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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。

This study aims to propose and estimate the urban tourism performance index (UTPI), an index that can measure and track the month-by-month tourism performance on main tourism cities since the initial outbreak of the COVID-19 pandemic. The UTPI is estimated for the following urban destinations: Bangkok, Paris, London, Dubai, Singapore, Kuala Lumpur, New York, Istanbul, Tokyo, Seoul, Osaka, Phuket, Milan, Barcelona, Bali and Hong Kong.

Monthly based data measuring the tourism industry’s performance for these urban destinations has been collected. This data includes airlines’ and hotels’ performance, as well as potential tourists’ online searches. The obtained data has been combined using a principal component analysis, generating the UTPI.

The UTPI shows that all urban areas analyzed in this study experienced a devastating negative impact because of the COVID-19 pandemic outbreak. However, the tourism recovery evolution follows heterogeneous patterns.

The proposed index can be estimated using additional variables. Moreover, the index is only estimated for 16 tourism cities. Future studies can reproduce the methodology by incorporating further variables and amplifying the geographical coverage.

The UTPI might be useful for researchers and policymakers interested in using a measure of tourism performance during the COVID-19 pandemic in some of the most important urban destinations. Likewise, the UTPI index may serve as a suitable aggregated measure of tourism performance in a post-COVID-19 era or to monitor tourism during future crises.

This study analyzes the tourism performance during the COVID-19 pandemic from an urban perspective.

Cambodia's tourism sector has increasingly been playing a crucial role and is the key to the country's socio‐economic development. The purpose of this paper is to investigate how value changes in Cambodian society affect development of the tourism industry and to evaluate the events having potential impact on tourism market development.

The Delphi qualitative forecasting technique has been utilized in a variety of settings as a powerful market research tool. In this empirical study, the Delphi method is utilized to predict the future tourism and hospitality scenarios for Cambodia from 2005 through 2020, as well as their marketing policy implications at regional and national levels. A representative sample of diverse groups of Cambodia tourism and hospitality industry experts were pooled for data collection.

The study results indicate that experts predict more structural changes will be taking place in the tourism and hospitality industry. An interesting study finding is that most of the tourism and hospitality events will take place in the medium and long‐term horizon. It is predicted that there will not be much change in value orientations of Cambodians, except for significant change in high value of materialism and interactive learning and cultural exchanges.

The research offers implications for tourism researchers, the Cambodian government tourism ministry, as well as tourism industry actors.

The paper offers greater insights into the working of qualitative forecasting in the development of tourism market planning in emerging markets.

The purpose of this study is to inspect factors influencing profitability in the Italian hospitality industry during the period 2008-2016.

This paper examines the profitability and its determinants using a sample of 2,366 Italian hotels. The author applies a multidimensional measure of profitability comprising return on equity, return on assets, occupancy rate and gross operating profit per available room. The author investigates variables influencing performance and includes them into five groups: market variables, business model, ownership structure, management education and control variables.

The results show that financial crisis, business model and ownership structure affect hotel firms’ profitability. Particularly, findings suggest that size, internationalization, location, accommodation as first activity and chain affiliation influence profitability positively.

Results confirm the importance of firm-specific factors for evaluating the profitability of a hotel firm. Findings also provide new evidence for academics to assess factors that would guarantee profitability of hotels in developed countries such as Italy.

This investigation offers valued information and strategic suggestions for hotel investors, hotel owners, hotel managers, tourism playmakers and government.

This paper offers an in-depth examination of the practices and characteristics of profitable hotels in Italy. Few empirical studies examined the determinants of performance in the European and Italian hospitality field so far. Hence, this study attempts to bridge the gap in prior literature on profitability of the Italian hospitality industry.

This study aims to examine cash dividend practices of travel and leisure (T&L) companies listed on the London Stock Exchange (LSE).

The study uses a panel data set of 524 firm-year observations of 55 unique publicly listed UK T&L companies between 2007 and 2019. First, it uses a modified version of Lintner’s (1956) partial adjustment model for analysis regarding the target payout ratio and dividend smoothing. Second, it performs logit and Tobit models in ascertaining the association between financial characteristics and divided decisions of T&L firms. Finally, it applies the modified specification of the partial adjustment model on different sub-samples that are partitioned based on various financial factors to determine how the financial characteristics of T&L companies affect their dividend behavior.

The results show that UK T&L companies have long-term payout ratios and adjust their cash dividends by moving gradually to their target at a serious degree of smoothing. The findings also detect that financial characteristics of T&L firms (i.e. profitability, debt and size) have significant effects on their dividend payments decisions. In particular, more profitable and larger T&L corporations are more likely to pay cash dividends, whereas T&L companies with more debt are less likely to pay cash dividends in the UK. The results further reveal that although such financial characteristics also have important impacts on the target payout ratios and dividend smoothing levels, UK T&L companies generally adopt stable dividend policies over the period 2007-2019.

This is thought to be the first study to provide insights on dividend policy practices of UK travel and leisure corporation listed on the LSE.

This paper investigates the short-term market impact of the beginning of the military conflict between Russia and Ukraine (February 24, 2022) on a set of airline stocks listed.

This study uses an event study methodology, cross-section analyses and interaction effects to study the effect of the war on airline stock prices and firm-specific characteristics that explain the cumulative abnormal return.

