A study of total beta specification through symmetric regression: the case of the Johannesburg Stock Exchange

A topic of recent interest is risk management in equity investments from emerging markets. One traditional measure for systematic risk of an asset is beta, which is constructed through ordinary least squares (OLS) regression between historical returns on an individual asset and an index representing the overall market. OLS regression assumes all the error lies within the asset returns. Tofallis (Eur J Oper Res 187(3):1358–1367, 2008) made the case for constructing a systematic risk measure through symmetric regression, where error is assumed to be present in the returns of both the asset and the index. In this paper, we construct a systematic risk measure using symmetric regression for the case of the Johannesburg Stock Exchange (JSE). This paper makes the case that the so-called ‘total beta’ parameter provides a more realistic and stable estimator for market-related risk and return. The total beta estimate, explicitly allowing for error in both variables, is less likely to underestimate the magnitude of the beta parameter.     

Measuring Plant Cover in Sagebrush Steppe Rangelands: A Comparison of Methods

Methods that are more cost-effective and objective are needed to detect important vegetation change within acceptable error rates. The objective of this research was to compare visual estimation to three new methods for determining vegetation cover in the sagebrush steppe. Fourteen management units at the US Sheep Experiment Station were identified for study. In each unit, 20 data collection points were selected for measuring plant cover using visual estimation, laser-point frame (LPF), 2 m above-ground-level (AGL) digital imagery, and 100-m AGL digital imagery. In 11 of 14 management units, determinations of vegetation cover differed (P < 0.05). However, when combined, overall determinations of vegetation cover did not differ. Standard deviation, corrected sums of squares, coefficient of variation, and standard error for the 100 m AGL method were half as large as for the LPF and less than the 2-m AGL and visual estimate. For the purpose of measuring plant cover, all three new methods are as good as or better than visual estimation for speed, standard deviation, and cost. The acquisition of a permanent image of a location is an important advantage of the 2 and 100 m AGL methods because vegetation can be reanalyzed using improved software or to answer different questions, and changes in vegetation over time can be more accurately determined. The reduction in cost per sample, the increased speed of sampling, and the smaller standard deviation associated with the 100-m AGL digital imagery are compelling arguments for adopting this vegetation sampling method.     

News sentiment to market impact and its feedback effect

Although market feedback on investor sentiment effect has been conceptually identified in the existing finance literature and investment strategies have been designed to explore this effect, there lacks systematic analysis in a quantified manner on such effect. Digitization of news articles and the advancement of computational intelligence applications have led to a growing influence of news sentiment over financial markets in recent years. News sentiment has often been used as a proxy for gauging investor sentiment and reflecting the aggregate confidence of the society toward future market. Previous studies have primarily focused on elucidating the unidirectional impact of news sentiment on market returns and not vice versa. In this study, we analyze more than 12 millions of news articles and document the presence of a significant feedback effect between news sentiment and market returns across the major indices in the US financial market. More specifically, we find that news sentiment exhibits a lag-5 effect on market returns and conversely market returns elicit consistent lag-1 effects on news sentiment. This aligns well with our intuition that news sentiment drives trading activity and investment decisions. In turn, heightened investment activity further stimulates involuntary responses, which manifest in the form of more news coverage and publications. The evidence presented highlights the strong correlation between news sentiment and market returns and demonstrates the benefits of advancing knowledge in data-driven modeling and its interaction with market movements.     

The data game: Measurement,uncertainty, and the challenge of quality

“Measurement, Uncertainty, and the Challenge of Quality,” by Carl Frankel, argues that corporations expect too much of science and measurement, in parallel with a culture that is similarly disposed. While science and measurement are essential to environmental progress, they are also limited in important and often overlooked ways. For instance, risk assessment provides only grossly approximate answers, and subjective quality—a central component of sustainable development—is rarely measured at all. New strategies for measuring the qualitative aspects of experience are urgently required.     

