The pricing and underwriting costs of Japanese REIT IPOs

This study investigates 40 Japanese REIT IPOs during 2001 to 2006 and finds evidence that higher final offer prices are reflected in higher underpricing levels by such IPOs. There is also some evidence that the engagement of one of the big three Japanese underwriting firms suggests less money is left on the table. Economies of scale in underwriting fees for Japanese REIT IPOs are also found. Specifically, the percentage underwriting fees decrease with higher amounts of equity capital sought but the percentage fee decreases at a diminishing rate.

Herding behaviour in the Australian loan market and its impact on bank loan quality

We examine the effect of herding behaviour on the credit quality of bank loans in Australia. We find that bank herding varies with different types of loans. It tends to be more prevalent in owner-occupied housing loans and credit cards than other types of loans. During the global financial crisis period, herding in owner-occupied housing loans was most pronounced due to the flight-to-quality phenomenon in the housing sector. Furthermore, we find that the big four banks tend to herd more than smaller and regional banks. Bank herding behaviour is countercyclical, as it is negatively related to real GDP growth and the cost of funding but is positively related to market risk. Regulatory capital requirements may also encourage herding as banks are required to hold less risk-weighted capital for residential loans. Most importantly, bank herding is related to higher impaired assets and therefore lower loan quality. Our findings may have implications for policymakers and bank regulators.

Integrating internet-of-things with the power of cloud computing and the intelligence of big Data analytics- a three layered approach

This paper is written through the vision on integrating Internet-of-Things (IoT) with the power of Cloud Computing and the intelligence of Big Data analytics. But integration of all these three cutting edge technologies is complex to understand. In this research we first provide a security centric view of three layered approach for understanding the technology, gaps and security issues. Then with a series of lab experiments on different hardware, we have collected performance data from all these three layers, combined these data together and finally applied modern machine learning algorithms to distinguish 18 different activities and cyber-attacks. From our experiments we find classification algorithm RandomForest can identify 93.9% attacks and activities in this complex environment. From the existing literature, no one has ever attempted similar experiment for cyber-attack detection for IoT neither with performance data nor with a three layered approach.

Towards an organisational disaster risk management culture and practice for banks

The disaster risk management culture and practice that is evident within banks will significantly impact upon the capability and preparedness of institutions and their personnel to plan for, and respond to, an occurrence that may affect the continuity of critical business functions. The principal outcome of this paper is the development of a structured education and training framework that will support the achievement of banks' disaster risk management objective. The education and training framework comprises three specific programs: 1. an induction/awareness program targeted to all personnel; 2. a contingency planning program - a specialist program for disaster risk management personnel; and 3. an executive program designed for senior management, directors and strategic decision makers.

An education and training framework for disaster risk management in banks

Banks are the most significant financial institutions operating within nation-state and the global financial system. These institutions are exposed to a wide range of operational risks. Disaster risk management is a critical component of the wider operational risk management. The Bank for International Settlements, in conjunction with nation-state prudential regulators, is introducing measures that will require banks to identify, measure and manage operational risks within the context of new capital adequacy requirements. An essential part of any risk management process is education and training. This paper presents a structured education and training framework that will support the achievement of banks’ disaster risk management objectives. The education and training framework comprises three specific programs: (1) an induction/awareness program targeted to all personnel, (2) a contingency planning program – a specialist program for disaster risk management personnel, and (3) an executive program designed for senior management, directors and strategic decision makers.

The measurement of the number, uniqueness, and valence of brand associations across three product categories

The research reported in this paper investigated the measurement of brand associations across three product categories. Brand associations had not been tested previously across all three categories of fast-moving consumer good, service, and durable in the one study. A free association method was used to generate brand associations for a fast-moving consumer good (shampoo), a service (banks) and a durable good (cars). The findings indicate that the first brand a respondent recalled has the greatest number of positive, unique and total brand associations. In addition, the findings indicated that durable goods have the highest number of associations, and the greatest number of unique and favourable brand associations. Further, banks and financial services had the fewest positive associations, which may have reflected attitudes to banks at the time of the research. These findings have implications for the manner in which respondents use information to recall brands, and how they process brand information when faced with a cue. Respondents use a depth and breadth of brand associations to generate brand information.

