Hedging and pricing early-exercise options with complex fourier series expansion

We introduce a new numerical method called the complex Fourier series (CFS) method proposed by Chan (2017) to price options with an early-exercise feature—American, Bermudan and discretely monitored barrier options—under exponential Lévy asset dynamics. This new method allows us to quickly and accurately compute the values of early-exercise options and their Greeks. We also provide an error analysis to demonstrate that, in many cases, we can achieve an exponential convergence rate in the pricing method as long as we choose the correct truncated computational interval. Our numerical analysis indicates that the CFS method is computationally more comparable or favourable than the methods currently available. Finally, the superiority of the CFS method is illustrated with real financial data by considering Standard & Poor’s depositary receipts (SPDR) exchange-traded fund (ETF) on the S&P 500® index options, which are American options traded from November 2017 to February 2018 and from 30 January 2019 to 21 June 2019.     

基于循环经济的绍兴休闲观光农业发展研究

［目的］休闲观光农业建设是绍兴市产业转型升级的关键一步，探寻休闲观光农业新模式，能够为休闲农业发展提供理论参考。［方法］文章采用变异系数法确定指标权重，多因素综合分析法测算观光农业发展水平，从循环经济角度出发，评价2001—2016年绍兴市休闲观光农业发展可持续性，提出发展中存在的问题并探索循环型的休闲观光农业新模式。［结果］（1）2001—2016年以来，经济发展可持续性得分较高，资源环境可持续得分次之，循环经济可持续发展偏低。（2）现阶段绍兴市休闲观光农业发展主要存在休闲观光农业自然环境不断遭到破坏，休闲观光农业缺乏整体规划，休闲观光农业旅游支撑体系不够健全等问题。（3）未来发展中，循环经济发展下的休闲观光农业可以开发建设时空复合循环型、资源综合利用循环型、能量多级利用循环型、综合开发利用循环型等4种模式。［结论］未来绍兴市应将循环经济的理念融入到休闲观光农业中，因地制宜，科学选择循环型休闲观光农业发展模式； 规划先行，科学利用农业旅游资源； 强化保障，建立休闲观光农业支撑体系，全面推动休闲观光农业健康持续发展。     

家庭承包地“三权”分置的制度逻辑探究 ——基于制度需求与供给的视角

研究目的:阐明"三权"分置的制度逻辑,为制度供给的增量调整提供一种思路。研究方法:文献分析法、政策文本分析法。研究结果:当下农民、新型农业经营者出现新的制度诉求,既有土地承包经权营制度不足以满足该需求。承包地制度供给创新要做实承包权,辨明"三权"分置下经营权所处的位置。土地经营权的权利塑造过程应坚持物债二分法,实现物权法、合同法双重法制途径的并重。研究结论:承包地"三权"分置本质上是理论创新问题,辨清"三权"分置的制度逻辑,仍需以实践需求为出发点,新的制度供给是一个增量调整与立法跟进问题。对经营权性质的探讨有必要融入物债二分逻辑,对于短期限的土地经营权,应按照契约自由原则,实行意思主义,权利类型、权利内容经双方自由创设,对长期存续的土地经营权可实现物权化,实行物权法定主义,按照法定规格与程序流转。     

Are they telling the truth? Revealing hidden traits of satisfaction with a public bike-sharing service

Public bike-sharing systems (BSSs) are an emerging mode of transportation introduced by municipalities to solve congestion problems in metropolitan areas, especially when integrated with other types of transportation. In the last years, the number of public bike-sharing services has been constantly on the rise all over the world, and generally the overall satisfaction with them is high. However, satisfaction with public services is driven by mechanisms that can differ from those in the private sector. It is important to establish to what extent a high satisfaction is genuine or simply ephemeral. Even “old” public services (like public transportation) become “gold” when accompanied by the introduction of new technologies. In this paper we analyze this phenomenon using data from a satisfaction web-survey conducted among customers of the public BSS “BikeMi” in Milan, Italy, in a period when mobile technologies have been introduced to speed up the service. On analyzing the responses to satisfaction questions using simple summary statistics, the level of satisfaction resulted very high. However, our aim was to look for potential “darker” sides of the service by detecting possible hidden satisfaction components. For this purpose, we used the Nonlinear Principal Components Analysis, which is particularly powerful in this context. A simple textual analysis was also performed as a validating test. Results from our analysis indicated that satisfaction is flawed by a set of factors like the mechanics of the bikes, the picking and dropping system, and the apps used to organize the service. Less concern was detected for more general aspects of the service.     

