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This paper explores abnormal price changes in the FOREX by using both daily and intraday data on the EURUSD, USDJPY, USDCAD, AUDUSD and EURJPY exchange rates over the period 01.01.2008–31.12.2018.

It applies a dynamic trigger approach to detect abnormal price changes and then various statistical methods, including cumulative abnormal returns analysis, to test the following hypotheses: the intraday behaviour of hourly returns on overreaction days is different from that on normal days (H1), there are detectable patterns in intraday price dynamics on days with abnormal price changes (H2) and on the following days (H3).

The results suggest that there are statistically significant differences between intraday dynamics on days with abnormal price changes and normal days respectively; also, prices tend to change in the direction of the abnormal change during that day, but move in the opposite direction on the following day. Finally, there exist trading strategies that generate abnormal profits by exploiting the detected anomalies, which can be seen as evidence of market inefficiency.

New evidence on abnormal price changes and related trading strategies in the FOREX.

The purpose of this study is to investigate whether the earnings surprise influences decision to make earnings announcements during or after the trading hours is influenced by the earnings surprise resulting from the difference between consensus earnings estimates and the actual reported earnings.

Event study methodology was employed to test the hypotheses relating to earnings surprise and timing of earnings announcements. Twelve quarterly earnings announcements of 30 companies, drawn from BSE SENSEX of India, were studied to test the hypothesized relationships.

The study has found statistically significant differences in the market responses to the earnings announcements made during and after the trading hours. The market demonstrated a negative response to the earnings announcements made after the trading hours. Further, the results of the logistic regression have shown that the presence of significant earnings surprises is likely to induce firms to make earnings announcements after the trading hours. The results indicate that those firms that intend to reduce the overreaction and underreaction to earnings surprises are likely to make earnings announcements after the trading hours.

This paper highlights the market response to the earnings announcement made during and after the regular trading hour. Further, the paper examines if the earnings surprise influences the decision to announce the results.

The crude oil market has experienced an unprecedented overreaction in the first half of the pandemic year 2020. This study aims to show the performance of the global crude oil market amid Covid-19 and spillover relations with other asset classes.

The authors employ various pandemic outbreak indicators to show the overreaction of the crude oil market due to Covid-19 infection. The analysis also presents market connectedness and spillover relations between the crude oil market and other asset classes.

One of the essential findings the authors report is that the crude oil market remains more responsive to pandemic fake news. The shock of the global pandemic panic index and pandemic sentiment index appears to be more promising. It has also been noticed that the energy trader's sentiment (OVX and OIV) was measured at a too high level within the Covid-19 outbreak. Volatility spillover analysis shows that crude oil and other market are closely connected, and the total connectedness index directs on average 35% contribution from spillover. During the initial growth of the infection, other macroeconomic and political events remained to favor the market. The second phase amidst the pandemic outbreak harms the global crude oil market. The authors find that infectious diseases increase investor panic and anxiety.

The crude oil investors' sentiment index OVX indicates fear and panic due to infectious diseases and lack of hedge funds to protect energy investments. The unparalleled overreaction of the investors gauged in OVX indicates market participants have paid an excessive put option (protection) premium over the contagious outbreak of the infectious disease.

The empirical model and result reported amid Covid-19 are novel in terms of employing a news-based index of the pandemic, which are based on the content analysis and text search using natural processing language with the aid of computer algorithms.

原油市場在流行病肆虐的2020年的頭半年經歷史無前例的過度反應。本文旨在顯示全球原油市場在2019冠狀病毒病流行期間的表現及原油市場與其它資產類別之溢出關係.

我們使用各種大流行病爆發的指標，來顯示原油市場因2019冠狀病毒病的感染而過度反應。我們的分析亦涉及市場的關聯性及原油市場與其它資產類別之溢出關係.

我們其中一個基本的發現是: 原油市場仍對大流行病的虛假新聞有更迅速的反應。全球大流行病恐慌性指數及大流行病情緒指數所帶來的震驚似乎是有希望的。大家亦察覺，能源交易商的情緒(OVX及OIV) 在2019冠狀病毒病爆發期間被測量為處於太高的水平。波動溢出分析顯示、原油與其它市場有密切的關係，而總關聯度指數引導平均35%來自溢出量的作用。在感染傳播初期，其它的宏觀經濟和政治事件仍對市場有利。在大流行病爆發期間的第二階段則損害全球原油市場。我們發現，傳染病會增加投資者的恐慌和焦慮.

原油投資者的情緒指數OVX顯示因傳染病及因缺乏對沖基金來保障能源投資而帶來的懼怕和恐慌。於OVX測算到的投資者空前的過度反應顯示市場參與者就這傳染病的感染爆發付出過量的賣權(保障)權利金.

我們的經驗模型和在2019冠狀病毒病肆虐期間匯報的研究結果，從使用以新聞為基礎的流行病指數的角度而言是新穎的。而這些全以內容分析和正文搜尋為基礎、使用自然語言處理，並輔以計算機算法.

