Do Natural Disasters Alter Tourism Industry Risks Differently over Time?

Abstract

This study adopted the event study method to explore the effect of the Hualien earthquake on the performance of tourism stocks in Taiwan. This earthquake occurred on 3 April 2024 and affected Hualien and Taitung. The present study examined the short-term (10 trading days), medium-term (12 weeks), and long-term (5 months) performance of all listed tourism companies in Taiwan (overall sample) and six listed tourism companies with a branch in Hualien or Taitung (six-company sample). The results indicated that the stocks of the overall sample rebounded soon after the earthquake but declined over the long-term period. By contrast, the stocks of the six-company sample exhibited a persistent negative return immediately after the earthquake and gradually recovered in the long term. The findings of this study enhance theoretical understanding regarding the effects of a disaster on the stock market. Moreover, they serve as a reference for practical decision-making related to government risk response, investor behavior, and corporate crisis management in high-risk industries, such as tourism. Strengthening disaster preparedness and corporate branding after a disaster is critical for stabilizing market sentiment and industry resilience.

1. Introduction

Taiwan is located in the Pacific Rim of Fire and is at high risk of natural disasters. Taiwan’s economy has been repeatedly affected by strong earthquakes. An earthquake with a magnitude of 7.4 occurred off the coast of Hualien County, Taiwan, on 3 April 2024. This earthquake was one of the strongest earthquakes to occur in Taiwan in the last 25 years [1]. The number of tourists visiting Hualien in 2024 was 54.29% lower than that in 2023. This represents the largest drop in Hualien tourist numbers in the last decade and demonstrates the profound effects of natural disasters on local economies [1]. Natural disasters reduce both domestic and international tourism and cause difficulties to local hospitality and tourism industries. According to the Tourism Administration of the Ministry of Transportation and Communications in Taiwan, 31 accommodation operators in Hualien County have closed down or sold their businesses since 2024 [2]. The tourism industry is extremely vulnerable to natural disasters because of its service-oriented nature and location dependence [3,4].

Natural disasters often have substantial negative short-term effects on stock prices. Stock prices tend to fall during disasters [5]. Natural disasters have negative effects on stock markets and industries. Different industries have different sensitivities to disasters. Safe-haven stocks (i.e., gold and public utilities) increase in price after natural disasters. Conversely, banking stocks decrease in price after natural disasters [6,7]. Thus, natural disasters have heterogeneous effects on financial markets. Research into the response patterns of different industries in different disaster situations is warranted.

The effects of natural disasters on financial markets are complex and crucial. Natural disasters are increasing in frequency and intensity. Accordingly, their threats to economic and financial systems are increasing [8]. In particular, the effects of natural disasters on sensitive industries, such as tourism, may affect the stability of financial markets [9]. The tourism industry is one of the most vulnerable sectors to crises because of its location dependence and demand elasticity characteristics [4]. Tourism and hospitality stocks are particularly vulnerable to natural disasters, epidemics, and other events, with these stocks often performing poorly during crises [9,10,11].

The present study was motivated by two factors. First, limited empirical evidence exists regarding the effects of natural disasters on the tourism industry [9]. Additionally, most research on the Taiwanese market has focused on the overall market or specific major events, with limited in-depth analysis conducted on Taiwan’s tourism stocks. The tourism industry is closely related to economic development and employment in Taiwan. Thus, exploring the effects of natural disasters on the prices of tourism stocks in Taiwan is crucial. Second, the 2024 Hualien earthquake is a suitable event for exploring the aforementioned effects. By comparing the effects of this earthquake on tourism stocks in Taiwan during different periods within the same year, this study investigated the financial effects of a disaster [7]. The findings of this study not only have academic value but also serve as a practical reference for predicting investment risks in tourism stocks.

This research used the event study method to conduct an empirical analysis of the short-term (10 trading days), medium-term (12 weeks), and long-term (5 months) effects of the 2024 Hualien earthquake on the stock prices of (1) listed tourism companies throughout Taiwan and (2) listed tourism companies with a branch in the Hualien or Taitung region.

2. Literature Review

In the past two decades, considerable research has been conducted on the effects of natural disasters on the tourism industry and stock market, including tourism stocks. The following text summarizes the main findings of such research.

