The behavior of extreme values in Germany's stock index futures: An application to intradaily margin setting

Recent defaults and large financial losses attributed to derivative security investing point to an area of finance not often researched, i.e. the probabilities of observing extreme occurrences. This paper examines this behavior for German stock index futures (FDAX) contracts. Its empirical results indicate that large FDAX intradaily price changes follow a Fréchet extreme value distribution and the extreme value distribution probabilities may be confidently used to help set intradaily margin levels.     

Prediction of index futures returns and the analysis of financial spillovers—A comparison between GARCH and the grey theorem

This paper adopts the GM(1, 1) model to predict the rates of return of nine major index futures in the American and Eurasian markets. In a further step, by means of local grey relational analysis and by employing the GM(1, N) model for the first time, the variation relatedness and the main influencing factor among the above mentioned targeted markets is determined. Then, a comparison between GARCH/TGARCH and the grey theory with regard to predictive power is conducted. The findings reveal that the GARCH/TGARCH model performs better than the GM(1, 1), including the optimal α method, in terms of forecasting capabilities. Meanwhile, it is also found that GARCH and spillover effects indeed exist. Moreover, GM(1, N) also reveals that the daily rate of return of the Dow Jones index futures has the most influence on the rates of return of the other index futures.     

Elliott wave principle and the corresponding fractional Brownian motion in stock markets: Evidence from Nikkei 225 index

This paper examines one of the vital technical analysis indicators known as the Elliott wave principle. Since these waves have a fractal nature with patterns that are not exact, we first determine the dimension of them. Our second aim is to find a linkage between Elliott wave principle and fractional Brownian motion via comparing their Hausdorff dimensions. Thirdly, we consider the Nikkei 225 index during Japan asset price bubble, which is a perfect example of an Elliott wave.     

Statistics of extremes for IID data and breakthroughs in the estimation of the extreme value index: Laurens de Haan leading contributions

In the last decades there has been a shift from the parametric statistics of extremes for IID random variables, based on the probabilistic asymptotic results in extreme value theory, towards a semi-parametric approach, where the estimation of the right tail-weight, under a quite general framework, is of major importance. After a brief presentation of classical Gumbel’s block methodology and of later improvements in the parametric framework (multivariate and multi-dimensional extreme value models for largest observations and peaks over threshold approaches), we present a coordinated overview, over the last three decades, of the developments on the estimation of the extreme value index under a semiparametric framework. Laurens de Haan has been one of the leading scientists in the field, (co-)author of many seminal ideas, that he generously shared with dozens (literally) of colleagues and students, thus achieving one of the main goals in a scientist’s life: he gathered around him a bunch of colleagues united in the endeavour of building knowledge. The last section is a personal tribute to Laurens, who fully lives his ideal that co-operation is the heart of Science. To Laurens de Haan, a token of friendship.     

Investigation of the mechanical behavior of two-component granular composites in terms of structural models

A structural model is suggested for elastomers filled with particles of two fractions — with diameters exceeding 10 μm and submicronic ones. In each fraction, the particle diameter varies randomly, but between the fractions, the average particle diameter differs by several orders of magnitude. It is assumed that the small particles, together with the matrix, behave as a homogeneous medium relative to the large ones. By using this model, the mechanical behavior of composites based on elastomers filled with different volume contents of solid particles is investigated. __________ Translated from Mekhanika Kompozitnykh Materialov, Vol. 43, No. 2, pp. 191–200, March–April, 2007.     

中国能源消费驱动因素的实证研究:基于投入产出的结构分解分析

随着中国工业化进程加快,中国成为世界上第二大能源消费国.中国以煤炭为主化石能源的大量消费,造成了一系列的环境、经济、社会和政治问题.因此,制定合理的能源战略对中国的长期可持续发展至关重要.为了给科学合理的能源政策——尤其是中国的节能政策和相关气候变化政策的制定提供科学依据,很有必要对中国快速增长的能源消费背后的驱动因素加以研究.利用基于投入产出的结构分解模型,克服了经典的IPAT模型结果过于整合的缺点,研究了人口增长、效率、生产结构以及生活方式和水平等因素对中国能源消费的影响.经研究发现,1992至2007年间,人均GDP的提高是中国能源消费增长的最大驱动力,推动了241.93%的能源消费增量.人均GDP的推动作用随着中国经济的持续增长而增强.而能源强度的降低则部分抵消了能源消费的增量,抵消幅度达到128.73%.随着目前中国重化工业化进程加快,近年来能源强度的抵消能力有所减弱.从最终使用的角度看,总资本形成和出口则是推动能源消费增长的重要驱动力,分别为中国能源消费的增长贡献了42.42%和39.43%.     

