Comparative Analysis of Stock Prices, Abnormal Return, Cumulative Abnormal Return, and Trading Volume Activity in the Indonesia Stock Exchange: An Event Study of the Russia-Ukraine War

The Russia-Ukraine war has captured international attention and raised concerns about its potential implications on global financial markets. This study aimed to investigate the interplay between geopolitical events, market reactions within the Indonesia Stock Exchange (IDX), and the market efficiency of the IDX. The study employed event study methodology and analyzed changes in stock prices, abnormal returns, cumulative abnormal returns, and trading volume activity. The sample comprised 53 companies in the energy sector and 57 companies in the food and beverage sector listed on the IDX. The analysis focused on data from 10 days before and after three Russia-Ukraine conflict-related events, namely (1) the announcement of Russia’s invasion of Ukraine on the 24th of February 2022, (2) the announcement of an oil import embargo on Russia by the European Union on the 31st of May 2022, and (3) the announcement of the first wheat export ship’s departure from the port of Odesa on the 1st of August 2022. Both paired sample t-tests and paired sample Wilcoxon signed rank tests were conducted to assess the statistical significance of differences in the means of paired samples. The findings revealed significant differences in average stock prices before and after all three events in the energy sector. However, only events 2 and 3 displayed significant differences in average abnormal returns and cumulative abnormal returns. Moreover, events 1 and 3 exhibited significant differences in average trading volume activity. In the food and beverage sector, a significant difference in average stock prices was observed before and after event 2, while all three events presented significant differences in average abnormal returns and cumulative abnormal returns. Furthermore, event 3 showed a significant difference in average trading volume activity. These findings indicated that the IDX displayed varying reactions to different Russia-Ukraine conflict-related events. Notably, events involving multiple countries or entities exerted a greater impact on the energy and food and beverage sectors within the IDX, leading to more pronounced market reactions. Additionally, the findings suggested that the IDX exhibited a semi-strong form of market efficiency.

Introduction

In today’s interconnected and globalized world, geopolitical events have a profound impact on global financial markets, with their repercussions often extending beyond the borders of the countries directly involved. Geopolitical events, ranging from geopolitical conflicts and trade disputes to natural disasters and pandemics, possess the potential to influence financial markets significantly, sparking substantial market reactions. One such geopolitical event that has drawn international attention and raised widespread concerns about its implications for economies and financial markets worldwide is the Russia-Ukraine war. Despite the geographical distance between Indonesia and the epicentre of the Russia-Ukraine war, the Indonesia Stock Exchange (IDX) remains intrinsically connected to the global financial system, rendering it susceptible to external shocks and the spillover effects of geopolitical events. As a vital platform for domestic and international investors to trade stocks and securities, the IDX plays a pivotal role in shaping Indonesia’s economic landscape. The Russia-Ukraine war, characterized by heightened geopolitical tensions, economic uncertainties, increases in commodity prices—particularly energy and natural resources—and trade disruptions, holds the potential to significantly impact the functioning of the IDX, leading to fluctuations in stock prices, trading volumes, and overall market volatility.

The impact of the Russia-Ukraine war on the IDX became evident on the 24^th of February 2022, following Russia’s invasion and military attacks on Ukraine. The invasion raised concerns among investors in the IDX, prompting them to take precautionary measures to safeguard their funds by divesting from risky assets, including stocks. This shift in investor sentiment had a direct impact on the Jakarta Composite Index (IDX Composite), which closed the trading day in the red zone, weakening by 102.2 points or 1.48% to reach 6,817.82, as shown in Fig. 1 (Safitri, 2022). Simultaneously, the downturn in the market affected 492 companies listed on the IDX, causing their stock prices to decline (Shemi, 2022).

Fig. 1. Jakarta Composite Index on the Day of Russia’s Invasion of Ukraine on the 24^th of February 2022. Source: Jayani (2022).