This study analyzes whether KOSPI200 option returns can be predicted by call-put implied volatility spreads. Doran et al. (2013) show that call-put implied volatility spreads predict the option returns of a specific moneyness as well as underlying asset returns in the US options market. Our study examines whether the same results are shown in the KOSPI200 options market, which has different characteristics in investor compositions and trading behaviors. According to the results, the call-put implied volatility spreads cannot predict the future returns of the underlying index significantly in the KOSPI200 options market. Only, the call-put spreads can predict the future option returns. More specifically, the increase in implied volatility spreads is able to predict the decrease in call option returns and the increase in put option returns in the KOSPI200 options market. This supports the overreaction hypothesis in all ranges of option moneyness, which is in contrast to the result of Doran et al. (2003).

Despite its devastating nature, the COVID-19 pandemic has also catalyzed a substantial surge in the adoption and integration of technological tools within economies, exerting a profound influence on the dissemination of information among participants in stock markets. Consequently, this present study delves into the ramifications of post-pandemic dynamics on stock market behavior. It also examines the relationship between investors' sentiments, underlying behavioral drivers and their collective impact on global stock markets.

Drawing upon data spanning from 2012 to 2023 and encompassing major world indices classified by Morgan Stanley Capital International’s (MSCI) market and regional taxonomy, this study employs a threshold regression model. This model effectively distinguishes the thresholds within these influential factors. To evaluate the statistical significance of variances across these thresholds, a Wald coefficient analysis was applied.

The empirical results highlighted the substantive role that investors' sentiments and behavioral determinants play in shaping the predictability of returns on a global scale. However, their influence on developed economies and the continents of America appears comparatively lower compared with the Asia–Pacific markets. Similarly, the regions characterized by a more pronounced influence of behavioral factors seem to reduce their reliance on these factors in the post-pandemic landscape and vice versa. Interestingly, the post COVID-19 technological advancements also appear to exert a lesser impact on developed nations.

This study pioneers the investigation of these contextual dissimilarities, thereby charting new avenues for subsequent research studies. These insights shed valuable light on the contextualized nexus between technology, societal dynamics, behavioral biases and their collective impact on stock markets. Furthermore, the study's revelations offer a unique vantage point for addressing market inefficiencies by pinpointing the pivotal factors driving such behavioral patterns.

This paper examines whether there are differences in the nature of the price discovery process across established versus emerging stock markets using a twenty-country sample.

The authors analyse security returns for traces of predictability or non-randomness using variance ratio tests, Granger-Causality models and runs tests.

The findings pinpoint at predictabilities which seem inconsistent with market efficiency, and they suggest that the inherent cause of predictability differs across groups.

The authors present empirical evidence which may be used to attain a deeper understanding of the links between predictability and market efficiency, in view of the conflicting evidence in prior literature.

Whilst the pricing process in emerging markets may be hindered by delayed adjustments, in case of established markets it seems that there is a higher tendency for price reversals which could be due to prior over-reactions.

This study presents evidence of substantial differences in predictability across developed and emerging markets which was gleaned through the rigorous application of different empirical tests.

This study examines the long term effects of macroeconomic fundamentals on apartment price dynamics in major metropolitan areas in Sweden and Germany.

The main approach is panel cointegration analysis that allows to overcome certain data restrictions such as spatial heterogeneity, cross-sectional dependence, and non-stationary, but cointegrated data. The Swedish dataset includes three cities over a period of 23 years, while the German dataset includes seven cities for 29 years. Analysis of apartment price dynamics include population, disposable income, mortgage interest rate, and apartment stock as underlying macroeconomic variables in the model.

The empirical results indicate that apartment prices react more strongly on changes in fundamental factors in major Swedish cities than in German ones despite quite similar development of these macroeconomic variables in the long run in both countries. On one hand, overreactions in apartment price dynamics might be considered as the evidence of the price bubble building in Sweden. On the other hand, these two countries differ in institutional arrangements of the housing markets, and these differences might contribute to the size of apartment price elasticities from changes in fundamentals. These arrangements include various banking sector policies, such as mortgage financing and valuation approaches, as well as different government regulations of the housing market as, for example, rent control.

In distinction to the previous studies carried out on Swedish and German data for single-family houses, this study focuses on the apartment segment of the market and examines apartment price elasticities from a long term perspective. In addition, the results from this study highlight the differences between the two countries at the city level in an integrated long run equilibrium framework.

How do organisations know which problems are worthy of their attention? Despite good intentions, many attempts to solve problems fail. One reason for this failure might be because of attempts to solve non-problems or to solve problems with insufficient means, a concept proposed by Deming as tampering. The purpose of this paper is to suggest a definition of tampering, outline what is currently known about possible practical implications of tampering and to suggest how to extend this knowledge by proposing an agenda for future research.

To fulfil the purpose, a narrative literature review was conducted.

Through this review, common aspects of what constitutes tampering are identified and the following definition is proposed: Tampering is a response to a perceived problem in the form of an action that is not directed at the fundamental cause of the problem, which leads to a deterioration of the process or the process output. In addition, recommendations are generated regarding how tampering manifests itself in practice and why tampering occurs. These recommendations could be studied in future research.

