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This paper aims to examine how pioneering advantage interacts with the compromise effect generated by new product entries. Building on prior work on pioneering advantage and extreme aversion, this research moves toward understanding how the choice share of a pioneer realigns as a consequence of new product entries generating compromise-like scenarios.

The authors run three experiments to test their propositions. The authors present one study which documents the effect. The second study provides process evidence. The third study suggests how brands can neutralize the adverse effect on their share generated by the followers’ entry/positioning.

In three studies, the authors showed that when a pioneering product becomes intermediate in a choice set, its share is more adversely affected than when it becomes extreme. The authors show that this depends on consumers’ propensity to use non-compensatory decision rules in the presence of a pioneering alternative. The authors also document that the relative disadvantage of the intermediate pioneer can be overcome when the reasons for selecting an intermediate alternative based on a compensatory decision rule are restored.

The research provides guidelines for managers wanting to enter product categories where a pioneer already exists. The authors show that opting for an extreme position that renders the pioneer intermediate can be rewarding. In contrast, being the second extreme player in a market where the pioneer becomes extreme reduces the expected share of this last entrant.

The authors’ contribution is in showing that this decision strategy can clash with the rule consumers generally use in a compromise setting and that this clash generates two different effects when the pioneer becomes intermediate or extreme.

The purpose this paper is to examine how aware and prepared the elderly and a number of related housing associations (HAs) are of extreme weather events and the impact on their built assets as a result of climate change. It investigates how extreme weather and associated risks are perceived and the measures taken to protect the assets.

Desk research and two questionnaire surveys were conducted to collect data and information in relation to the awareness of extreme weather events and how built assets are adapted as a response. Survey results were tabulated and analysed using qualitative coding techniques and examined to identify relationships and patterns across different criteria in relation to awareness and built form adaptation to extreme weather events.

The surveys illustrate that awareness is high but the actions carried out as adaptations do not significantly reduce risks. Lack of personalisation of the risk and the resulting avoidance behaviour seems to prevent any considerable actions being taken. Thus, the elderly seem to accept basic energy saving measures as extreme weather adaptations rather than seek substantial actions that minimise risk to their houses. The results highlight the need to identify different design, construction and management solutions to improve resilience of different dwelling types to different economic sectors and different community groups.

The HA survey sample is too small to derive general conclusions but illustrates the varying positions of different organisations. Future research will further the survey with a larger sample and extend to local authorities (LAs).

The findings provide valuable information and insights to all related stakeholders in formulating programmes in securing built assets in extreme weather events.

Provide an understanding of the awareness and the preparedness of a vulnerable group, the elderly, and their dwellings to extreme weather events.

While the government hold consultations and dissemination events at national and regional levels, individual community groups and local agencies who are directly involved in providing services are not yet engaged in this dialogue. These two surveys made an attempt to gauge the awareness and the preparedness of the respondents of two such segments, in adapting their homes and built assets as a response to extreme weather associated risks.

Modern property investment allocation techniques are typically based on recognised measures of return and risk. Whilst these models work well in theory under stable conditions, they can fail when stable assumptions cease to hold and extreme volatility occurs. This is evident in commercial property markets which can experience extended stable periods followed by large concentrated negative price fluctuations as a result of major unpredictable events. This extreme volatility may not be fully reflected in traditional risk calculations and can lead to ruin. The paper aims to discuss these issues.

This research studies 28 years of quarterly Australian direct commercial property market performance data for normal distribution features and signs of extreme downside risk. For the extreme values, Power Law distribution models were examined as to provide a better probability measure of large negative price fluctuations.

The results show that the normal bell curve distribution underestimated actual extreme values both by frequency and extent, being by at least 30 per cent for the outermost data point. For the statistical outliers beyond 2 SD, a Power Law distribution can overcome many of the shortcomings of the standard deviation approach and therefore better measure the probability of ruin, being extreme downside risk.

In highlighting the challenges to measuring property market performance, analysis of extreme downside risk should be separated from traditional standard deviation risk calculations. In recognising these two different types of risk, extreme downside risk has a magnified domino effect with the tendency of bad news to come in crowds. Big price changes can lead to market crashes and financial ruin which is well beyond the standard deviation risk measure. This needs to be recognised and developed as there is evidence that extreme downside risk determinants are increasing by magnitude, frequency and impact.

Analysis of extreme downside risk should form a key part of the property decision process and be included in the property investment manager’s toolkit. Modelling techniques for estimating measures of tail risk provide challenges and have shown to be beyond traditional risk management practices, being too narrow and constraining a definition. Measuring extreme risk and the likelihood of ruin is the first step in analysing and dealing with risk in both an asset class and portfolio context.