科研单位减员过程中员工心理变化的实证研究

本文使用相关分析和回归分析等方法,探讨了科研单位进行减员过程中管理者的各种决策特点与员工心理特征的相互关系     

中国资本市场价值溢价与CAPM实证研究

以1995年7月-2005年12月我国证券市场深沪两市的上市公司为样本,考察了价值溢价随规模变化的规律,并检验了CAPM能否解释价值溢价以及与权益帐面市值比B/M(或规模)无关的贝塔(β)能否与股票的平均收益相补偿.实证检验发现:1)中国股市存在一定程度的价值溢价,尤其是小规模(Size)价值股在平均收益上存在着明显的价值溢价,而大规模(Size)价值股则不存在价值溢价现象;2)CAPM能够解释我国股市从1995年7月至2005年12月期间的价值溢价.从CAPM对由不同规模(Size)和B/M构造的6个组合的回归结果来看,相对于贝塔(β)为常数情况下,允许贝塔(β)的每年变化会略微增加CAPM对平均收益能力的解释能力;3)在我国股市上,只有与B/M(或规模)有关的贝塔(β)才能解释股票的收益,而与B/M(或规模)无关的贝塔(β)则不能解释股票的收益.     

Learning multicriteria classification models from examples: Decision rules in continuous space

The classification problem statement of multicriteria decision analysis is to model the classification of the alternatives/actions according to the decision maker's preferences. These models are based on outranking relations, utility functions or (linear) discriminant functions. Model parameters can be given explicitly or learnt from a preclassified set of alternatives/actions.In this paper we propose a novel approach, the Continuous Decision (CD) method, to learn parameters of a discriminant function, and we also introduce its extension, the Continuous Decision Tree (CDT) method, which describes the classification more accurately.The proposed methods are results of integration of Machine Learning methods in Decision Analysis. From a Machine Learning point of view, the CDT method can be considered as an extension of the C4.5 decision tree building algorithm that handles only numeric criteria but applies more complex tests in the inner nodes of the tree. For the sake of easier interpretation, the decision trees are transformed to rules.     

Efficiency of the medical care industry: Evidence from the Italian regional system

What might be the relation between clinical research and efficiency of medical care suppliers? Is the hypothesis of a positive relation consistent? Considering efficiency as the supplier’s ability to maximize the number of patients hospitalized in a mobility process among regions (i.e. mobility balance), this work aims at highlighting the existence of a positive externality of pharmaceutical clinical research on that kind of efficiency. In other words, an externality is able to affect the patients’ perception of good/bad quality of outputs supplied by the medical care industry, leading their mobility process. Taking Italy and the mobility of patients among regions into account, an Operational Research study will be performed in order to support this assumption.The goal of this work is to show an alternative way to increase the efficiency of medical care suppliers on the market of health care, that is to say, through their competitiveness on the market of human experimentation.     

Compromise programming: A utility-based linear-quadratic composite metric from the trade-off between achievement and balanced (non-corner) solutions

In this paper, compromise programming (CP) is viewed as the maximization of the decision maker’s additive utility function (whose arguments are the criteria under consideration) subject to an efficient frontier of criteria and the non-negativity constraints in a deterministic context. This is equivalent to minimizing the difference (‘distance’) between utility at the ideal point and utility at a frontier point on the criteria map, a meaningful statement as minimizing distances to the utopia is the ethos of compromise programming. By Taylor expansion of utility around the ideal point, the distance to the utopia becomes the weighted sum of linear and quadratic CP distances, which gives us the composite metric. While the linear terms pursue achievement, the quadratic ones pursue balanced (non-corner) solutions. Because some decision makers fear imbalance while others prefer large achievements even to the detriment of balance, the paper defines an aversion to imbalance ratio, so that the composite linear-quadratic metric should conform to this ratio depending on the decision maker’s preferences and attitudes. As the problem of selecting an appropriate metric is an ongoing issue in CP, the paper is a contribution to theory and practice. For the sole purpose of suggesting industrial applications, an example is developed.     