Studies on the effects of earthquakes on the tourism industry have mainly focused on post-disaster infrastructure reconstruction and tourism revitalization policies [12,13,14], post-disaster tourist psychology [15,16], and post-disaster tourism planning [17]. For example, Antonaglia et al. (2025) [18] examined the effect of the 2009 L’Aquila earthquake in Abruzzo, central Italy, on inbound tourism. They found that the earthquake had adverse long-term effects on the tourism industry, with a significant decline noted in overnight stays. Biardeau and Sahli (2024) [19] stated that the higher the intensity of an earthquake, the greater the subsequent reduction in tourist arrivals and increase in tourism expenditure.

Natural disasters can greatly influence the stock market. Chen (2007) [3] conducted a study on hotel and tourism stocks in China and Taiwan, finding that both macroeconomic factors and extraordinary events can greatly affect the returns of these stocks [20]. Zopiatis et al. (2018) [4], Brounen and Derwall (2010) [21], and Kumar and Liu (2013) [22] explored the performance of tourism stocks in various countries during crises, incorporating unpredictable noneconomic events (such as natural disasters, wars, and terrorist attacks) into their analyses. Their results have confirmed that the tourism industry is one of the most vulnerable sectors to crises. Zopiatis et al. (2018) [4] used the event study method to investigate the influences of unexpected events on tourism stocks; they identified that most such events triggered negative abnormal returns (ARs) for tourism stocks. Chang et al. (2018) [9] explored the effects of political events and natural disasters on the number of tourists visiting Taiwan and the prices of tourism stocks in Taiwan. Their results indicated that major events led to abnormal changes in tourism demand and ARs in tourism stocks.

Antonaglia et al. (2025) [18] noted that natural disasters, especially earthquakes, can have long-term negative effects on tourism, such as causing a significant decline in the number of tourists. Khan et al. (2025) [23] found that earthquakes have significant negative effects on the stock market. They indicated that earthquakes cause a substantial negative shock to the stock market on the next trading day after their occurrence. Pandey and Al-Ahdal (2024) [24] investigated the effect of the Turkey–Syria earthquake on stock market returns. They noted that the earthquake had a significant negative effect on the cumulative returns of the stocks of all industries except for the commodities industry. Average returns went from −0.79% on the event day (day t) to −11.04% two days later (day t + 2). Sakariyahu et al. (2023) [25] also found that the aforementioned earthquake had a significant negative influence on stock market returns in Turkey, Syria, and neighboring countries. Studies have explored the sensitivity of different financial subsectors to disasters. Chen et al. (2023) [26] indicated that security companies are highly sensitive to all types of disasters and that the banking industry is only sensitive to earthquakes. Moreover, they noted that the insurance industry’s cumulative ARs (CARs) under natural disasters are usually not significant. Disaster events can cause substantial changes in the relationship between tourists and the affected destination, which affect the post-disaster recovery of the tourism market and tourism stocks.

Yildirim and Alola (2020) [27] noted that the effects of natural disasters on the stock market vary over time. They noted that earthquakes have long-term but not short-term effects on the Turkish stock index, possibly because of long-term policy uncertainty and exchange rate fluctuations. Worthington and Valadkhani (2004) [28] employed the event study method to analyze the responses of the Australian stock market to 42 natural disasters, including storms, floods, and earthquakes, from 1982 to 2002. Their results showed that the effects of different types of disasters on the stock market had varying directions and magnitudes [6]. Overall, the literature indicates that the tourism industry is vulnerable to excessive stock price fluctuations during natural disasters because of its high demand elasticity and the deep influence of psychological expectations [4].