To the best of the authors’ knowledge, this is the first paper that suggests a revitalisation of tampering. The results presented in this paper form the basis for continued studies on how tampering in organisations can be understood, managed and prevented.

The present research aims to examine a range of momentum trading strategies for the tourism and hospitality sector.

The paper followed the methodology of Jegadeesh and Titman (1993) to construct the portfolios. In this methodology, all portfolios were formed and evaluated by their cumulative stock returns over the past J periods and holding the position for the next K periods. In total, nine formation and holding periods were used, represented by 3, 6 and 12. For example, strategy 3–3 (that is, strategy with J = 3 and K = 3) refers to the strategy that stocks are ranked based on their previous three months and then held for the next three months.

The findings demonstrated that none of these momentum investing strategies was profitable. Most of the results, however, show positive, but insignificant momentum returns. This finding can be interpreted as price reversal over a horizon of three to twelve months in the US hospitality and tourism sector. These results are robust to size, different formation and holding combinations, beta and turnover.

Regarding the research limitations, this paper only considers the US tourism and hospitality sector. Therefore, the extension of results to other developed and developing markets should be taken carefully. Also, this paper relies only on the methodology of Jegadeesh and Titman (1993). Other methodologies could be suitable avenues for future research.

Investors and portfolio managers who seek for earning abnormal returns by investing in the US HT stocks can attain their hopes by constructing portfolios based on existing guidelines in the literature and adopting a short-term reversal trading strategy or by buying past losers and selling past winners of the US tourism and hospitality stocks.

This research contributes to the hospitality finance literature by offering the investors who are interested in the US hospitality and tourism sector an uncomplicated trading rule that uses real return data and is expected to generate actual returns. Moreover, the momentum strategy of Jegadeesh and Titman (1993) is never used in the hospitality finance literature.

本研究旨在探討各種可應用於旅遊及酒店業的動量交易策略。

本文按照 Jegadeesh 和 Titman（1993）的研究方法來建造投資組合。使用這研究方法時，所有投資組合均以它們在過去J 時期的累積股票收益和在未來K 時期的持倉來建立及評價的。九個組成方式及持有期被使用，以3、6、12來表示。例如，策略3-3（那就是說，該策略以J = 3和 K = 3）指的策略是以有關的股票基於過去三個月而被分等級，繼而在未來三個月被持有。

研究結果顯示，這些投資策略全沒帶來利潤；唯大部分結果顯示正動能策略報酬，雖報酬是微不足道的。這研究結果或許可理解為在美國酒店及旅遊業為期三至十二個月的價格逆轉。這些結果就規模、不同組成方式和持有組合、beta 和成交量而言是強而有力的。

就研究的局限而言，本文只是考慮美國的酒店及旅遊業；因此，如把研究結果伸延至其它已開發或發展中的市場，則需小心處理。另外，本文只依賴 Jegadeesh 和 Titman（1993）的研究方法，就此，使用其它研究方法會是日後相關研究的適當途徑。

欲透過投資於美國酒店及旅遊股票而尋求賺取異常收益的投資者和投資組合經理可如願以償，方法是基於文獻內現存的準則建造投資組合，以及採用短期的逆轉交易策略，或買入美國酒店及旅遊業過去輸家及賣出過去贏家。

本研究為酒店金融文獻作出貢獻，因研究為對美國酒店及旅遊業有興趣的投資者提供了使用實際收益數據及預期可創造實際回報的簡單交易規則；而且， Jegadeesh 和 Titman（1993）的動量策略從未在酒店金融文獻內被使用過。

The purpose of this paper is to consider the economic information content within several popular stock market factors and to the extent to which their movements are both explained by economic variables and can explain future output growth.

Using US stock portfolios from 1964 to 2019, the authors undertake three related exercises: whether a set of common factors contain independent predictive ability for stock returns, what economic and market variables explain movements in the factors and whether stock market factors have predictive power for future output growth.

The results show that several of the considered factors do not contain independent information for stock returns. Further, most of these factors are neither explained by economic conditions nor they provide any predictive power for future output growth. Thus, they appear to contain very little economic content. However, the results suggest that the impact of these factors is more prominent with higher macroeconomic risk (contractionary regime).

The stock market factors are more likely to reflect existing market conditions and exhibit a weaker relation with economic conditions and do not act as a window on future behavior.

Fama and French three-factor model still have better explanations for stock returns and economic information more than any other models.

This paper contributes to the literature by examining whether a selection of factors provides unique information when modelling stock returns data. It also investigates what variables can predict movements in the stock market factors. Third, it examines whether the factors exhibit a link with subsequent economic output. This should establish whether the stock market factors contain useful information for stock returns and the macroeconomy or whether the significance of the factor is a result of chance. The results in this paper should advance our understanding of asset price movement and the links between the macroeconomy and financial markets and, thus, be of interest to academics, investors and policy-makers.