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This paper provides a thorough examination of Socios.com, a blockchain platform that integrates token sales with the fan experience in the sports industry. The study focuses on three key aspects: the performance, bubble phenomenon and dynamics of fan tokens. The author aims to address important questions that may concern potential supporters and investors. Might sports fans incur financial losses due to their team loyalty? Is the fan token market just a passing trend? Are fan tokens driven by the behaviour of the cryptocurrency market?

This analysis aims to involve several methodologies. The author evaluates the short- and long-term performance of fan tokens by computing first-day and buy-and-hold (abnormal) returns. The author also employs the Phillips, Shi, and Yu's (PSY) real-time bubble detection method to investigate the presence of bubble phenomenon in the fan token market segment. Finally, the author examines the potential dependences between fan tokens, Chiliz and the cryptocurrency market (represented by the CCi30 index) using both Pearson/Kendall correlations and the wavelet coherence approach.

The study presents three notable contributions to the existing literature. First, the author demonstrates that investing in fan tokens to support one's favourite sports teams can lead to financial losses, whereas traders can potentially outperform the market by investing in Chiliz. Second, the author states that fan tokens were a short-lived trend, as evidenced by their decline in value after the bubble burst in 2021. Third, the findings indicate that the fan token market was influenced by the cryptocurrency market and Chiliz during periods of market downturns.

To the best of author’s knowledge, this is the first paper to conduct a comprehensive analysis of the performance, bubble phenomenon and dynamics of the token market fan segment, along with the exclusive on-platform currency, Chiliz.

This paper aims to develop a research model that investigates the probable antecedents and outcomes of psychological capital (PSY-capital). More specifically, high-quality relationships (HQRs) and psychological safety (PSY-safety) are tested as the antecedents and organizational deviant behaviors (ODBs) is tested as the outcome.

Data was gathered from the restaurant staff and their direct supervisors through a 10-day time-lag design in two different rounds. Structural equation modeling was used to evaluate the direct and mediation.

Drawing upon social identity theory (SIT), the findings reveal that PSY-safety functions as a mediator of the effect of HQRs on PSY-capital. Additionally, the results proved that PSY-capital mediates the relationship between PSY-safety and ODBs.

Considering the results, restaurant managers should pay ample attention to and make every effort to develop HQRs among organizational members. Through this, manager paves the way for PSY-safety which causes employees to develop PSY-capital and eventually display less deviance. Additionally, the authors recommend that company managers serve as role models for their staff, sharing information with and respecting them to create an environment of mutual trust, similar goals and knowledge sharing.

This research contributes significantly to the existing hospitality literature (specifically foodservice) by testing the mechanism through which HQRs lead to PSY-capital and the mediation effect of PSY-capital in the relationship between PSY-safety and ODBs.

The purpose of this paper is to test for bubbles in the US hard red spring (HRS) wheat market from 2004 to 2014, with particular focus on 2007-2008 when the market experienced record-high price volatility.

The authors apply a recently developed bubble testing procedure to cash, rolling nearby futures contract, and individual futures contract prices of HRS wheat sampled at daily, weekly, and monthly frequencies. Two critical value (CV) sequences are derived to date-stamp bubbles, one from Monte Carlo simulations, and the other from recursive wild bootstrap procedure.

The authors find that regardless of the price series adopted, sampling frequency chosen, or CVs used, bubbles account for only a small fraction of the HRS wheat price behavior during 2004-2014. However, much sharper differences are detected regarding the key policy question of bubble behavior during 2007-2008. Individual futures contract prices during this period suggest only a minimal number of bubble days, while rolling nearby futures and cash prices indicate bubbles lasting much longer. Since theory suggests that prices for individual futures contracts are more likely to provide a clearer test of bubble components, the authors conclude there is little evidence that the spike in spring wheat prices to $25 per bushel in 2007-2008 was a bubble.

This paper is the first in the literature to examine the sensitivity of bubble testing to different types of data, sampling frequencies, and inference procedures.

The aim of this paper is to examine dynamic linkages between price and rent and between property types. Intuition suggests that housing market segments experience different market cycles in response to macroeconomic shocks. However, they may be dynamically interlinked in urban areas because of substitutability. The linkage may even change, if preference weakens for multiple occupancies. A sudden reduction in apartment demand may create repercussions to other housing segments. Past analyses, despite their contributions, are static and do not consider possible linkages between property types. To fill this void, this paper investigates the price-rent dynamics for urban homes by adopting the case of Singapore.