The following findings were obtained from the aforementioned literature review. First, disasters have short-term negative effects on stock markets. Most relevant studies have found that after a natural disaster occurs, the stock market in the affected area has significant negative ARs. For example, Tavor et al. (2019) [5] indicated that natural disasters cause stock price indices to fall on the event day and in the subsequent 2 days; they noted that sudden events (such as earthquakes) have short-term negative effects on the stock market. Second, the magnitude and direction of the effect of a disaster on the stock market depends on the type and intensity of the disaster. Major disasters such as severe earthquakes or tsunamis may cause large declines and long recovery periods in the stock market. The severity of a disaster (assessed in terms of aspects such as the number of casualties and economic losses) is usually positively correlated with the absolute value of abnormal stock market returns; that is, the more severe a disaster, the greater the decline in stock prices. Third, stock prices in different sectors have varying vulnerability to disasters. The tourism industry is a highly vulnerable sector, and crisis events often have a significant effect on the prices of tourism stocks [4]. By contrast, some safe-haven industries (such as gold and public utilities) are relatively resistant to stock price declines after disasters, even exhibiting price rises in some cases [7]. Fourth, market reactions to sudden earthquakes occur after the event, with investors only able to react passively to the event. Finally, disaster events generally have short-term effects on stock prices. Many studies have emphasized that natural disasters cause immediate decreases in stock prices and have minimal long-term effects. Stock markets tend to return to normal within a few days or weeks after a disaster, exhibiting a certain degree of resilience and rebound as rescue and recovery operations progress and cooler emotions prevail. Secondary shocks (such as policy uncertainty or cascading crises) prolong recovery periods [5,29].

3. Research Design

3.1. Sample

This study analyzed 29 tourism stocks listed on the Taiwan Stock Exchange in 2025. The listed stocks belong to companies that operate in tourism-related sectors, such as the hotel industry (e.g., Regent Hotels 2707), travel industry (e.g., Lion Travel 2731), and leisure and catering industry (e.g., Wangpin Catering 2727). Six of the listed stocks, including those of Regent Holdings (2707), had a branch in Hualien or Taitung.

3.2. Study Period and Event Selection

The study period covers all of 2024 to ensure the inclusion of the target event and sufficient post-event data. The target event was the 3 April 2024, Hualien–Taitung earthquake (i.e., the 2024 Hualien earthquake). This natural disaster had an immediate effect on the stock market. This research employed the event study method to investigate the effect of this earthquake on the tourism industry in Taiwan.

3.3. Data Sources and Frequency

Stock price data were obtained from the Taiwan Economic Journal or from public information released by the Taiwan Stock Exchange. The daily closing price of each listed company in the sample was collected, and a weighted stock price index (Taiwan Stock Exchange Capitalization Weighted Stock Index) was used as the market benchmark index. Daily, weekly, and monthly stock price data were collected [5].

3.4. Model Selection: Event Study Method

The event study method is used to explore whether a special event or related information produces an abnormal reaction in stock price returns [11,30,31,32]. This method has been widely used to investigate the ARs resulting from financial information, such as dividend announcements, earnings releases, and information on the implementation of treasury stock [33,34,35,36,37]. The present study used an ordinary least squares method to develop a regression model for calculating the theoretical return of each stock in the research sample over different periods. It then determined the AR by subtracting the theoretical return from the actual return. The developed model is expressed as follows:

$${\mathrm{R}}_{i,t}=a_i+{\mathsf{\beta }}_i{\mathrm{R}}_{\mathrm{m}}+{\mathsf{\epsilon }}_{it}$$

(1)

where ${\mathrm{R}}_{i,t}$ represents the expected rate of return for the stock of company i in period t, ${\mathrm{R}}_{\mathrm{m}}$ is the rate of return of the market portfolio in period t, $a_i$ is a constant, ${\mathsf{\beta }}_i$ is the systematic risk, and ${\mathsf{\epsilon }}_i$ is the residual term.

AR is defined as follows:

$${\mathrm{A}\mathrm{R}}_i={\mathrm{R}}_i-\mathrm{E}\left({\mathrm{R}}_i\right)$$

(2)

where ${\mathrm{A}\mathrm{R}}_i$ represents the AR of the stock of company i, ${\mathrm{R}}_i$ denotes the actual return of company i, and $\mathrm{E}\left({\mathrm{R}}_i\right)$ is the expected return of the stock of company i.

Average AR is defined as follows:

$${\overline{\mathrm{A}\mathrm{R}}}_t={\displaystyle \frac{1}{\mathrm{N}}}\sum _{i=1}^{\mathrm{N}}{\mathrm{A}\mathrm{R}}_i$$

(3)

where ${\overline{\mathrm{A}\mathrm{R}}}_t$ is the average AR of all companies in the sample during period t and N represents the total number of observations.