Urban planning at the turn of the 21st century

Contemporary urban planning is characterised by the following: (a) a large amount of specific research gives a large quantity of facts, but like stones of the mosaic do hot make an entire picture; (b) in the basis of these researches no one finds entire creative conceptions; (c) the theories lose touch with practical design matter; (d) in contradiction to the classical architectural epoch, urban planning loses touch with the construction of buildings; (e) the practice of urban planning and the construction of buildings lose touch with historical traditions. The corollary of these academic and unnatural specialisations is a break not only from “the tie of times” but also from the ties inside the profession. This situation has an effect on the practice of urban planning and architecture; society returns to destructive criticism. It is impossible to get away from this fact. The author makes an attempt to change this situation for the better — at least in some measures. On the basis of many years study of the results of research this paper presents a concept of contemporary urban planning. This concept is not in the form of hard recommendations, but expedient methods for the solution of problems. It is proved by the author's projects.     

Social cost‐benefit analysis of intensive versus traditional shrimp farming: A case study from India

This paper attempts a social cost‐benefit analysis of intensive versus traditional shrimp farming in West Bengal, India. Using primary data, the paper shows that although intensive shrimp farming yields high returns as compared to traditional shrimp farming, when the opportunity costs and environmental costs of shrimp farming, including disease risk, are accounted for, intensive shrimp farming loses its advantage. Sensitivity analysis shows that if the expected benefits were to fall short by 15% and costs rise by a similar proportion, intensive shrimp farmers would report higher losses than traditional shrimp farmers. Large traditional shrimp farmers continue to report positive net returns. These results are also most pronounced for small and marginal intensive shrimp farmers. Further, if the probability of disease risk is also accounted for, intensive shrimp farming reports significant losses whereas traditional shrimp farming in most cases shows positive net returns. In light of the high social costs and risks, this paper questions the rationale behind promoting intensive shrimp farming, especially among small and marginal holdings, as an income‐generating activity or poverty alleviation measure in the absence of an enabling environment. It suggests that policymakers need to factor in sustainability concerns and the local context when formulating policies to promote intensive shrimp farming.     

STATISTICAL TERMINOLOGY: DEFINITIONS AND INTERPRETATION FOR FLOOD PEAK ESTIMATION1

ABSTRACT: Considerable effort is expended each year in making flood peak estimates at both gaged and ungaged sites. Many methods, both simplistic and complex, have been proposed for making such estimates. The hydrologist that must make an estimate at a particular site is interested in the accuracy of the estimate. Most methods are developed using either statistical analyses or analytical optimization schemes. While publications describing these methods often include some statistical measure of goodness-of-flt, the terminology often does not provide the potential user with an answer to the question,‘How accurate is the estimate?’ That is, statistical terminology often are not used properly, which may lead to a false sense of security. The use of the correct terminology will help potential users evaluate the usefulness of a proposed method and provide a means of comparing different methods. This study provides definitions for terms often used in literature on flood peak estimation and provides an interpretation for these terms. Specific problems discussed include the use of arbitrary levels of significance in statistical tests of hypotheses, the identification of both random and systematic variation in estimates from hydrologic methods, and the difference between accuracy of model calibration and accuracy of prediction.     

Impact of the FTSE4Good Index on firm price: an event study

This paper examines whether corporate financial performance is affected by public endorsement of environmental and social performance. Event study methodology, which relies on the notion of market efficiency, is used to examine the relationship between positive and negative announcements and changes in share prices or daily returns. Inclusion in and deletion from the FTSE4Good UK Index is used as a proxy measure for good (poor) corporate social responsibility. The abnormal or unexpected daily returns associated with an event are calculated and their significance tested. The results show a trend towards positive and negative announcements having the expected effects on daily returns. But these movements are not significant and the data do not suggest that a firm's presence on the index brings it any significant financial return for signalling its corporate social responsibility.     

Dynamic real-time risk analytics of uncontrollable states in complex internet of things systems: cyber risk at the edge

The Internet of Things (IoT) triggers new types of cyber risks. Therefore, the integration of new IoT devices and services requires a self-assessment of IoT cyber security posture. By security posture this article refers to the cybersecurity strength of an organisation to predict, prevent and respond to cyberthreats. At present, there is a gap in the state of the art, because there are no self-assessment methods for quantifying IoT cyber risk posture. To address this gap, an empirical analysis is performed of 12 cyber risk assessment approaches. The results and the main findings from the analysis is presented as the current and a target risk state for IoT systems, followed by conclusions and recommendations on a transformation roadmap, describing how IoT systems can achieve the target state with a new goal-oriented dependency model. By target state, we refer to the cyber security target that matches the generic security requirements of an organisation. The research paper studies and adapts four alternatives for IoT risk assessment and identifies the goal-oriented dependency modelling as a dominant approach among the risk assessment models studied. The new goal-oriented dependency model in this article enables the assessment of uncontrollable risk states in complex IoT systems and can be used for a quantitative self-assessment of IoT cyber risk posture.