The authors observe a negative and statistically significant stock price reaction at and around the beginning of the military conflict between Russia and Ukraine, for 74 listed airlines. These results are consistent with investment portfolio rebalancing and asset pricing perspective. Moreover, this study's results show a higher negative stock market reaction for airlines based in Europe. Empirical evidence suggests the existence of a “proximity penalty” for European companies. Finally, this study's results provide insights into which airline-specific characteristics emerge as value drivers. Larger, well-capitalized (high liquidity and low debt) and profitable airlines firms with less institutional ownership have superior stock market returns and show more able to handle with the losses resulting from the war.

This paper fills a gap in the literature about the impact of the Russia–Ukraine war on the airline industry.

The purpose of this paper is to analyze the market response of the aerospace and defense industry and the airline industry to the ongoing conflict between Ukraine and Russia based on the sentiments from war-related news articles over the period from October 2021 to June 2022.

The study uses the news article database of Global Database of Events, Languages and Tone (GDELT) to create a new set of variables that reflect the news sentiment regarding war and conflict. By investigating the newly created sentiment variables in combination with traditional event study methodology, the authors seek to find out whether sentiment indicators can be helpful to rationalize the evolution of the different stock markets before and after the conflict.

The authors' results point out a significant negative impact of the war on the airline market and a positive impact on the defense market. The authors' study also introduces a new set of war-related news-based sentiment variables that is significant to explain the evolution of the two markets before and after the war. The relationships between this study's new set of variables and the performance of the two markets are also proven to be significantly impacted by the invasion.

To the best of the authors' knowledge, this is the first research to use the news sentiment related to the topic of war and conflict to explain the market movement of different industries during the Ukraine invasion.

With a sample of 22 banks, this study examines the significance of the news contents about the privatization of two public sector banks in India. New information does impact the stock markets. This study provides evidence on how the privatization of public sector banks impacted the returns of the Indian banking sector.

This study employs the standard event study methodology with the market model for estimating the normal returns.

The statistical results indicate that while the private sector banks experienced positive average abnormal returns on the event day, the cumulative effect of the announcement is negatively significant for both private and public sector banks. The statistical results also provide evidence of information leakage, with significant results before the announcement date. The shorter event windows analysis exhibits significant positive returns in the 5-days [−2, +2] window for the private sector banks and the entire sample, signifying a positive short-term impact on the private sector banks.

The event study literature captures the impacts of many events. However, to the best of our knowledge, the impacts of the privatization of the Indian public sector banks have never been examined using the event study methodology. Hence, this study anticipates being the first-ever study to fill this gap and extend the available literature in finance. In addition, although we provide Indian evidence, future studies may be oriented to capture cross-country impacts.

The authors examine the impacts of corporate announcements on stock returns during the pandemic stress.

The authors employ the event study methodology with the market model on a sample of 90 events (announcement and ex-date).

The authors find that all the corporate announcements do not impact the stock returns in a similar pattern. While the bonus announcement, ex-bonus and ex-split events led to positive significant abnormal returns on the event date, the rights issue and stock-split announcements failed to influence the stock returns. The findings suggest that before making such announcements, the corporates should wait until the market recovers because even the positively impacting events result in negative market responses during pandemic stress.

This study will guide the policymakers to stimulate share prices during such pandemics with the help of various corporate announcements. The investors will be assisted in understanding the stock market mechanism and making wise decisions before reacting to corporate actions during a pandemic or emergency period. While the policymakers are concerned with influencing the share prices, the investors are concerned with the composition of the risk-return parameters in their portfolio. This study will act as an essential investment tool for both.

To the best of the authors’ knowledge, the authors conduct the first-ever study to examine the impacts of corporate announcements during a pandemic stress period that significantly contributes to the literature. The authors examine the announcement effects in India and accurately anticipate that this study will be a pioneer in this field. This study also paves the way for future researches in this area.

This article examines dynamic volatility spillovers between stock index returns of four main hospitality sub-sectors in US during the coronavirus disease 2019 (COVID-19) pandemic. These are tourism and travel, hotel and lodging, recreational services and food and beverages. Volatility spillovers are explicitly used as accurate and informative proxies for risk contagion between sectors during turbulent times.

The authors employ dynamic conditional correlation-generalized autoregression heteroskedasticity (DCC-GARCH) and wavelet coherence analysis (WCA) to analyze the phenomenon. The authors’ timeframe is divided into three main sub-periods, namely the pre-pandemic, the first wave and the second wave periods.

This study’s results reveal immense negative shocks in returns of all four sub-sectors on the Black Monday (8th March 2020). Moreover, high volatility persistence was observed during both waves with an exception of tourism and travel which exhibited lower volatility persistence during the second wave. The authors discovered magnified contagion effects between tourism and travel, hotel and lodgment and recreational services during the first wave of the pandemic with tourism and travel being the main volatility transmitter. Lower magnitudes of spillovers were observed between food and beverages and other sub-sectors with a decoupling effect being evident during the second wave.

This study’s findings contribute to the contagion theory by providing evidence of disproportional volatility spillover among hospitality sub-sectors despite being exposed to similar turbulent economic conditions.

Crucial implications can be drawn from this study’s findings to assist in risk management, asset valuation and portfolio management. The importance of close monitoring, safety measures, international diversification and adequacy of liquid assets during health crises cannot be stresses enough for hospitality firms. Retail investors, speculators and asset managers can take advantage of this study’s findings to design trading strategies and hedge against risk.

A body of knowledge pertaining to effects of crises such as COVID-19 on hospitality stocks has been proliferating. Nonetheless, there is still a relative dearth of empirical literature on volatility spillover between hospitality sub-sectors especially during periods of rising economic uncertainties.