This paper applies a methodology from Phillips et al. (2015) to Singaporean housing (price and rent) data. Phillips et al. (2015) recently proposed a test for an explosive root in time series data and has spurred several empirical applications in the bubble literature.

This paper finds for Singapore that the markets were subjected to explosive growth (where rents grew at a higher rate than prices did) during the Global Financial Crisis. Also, the results suggest that rent drives price and that non-landed housing (offices in central areas) leads to other residential housing (non-residential housing) in both price and rent.

Overall, the present findings suggest that rent drives price, while property types are interlinked. Non-landed homes and offices in central areas are the sources of repercussions. Under normal circumstances, rental shocks may be propagated positively from nonlanded housing (central offices) to the other residential (non-residential) property types as the present findings suggest, which enables us to infer that a decrease in non-landed housing (central offices) rent may lead to an increase in rent on other property types because pandemic shocks only shift demand fromone property type to another, unlike typical macroeconomic shocks.

Urban homes are faced with uncertainty arising from the COVID-19 outbreak for which city residents have a stronger incentive to exile to suburbs. Urban life may no longer be attractive because of social distancing and work from home policy. This has implications for urban home demands that are closely linked to urban house price and rent. In the present study, the paper set out to investigate the price-rent and property-type dynamics for urban homes in Singapore.

After the COVID-19 outbreak, the Federal Reserve has undertaken several monetary policies to alleviate the pandemic consequences on the stock markets leading to a misunderstanding on the cryptocurrency market response. This paper aims to evaluate the effects of the Federal Reserve monetary policy on the Islamic and conventional cryptocurrency dynamics during the COVID-19 pandemic. We, specifically, examine the associate bubbles and feedbacks effects.

This paper developed a novel methodology that detects market bubbles using the statistical indicators defined by Psychological (PSY) tests. It also investigated the effect of the Federal Open Market Committee (FOMC) announcements on conventional and Islamic cryptocurrencies compatible with Islamic laws “Shari’ah” by using the event-driven regression.

The empirical results show that the FOMC announcements have a positive significant effect after one day of the event and a negative effect before two days of the announcement on the conventional cryptocurrency markets. However, the reaction of Islamic cryptocurrencies to these events is not significant except for Hello Gold after one day of the announcement. Besides, the Hello Gold and X8X cryptocurrencies present no bubbles during this period. However, Bitcoin and Ethereum markets have short-lived bubbles.

The main contribution of this study is the investigation of the response and vulnerability to pandemic shocks of a new category of cryptocurrencies backed by tangible assets. This work has practical implications as it provides new insights into trading opportunities and market reactions.

To our knowledge, this work is the first study that compares the response of Islamic and conventional cryptocurrency markets to FOMC announcements during the COVID-19 pandemic and examines the presence of bubbles in these markets. Besides, the originality of this work is derived from the novelty of the data employed and the method used (PSY tests) in this study.

The diagnostic process after referral to an acute psychiatric treatment facility consists of more than the clinical investigation and laboratory tests. Psychometric tests in a broad range of languages may be such an augmentation of our diagnostic armamentarium. Whether such tests are in use, and how they are distributed among different patient categories was the aim of the study. All referrals in one calendar year (N=1168), as they are depicted in the hospital computerized medical records, were investigated. Fifty-six (6.1%) out of 926 ethnic Norwegians and six (3.0%) out of 198 non-Western immigrants were tested, whereas none of the 44 Western immigrants. The difference between ethnic Norwegians and the immigrants was significant (Z=-3.05 and P=0.002). Psychometric tests were thus almost not in use, and even lesser so in immigrants. Mean number of resident days was higher among those tested, 11.7 (SD=11.2) versus those not tested, 7.4 (SD=10.4) days, t=2.97 and P=0.004. Length of stay for ethnic Norwegians did not differ from that for non-Western immigrants 11.4 versus 11.7, respectively. The patients tested were older than those not tested. Mean age was 43.0 (SD=14.4) versus 38.8 (SD=12.1), with a t=2.65 and P=0.03. The difference in resident days between all immigrants and ethnic Norwegians was significant with a Z=−2.232 and P=0.026. Level of testing was higher in ethnic Norwegians, and the tested patients stayed longer, maybe indicating more room for testing. Whether this low test-activity influences treatment quality is an unsettled question.

