Stock Market Return and Volatility: Day-of-the-week Effect

Cataloged from PDF version of article.This paper examines the stock market returns and volatility relationship using US daily returns from May 26, 1952 to September 29, 2006. The empirical evidence reported here does not support the proposition that the return-volatility relationship is present and the same for each day of the week. © 2010 Springer Science+Business Media, LLC

CrowdHiLite: A Peer Review Service to Support Serious Reading on the Screen

The advent of smart devices and consumerisation of IT has produced a significant and permanent shift away from print-based reading to digital reading. This, in turn, has changed people’s reading behaviours and suggests that adapted mechanisms should be considered to support digital reading. It is particularly important for novice readers who need to read in-depth scientific literature in their chosen field. In this paper, we propose CrowdHiLite, a novel service architecture that allows expert readers to provide suggestion on individual readers’ highlights to support their reading on the screen through the use of crowdsourcing technique. A demonstration was also provided to show how it would work in real world. A preliminary experiment comparing novice readers’ reading performance with expert rated highlights and normal highlights on the same document found improved reading efficiency and comprehension with the former

Human-Centred Design for Intelligent Environments: Preface to the proceedings of the workshop on Human Centred Design for Intelligent Environments.

Preface to the proceedings of the workshop on “Human Centred Design for Intelligent Environments” organised in conjunction with the 2016 BCS British HCI Conference held at Bournemouth University, July 11th-15th 2016

Exploring the Roles of Social Participation in Mobile Social Media Learning: A Social Network Analysis

Social media is increasingly becoming an essential platform for social connectivity in our daily lives. The availability of mobile technology has further fueled its importance – making it a ubiquitous tool for social interaction. However, limited studies have been conducted to investigate roles of social participation in this field. Thus, the study investigates roles of social participation in mobile social media learning using the “ladder of participation and mastering.” Participants were students taking an educational technology course in a local university. The study was conducted in a four-month period. Data was collected from discussions while learning among the students a social media platform, Facebook groups, on mobile devices. The data was analyzed using a social network analysis tool, NodeXL. Data was analyzed based on egocentric networks, betweeness centrality, and closeness centrality. The findings revealed that there are four roles of social participation in mobile social media, which are: (i) lurkers; (ii) gradually mastering members/passive members; (iii) recognized members; and (iv) coaches. The findings also indicated that over the course of four months, learners can inter-change roles of social participation – becoming more central or less central in learning discussions. As a result, a roles of social participation continuum for mobile social media learning is proposed. Future research could be conducted in other fields to investigate whether the continuum produced could be used to understand the relationship between mobile social media learning and social participation roles

Neural net diagnostics for VLSI test

This paper discusses the application of neural network pattern analysis algorithms to the IC fault diagnosis problem. A fault diagnostic is a decision rule combining what is known about an ideal circuit test response with information about how it is distorted by fabrication variations and measurement noise. The rule is used to detect fault existence in fabricated circuits using real test equipment. Traditional statistical techniques may be used to achieve this goal, but they can employ unrealistic a priori assumptions about measurement data. Our approach to this problem employs an adaptive pattern analysis technique based on feedforward neural networks. During training, a feedforward network automatically captures unknown sample distributions. This is important because distributions arising from the nonlinear effects of process variation can be more complex than is typically assumed. A feedforward network is also able to extract measurement features which contribute significantly to making a correct decision. Traditional feature extraction techniques employ matrix manipulations which can be particularly costly for large measurement vectors. In this paper we discuss a software system which we are developing that uses this approach. We also provide a simple example illustrating the use of the technique for fault detection in an operational amplifier

Economic performance and unemployment: Evidence from an emerging economy

Purpose - This article seeks to examine whether or not various macroeconomic policy shocks have different effects on overall unemployment and the unemployment by different levels of education in Turkey. These effects are assessed separately for male and female unemployment. Design/methodology/ approach - To examine the relationship, a quarterly VAR model with a recursive order is employed to estimate the effects of real GDP, price, exchange rate and interbank interest rate on unemployment for the period from 1988:01 to 2003:04. Findings - Main findings indicate that monetary policy does not affect the total unemployment as well as the components of unemployment by educational level and by gender in Turkey. On the other hand, income policies, which include fiscal policies, and unemployment itself, might be the main factors that affect the behavior of total unemployment and its various components. Research limitations/implications - These findings suggest that policy makers should concentrate on non-monetary policies to hamper the unemployment in Turkey. Originality/value - The present study is the first empirical examination of the relationship between various macroeconomic policy shocks and the unemployment both across gender and education levels in a single study. © Emerald Group Publishing Limited