CAR is calculated by adding the ARs of all companies as follows:

$${\mathrm{C}\mathrm{A}\mathrm{R}}_{[{\mathsf{\tau }}_1,{\mathsf{\tau }}_2]}={\displaystyle \frac{1}{\mathrm{N}}}\sum _{i=1}^{\mathrm{N}}\sum _{t={\mathsf{\tau }}_1}^{{\mathsf{\tau }}_2}{\mathrm{A}\mathrm{R}}_{i,t}$$

(4)

where ${\mathrm{C}\mathrm{A}\mathrm{R}}_{[{\mathsf{\tau }}_1,{\mathsf{\tau }}_2]}$ represents the CAR from period τ₁ to period τ₂ (i.e., the sum of the average ARs of all companies from period τ₁ to period τ₂).

4. Results

4.1. Short-Term Effects of the 2024 Hualien Earthquake on Tourism Stocks

Figure 1 shows the average AR and CAR trends of the 29 included stocks over a short-term period (10 trading days) after the 2024 Hualien earthquake. The average AR fluctuated between positive and negative values during this period, and the CAR changed from negative to positive from the third trading day after the earthquake.

Figure 2 displays the average AR and CAR trends over the aforementioned period for the stocks of the six tourism companies that had a branch in Hualien or Taitung. The average AR of the six stocks fluctuated between positive and negative after the earthquake, whereas their CAR mostly remained negative.

Table 1. Average AR and CAR values for overall sample and six-company sample over short-term period (10 trading days) after 2024 Hualien earthquake [unit: percentage (%)].

Period (Day)	Overall Tourism		Own the 6 Company in Hualien and Taitung
	AR	CAR	AR	CAR
0	−0.588	−0.588	−1.380	−1.380
1	−0.109	−0.697	−2.305 ***	−3.685 ***
2	0.533	−0.164	0.232	−3.453 **
3	1.095 ***	0.931	0.487	−2.967 *
4	3.917 ***	4.848 ***	2.909 ***	−0.057
5	0.515	5.363 ***	0.233	0.176
6	−0.551	4.812 ***	−1.335	−1.159
7	−1.795 ***	3.017 ***	−2.522 ***	−3.681
8	1.394 ***	4.411 ***	0.985	−2.696
9	0.871 **	5.282 ***	0.532	−2.164
10	−1.100 ***	4.183 ***	−1.999 **	−4.163

Note: *** indicates significance at the 1% level. ** indicates significance at the 5% level. * indicates significance at the 10% level.

compares the average AR and CAR values over 10 trading days after the 2024 Hualien earthquake for the entire research sample (29 stocks) and for the six companies with a branch in Hualien or Taitung. For the entire sample, significant positive average ARs occurred on the third, fourth, eighth, and ninth trading days after the earthquake. A significant negative average AR was observed on the seventh trading day. Moreover, the CAR was positive from the fourth trading day to the tenth trading day. By contrast, for the six-stock sample, significant negative average ARs occurred on the first, seventh, and tenth trading days after the earthquake, and a significant positive average AR was observed only on the fourth trading day. Furthermore, the CAR was negative on the first, second, and third trading days after the earthquake.

4.2. Medium-Term Effect of the 2024 Hualien Earthquake on Tourism Stocks

Figure 3 depicts the average AR and CAR trends of the entire research sample over a medium-term period (12 weeks) after the 2024 Hualien earthquake. The results indicate that the average AR of the entire sample was mostly negative in the weeks following the earthquake. The CAR was negative in the week of the event (week 0), became positive from the first week to the tenth week after the event, and then became negative in the 11th week following the event.

Figure 4 shows the average AR and CAR trends of the six-stock sample over 12 weeks after the Hualien earthquake. The average AR and CAR of this sample were mostly negative during the period.

Table 2. Average AR and CAR values for overall sample and six-company sample over medium-term period (12 weeks) after 2024 Hualien earthquake [unit: percentage (%)].