Cryptocurrencies lack fundamental values and are often subject to behavioral bias leading to market bubbles. This study aims to investigate the contribution of the coronavirus pandemic to the creation of market bubbles.

This study identifies four major cryptocurrency market bubbles by using the Phillips et al. (2016) (hereafter PSY) test. Subsequently, the co-movements of the coronavirus proxies with PSY measurement using the wavelet approach were studied.

Short-lived bubbles are detected at the beginning of the studied period, and more extended bubble periods are identified at the end. Besides, the empirical results show evidence of significant negative co-movement between each pandemic proxy and each cryptocurrency bubble measurement.

Given the complex financial dynamics of the cryptocurrency markets due to some behavioral biases in some circumstances, investors can benefit from the date stamping of the bubbles bursting to make the best trading positions. In the same way, governments could support the healthy development of cryptocurrencies by preventing bubbles during such pandemics.

The financial bubble is commonly attributed to a change in investor behavior. Because traders and investors think they can resell the asset at a higher price in the future. This study explored the contribution of the COVID-19 pandemic in the creation of these bubbles by date stamping their occurrence and explosive periods. To the best of the authors’ knowledge, this study is the first attempt that explores the contribution of the COVID-19 pandemic to the creation of bubbles caused by a change in the investors’ behavior.

After the COVID-19 outbreak, the Federal Reserve has undertaken several monetary policies to alleviate the pandemic consequences on the markets. This paper aims to evaluate the effects of the Federal Reserve monetary policy on the cryptocurrency dynamics during the COVID19 pandemic.

We examine the response and feedback effects via an event study methodology. For this purpose, abnormal returns (AR) and cumulative abnormal returns (CARs) around the first FOMC (Federal Open Market Committee) announcement related to the COVID-19 pandemic for the top five cryptocurrencies are explored. We, further investigate the effect of the eight FOMC statement announcements during the COVID19 pandemic on these cryptocurrencies (Bitcoin, Ethereum, Tether, Litecoin, and Ripple). In the above-mentioned crypto-currency markets, we investigate the presence of bubbles by using the PSY test. We then examine the concordance of the dates of these bubbles with the dates of the FOMC announcements.

The empirical results show that the first FOMC event has a negative significant effect after 4 days of the announcement date for all studied cryptocurrencies except Tether. The results also indicate that cumulative abnormal returns are significant during the event windows of (−3,8), (−3,9), and (−3,10). Besides, we find that Bitcoin, Ethereum and, Litecoin lived short bubbles lasting for a few days. However, Ripple and Tether markets present no bubbles and no explosive periods.

This paper presents trained proof that FOMC announcements have a positive effect on volatility's predictive capacity. This work therefore promotes the study of the data quality of volatility in future research as well.

The justified effect of the FOMC announcements on cryptocurrency as a speculative asset has practical implications for investors in building their trading strategies in anticipation of the next FOMC announcement. Therefore, this study implies that the FOMC announcements contain very relevant information for investors in the cryptocurrency market. This research may not only encourage a better understanding of the evolution of the expectations of policymakers, but also facilitate a better understanding of how these expectations are developed.

The COVID-19 pandemic has disturbed the stability of financial markets, inciting the Fed to take some monetary regulations. To the best of our knowledge, this study is the first one that analyses the response of five major cryptocurrencies to FOMC announcements during COVID 19 pandemic and associates these dates with bubble occurrences.

Outlines an effective procedure for recruitment. Briefly considers job analysis, methods of recruitment, methods of assessment, reference checks and job previews. Encourages employers to see this area as long term investment in their human resource portfolio.

States that psychological testing can be classified into several major categories and that the tremendous variance in psychological measurements makes evaluating the usefulness or value of these tools complex. Reviews and assesses the literature in this field to determine whether, if responsibily used, psychological tests are valuable tools for evaluation. Concludes that they are of use, but the user should have some knowledge of the limitations of the tools.