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The purpose of this paper is to build a phase-type risk model with stochastic return on investment and random observation periods to characterize the ruin quantities under which the insurance company may take effective investment strategies to avoid bankruptcy.

By the Markov property and Ito’s formula, this paper derives the integro-differential equations in which the interclaim times follow a phase-type distribution. Using the sinc method, this paper obtains the approximate solutions of the expected discounted penalty function. The numerical examples are given to verify the robustness of the proposed sinc method.

This paper discloses the relationship between the investment strategy and initial surplus level. The insurance company with a high initial surplus level prefers high risk portfolios to earn more profit. Contrarily, the insurance company would invest low risk portfolios to avoid bankruptcy. In addition, this paper shows that a short observation period would bring higher ruin probability.

The risk model is distinct in that a phase-type risk model is constructed with stochastic return on investment and random observation periods. These considerations in the risk model are in sharp contrast to the setting in which the stochastic return on investment is observed continuously. In practice, the insurance company only can periodically observe the surplus level to check the balance of the book. This setting, therefore, is difficult to adopt. This paper develops a sinc method to solve the approximate solutions of the expected discounted penalty function.

The purpose of this paper is to present a novel approach to coordination of multi‐agent teams, and in particular multi‐robot teams. The new approach is based on models of organisational sociology, namely the concept of social networks. The social relationships used in the model that is presented in this paper are trust and kinship relationships, but modified for use in heterogeneous multi‐robot teams.

The coordination of a robot team is achieved through task allocation. The proposed task allocation mechanism was tested in the multi‐robot team task allocation simulation.

The social networks‐based task allocation algorithm has performed according to expectations and the obtained results are very promising. Some intriguing similarities with higher mammalian societies were observed and they are discussed in this paper. The social networks‐based approach also exhibited the ability to learn and store information using social networks.

The research focused on simulated environments and further research is envisaged in the physical environments to confirm the applicability of the presented approach.

In this paper, the proposed coordination was applied to simulated multi‐robot teams. It is important to note that the proposed coordination model is not robot specific, but can also be applied to almost any multi‐agent system without major modifications.

The paper emphasizes applicability of considering multi‐robot teams as socially embodied agents. It also presents a novel and efficient approach to task allocation.

The purpose of this paper is to investigate the moderating effect of disease risk in terms of the major signals (i.e. status, reputation and self-representation) on the e-consultation platforms.

In this study, the proposed research hypotheses are tested using the transaction data collected from xywy.com (in Need of Therapy). In fact, xywy.com is one the leading e-consultation service websites in China that provides a platform for the interactions between the physicians and patients (Yu et al., 2016; Peng et al., 2015). Generally speaking, it has all the needed design elements and in other words, a standard e-consultation website should have such items/components as physician homepage, physician review, free consultation, paid consultation and recommendation systems.

The obtained results reveal that all attributes including status, reputation and self-representation have a positive impact on physician’s online order volume. Moreover, there is a positive moderating effect of disease risk onto the online reputation, indicating a higher effect exists for the diseases with high risk. However, the effect of offline status and online self-representation is not moderated by the disease risk, indicating market signals (online reputation) may have a stronger predictive power than seller signals (offline status and online self- representation), and therefore market signals are more effective when/if the disease risk is high.

E-consultation has gradually become a significant trend to provide the healthcare services, in the emerging economy such as China because of shortage of medical resources but having an adequate access in internet usage. The impacts of signals on the health care market have been validated by previous studies. However, the research focusing on the moderating effect of signaling environment in the health care industry is still lacking. As a result, the value of this research helps to bridge the aforementioned research gap.

This paper examines the Random Walk Hypothesis (RWH) for aggregate New Zealand share market returns, as well as the CRSP NYSE‐AMEX (USA) index during the 1980‐2001 period. Using several indices, we rely on the variance‐ratio test and find evidence to support the rejection of the RWH with some evidence of a momentum effect. However, we find evidence to suggest the behaviour of share prices to be time‐dependent in New Zealand. For example, we find the indices tested were closer to random after the 1987 share market crash. Further analysis showed even stronger results for periods subsequent to the passage of the Companies Act 1993 and the Financial Reporting Act 1993. We also find evidence that indices based on large capitalisation stocks are more likely to follow a random walk compared to those based on smaller stocks. For the USA index, we find stronger evidence of random behaviour in our sample period compared to the earlier period examined by Lo and Mackinlay (1988)

THERE is a tendency to regard the industrial problems which face us as unique to British firms. That is a blinkered outlook in days when the commerce of thought is international and no country is insulated from another.