The purpose of this paper is to investigate and compare the extreme behavior of securitized real estate and stock market returns as well as their value‐at‐risk (VaR) dynamics in international investing. Extreme value theory using the block maxima method is applied to ten securitized real estate and equity market indices representing Asian, European and North American markets.

The paper models the maxima and minima of all return series within the extreme value theory (EVT) framework and derive the VaR estimates. It then compares the VaR estimates derived from the EVT and the normal distribution and investigates the impact of clustered returns on the VaR estimates. Finally, both the conventional standard deviation measure and VaR method are conducted to evaluate and compare the impact of the Asian financial turmoil on the real estate and stock market risk profiles.

Evidence shows that Asian real estate and equity maxima and minima return series are characterized by a fat‐tailed Fréchet distribution. The frequency and severity of extreme Asian real estate returns are greater than their European and North American counterparts. Securitized real estate markets are riskier than the broader stock markets before and during the Asian financial turmoil. In contrast, many stock markets become riskier after the financial crisis with their VaRs higher than the equivalent VaR estimates for the real estate series.

Knowledge about real estate market returns exhibit extreme behavior can help investors and fund managers understand the distribution of real estate market returns better and obtain potentially more accurate real estate return forecasts.

International real estate portfolio risk management should include both extreme risks and standard deviations. Accordingly, global investors should be even more cautious in formulating their diversification strategies since gains from diversification can be reduced significantly by the severity of extreme return levels.

The paper characterizes the distribution of extreme returns for a broad spectrum of international securitized real estate markets from three continents. The extreme value investigation is also conducted for broader stock markets corresponding to the individual real estate markets. The July 1997 turmoil that occurred in Asian financial markets provides interesting exploratory opportunities within which this paper estimates and compares the extreme market risk with the conventional standard deviation measure.

In contrast to recent US studies, almost all prior UK studies have not supported the incremental information content of cash flow beyond earnings. In addition, to date no UK study has addressed the effect of earnings extremity on the incremental information content of cash flow and earnings whilst controlling for the extremity of cash flow. Therefore, and in order to assess the generality of recent US findings, the aim of this study is to examine the incremental information content of cash flow from operations and earnings and the effect of extreme earnings on the incremental information content of cash flow from operations in the UK firms.

Based on market‐based accounting research, this study uses statistical associations between accounting data (earnings and cash flow) and stock returns to assess/measure the incremental information content (value relevance) of cash flow and earnings and the effect of extreme earnings on the incremental information content of cash flow and earnings. The paper follows the recent methodology in this area that employs the level and change of cash flow and earnings as an estimation of their unexpected components and isolates the extreme cash flow and earnings apart from the moderate ones.

The results show that both earnings and cash flow from operations have incremental information content beyond each other. It is also found that extreme earnings lead to incremental information content for only moderate (not extreme) cash flow. These results are consistent with the findings of the recent US studies.

Overall, the findings of this study support the usefulness of using cash flow information, in addition to earnings in firm valuation by investors in the UK market, especially when earnings are extreme and cash flow is moderate. The accounting interpretation of these results, in terms of disclosure of earnings components, is discussed.

The study makes the following contributions to the incremental information content of cash flow and earnings literature in the UK. First, this study employs actual cash flow data derived from cash flow statements. Second, none of the prior UK studies shares the current research focus, which is to examine the effect of earnings extremity on the incremental information content of cash flow and earnings whilst controlling for the extremity of cash flow itself. Third, this study employs a large sample size for a more recent period.

The purpose of this study is to explore the extent to which teamwork (developed either during an initial training phase or during a subsequent deployment phase) is influenced by the nature of the team’s environment (extreme vs non-extreme) and the extent to which teamwork is one of the explaining mechanisms for team performance.

Data was collected from 60 teams at 2 time-points: training phase in The Netherlands or Germany and deployment phase (in locations such as Afghanistan and Bosnia-Herzegovina).

This study’s results indicate that when teams consider working in extreme environments, they develop higher levels of teamwork as compared to teams expecting to work in non-extreme environments. These differences remain stable also during the deployment phase, such that teams operating in extreme environments will continue to have higher levels of teamwork as compared to teams operating in non-extreme environments.

With this study, the authors contribute to the teamwork quality research stream by empirically studying how teamwork quality develops in unique military contexts such as extreme environments. Studies in such contexts are relatively rare.

The purpose of this paper is to explore the incidence of “extreme jobs” among middle managers in acute hospitals, and to identify individual and organizational implications.

The paper is based on interviews and focus groups with managers at six hospitals, a “proof of concept” pilot with an operations management team, and a survey administered at five hospitals.