Period (Week)	Overall Tourism		Own the 6 Company in Hualien and Taitung
	AR	CAR	AR	CAR
0	−0.684	−0.684	−1.690	−1.690
1	3.800 ***	3.116 *	−0.491	−2.181
2	2.519 **	5.635 ***	0.071	−2.110
3	7.283 ***	12.918 ***	4.044 *	1.934
4	3.814 ***	16.731 ***	1.430	3.365
5	−5.027 ***	11.704 ***	−3.052	0.312
6	0.612	12.316 ***	−0.812	−0.500
7	−7.356 ***	4.961	−5.384 **	−5.883
8	3.201 ***	8.162 **	1.662	−4.222
9	−2.579 **	5.583	−3.480	−7.702
10	−3.101 ***	2.481	−0.959	−8.660
11	−2.947 **	−0.466	−2.749	−11.409
12	−2.213 *	−2.678	−0.887	−12.296

Note: *** indicates significance level at the 1% level. ** indicates significance at the 5% level. * indicates significance at the 10% level.

presents the average AR and CAR values of the overall sample and six-stock sample over a medium-term period (12 weeks) after the 2024 Hualien earthquake. The overall sample exhibited significant positive average ARs in the first, second, third, fourth, and eighth weeks after the earthquake. Moreover, the sample exhibited significant negative average ARs in the 5th, 7th, 9th, 10th, 11th and 12th weeks. The CAR of the overall sample was positive in the first, second, third, fourth, fifth, sixth, and eighth weeks after the earthquake. The six-stock sample showed a significant positive average AR in the third week after the earthquake and a significant negative average AR in the seventh week. The CAR of this sample did not show significant deviation during the entire 12-week period, with no significant positive or negative CAR being noted.

4.3. Long-Term Effect of 2024 Hualien Earthquake on Tourism Stocks

Figure 5 depicts the average AR and CAR trends of the entire research sample over a long-term period (5 months) after the 2024 Hualien earthquake. The average AR and CAR of this sample changed from positive to negative in the first and second months after the earthquake, respectively.

Figure 6 displays the average AR and CAR trends of the six-stock sample over a long-term period (5 months) after the 2024 Hualien earthquake. The average AR of this sample was negative in most months, with positive average ARs occurring only in the month of the earthquake (month 0) and the fourth month following the earthquake. The CAR of the sample mostly remained negative throughout the 5-month period.

Table 3. Average AR and CAR values for overall sample and six-company sample over long-term period (5 months) after 2024 Hualien earthquake [unit: percentage (%)].

Period (Month)	Overall Tourism		Own the 6 Company in Hualien and Taitung
	AR	CAR	AR	CAR
0	14.645 ***	14.645 ***	3.098	3.098
1	−5.642 **	9.003 ***	−6.120	−3.022
2	−9.617 ***	−0.614	−5.974	−8.996
3	0.046	−0.569	−2.335	−11.330
4	−4.746 **	−5.315	4.065	−7.265
5	−5.448 **	−10.762 *	−6.426	−13.691

Note: *** indicates significance at the 1% level. ** indicates significance at the 5% level. * indicates significance at the 10% level.

presents the monthly AR and CAR values for the overall sample and the six-stock sample over 5 months since the 2024 Hualien earthquake. The overall sample exhibited a significant positive average AR in month 0 and significant negative average ARs in the first, second, fourth, and fifth months after the earthquake. The CAR of this sample exhibited significant positive values in months 0 and 1 but showed a significant negative value in the fifth month. By contrast, the six-stock sample did not exhibit significant positive or negative average AR and CAR values during the 5-month period, indicating that the earthquake did not cause a significant deviation in the performance of the six stocks over a long-term period.

5. Discussion

This study explored the effect of a strong earthquake on the stock prices of tourism companies in Taiwan. Short-term (10 trading days), medium-term (12 weeks), and long-term (5 months) effects were analyzed. Two samples were considered in the exploration: (1) a sample containing the stocks of 29 tourism companies listed on the Taiwan Stock Exchange in 2025 (overall sample) and (2) a sample containing the stocks of six tourism companies with a branch in Taitung or Hualien. The empirical results of this study indicated that the AR and CAR trends of tourism stocks in Taiwan differed with the time scale and sample.

