Option pricing when asset returns jump interruptedly

This paper proposes an extension of Merton's jump‐diffusion model to reflect the time inhomogeneity caused by changes of market states. The benefit is that it simultaneously captures two salient features in asset returns: heavy tailness and volatility clustering. On the basis of an empirical analysis where jumps are found to happen much more frequently in risky periods than in normal periods, we assume that the Poisson process for driving jumps is governed by a two‐state on‐off Markov chain. This makes jumps happen interruptedly and helps to generate different dynamics under these two states. We provide a full analysis for the proposed model and derive the recursive formulas for the conditional state probabilities of the underlying Markov chain. These analytical results lead to an algorithm that can be implemented to determine the prices of European options under normal and risky states. Numerical examples are given to demonstrate how time inhomogeneity influences return distributions, option prices, and volatility smiles. The contrasting patterns seen in different states indicate the insufficiency of using time‐homogeneous models and justify the use of the proposed model. Copyright © 2012 John Wiley & Sons, Ltd.     

合作博弈视角下城市道路交通拥堵收费研究

城市道路交通设施作为准公用物品,其外部效应必然导致交通拥堵的发生,实施拥堵收费的目的则是使交通拥堵产生的外部成本内部化,确保城市道路资源得到高效配置,应用经济杠杆来调节交通需求,以缓解交通拥堵.本文应用合作博弈相关理论对城市道路拥堵网络问题进行了分析,从同一时刻各个路段的通勤者数目这一角度定义拥堵成本,重点证明了拥堵成本为凸函数的城市道路拥堵网络博弈存在非空的核,拥堵成本为凹函数的城市道路交通网络博弈虽不存在非空的核,但总是存在最优的树网络,最后,结合上述结论对城市道路拥堵收费进行讨论,从理论上对拥堵收费的合理性进行了说明,并提出了进一步研究的方向.     

基于区间效率的贷款定价研究

以存款利息支出率、费用支出率、预期违约损失率、目标利润率等4个定价指标作为输入,以贷款利率作为输出,采用支持向量机回归算法建立基于区间效率的贷款定价模型.创新与特色一是通过区间数形式来反映预期违约损失率、目标利润率、费用支出率等,改变了现有研究将目标利润、贷款费用、违约损失等变量看作确定性数值来定价的现状.使贷款利率更具有竞争性.二是通过比较不同核函数、核参数下的训练样本的贷款效率区间与合理的贷款效率区间的匹配程度,确定贷款定价模型最优的核函数和核参数,进而建立了贷款定价模型.间接解决了在考虑贷款价格能否被银行、客户接受情况下贷款利率确定的问题.     

Asset Pricing Using Finite State Markov Chain Stochastic Discount Functions

This article fuses two pieces of theory to make a tractable model for asset pricing. The first is the theory of asset pricing using a stochastic discounting function (SDF). This will be reviewed. The second is to model uncertainty in an economy using a Markov chain. Using the semi-martingale dynamics for the chain these models can be calibrated and asset valuations derived. Interest rate models, stock price models, futures pricing, exchange rates can all be introduced endogenously in this framework.     

Option pricing in incomplete markets

Expected utility maximization is a very useful approach for pricing options in an incomplete market. The results from this approach contain many important features observed by practitioners. However, under this approach, the option prices are determined by a set of coupled nonlinear partial differential equations in high dimensions. Thus, it represents numerous significant difficulties in both theoretical analysis and numerical computations. In this paper, we present accurate approximate solutions for this set of equations.     

A dynamic pricing approach for returned products in integrated forward/reverse logistics network design

During the last decade, the stringent pressures from environmental and social requirements have spurred an interest in designing a reverse logistics network. In this paper, we address the problem of designing and planning a multi-echelon, multi-period, multi-commodity and capacitated integrated forward/reverse logistics network. Returned products are categorized with respect to their quality levels, and a different acquisition price is offered for each return type. Furthermore, the reservation incentive of customers, the expected price of customers for one unit of used product described by uniform distribution, is applied to model the customers’ return willingness. Due to the fact that the remaining worthwhile value in the used products is the corporation’s key motivation for buying them from customers, a dynamic pricing approach is developed to determine the acquisition price for these products and based on it determine the percentage of returned products collected from customer zones. The used products’ acquisition prices at each time period are determined based on the customers’ return willingness by each collection center.     

Pricing and effort investment for a newsvendor-type product

We investigate a dominant retailer’s optimal joint strategy of pricing and timing of effort investment and analyze how it influences the decision of the manufacturer, the total supply chain profit, and the consumers’ payoff. We consider two pricing schemes of the retailer, namely, dollar markup and percentage markup, and two effort-investment sequences, namely, ex-ante and ex-post. A combination of four cases is analyzed. Our results show that: (1) under the same effort-decision sequence, a percentage-markup pricing scheme leads to higher expected profit for the retailer and the whole supply chain, but a lower expected profit for the manufacturer and a higher retail price for the consumers; (2) under the same markup-pricing strategy, the dominant retailer always prefers to postpone her effort decision until the manufacturer makes a commitment to wholesale price, since it can result in a Pareto-improvement for all the supply chain members. That is, the retailer’s and manufacturer’s expected profits are higher and the consumers pay a lower retail price; and (3) among the four joint strategies, the dominant retailer always prefers the joint strategy of percentage-markup plus ex-post effort decision. However, the dominated manufacturer always prefers the joint strategy of dollar-markup plus ex-post effort decision, which is also beneficial to the end consumers.     

A continuous-time dynamic pricing model knowing the competitor’s pricing strategy

In this paper we consider a dynamic pricing model for a firm knowing that a competitor adopts a static pricing strategy. We establish a continuous time model to analyze the effect of dynamic pricing on the improvement in expected revenue in the duopoly. We assume that customers arrive to purchase tickets in accordance with a geometric Brownian motion. We derive an explicit closed-form expression for an optimal pricing policy to maximize the expected revenue. It is shown that when the competitor adopts a static pricing policy, dynamic pricing is not always effective in terms of maximizing expected revenue compared to a fixed pricing strategy. Moreover, we show that the size of the reduction in the expected revenue depends on the competitor’s pricing strategy. Numerical results are presented to illustrate the dynamic pricing policy.     

An adaptive averaging binomial method for option valuation

We introduce efficient accurate binomial methods for option pricing. The standard binomial approximation converges to continuous Black–Scholes values with the saw-tooth pattern in the error as the number of time steps increases. When we introduce local averages of payoffs at expiry, the saw-tooth pattern in the error has been reduced and the approximation becomes reliable. Furthermore, we employ adaptive meshes around non-smooth regions for efficiency. Numerical experiments illustrate that the proposed method gives more accurate values with less computational work compared to other methods.