The purpose of this paper is to utilize a constrained random portfolio-based framework for measuring the skill of a cross-section of Indian mutual fund managers. Specifically, the authors test whether the observed performance implies superior investment skill on the part of mutual fund managers. Additionally, the authors investigate the suitability of mutual fund investments under diverse investor expectations.

The authors use a new skill measurement methodology based on a cross-section of constrained random portfolios (Burns, 2007).

The authors find no evidence of superior investment skill in the sample of Indian equity mutual funds. Using a series of statistical tests, the authors conclude that the mutual funds fail to outperform the random portfolios. Furthermore, mutual funds show no persistence in their performance over time. These results are robust to choice of performance measure and the investment horizon. However, mutual funds provide lower downside risks and may be suitable for investors with high degree of risk aversion.

The authors extend Burns’ (2007) methodology in several aspects, especially by using a much wider range of performance and downside risk measures to address diverse investor expectations. To the best of the authors’ knowledge, this is first study to apply the constrained random portfolios-based skill tests in an emerging market.

The purpose of this paper is to test the performance of momentum strategies and identify the sources of their profits.

To identify the main source of momentum profits, first, the bootstrap method with replacement was used. Then, to eliminate the existence of the small sample bias, the bootstrap method without replacement and the block bootstrap method were employed. In this case, when the authors draw the observations without replacement the random effect is reduced, whereas the resampling procedure is based on the random draw.

The empirical results show the existence of a small sample bias in the bootstrap method with replacement, and that the time‐series relations of stock returns are the main source of momentum profits.

To ensure the random effect of the draws, the authors develop a new resampling procedure called the mixed bootstrap method.

A troublesome tool may represent capital investment standing idle and the toolroom itself, therefore, calls for efficient management if capital expenditure is to be successfully deployed. Production engineers may cast around for means of saving costs but seldom pay attention to the toolroom. Is this because toolmakers are craftsmen and it is implied, therefore, they always work effectively when making tools or repairing old ones? This may be so, but there are many cases in the past, the present and, no doubt, in the future where tools costs are far too high relative to the product involved.

The use of models for detecting earnings management in the academic literature, using accrual and real manipulation, is commonplace. The purpose of the current study is to compare the power of these models in a United Kingdom (UK) sample of 19,424 firm-year observations during the period 1991–2018. The authors include artificially-induced manipulation of revenues and expenses between zero and ten percent of total assets to random samples of 500 firm-year observations within the full sample. The authors use two alternative samples, one with no reversal of manipulation (sample 1) and one with reversal in the following year (sample 2).

The authors include artificially induced manipulation of revenues and expenses between zero and ten percent of total assets to random samples of 500 firm-year observations within the full sample.

The authors find that real earnings manipulation models have lower power than accrual earnings manipulation models, when manipulating discretionary expenses and revenues. Furthermore, the real earnings manipulation model to detect overproduction has high misspecification, resulting in artificially inflating the power of the model. The authors examine an alternative model to detect discretionary expense manipulation that generates higher power than the Roychowdhury (2006) model. Modified real manipulation models (Srivastava, 2019) are used as robustness and the authors find these to be more misspecified in some cases but less in others. The authors extend the analysis to a setting in which earnings management is known to occur, i.e. around benchmark-beating and find consistent evidence of accrual and some forms of real manipulation in this sample using all models examined.

This study contributes to the literature by providing evidence of misspecification of currently used models to detect real accounts manipulation.

Based on the findings, the authors recommend caution in interpreting any findings when using these models in future research.

The findings address the earnings management literature, guided by the agency theory.

THE Electronic Computer Exhibition and the B.I.M. conference have provided material for serious contemplation. Sir Harold Gillett, Lord Mayor of London, opening the Exhibition suggested that we are living in the age of the second industrial revolution. There are some who share the Lord Mayor's view and others who take the whole matter in their stride. One thing is certain, we shall be able to do more—and do it more efficiently.