     

Fusing strategic risk and futures methods to inform long-term strategic planning: case of water utilities

Risks and futures methods have complementary strengths as tools for managing strategic decisions under uncertainty. When combined, these tools increase organisational competency to evaluate and manage long-term risks, improving the flexibility and agility of the organisation to deal with gross uncertainties. Here, we set out a framework to guide the assessment of strategic risks for long-term business planning, based on its application at Portugal’s largest water utility, Empresa Portuguesa das Águas Livres. Our approach extends strategic risk assessment by incorporating scenario planning—a futures approach used to help the utility move beyond single point forecast of risks to focus on critical dimensions of uncertainty that are fundamental to the resilience of corporate objectives and their vulnerability to external pressures. We demonstrate how we combine two complementary approaches—risk and futures—and use them to assess (i) how a set of baseline strategic risks for a water utility evolves under alternative futures, (ii) the aggregate corporate-level risk exposure, and (iii) the process and responses needed to manage multiple, interdependent strategic risks. The framework offers a corporate approach to evolving strategic risks and improves a utility’s (i) knowledge of uncertainties, (ii) ability to assess the impacts of external developments over long time horizons and the consequences of actions and (iii) degree of flexibility to adapt to possible future challenges. The framework supports risk managers in their long-term strategic planning, through the appraisal and management of multiple, interdependent long-term strategic risks and can be replicated in other organisational contexts to bridge operational and corporate perspectives of enterprise risk.

     

Long memory in energy futures markets: Further evidence

This paper investigates long memory (or long-range dependence) in price returns and volatilities of energy futures contracts with different maturities. Based on a modified rescaled range analysis and three local Whittle methods, the results from rolling sample test suggest that the returns showed little or no long-range dependence over time but the volatilities displayed significant time-varying long-range dependence. Our evidence shows that some extreme events could cause long memory in returns and volatilities, leading to market inefficiency. Employing multiscale analysis, we find that the returns displayed no long-range dependence for any of the chosen time scales. Significant long-range dependence only existed in volatilities for daily time scales but not for monthly or yearly time scales.     

EVALUATING DIRECT BENEFIT ESTIMATION PROCEDURES FOR IRRIGATION PROJECTS: A SIMPLIFIED APPROACH1

ABSTRACT: An integral part of evaluating the net benefits generated by an existing or proposed irrigation project is the assessment of the associated impacts in commodity markets. Traditionally, these impacts have been measured by either assuming no change in commodity prices and calculating net returns to project farmers, or by allowing commodity prices to fall in accordance with a given elasticity of demand and subtracting commodity production costs from the associated area under the commodity demand curve. In either case, it is implicitly assumed that supply is perfectly inelastic. This article establishes that traditional approaches to measuring direct benefits are biased. Formulae are presented for calculating the maximum absolute and relative error which may result from using these techniques as a function of project size. Direct benefit estimates are then evaluated for three irrigation projects in Nebraska, illustrating how these results can be used to improve project evaluation procedures.     

Assessment practices in the policy and politics cycles: a contribution to reflexive governance for sustainable development?

ABSTRACT

This article examines systematic assessment practices linked to sustainable development policies. We consider five types of assessment—monitoring, policy evaluation, formal audit, peer review, and specialist reporting—and explore their fate in the policy and electoral politics cycles. In contrast to traditional views of the policy cycle, we note that systematic assessments provide complementary feedback around the entire policy cycle. However, despite this omnipresence, their policy relevance is usually severely limited, inter alia because the policy cycle captures only parts of the political reality. A major concern for politicians (but not necessarily for policy or governance scholars) that goes far beyond the formulation and implementation of policies is the broader cycle of electoral politics that determines the state's political personnel as well as government priorities. Here, we highlight that the findings of systematic assessments are often lost in a cacophony of voices to which politicians are more carefully attuned, such as media responses and opinion polls, implying that scientific evidence is simply ‘overwritten’ with other kinds of evidence representing alternative rationalities and priorities. Despite numerous shortcomings, the true value of systematic assessment practices lies in their potential to furnish ammunition to state and non-state actors interested in securing change.     