Six of the original dimensions of extreme jobs, identified in commercial settings, apply to hospital management: long hours, unpredictable work patterns, tight deadlines with fast pace, broad responsibility, “24/7 availability”, mentoring and coaching. Six healthcare-specific dimensions were identified: making life or death decisions, conflicting priorities, being required to do more with fewer resources, responding to regulatory bodies, the need to involve many people before introducing improvements, fighting a negative climate. Around 75 per cent of hospital middle managers have extreme jobs.

This extreme healthcare management job model was derived inductively from a qualitative study involving a small number of respondents. While the evidence suggests that extreme jobs are common, further research is required to assess the antecedents, incidence, and implications of these working practices.

A varied, intense, fast-paced role with responsibility and long hours can be rewarding, for some. However, multi-tasking across complex roles can lead to fatigue, burnout, and mistakes, patient care may be compromised, and family life may be adversely affected.

As far as the authors can ascertain, there are no other studies exploring acute sector management roles through an extreme jobs lens.

The purpose of this paper is to examine pro-poor urban asset adaptation to climate variability and change. It constructs a conceptual framework that explores the appropriate asset adaptation strategies for extreme poor households as well as the process of supporting these households and groups in accumulating these assets.

Qualitative data are obtained from life histories, key informant interviews (KIIs) and focus-group discussions (FGDs). These data are collected, coded and themed.

This research identifies that households among the urban extreme poor do their best to adapt to perceived climate changes; however, in the absence of savings, and access to credit and insurance, they are forced to adopt adverse coping strategies. Individual adaptation practices yield minimal results and are short lived and even harmful because the urban extreme poor are excluded from formal policies and institutions as they lack formal rights and entitlements. For the poorest, the process of facilitating and maintaining patron–client relationships is a central coping strategy. Social policy approaches are found to be effective in facilitating asset adaptation for the urban extreme poor because they contribute to greater resilience to climate change.

This study analyses the empirical evidence through the lens of a pro-poor asset-adaptation framework. It shows that the asset-transfer approach is an effective in building household-adaptation strategies. Equally important is the capacity to participate in and influence the institutions from which these people have previously been excluded.

Research on price extremes and overreactions as potential violations of market efficiency has a long tradition in investment literature. Arguably, very few studies to date have addressed this issue in cryptocurrencies trading. The purpose of this paper is to consider the extreme value modelling for forecasting COVID-19 effects on cryptocoin markets. Additionally, this paper examines the importance of technical trading indicators in predicting the extreme price behaviour of cryptocurrencies.

This paper decomposes the daily-time series returns of four cryptocurrency returns into potential maximum gains (PMGs) and potential maximum losses (PMLs) at first and then tests their lead–lag relations under an econometric framework. This paper also investigates the non-random properties of cryptocoins by computing the incremental explanatory power of PML–PMG modelling with technical trading indicators controlled. Besides, this paper executes an event study to identify significant changes caused by COVID-19-related events, which is capable of analysing the cryptocoin market overreactions.

The findings of this paper produce the evidence of both market overreactions and trend persistence in the potential gains and losses from coins trading. Extreme price behaviour explains volatility and price trends in crypto markets before and after the outbreak of a pandemic that substantiate the non-random walk behaviour of crypto returns. The presence of technical trading indicators as control variables in the extreme value regressions significantly improves the predictive power of models. COVID-19 crisis affects the market efficiency of cryptocurrencies that improves the usefulness of extreme value predictions with technical analysis.

This paper strongly supports for the robustness of technical trading strategies in cryptocurrency markets. However, the “beast is moving quick” and uncertainty as to the new normalcy about the post-COVID-19 world puts constraint on making best predictions.

The paper contributes substantially to our understanding of the pricing efficiency of cryptocurrency markets after the COVID-19 outbreak. The findings of continuing return predictability and price volatility during COVID-19 show that profitable investment opportunities for cryptocoin traders are prevailing in pandemic times.

The paper is unique to understand extreme return reversals behaviour of cryptocurrency markets regarding events related to COVID-19 breakout.

From a regulatory point of view, as explained by Dimson and Marsh [1994, 1995], the amount of capital required by a financial institution to ensure an acceptably small probability of failure should depend on the risk associated with the assets detained in its portfolio. Dimson and Marsh [1994] conduct an empirical study on long and short equity trading books of securities firms acting as market makers. They consider different existing regulations: the comprehensive approach, as applied in the United States by the Securities and Exchange Commission; the building‐block approach, as proposed by the Basle Committee on Banking Supervision, and incorporated in the European Community [1992] Capital Adequacy Directive (CAD); and the portfolio approach, which in the U.K. forms part of the rules of the Securities and Futures Authority [1992]. All three methods are compared via the position risk requirement (PRR) that determines the amount of capital that financial institutions have to put aside. As shown by the authors in their empirical study, the methods proposed by the international regulators are barely related to the risk of the portfolios! Only for the national U.K. rules, the PRR and the risk of a portfolio show positive correlation.