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In 1997 Tom was a 32‐year‐old man with a diagnosis of severe intellectual disability and autism who engaged in high‐rate challenging behaviour. Tom's out‐of‐area placement was about to break down and he needed help urgently. For 16 months specialist challenging behaviour services supported Tom directly in a single‐occupancy service. They conducted functional assessment and delivered multi‐level intervention, including medication withdrawal, environmental enrichment, skills teaching, augmented communication and targeted behavioural intervention. Support was then transferred to mainstream learning disability services. Following intervention, the rate of challenging behaviour shown by Tom fell significantly from more than 200 instances per day to almost none. Community involvement and engagement increased. Tom moved into shared accommodation with support from mainstream learning disability services at no additional cost. Improvement at intervention was still apparent 10 years later. Tom's story adds to a growing number of articles showing how focused intervention can deliver lasting improvement in quality of life. Four aspects of Tom's story are discussed in the light of the Mansell Report.

Gives an in depth view of the strategies pursued by the world’s leading chief executive officers in an attempt to provide guidance to new chief executives of today. Considers the marketing strategies employed, together with the organizational structures used and looks at the universal concepts that can be applied to any product. Uses anecdotal evidence to formulate a number of theories which can be used to compare your company with the best in the world. Presents initial survival strategies and then looks at ways companies can broaden their boundaries through manipulation and choice. Covers a huge variety of case studies and examples together with a substantial question and answer section.

This study aims to examine the market returns of the Ukrainian stock and bond markets to determine whether they exhibit calendar anomalies including the January effect, weekend effect, and turn‐of‐the‐month (TOM) effect. Ukraine provides an opportunity to examine the efficiency of an emerging market, adding to the extensive body of research on calendar anomalies.

Regression analysis is used to examine the relationship between January returns vs non‐January returns, Monday returns vs non‐Monday returns, and TOM returns vs non‐TOM returns. Non‐parametric t‐tests and Wilcoxon signed rank tests are also used to examine TOM returns vs the rest of the month returns.

There is no evidence of a January effect or a weekend effect in the Ukrainian stock and bond markets. However, our results support a TOM effect in the Ukrainian stock market. The mean daily TOM return is 0.35 vs 0.24 per cent for the rest of the month. Additionally, in 63 per cent of the months, the mean daily TOM return exceeds the return for the rest of the month.

The data are limited to five‐years of daily returns and two different Ukrainian indexes. Thus, the results could be biased by the time period analyzed. The results are important for portfolio managers and investors as they can benefit from the TOM effect, but not the January effect and weekend effect.

This is the first study to our knowledge that has extensively examined the calendar anomalies in the Ukrainian stock and bond markets.

The attention-based view (ABV) of the firm highlights the role of decision makers’ attention in firm behavior. The ABV vastly improves our understanding of decision makers’ focus of attention; how that focus is situated in an organization’s procedural and communication channels; and how the distribution of the focus of attention among decision makers participating in those procedural and communication channels affects their understanding of a situation, their motivation to act, and, ultimately, their behavior. Significant progress has been made in recent years in refining and extending the ABV. However, the role of individual differences in the capacity to read other people’s desires, intentions, knowledge, and beliefs – that is, the theory of mind (ToM) – has remained on the sidelines. The ToM is a natural complement to the ABV. In this study, we explore how the ToM allows for an understanding of the advantage that organizations have over markets within the ABV.

The COVID-19 pandemic, a sudden and disruptive external shock to the USA and global economy, profoundly affected various operations. Thus, it becomes imperative to investigate the repercussions of this pandemic on the US housing market. This study investigates the impact of the COVID-19 pandemic on a crucial facet of the real estate market: the Time on the Market (TOM). Therefore, this study aims to ascertain the net effect of this unprecedented event after controlling for economic influences and real estate market variations.

Monthly time series data were collected for the period of January 2010 through December 2022 for statistical analysis. Given the temporal nature of the data, we conducted the Durbin–Watson test on the OLS residuals to ascertain the presence of autocorrelation. Subsequently, we used the generalized regression model to mitigate any identified issues of autocorrelation. However, it is important to note that the response variable derived from count data (specifically, the median number of months), which may not conform to the normality assumption associated with standard regression models. To better accommodate this, we opted to use Poisson regression as an alternative approach. Additionally, recognizing the possibility of overdispersion in the count data, we also explored the application of the negative binomial model as a means to address this concern, if present.

This study’s findings offer an insightful perspective on the housing market’s resilience in the face of COVID-19 external shock, aligning with previous research outcomes. Although TOM showed a decrease of around 10 days with standard regression and 27% with Poisson regression during the COVID-19 pandemic, it is noteworthy that this reduction lacked statistical significance in both models. As such, the impact of COVID-19 on TOM, and consequently on the housing market, appears less dramatic than initially anticipated.

This research deepens our understanding of the complex lead–lag relationships between key factors, ultimately facilitating an early indication of housing price movements. It extends the existing literature by scrutinizing the impact of the COVID-19 pandemic on the TOM. From a pragmatic viewpoint, this research carries valuable implications for real estate professionals and policymakers. It equips them with the tools to assess the prevailing conditions of the real estate market and to prepare for potential shifts in market dynamics. Specifically, both investors and policymakers are urged to remain vigilant in monitoring changes in the inventory of houses for sale. This vigilant approach can serve as an early warning system for upcoming market changes, helping stakeholders make well-informed decisions.

