatives. Despite the richness of information included in the spot model, we obtain closed‐form formulae for futures prices and semiexplicit formulae for spread options and European options on electricity forward contracts. An analysis of the electricity price risk premium is provided showing the contribution of demand and capacity to the futures prices. We show that when far from delivery, electricity futures behave like a basket of futures on fuels.     

我国上市公司股票期权激励问题研究

本文首先阐述了股票期权的含义及理论基础;其次,在介绍了我国股票期权实施现状的基础上,系统地分析了我国公司所面临的相关法律法规、外部市场环境及内部治理结构等方面的问题;最后,针对以上存在的各项问题提出了相应的对策建议。     

PRICING ASIAN OPTIONS FOR JUMP DIFFUSION

We construct a sequence of functions that uniformly converge (on compact sets) to the price of an Asian option, which is written on a stock whose dynamics follow a jump diffusion. The convergence is exponentially fast. We show that each element in this sequence is the unique classical solution of a parabolic partial differential equation (not an integro‐differential equation). As a result we obtain a fast numerical approximation scheme whose accuracy versus speed characteristics can be controlled. We analyze the performance of our numerical algorithm on several examples.     

基于期权定价理论的风险投资决策

项目评价的传统方法———净现值(NPV)法在应用于风险投资项目时,由于低估了投资价值,往往会使得投资者失去一些有价值的投资机会。结合风险投资的特性,将期权定价理论应用于风险投资决策中,并建立连续及离散两种状态下的决策模型     

试论营销策略中的期权因素

营销策略由产品、价格、地点和促销构成,产品由核心产品、有形产品和附加产品组成。附加产 品在产品构成中的作用越来越重要,附加产品的性质类似于期权。通过附加产品,企业和消费者之间存 在着契约关系,可以利用期权的分析方法对附加产品进行分析,并利用期权定价模型对其进行定价。     

中国鞋类产品出口受阻的原因及对策

长期以来,“薄利多销”的低价策略成为我国鞋类企业扩大出口创汇、走向国际市场的一大法宝,但从近期我国鞋类出口面临一系列的贸易摩擦来看,低价策略并非当今出口企业的最佳选择,若不及时调整这种策略,可能会严重制约企业的发展。本文分析了鞋类企业低价竞销产生的原因及其危害性,并就如何解决这一问题进行了初步的探讨。     

我国建立技术性贸易壁垒预警机制的问题研究

在当前关税大幅下降和传统非关税壁垒不断消除和规范的情况下,技术贸易壁垒正成为逐步替代关税和一般非关税措施的重要贸易壁垒,成为发达国家实行贸易保护主义的主要手段和高级形式。面对新形势,有针对性地建立一套由政府、行业协会和企业共同参与的技术性贸易壁垒预警体系,对促进我国对外贸易可持续发展具有非常重要的意义。     

Machine learning for pricing American options in high-dimensional Markovian and non-Markovian models

In this paper we propose two efficient techniques which allow one to compute the price of American basket options. In particular, we consider a basket of assets that follow a multi-dimensional Black–Scholes dynamics. The proposed techniques, called GPR Tree (GRP-Tree) and GPR Exact Integration (GPR-EI), are both based on Machine Learning, exploited together with binomial trees or with a closed form formula for integration. Moreover, these two methods solve the backward dynamic programing problem considering a Bermudan approximation of the American option. On the exercise dates, the value of the option is first computed as the maximum between the exercise value and the continuation value and then approximated by means of Gaussian Process Regression. The two methods mainly differ in the approach used to compute the continuation value: a single step of the binomial tree or integration according to the probability density of the process. Numerical results show that these two methods are accurate and reliable in handling American options on very large baskets of assets. Moreover we also consider the rough Bergomi model, which provides stochastic volatility with memory. Despite that this model is only bidimensional, the whole history of the process impacts on the price, and how to handle all this information is not obvious at all. To this aim, we present how to adapt the GPR-Tree and GPR-EI methods and we focus on pricing American options in this non-Markovian framework.