A scenario discovery study of the impact of uncertainties in the global container transport system on European ports

The global container transport system is changing quickly. Ports can be severely affected by these changes; therefore, ports need insight into how the system might change and what the impact of this will be on their competitive position. Given the intrinsic complexity of the container transport system and the presence of a wide range of deeply uncertain factors affecting the system, we use an exploratory modeling approach to study future scenarios for the global container network. Using scenario discovery and worst-case discovery, we assess the implications of various uncertain factors on the competitive position of the port of Rotterdam. It is found that overall the competitive position of Rotterdam is quite robust with respect to the various uncertain factors. The main vulnerability is the quality of the hinterland connections. A modest deterioration of the quality of the hinterland connections, resulting in increased travel time, will result in a loss of throughput for Rotterdam.     

Corporate Governance,Companies’ Disclosure Practices and Market Transparency: A Cross Country Study

We examine the link between corporate governance, companies’ disclosure practices and their equity market transparency in a study of more than 5,000 listed companies in 23 countries covering the period 1 January 2003 to 31 December 2008. Our results confirm the belief that better‐governed firms make more frequent disclosures to the market. We also find greater disclosure in common law relative to code law countries. However firms with better governance in both code and common law countries make more frequent disclosures. We measure market transparency by the timeliness of prices. In contrast to single country studies, results show, for the 23 countries collectively, better corporate governance is associated with less timely share prices. This would suggest that a firm substitutes better corporate governance for transparency. We are thus led to the conclusion that even if information is disclosed more frequently by better‐governed firms, it does not necessarily follow that information is reflected in share prices on a timelier basis.     

Private information flow and price discovery in the U.S. treasury market

Using intraday data, we identify the intensity of private information flow in the U.S. Treasury market. Our results show that the intensity of private information flow is highly correlated with public information shocks and higher for longer maturity bonds. More importantly, we find that bond price changes associated with high intensity of private information flow tend to be persistent, whereas those associated with low intensity of private information flow are more likely reversed. While public information and private information are the main determinants of bond price variations on days with news announcements, private information and liquidity shocks are important determinants of bond price variations on days with no significant events. Finally, we show that the depth of limit order book is inversely related to the intensity of private information flow. Nevertheless, informed dealers do not seem to use hidden orders to disguise their trading intentions.     

Linear and nonlinear dynamic relationships between housing prices and trading volumes

This study applied linear and nonlinear causality tests and estimation models to investigate the efficiency of housing prices and volumes in the United States and its four major regions. The results of this study confirm that housing volumes can function as a price-discovery indicator. According to the nonlinear volatility of housing prices, this study verified numerous hypotheses. Housing returns can also influence housing volume. The results of this study imply that housing price efficiency can vary based on market conditions. Consequently, estimating the behavior of housing prices through a linear model can result in underestimating the information reflected by housing returns.     

Literature-related discovery (LRD): Potential treatments for cataracts

Literature-related discovery (LRD) is the linking of two or more literature concepts that have heretofore not been linked (i.e., disjoint), in order to produce novel, interesting, plausible, and intelligible knowledge (i.e., potential discovery). The open discovery systems (ODS) component of LRD starts with a problem to be solved, and generates solutions to that problem through potential discovery. We have been using ODS LRD to identify potential treatments or preventative actions for challenging medical problems, among myriad other applications.This paper describes the second medical problem we addressed (cataract) using ODS LRD; the first problem addressed was Raynaud's Phenomenon (RP), and was described in the third paper of this Special Issue. Cataract was selected because it is ubiquitous globally, appears intractable to all forms of treatment other than surgical removal of cataracts, and is a major cause of blindness in many developing countries.The ODS LRD study had three objectives: a) identify non-drug non-surgical treatments that would 1) help prevent cataracts, or 2) reduce the progression rate of cataracts, or 3) stop the progression of cataracts, or 4) maybe even reverse the progression of cataracts; b) demonstrate that we could solve an ODS LRD problem with no prior knowledge of any results or prior work (unlike the case with the RP problem); c) determine whether large time savings in the discovery process were possible relative to the time required for conducting the RP study. To that end, we used the MeSH taxonomy of MEDLINE to restrict potential discoveries to selected semantic classes, as a substitute for the manually-intensive process used in the RP study to restrict potential discoveries to selected semantic classes. We also used additional semantic filtering to identify potential discovery within the selected semantic classes.All these goals were achieved. As will be shown, we generated large amounts of potential discovery in more than an order of magnitude less time than required for the RP study. We identified many non-drug non-surgical treatments that may be able to reduce or even stop the progression rate of cataracts. Time, and much testing, will determine whether this is possible. Finally, the methodology has been developed to the point where ODS LRD problems can be solved with no results or knowledge of any prior work.     