Measuring bioavailability: from a scientific approach to standard methods

Biological effects are not related to the total concentration of a contaminant in the soil and soil-like materials. Organisms respond only to the fraction that is biologically available. The bioavailable fractions of contaminants are dependent on soil properties and various processes varying with time and on the behavior or the target organism. Bioavailability may be assessed in two complementary ways: (i) by chemical methods (e.g., extraction methods), which determine a defined available fraction of a well defined class of contaminants; and (ii) by biological methods, which expose organisms to soil or soil eluates to monitor effects. Although there is scientific discussion on the concept of bioavailability, the literature gives enough evidence to recognize bioavailability as a promising tool in risk assessment. A large number of methods are available. Under regulatory aspects of soil protection, a risk assessment should be based on the same common concept of determination and assessment of exposure and measuring and assessment of effects. A harmonized framework on bioavailability is necessary to promote the development and introduction of workable (international) standard methods to be used in soil and site assessment. The working group 'Bioavailability' of ISO/TC190-Soil Quality has developed a guidance document for development and selection of methods to assess bioavailability for different target species with regard to several classes of contaminants. The way to this standard, on the border of science and regulation, is described in this article.     

Heterogeneous and unconventional coalitions around global food risks: integrating Brazil into the debates

Current debates about food-borne risks (GMOs and BSE) have not only deepened public concern about how food is produced on farms, processed in factories, and transported, stored and traded. More importantly, these debates have exposed a crisis related to central social issues, such as the role of science, politics and business corporations in the decision-making processes for determining which risks societies should, or are prepared to, assume. In this article, I discuss how cultural and social constructivist studies of environmental and health risks and Ulrich Beck's theory of world risk society can contribute to the analysis of how to deal with these conflicts. The criticism of quantitative methods of risk analysis has resulted in a certain idealization of the lay knowledge of risks as being intuitively more correct than the scientific one. One consequence of this polarization between expert and lay knowledge—idealizing the latter—is a disappointing vagueness when looking for alternatives on how to deal practically with risks that have important consequences. A key obstacle to the implementation of some of the suggestions presented by the critical risk analysis approach is that, for example, in the current global dynamics of food-borne risks we can find heterogeneous alliances for and against GMOs allying lay people and experts, as well as conventional and unconventional social actors, in a complicated manner, at the regional, national and international levels. Since a significant part of the analysis of manufactured risks focuses on the situation of highly industrialized countries, a more complex perspective of these lay and scientific alliances can be obtained from a more extensive study of the reactions surrounding GMOs and BSE in less-industrialized countries, such as Brazil. Copyright © 2002 John Wiley & Sons, Ltd.     

流域污染物通量测算方法研究

流域水系内污染物通量不仅能够用于评价各类污染源的水污染物入河负荷,也是对流域污染特征,水污染物在河流水体中复杂迁移、转化过程的最直观反应。准确测算流域水系内污染物跨界通量及其时空分布是进行流域水环境风险预警和风险管理的重要前提之一。针对目前多种污染物通量测算方法在进行污染物年通量估算时,结果不确定性大这一突出问题,以流域水质监测站年内逐日流量、悬浮颗粒物监测数据作为悬浮颗粒物年通量参考值,基于以月、半月、周为周期的监测策略,将逐日流量、悬浮颗粒物监测数据重新筛选抽样构造,由此,系统分析了不同流域集水面积、污染通量监测频次和目前常用通量估算方法对污染物年通量估算不确定性的影响。所得方法和结论可为进一步制定流域污染物通量的测算规范提供方法指引和技术支持。     