Spatial movement patterns among intra-destinations using social network analysis

To explore popularly visited tourist locations, travel movement patterns, and movement points, this study collected samples of 321 Chinese tourists and 337 Japanese tourists who were visiting major tourist destinations in Seoul and its vicinity in South Korea. Results of analyzing movement patterns showed that Japanese tourists tend to be clustered around popular attractions, whereas Chinese tourists tend to spread over a larger area of attractions. Some specific shopping and amusement attractions were the locations most popularly visited by both groups. The start points and end points in the two groups’ itineraries were dissimilar overall, even though their patterns were similar in regard to major preferred tourist attractions. Thus, the findings of this study have the potential to contribute to understanding spatial mobility in a tourism destination through tracking tourists’ movement patterns.     

Exploring pilgrim satisfaction on facilities for religious events: a case of Ratha Yatra at Puri

This article relates to the annual Ratha Yatra festival at Puri, India, and aims at quantifying the pilgrim perception of the event on three major aspects of every facility – adequacy, quality, and signage – to measure their satisfaction. A questionnaire survey (N?=?680) was conducted, from which a five-factor structure was extracted using exploratory principal component analysis, further examined through partial least squares-path modeling. The final model was found to have significant positive effects on three factors that comprised adequacy and quality of physiological needs, quality of ancillary facilities, and signage. The outcome may be utilized in planning other pilgrim events for achieving a higher pilgrim satisfaction score.     

The U.S. tourists’ perceptions of destination China over two transformative periods

This study conducted a textual analysis of The New York Times to examine the U.S. tourists’ perceived image of China as a destination by comparing the two periods of January 1980–May 1989 and January 2005–December 2015. The study found a drastic shift of the U.S. tourists’ affective image of China as a destination from being favorable and positive in the early period to being unfavorable and negative in the recent period. The affective image was characterized by the two domains of Exoticism and Sense of Superiority in the 1980s, as compared to the two domains of Ordinary and Negative National Image in the recent 10 years. Paradoxically, such a sentimental shift on the part of the U.S. tourists occurred while their perception of China’s destination attributes either did not change or grew more positive.     

水源地突发水污染政府应急预留水量需求预测

近年来,随着工业化和产业化的快速发展,水源地突发水污染事件频发。为应对紧急情况下的水资源非常规需求,保障经济社会稳定发展,政府需要安排一部分应急预留水量。如何合理预测政府应急预留水量的规模是一个值得探讨的课题。提出了一种基于案例推理技术的政府应急预留水量需求预测方法,具体思路是:借助于案例库,利用主成分分析法从众多影响水源地突发水污染事件的因素中提取出两两不相关的因子,以此作为案例的特征属性,基于加权曼哈顿距离测算相似度,依此得到匹配案例,进而测算政府应急预留水量。以太湖流域常州地区水源地为例,进行政府预留水量需求量的预测与分析。该方法可以为政府应急预留水量的配置、储备等提供相关理论知识。     

Economic development,food demand and the consequences for agricultural resource requirements: an application to Indonesia

We analyse food demand patterns of Indonesian households from a resource intensity perspective and quantify the impact of changed demand patterns on the use of three major resource inputs: fossil fuel; land; and water in agricultural production. Using Indonesian Family Life Survey data, 13 major food items (which constitute 70 per cent of food expenditure) are categorised into low, moderate and high resource intensity, and income elasticity and Engel curves are estimated for the period from 1997 to 2007. Our results show that income growth in Indonesia is associated with demand patterns that are more resource intensive. By 2007, per capita requirements of fossil fuel, land and water increased by 42.7 per cent (3.13 MJ), 44.9 per cent (1.24 m²) and 50.4 per cent (2.1 kL), respectively, relative to 1997. The results imply that, at least for Indonesia, changed food demand patterns resulting from economic development will increase the demand for natural resources substantially.     

Big data driven cycle time parallel prediction for production planning in wafer manufacturing

Cycle time forecasting (CTF) is one of the most crucial issues for production planning to keep high delivery reliability in semiconductor wafer fabrication systems (SWFS). This paper proposes a novel data-intensive cycle time (CT) prediction system with parallel computing to rapidly forecast the CT of wafer lots with large datasets. First, a density peak based radial basis function network (DP-RBFN) is designed to forecast the CT with the diverse and agglomerative CT data. Second, the network learning method based on a clustering technique is proposed to determine the density peak. Third, a parallel computing approach for network training is proposed in order to speed up the training process with large scaled CT data. Finally, an experiment with respect to SWFS is presented, which demonstrates that the proposed CTF system can not only speed up the training process of the model but also outperform the radial basis function network, the back-propagation-network and multivariate regression methodology based CTF methods in terms of the mean absolute deviation and standard deviation.