In the short-term period (10 trading days) after the earthquake, the prices of the stocks in the overall sample first decreased and then increased. The overall sample exhibited negative ARs on the day of the earthquake and the following trading day (first trading day) but then rebounded quickly. Except for the seventh and tenth trading days, on which the ARs were negative, the ARs on the remaining trading days were positive, especially on the fourth, fifth, eighth, and ninth trading days. The CAR of the overall sample changed from negative to positive on the fourth trading day and remained positive until the 10th trading day, indicating that market panic had eased in less than a week. This rapid recovery was related to the market’s reassessment of the effect of the earthquake, with the market believing that the earthquake had a limited effect on the tourism sector in Taiwan. The recovery was also encouraged by positive government information, which resulted in bargain hunting behavior. The six companies with a branch in Hualien or Taitung experienced sharp short-term losses. The share prices of these companies fell sharply on the first trading day after the earthquake, and the average AR of their shares was negative on the first, second, seventh, and tenth trading days. On the fourth trading day, the AR temporarily became positive because of the news of government subsidies. The CAR of the six-stock sample was negative from the first to the third trading days, indicating that the six companies experienced immediate and sustained losses after the earthquake. Overall, in the short term, the earthquake mainly affected the six tourism companies with a branch in Taitung or Hualien, with the overall Taiwanese tourism industry quickly resuming its upward trend in stock prices after the earthquake.

In the medium-term period (12 weeks) after the earthquake, the prices of the stocks in the overall sample first increased and then decreased. Moreover, the overall sample and six-stock sample exhibited diverging trends. The overall sample exhibited significant positive average ARs from the first week to the fourth week after the earthquake, and its CAR remained positive until the sixth week, indicating high excess returns in the early post-earthquake period. This period coincided with the Spring Festival and Mother’s Day, which correspond to periods of increased domestic tourism demand in Taiwan. In addition, the Taiwanese government launched tourism subsidies for Hualien and Taitung from the eighth week, which increased stock prices. The positive momentum gradually faded from the fifth week, and the overall sample exhibited negative average ARs in the 5th, 7th, and 9th–12th weeks, with the previous gains being eliminated. By week 12, the CAR had returned to its normal level. This trend reflected that the market had gradually recognized the negative effect of the earthquake on tourism demand. The performance of the six-company sample was flat in the medium-term period, with limited volatility. The weekly average ARs of this sample exhibited no obvious trend. The average AR was briefly positive in the third week, which reflected the market’s short-term optimistic expectations; it became negative in the seventh week, possibly because of the approaching summer vacation and the decline in market confidence in the tourism industries in Hualien and Taitung. Overall, the six companies did not have significant CAR values in the medium term, and their stock prices generally returned to normal after early adjustments.

During the long-term period (5 months), the earthquake had a continuous negative effect on the stocks in the overall sample; its effect on the stocks in the six-company sample gradually subsided. The overall sample showed a significant positive average AR in the month of the earthquake (month 0), indicating that tourism operations were not immediately affected in this month; the Taiwanese government’s rapid disaster relief and revitalization measures stabilized the market. The overall sample showed significant negative average AR values in the first, second, fourth, and fifth months after the earthquake. The CAR of this sample became negative (approximately −10%) in the fifth month, reflecting that tourism demand gradually reduced after the earthquake and investors became pessimistic regarding the overall outlook of the tourism industry. The aforementioned long-term decreases in the average AR and CAR correspond to the decline in tourism at Hualien, which resulted in the closure of many accommodation businesses in 2024. The stock price performance of the six-company sample did not show any significant abnormal changes in the long-term period. The monthly ARs and CAR of this sample were not significant in the 5 months after the earthquake, with the stock prices of the sample tending to stabilize during this period. A possible reason for this trend is that investors had fully understood the negative effect of the earthquake on tourism operations in Hualien and Taitung in the early stage of the post-earthquake period. In addition, most of the six companies are national companies, with their business in Hualien and Taitung accounting for a limited proportion of their overall business. Revenue from other regions partially offset the losses made in Hualien and Taitung. Moreover, government rescue measures eased market concerns regarding the long-term operations of the six companies.

