Efficient willow tree method for European-style and American-style moving average barrier options pricing

Moving average options are widely traded in financial markets, but exiting methods for pricing this type of option are too slow. This paper proposes two efficient willow tree methods for pricing European-style and American-style moving average barrier options (MABOs). We first solve the finite-dimensional partial differential equation model for discretely monitored MABOs by willow tree methods, and then compute the value of continuously monitored MABOs by Richardson’s two-point extrapolation. Our new willow tree method employs the interpolation error minimization technique to reduce complexity. The corresponding convergence rate and error bounds are also analyzed. It shows that our proposed methods can provide the same accuracy as the binomial tree approach and Monte Carlo simulation, but require much less computing time. The numerical experiments support our claims.     

Towards an early warning system for sovereign defaults leveraging on machine learning methodologies

In this study, we address the topic of credit risk stemming from central governments from a technical point of view. First, we explore various econometric and machine learning techniques to build an enhanced sovereign rating system that effectively differentiates the risk of default among countries. Our empirical results indicate that the machine learning method of XGBOOST has a superior out-of-sample and out-of-time predictive performance. Then, we use the models developed to calibrate a sovereign rating system and provide useful insights into the set-up of a parsimonious early warning system. Our results provide a more concise view of the most robust method for classifying countries’ default risk with significant regulatory implications, given that the efficient assessment of sovereign debt is crucial for effective proactive risk measurement.     

Adaptation of Agroforestry Systems in South-Eastern Mexico through Integration of Farmer and Bioeconomic Evaluations

Agroforestry systems have been promoted as sustainable land-use systems for regions where shifting agriculture is the traditional predominant land-use. Although environmentally sustainable, agroforestry systems require investment to establish that may affect their economic sustainability. In the southern Yucatan Peninsula 47 agroforestry plots of two timber and 10 fruit tree species were established with 22 farmers in three communities covering two rainfall zones and five soil types. Some fruit trees had wide adaptability to different soil, rainfall and management conditions, e.g. Manilkara zapota; others were restricted to the best soil, rainfall management conditions, e.g. Persea americana. The Meliaceae timber trees responded little to rainfall and soil, but stem borer attack was markedly lower in less intensively managed systems. Level of system maintenance greatly affected costs, but also opportunities for intercropping and obtaining immediate income. All levels of managements had negative net present value (NPV) for the three-year establishment phase, but so does traditional maize production. Farmers preferred to inter-crop their agroforestry systems, but were often limited by site quality. Determining sustainable agroforestry options for farmers requires multiple decisions related to species adaptability to the site, farmer production objectives and farmer capacity to invest in different management strategies. One production technology did not fit all.     

Smooth convergence in the binomial model

In this article, we consider a general class of binomial models with an additional parameter λ. We show that in the case of a European call option the binomial price converges to the Black–Scholes price at the rate 1/n and, more importantly, give a formula for the coefficient of 1/n in the expansion of the error. This enables us, by making special choices for λ, to prove that convergence is smooth in Tian’s flexible binomial model and also in a new center binomial model which we propose. Ken Palmer was supported by NSC grant 93-2118-M-002-002.     

Competitive Positioning in International Logistics: Identifying a System of Attributes Through Neural Networks and Decision Trees

Abstract

Firms involved in international logistics must develop a system of service attributes that give them a way to be profitable and to satisfy customers' needs at the same time. How customers trade-off these various attributes in forming satisfaction with competing international logistics providers has not been explored well in the literature. This study explores the ocean freight shipping sector to identify the system of attributes that maximizes customers' satisfaction. Data were collected from shipping managers in Singapore using personal interviews to identify the chief concerns in choosing and evaluating ocean freight services. The data were then examined using neural networks and decision trees, among other approaches to identify the system of attributes that is connected with customer satisfaction. The results illustrate the power of these methods in understanding how industrial customers with global operations process attributes to derive satisfaction. Implications are discussed.     

Partitioning for Profit: An Empirical Study of Methods for Handling Unequal Costs of Error in Predictive Data Mining

This paper expands prior work on the Sequential Binary Programming (SBP) algorithm as a framework for cost-sensitive classification. The field of cost-sensitive learning has provided a number of methods to adapt predictive data mining from engineering and hard science applications to those in commerce. This discussion will test theoretical limitations of classical cost-sensitive algorithms empirically and outline the appropriate conditions under which various methods (specifically SBP) should be implemented in favor of others.     

Measuring customer equity and managing the customer asset: an explanatory study in the Australian hotels

Although there are a range of conceptual and theoretical studies about customer equity (CE) measurement and management in the literature, there are few empirical studies where these two concepts are examined together. This paper focuses on the need for a more synthesised approach and addresses calls for more research into this specific area of marketing management. A conceptual framework was developed that synthesises both customer lifetime value and customer relationship management from a customer equity management (CEM) perspective. The framework was used to empirically examine how four CE strategies, together with a firm’s use of the two types of customer data (aggregated and disaggregated), impact on CEM outcomes. Data were collected from 114 hotel managers in Australia and analysed through a decision tree methodology. The results show that hotels are utilising their CE strategies for acquisition purposes more than retention purposes (customer asset management), which overall appears to satisfice more than maximise their hotel’s capacity in achieving effective CE outcomes. The study’s contribution to theory is through empirically testing a framework that combines two discrete theoretical concepts in one study to provide insights to guide future research.     

Asymptotics of the price oscillations of a European call option in a tree model

It is well known that the price of a European vanilla option computed in a binomial tree model converges toward the Black-Scholes price when the time step tends to zero. Moreover, it has been observed that this convergence is of order 1/ n in usual models and that it is oscillatory. In this paper, we compute this oscillatory behavior using asymptotics of Laplace integrals, giving explicitly the first terms of the asymptotics. This allows us to show that there is no asymptotic expansion in the usual sense, but that the rate of convergence is indeed of order 1/ n in the case of usual binomial models since the second term (in     ) vanishes. The next term is of type   C ₂( n )/ n   , with   C ₂( n )  some explicit bounded function of n that has no limit when n tends to infinity.     

湖北省有关封山植树、退耕还林问题的探讨

封山植树、退耕还林是湖北省生态环境建设的重大战略举措。封山植树作为一项系统工程 ,必须解决森林培育方向 ,明确责权利 ,搞好政策支撑、科技支撑 ,保证苗木种质优化 ,正确认识合理利用森林资源与封山植树的关系。退耕还林项目的实施 ,必须从实际出发 ,充分认识退耕坡度、退耕模式等科学研究的重要意义 ,同时保障政策、法律、法规的有力支撑 ,针对资金不足的问题 ,提出生态补偿制度。     

我国对外反倾销威慑力能否有效抑制国际对华反倾销?

本文利用1981—2007年的国际对华反倾销数据和负二项回归方法,发现中国对外反倾销威慑和报复能力对国际对华反倾销产生了一定程度的抑制效应。此外还发现,宏观经济不是影响国际对华反倾销的主要原因;外国货币的升值会导致国际对华反倾销的增加;反倾销案件是国外利益集团要求政府对其实行贸易保护的结果。本文据此提出中国应维持汇率稳定,完善行业协会,降低对某些国家过高的出口集中度和适度对外反倾销的政策建议。