Literature-related discovery (LRD): Water purification

Literature-related discovery (LRD) is the linking of two or more literature concepts that have heretofore not been linked (i.e., disjoint), in order to produce novel, interesting, plausible, and intelligible knowledge (i.e., potential discovery). LRD has two main components that differ in their methodological approach to discovery: Literature-based discovery (LBD) produces potential discovery through analysis of the technical literature alone; Literature-assisted discovery (LAD) produces potential discovery through both analysis of the technical literature and use of selected authors of that literature. These authors generate potential discovery as proposers, workshop/panel participants, or in other active roles.The open discovery systems (ODS) component of LRD starts with a problem to be solved, and generates solutions to that problem through potential discovery. We have been using ODS LRD to identify potential treatments or preventative actions for challenging medical problems, among myriad other applications. The previous four papers in this Special Issue describe the application of ODS LRD (specifically, the ODS LBD variant) to Raynaud's Phenomenon (RP), cataracts, Parkinson's Disease (PD), and Multiple Sclerosis (MS).One goal of the present study was to determine whether LRD could be successfully applied (for the first time) to a challenging non-medical technical problem to generate potential discovery. The second goal was to explore the use of both LRD variants (LBD and LAD) to a non-medical technical problem. We selected the problem of water purification (WP) because of universal applicability and sponsor interest.We used LRD to identify purification concepts, technology components and systems that could lead to improved water purification techniques. We accessed many disparate disciplines to identify purification concepts from literatures not normally associated with water purification. We used two LBD approaches, Cluster Filtering and Latent Semantic Indexing (LSI), to search for potential discovery. We generated voluminous amounts of potential discovery, and believe we have only scratched the surface of what is possible. We also ran a short experiment using LAD to identify experts associated with potential discovery concepts, and use their expertise to generate potential discovery for water purification.     

中国股票市场透明度改革效果的理论与检验

文章通过观察我国股票市场微观结构特征,在理性预期的分析框架内,用贝叶斯模型解释交易成本、信息不对称和价格发现效率,给出交易前透明度增加对市场微观结构产生影响的三个假设。在此基础上,选择沪深300指数样本股票,采用三种不同检验方法对假设进行实证检验。检验结果表明:交易前透明度的增加,减少了交易成本,降低了股票交易中的信息不对称,提高了市场的价格发现效率。     

Web service discovery among large service pools utilising semantic similarity and clustering

With the rapid development of electronic business, Web services have attracted much attention in recent years. Enterprises can combine individual Web services to provide new value-added services. An emerging challenge is the timely discovery of close matches to service requests among large service pools. In this study, we first define a new semantic similarity measure combining functional similarity and process similarity. We then present a service discovery mechanism that utilises the new semantic similarity measure for service matching. All the published Web services are pre-grouped into functional clusters prior to the matching process. For a user’s service request, the discovery mechanism first identifies matching services clusters and then identifies the best matching Web services within these matching clusters. Experimental results show that the proposed semantic discovery mechanism performs better than a conventional lexical similarity-based mechanism.     

发现成本与创业机会

节约成本是创造财富的根本原因,斯密的分工创造财富的原理仅是节约成本的方式。通过对发现成本、内化成本及创业之间的关系进行分析,提出:创业是发现成本、节约成本最重要的形式;创业企业有不断发现成本、节约成本的机会;在发现成本、节约成本的过程中能挖掘更多的创业机会。     

The Lead‐Lag Relationship Between Cash and Stock Index Futures in a New Market

This paper investigates the lead‐lag relationship in daily returns and volatilities between price movements of the FTSE/ATHEX‐20 and FTSE/ATHEX Mid‐40 stock index futures and the underlying cash indices in the relatively new futures market of Greece. Empirical results show that there is a bi‐directional relationship between cash and futures prices. However, futures lead the cash index returns, by responding more rapidly to economic events than stock prices. This speed is much higher in the more liquid FTSE/ATHEX‐20 market. Moreover, results indicate that futures volatilities spill information over to the corresponding cash market volatilities in both investigated futures markets, but volatilities in the cash markets have no effect on the volatilities of futures markets. Overall, it seems that new market information is disseminated faster in the futures market compared to the stock market. This implies that the futures markets can be used as price discovery vehicles, providing further evidence that derivatives markets contribute to completing and stabilising capital markets in Greece. A further finding of this study is that futures volume and disequilibrium effects between cash and futures prices are important variables in the explanation of volatilities in cash and futures markets.