Extreme surfing : personal and psychological aspects of big wave riders

This qualitative study investigated personal and psychological aspects of big wave riders. A cross-sectional design with non probability purposive sampling was used to gain personal interviews with 32 elite surfers who regularly ride big, life threatening waves. Each athlete was asked three open questions: 1. What do you think are the most important qualities and attributes a surfer needs for riding big waves? 2. What type of mindset is best for riding big waves?, and 3.What motivates you to ride big waves? Content analysis of the taped interview transcripts revealed seven key qualities and attributes including having a thrill seeking, confident and goal oriented personality, a high level of mental strength and control, and an intimate relationship with the ocean. The best mindset included an individually defined arousal level, a committed attitude, and a simple, yet highly aware, focus. Motivations were primarily intrinsic, though drives indicative of a behavioral addiction to the act of riding big waves also emerged. Evidence of common developmental stages for riding big waves also arose from the interviews. Optimal mental approach and preparation techniques are discussed that will enable big wave riders, and other extreme athletes, to more safely and successfully manage extreme situations.

The nature of corporate social responsibility disclosures by the Bangladeshi commercial banks

The Bangladesh Bank is now encouraging corporate social responsibility (CSR) disclosure by banks however the adoption of CSR remains voluntary and not mandatory. The aim in this paper is to determine the nature and extent of corporate social responsibility disclosure in the banking sector in Bangladesh, and to assess the need to improve corporate social responsibility by such organisations. We observe, from our content analysis of the annual reports of three cases studies within the banking industry of Bangladesh, that corporate social responsibility disclosures focus on initiatives undertaken to support two critical two sectors within Bangladesh's economy. agriculture and the SME sector. Further disclosures address contributions and donations made by the banks to support underprivileged sections of Bangladesh society including destitute youth and women. Of the three cases examined in this study, two are relatively new entrants to the banking sector. We observed that the newest firm, incorporated in 1999, made no disclosures in regards to its corporate social responsibility and, as a consequence, conclude that the corporate governance mechanisms in this firm are likely to be unsophisticated.

Toka boot/the big jam : making music in rural East Timor

This article discusses a community music project in rural East Timor. Australian musician Gillian Howell lived for three months in the isolated town of Lospalos as an Asialink artist-in-residence, where she worked with local community members and visiting Australian musicians to share music and ideas, and to communicate across cultures. Three activities are described in detail: a songwriting project, a large-scale community music event and a series of informal jam sessions, particularly with respect to the context, teaching and learning models used. An evaluation of the impact of the project on participants, other community members and visiting musicians, indicated that stakeholders valued the project highly for a range of different reasons. These included fun and enjoyment, maintenance of cultural heritage, creative expression, English language learning and cross-cultural exchange. Learnings and recommendations for future similar cross-cultural collaborations include the value of integrating local music traditions with new participatory arts approaches.

Mates and majors: how the big fish survived

In October this year, the Queensland Government slashed funding to small-to-medium sized arts organisations. In part two of a three-part investigation, Ben Eltham asks why the smaller players were targeted, while the major institutions were protected.

Predicting psychological and subjective well-being from personality: incremental prediction from 30 facets over the Big 5

This study investigated the relationship between the Big 5, measured at factor and facet levels, and dimensions of both psychological and subjective well-being. Three hundred and thirty-seven participants completed the 30 Facet International Personality Item Pool Scale, Satisfaction with Life Scale, Positive and Negative Affectivity Schedule, and Ryff’s Scales of Psychological Well-Being. Cross-correlation decomposition presented a parsimonious picture of how well-being is related to personality factors. Incremental facet prediction was examined using double-adjusted r2 confidence intervals and semi-partial correlations. Incremental prediction by facets over factors ranged from almost nothing to a third more variance explained, suggesting a more modest incremental prediction than presented in the literature previously. Examination of semi-partial correlations controlling for factors revealed a small number of important facet-well-being correlations. All data and R analysis scripts are made available in an online repository.