A dynamic benchmarking system for assessing the recovery of inpatients: Evidence from the neurorehabilitation process

The shortage of medical resources (mainly beds) is a critical and increasingly prevalent problem affecting hospitals. Of the factors that contribute to these shortages, the ambiguity and insufficiency of the criteria used to identify whether an inpatient should be discharged are among the most detrimental. To address this issue, this study applies data envelopment analysis (DEA) on existing inpatient data from the Neurorehabilitation Center at Toronto’s Bridgepoint Hospital to create a dynamic benchmarking system to evaluate the health stage of an inpatient ready to be discharged. Unlike the more traditional parametric techniques, DEA provides non-subjective benchmarking that does not require any prior specification of the production function making it a more desirable choice for this application. The dynamic model categorizes the inpatient’s discharge status as rejected, under observation, or approved. This new approach not only allows managers to gain insight into the potential causes of medical resource shortages, but also allows clinicians to treat inpatients more effectively based on their discharge categories. For validation, the results of the dynamic model were compared with actual inpatient discharge assessments provided by the Bridgepoint Hospital.     

Dynamic effects in inefficiency: Evidence from the Colombian banking sector

Firms face a continuous process of technological and environmental changes that requires them to make managerial decisions in a dynamic context. However, costs and constraints prevent firms from making instant adjustments towards optimal conditions and may cause inefficiency to persist in time. We propose a dynamic inefficiency specification that captures differences in the adjustment costs among firms and non-persistent effects of inefficiency heterogeneity. The model is fitted to a ten year sample of Colombian banks. The new specification improves model fit and have effects on efficiency estimations. Overall, Colombian banks present high inefficiency persistence but important differences between institutions are found. In particular, merged banks present low adjustment costs that allow them to recover rapidly efficiency losses derived from merging processes.     

基于变结构协整方法的期货市场与证券市场关联性分析——沪深300股指期货与沪深300指数的实证分析

对我国沪深300指数与沪深300指数期货的周数据进行了关联性分析.首先利用EG检验和Johansen系统检验对两指数进行协整检验,然后通过3种变结构协整模型分别检验,结果找到了变点,得到了变机构长期均衡关系和误差修正模型,同时比较了4种模型的应用效果,给出了相关的政策建议.     

A differential equation model for predicting public opinions and behaviors from persuasive information: Application to the index of consumer sentiment

This paper shows that ideodynamics is a differential equation model capable ofpredicting public opinions and behaviors from persuasive information. Statistics are also developed for the model. The methodology is applied to predict the time trend of public opinion about the economy as quantified by the Index of Consumer Sentiment compiled by the University of Michigan. The explanatory variables are derived from news coverage of the economy in positive and negative terms.     

Comparing the validity of numerical judgements elicited by direct rating and point allocation: Insights from objectively verifiable perceptual tasks

Two popular methods for assigning numerical values to a set of to-be-judged objects in order to capture their relative standing are Direct Rating (DR) and Point Allocation (PA). People using PA distribute a fixed sum of 100 points among the objects, while people using DR rate each object on a fixed scale, typically 0–10, later rescaled to sum to 100. Prior research shows that these methods exhibit distinct profiles when values are ranked from largest to smallest, with DR being more test–retest reliable. But which method best translates people’s inner judgments into outer numerical values (is more valid)? Instead of examining subjective or abstract stimuli, we use objectively verifiable perceptual tasks, namely judgments of line length presented using bar charts. We show that (i) DR is more inter-rater reliable than PA; (ii) DR is more accurate than PA at the individual level; (iii) but there is no difference in accuracy when individual judgments are combined to form group-level estimates; and (iv) DR judgments were improved by using prior knowledge of method bias, whereas PA judgments were not.     

On the acceptance of trigonometry in wasan: Evidence from a text of Aida Yasuaki

The Dutch introduced trigonometry to Japan in the middle of the 17th century, but the use of trigonometry was rarely seen until the 18th century, and its use was limited to practical purposes such as surveying and astronomy. It was rarely used to solve geometry problems currently called wasan, the reason for which is not yet fully explained. In this paper, I summarize a book by Aida Yasuaki (1747–1817) in which he strongly criticizes the use of trigonometry for wasan, and try to find the origins of his antipathy.     

我国燃料油期货价格与现货价格动态关系:基于TVECM的实证研究

利用门限向量误差修正模型(TVECM)研究了我国燃料油期货价格与现货价格之间的动态关系,实证分析发现,两者之间存在显著的非线性关系,门限值0.100将系统分为两个状态,在极端状态中期货价格和现货价格的调整速度均比标准状态快.然而,在两个状态中期货市场均具有较高的价格发现功能.