碳中和评估与预测预估方法研究进展

人类活动排放的大量温室气体已经造成多种不利影响,为缓解这些不利影响,已有多个国家提出了碳中和目标。碳中和评估与预测预估是实现碳中和目标的科学基础,准确估算碳排放量和碳去除量是进行碳中和评估的关键,可以帮助决策者制定减排和增汇政策。本文梳理了碳排放量和碳去除量的估算方法以及预测预估方法的原理和特点,以期为准确评估碳中和现状以及预测预估未来情景下实现碳中和目标的可能性和路径提供方法论参考。碳排放量的估算方法可以分为用于支撑碳交易市场的碳排放核算方法、面向消费侧碳排放的估算方法和基于因素分解法的碳排放计量方法三大类;前两类方法主要用于历史碳排放量的盘点,第三类方法可用于碳排放量的预估。陆地生态系统碳去除量估算方法可以分为统计模型法、机理模型法和遥感模型法三大类;第一类方法应用最早但估算结果较粗糙,第二类方法模型应用最多但估算结果存在较大的不确定性,第三类方法观测范围大但缺乏预测预估能力。近年来,模型分析法在碳中和评估和预测预估上得到越来越广泛的应用。     

Metrics,decisions, and strategies: Environmental performance measurement in the electric utility industry

The twin challenges of increased competition and environmental consciousness are causing companies in the utility industry to re-examine their methods for measuring environmental performance. A new paradigm is emerging which has already appeared in other industries—treating environmental quality as a potential source of profitability and competitive advantage. This article discusses how utilities and industrial companies can develop an environmental performance measurement framework, integrate it into their strategic and operating business practices, and use it for evaluation of alternative environmental strategies.     

Comparison of three enzyme immunoassays for measuring 17beta-estradiol in flushed dairy manure wastewater

Natural steroidal estrogens are an environmental concern because low nanogram per liter concentrations in water can adversely affect aquatic vertebrate species by disrupting the normal function of their endocrine systems. There is a critical need to accurately measure estrogens in dairy wastes, a potential source of estrogens such as 17beta-estradiol, to assess the risk of estrogen contamination of agricultural drainage waters resulting from land application. Commercially available enzyme immunoassay (EIA) kits have been used for measuring 17beta-estradiol in livestock manure, but it is not known if different EIAs provide similar results. We compared three EIAs by measuring 17beta-estradiol in two samples of flushed dairy manure wastewater (FDMW). The measured concentrations of 17beta-estradiol in FDMW differed according to the immunoassay used. The differences were attributed to a matrix interference associated with coextracted humic substances. Future research should develop methods that enable routine measurement of 17beta-estradiol in livestock wastes by more conclusive analytical techniques such as gas chromatography-mass spectrometry.     

GIS‐Based Spatial Precipitation Estimation: A Comparison of Geostatistical Approaches1

Abstract: As one of the primary inputs that drive watershed dynamics, the estimation of spatial variability of precipitation has been shown to be crucial for accurate distributed hydrologic modeling. In this study, a Geographic Information System program, which incorporates Nearest Neighborhood (NN), Inverse Distance Weighted (IDW), Simple Kriging (SK), Ordinary Kriging (OK), Simple Kriging with Local Means (SKlm), and Kriging with External Drift (KED), was developed to facilitate automatic spatial precipitation estimation. Elevation and spatial coordinate information were used as auxiliary variables in SKlm and KED methods. The above spatial interpolation methods were applied in the Luohe watershed with an area of 5,239 km², which is located downstream of the Yellow River basin, for estimating 10 years’ (1991‐2000) daily spatial precipitation using 41 rain gauges. The results obtained in this study show that the spatial precipitation maps estimated by different interpolation methods have similar areal mean precipitation depth, but significantly different values of maximum precipitation, minimum precipitation, and coefficient of variation. The accuracy of the spatial precipitation estimated by different interpolation methods was evaluated using a correlation coefficient, Nash‐Sutcliffe efficiency, and relative mean absolute error. Compared with NN and IDW methods that are widely used in distributed hydrologic modeling systems, the geostatistical methods incorporated in this GIS program can provide more accurate spatial precipitation estimation. Overall, the SKlm_EL_X and KED_EL_X, which incorporate both elevation and spatial coordinate as auxiliary into SKlm and KED, respectively, obtained higher correlation coefficient and Nash‐Sutcliffe efficiency, and lower relative mean absolute error than other methods tested. The GIS program developed in this study can serve as an effective and efficient tool to implement advanced geostatistics methods that incorporate auxiliary information to improve spatial precipitation estimation for hydrologic models.