The myths big media peddle to demand deregulation

This article argues that big media in Australia promote three myths about rural and regional news in Australia as part of their case to deregulate the industry. These myths are that geography no longer matters in local news; that big media are the only ones who can save regional news; and that people in regional Australia can access less news that their city counterparts.

A hybrid approach to clustering in big data

Clustering of big data has received much attention recently. In this paper, we present a new clusiVAT algorithm and compare it with four other popular data clustering algorithms. Three of the four comparison methods are based on the well known, classical batch k-means model. Specifically, we use k-means, single pass k-means, online k-means, and clustering using representatives (CURE) for numerical comparisons. clusiVAT is based on sampling the data, imaging the reordered distance matrix to estimate the number of clusters in the data visually, clustering the samples using a relative of single linkage (SL), and then noniteratively extending the labels to the rest of the data-set using the nearest prototype rule. Previous work has established that clusiVAT produces true SL clusters in compact-separated data. We have performed experiments to show that k-means and its modified algorithms suffer from initialization issues that cause many failures. On the other hand, clusiVAT needs no initialization, and almost always finds partitions that accurately match ground truth labels in labeled data. CURE also finds SL type partitions but is much slower than the other four algorithms. In our experiments, clusiVAT proves to be the fastest and most accurate of the five algorithms; e.g., it recovers 97% of the ground truth labels in the real world KDD-99 cup data (4 292 637 samples in 41 dimensions) in 76 s.

The effect of holiday haemodialysis treatments on patient mood, adverse symptoms and subjective wellbeing using the Big Red Kidney Bus

BACKGROUND AND AIMS: People with end-stage kidney disease receiving haemodialysis are restricted to holidays where dialysis services are readily available. Holiday dialysis in regional, rural and remote areas is particularly challenging. The aims of this study were to (1) evaluate the wellbeing of those who received dialysis in a holiday haemodialysis bus, and (2) to measure patient wellbeing with that of a comparable cohort of haemodialysis patients. METHODS: A three machine haemodialysis bus, the Big Red Kidney Bus, was built to enable people, their families and carers to take holidays across a range of tourist destinations in Victoria, Australia. Measures included pre-post subjective wellbeing, dialysis symptoms and mood questionnaires complemented by post semi-structured telephone interviews. RESULTS: Participating holidaymakers were positive about the haemodialysis bus service and the standard of care experienced. They reported decreased dialysis side effects of fatigue, muscle cramp, and dry skin. The overall number of reported symptoms decreased and the perceived level of bother associated with symptoms also decreased. No changes in subjective wellbeing and mood were detected. Mean Personal Wellbeing Index scores were significantly higher than in a comparative haemodialysis sample. CONCLUSION: The Big Red Kidney Bus provided a safe and feasible holiday dialysis service. Holidaymakers' wellbeing was reflected by the decreased dialysis patient side effects.

Bailouts, monitoring, and penalties: an integrated framework of government policies to manage the too-big-to-fail problem

This paper discusses optimal government bailout policy where the costs of systemic failures and moral hazard problems are considered. We find that a three-tiered bailout policy that includes an ex post monitoring and bailout scheme for financial institutions with large systemic impacts ('too big to fail') is optimal. The optimal policy also requires a randomized bailout for medium-impact institutions ('Constructive Ambiguity'), and no bailout for institutions that have only minimal systemic consequences ('too small to save'). However, in a volatile, innovative market environment where individual institutions may know more than the government regulator, monitoring error could contribute to risk taking, leaving the government regulator to always play a 'catch-up' role in revising policy. Moreover, the optimal bailout policy may not be time-consistent: institutions not deemed 'too big to fail' may still have an incentive to take excessive risks and expect to be bailed out in case of insolvency, primarily due to the short-term orientation of the government. Finally, because an institution's systemic cost affects the probability of a bailout, we show that the boundary of an institution may be extended by the government subsidy.