This paper aims to study the relationship between the rental and selling prices, a very important topic that forms the fundamentals of real estate markets.

This theoretical paper makes use of a search and matching model of the housing market. The search and matching models are the benchmark models of the “matching” markets, such as the labour market and the housing market, where trade is a decentralised, uncoordinated and time-consuming economic activity.

Unlike the previous related literature, where this relation is usually analysed in the context of the present value equation, this paper shows the existence of a “dual” relation between rental and selling prices as follows: one in the homeownership market and another one in the rental market. This “dual” relation connects the rental and homeownership markets and allows to get equilibrium in both markets with positive house prices.

Several topics could be deepened for making the paper richer and more interesting, although at the cost of much more mathematics. First of all, the introduction of specific functional forms for both the rent function and the sale price function, so as to calculate both the elasticity of rent with respect to sale price and the elasticity of sale price with respect to rent. In this way, it would be possible to understand how each market (rental and homeownership) reacts to shock and policies that affect the other market.

In general, this framework could help policymakers to design housing policy reforms that take into consideration the effects on both markets. Indeed, some policies could have positive effects on rental markets but perverse effects on homeownership markets and vice versa.

None of the existing and related works of research have considered how to take advantage of the search and matching approach to derive both a “rent function” and a “sale price function” that connect closely the rental and homeownership markets.

This study aims to examine the presence of the day-of-the-week (DOW), January and turn-of-month (TOM) effect in 20 currency pairs against the US dollar, from January, 1995 to December, 2014.

Ordinary least square with GARCH (1,1) framework is used to examine the presence of DOW, January and TOM effect to test the efficiency of the currency markets. The sample period is later divided into two sub-periods of equal length, that is, from 1995 to 2004 and 2005 to 2014, to explore the time-varying behavior of the calendar anomalies. Further, the authors also use the non-parametric technique, the Kruskal–Wallis test, to provide robustness check for the results.

For the DOW effect, the results indicate that the returns on Monday and Wednesday are negative and lower than the returns on Thursday and Friday which show positive and higher returns. The returns of all the currencies are higher (lower) in January (TOM trading days) and lower (higher) during rest of the year (non-TOM trading days). However, these calendar anomalies seem to have disappeared for almost all currencies during 2005 to 2014 and indicate that the markets have achieved a higher degree of efficiency in the later part of the sample.

The results have important implications for both traders and investors. The findings suggest that the investors might not be able to earn excess profits by timing their positions in some particular currencies taking the advantage of DOW, January or TOM effect, which in turn indicates that the currency markets have become more efficient with time. The results might be appealing to the practitioners as well in a way that they can consider the state of financial market for financial decision-making.

The findings of lower returns on Monday and Wednesday and high returns during Thursday and Friday for all the currencies indicate that the foreign investors can take the advantage by going short on Monday and Wednesday and long on Thursday and Friday. Similarly, the returns of all the currencies are higher (lower) in January (TOM trading days) and lower (higher) during rest of the year (non-TOM trading days). During this period, investors in the currency markets could benefit themselves by taking long (short) positions in January (TOM trading days) and short (long) positions during rest of the year (non-TOM trading days).

The author provides a pioneer study on the presence of calendar anomalies (DOW, TOM and the January effect) across a wide range of currencies using 20 years of data from January 1995 to December 2014. To the best of the author’s knowledge, no study has examined the presence of January effect in the currency market; therefore, the author provides the first study in which January effect in a number of currencies is investigated.

This study seeks to examine the market returns of five domestic real estate investment trust (REIT) indices to determine whether they exhibit a turn‐of‐the‐month (TOM) effect.

A test is carried out for the TOM effect by employing a battery of parametric and non‐parametric statistical tests that address the concerns of distributional assumption violations. An OLS regression model compares the TOM returns with the rest‐of‐the‐month (ROM) returns and an ANOVA model examines the TOM period while controlling for monthly seasonalities. A non‐parametric t‐test examines whether the TOM returns are greater than the ROM returns and a Wilcoxon signed rank test examines the matched‐pairs of TOM and ROM returns.

A TOM effect in all five domestic REIT indices is found: real estate 50 REIT, all‐REIT, equity REIT, hybrid REIT, and mortgage REIT. More specifically, the six‐day TOM period, on average, accounts for over 100 per cent of the monthly return for the three non‐mortgage REITs, while the ROM period generates a negative return. Additionally, the TOM returns are greater than the ROM returns in 75 per cent of the months.

The data are limited to five‐years of daily returns and five different indices. Thus, the results could be biased on the selected time period.

These results are important to REIT portfolio managers and investors. Domestic REIT markets experience a TOM effect from which investors and portfolio managers can benefit.

The daily returns of all five major domestic REIT indices are examined. Data are evaluated which include daily returns after the passage of the REIT Modernization Act of 1999 that resulted in numerous changes for REITs. Whether the TOM effect can be detected with both parametric and non‐parametric tests is examined.