Overall, the short-, medium- and long-term analyses indicated that the stock market’s response to the 2024 Hualien earthquake had obvious temporal characteristics. In the short term, the market quickly stabilized after experiencing severe fluctuations. In the medium term, the negative effect of the earthquake was temporarily masked by policy and seasonal factors; subsequent fundamental pressures gradually emerged. In the long term, the market reflected the profound influence of the earthquake on the operations of the tourism industry in Taiwan. This study found differences in the stock price trends over different periods for the overall tourism industry in Taiwan and the six tourism companies with a branch in Taitung or Hualien. The stock prices of the six companies varied drastically in the immediate aftermath of the earthquake but then stabilized. By contrast, the returns in the overall industry gradually reduced over a long-term period after the earthquake. The empirical results of this study provide concrete evidence for understanding how the financial market reacts to natural disasters.

5.1. Theoretical Implications

The results of this study have several implications for finance and management theory. First, these results confirm the theoretical view that natural disasters increase market uncertainty and cause negative shocks. Earthquakes are unpredictable systemic risks that trigger investor panic and cognitive biases, leading to irrational selling and sharp price drops, which is consistent with behavioral finance theory [27,38]. Moreover, the results indicate that natural disasters result in economic losses and increased risk premiums, which cause stock prices to come under pressure over medium- and long-term periods. This finding is in line with the belief that the market gradually processes disaster-related information.

Second, the multiple-period analysis conducted in this study highlighted the differences between the short- and long-term market effects of a disaster. Another study concluded that disasters have a short-term effect on the market, with stock prices quickly returning to normal following a disaster [29]. The present study found that severe disasters can have long-term negative effects [27]. The prices of tourism stocks in Taiwan did not rebound to their original levels even 5 months after the earthquake. A short-term abnormal rebound does not eliminate the possibility of a long-term decline in stock prices. A lag effect may occur, where the initial market resilience fades away with the subsequent revelation of negative financial information related to a disaster.

Third, the results of this study highlight the vulnerability of the travel and tourism industry to natural disasters. The post-disaster trends of the decline and recovery of tourism stocks are considerably different from those of the broader market, reflecting the high demand elasticity and poor resilience of these stocks [4]. Over a long-term period, the tourism industry exhibits weaker recovery performance than the overall market does, which reflects the susceptibility of the tourism industry to disasters [4,21]. Therefore, industry differences should be considered in the assessment of the effects of a disaster on the stock market.

Finally, this study revealed the heterogeneity in the effects of a disaster on tourist companies with and without major operations in the disaster-hit area. This heterogeneity has implications for market efficiency and information transfer theories. The market can distinguish between tourism companies that are and are not severely affected by a disaster. Compared with tourism companies that are not severely affected by a disaster, severely affected companies exhibit a larger short-term decline in stock prices following the disaster; however, these prices stabilize over time. The stock prices of relatively unaffected companies recover faster than those of severely affected companies over a short-term period but exhibit long-term declines, which is consistent with the argument that the impact of disasters is localized and selective [7,26]. Investors can effectively use the aforementioned information to achieve differentiated pricing, with corporate risk diversification and crisis management capabilities becoming key factors in determining stock price resilience.

5.2. Practical Implication

The results of this study have practical implications. First, governments should formulate clear post-disaster emergency measures to quickly stabilize the tourism market and reduce market panic and long-term negative effects. Moreover, they must strengthen post-disaster market monitoring to prevent market disorder. Second, investors should enhance their awareness of risk management. Uncertainty and industry risk must be accounted for in investment decisions made during disasters. The effects of disasters on the tourism market can be reduced through asset and geographical diversification, and risks can be hedged using appropriate hedging tools. Third, tourism companies should establish effective crisis management mechanisms, including clear emergency plans, and rapidly resume operations after a disaster. These companies should also conduct appropriate public relation activities, implement suitable brand management strategies, and disclose their post-disaster measures to the market. Such steps can enable tourism companies to reduce the negative effects of a disaster on their business and stock prices and strengthen their ability to resist disaster-related risks. Finally, governments and tourism businesses should collaborate to develop a robust insurance and financial reserve mechanism to enhance tourism companies’ resilience to losses resulting from disasters, ensure their rapid post-disaster recovery, and reduce their financial burdens.