Additionally, the Russia-Ukraine war disrupted the global supply of energy commodities, resulting in a surge in energy prices due to Russia’s significant role as a major producer and exporter. Consequently, the price of Indonesian Crude Price (ICP) followed the upward trajectory of global crude oil prices and skyrocketed towards the US$100 level, surpassing the assumption of US$63 per barrel set in Indonesia’s 2022 State Budget (Andrianto, 2022). This surge in oil prices brought positive implications for the energy sector in Indonesia, as evidenced by the remarkable growth of the energy sector index. In 2022, the energy sector index outperformed all other sectoral stock indices, achieving an extraordinary growth rate that exceeded 100% (Rahmawati, 2022). Fig. 2 displays the performance trend of the Composite Index along with various sectoral indices throughout the year 2022, providing a clear visual representation of the energy sector’s outstanding performance in comparison to the Jakarta Composite Index (IDX Composite) and other sectoral stock indices.

Fig. 2. Performance trend of Jakarta Composite Index (IDX Composite) and sectoral indices in 2022. Source: Chandren (2023).

Moreover, the Russia-Ukraine conflict also disrupted the global supply of wheat, resulting in a rise in global wheat prices. While wheat is not a staple food in Indonesia, the country heavily relies on imported wheat for various processed food products, including instant noodles and bread, which are widely consumed by the Indonesian population. According to data provided by Indonesia’s Central Statistics Agency, in 2021, Indonesia imported a total of 11,172 tonnes of wheat and meslin, valued at US$3,449.8 million, with Ukraine standing out as the second-largest supplier, accounting for 2,834 tonnes valued at US$843.6 million (Badan Pusat Statistik-BPS, 2022). The increase in global wheat prices adversely affected food and beverage companies in Indonesia, such as PT Indofood CBP Sukses Makmur Tbk and PT Mayora Indah Tbk. Following the start of the Russia-Ukraine war, MYOR’s shares experienced the most significant decline of −14% in a week, while ICBP’s shares also stumbled with a decline of −12.94% (Fernando, 2022).

Several previous studies have examined the reaction of the stock market to the Russia-Ukraine war using an event study methodology. One of these studies conducted by Joshipura and Lamba (2022) investigated the impact of the Russian invasion of Ukraine on stock markets in 95 countries, including Indonesia. Their findings revealed significant and negative abnormal returns (AR) as well as cumulative abnormal returns (CAR) in the majority of the countries studied, reflecting an overall negative market reaction. In addition, their findings showed that the invasion triggered different short-term and long-term market reactions in each country. The findings of Joshipura and Lamba (2022) are supported by the study conducted by Boubakeret al. (2022) on the impact of the Russia-Ukraine invasion on markets in 23 developed and 24 emerging countries, including Indonesia, within the Morgan Stanley Capital Investment (MSCI) classification. In line with Joshipura and Lamba’s (2022) findings, Boubakeret al. (2022) also observed a negative CAR, indicating an overall negative market reaction while observing variations in market reactions across different countries. Additionally, Tambunanet al. (2023) conducted a study examining the reaction of the energy sector on the IDX to the Russian invasion of Ukraine. Tambunanet al. (2023) found significant differences in AR and trading volume activity (TVA) before and after the invasion, highlighting a notable market reaction in the energy sector on the IDX due to the invasion. The findings of Tambunanet al. (2023) are aligned with another study conducted by Kurniawan and Sudirman (2023), which also examined the market reactions in the energy sector on the IDX following the Russian invasion of Ukraine. Similar to Tambunanet al. (2023), Kurniawan and Sudirman (2023) noted significant differences in AR before and after the invasion, further supporting the presence of market reactions in the energy sector on the IDX caused by the invasion.

In summary, the collective findings of previous studies indicate that the Russia-Ukraine war events have a significant impact on investor decision-making and trigger market reactions, as evident from varying AR and CAR observed across different countries and sectors. However, despite this existing body of studies, there remains a research gap in understanding the market reactions of the IDX to the impacts of the Russia-Ukraine war-related events. To bridge this gap, this study aims to employ event study methodology to analyze and evaluate the market reactions of the IDX to three Russia-Ukraine war-related events, namely (1) the announcement of the Russian invasion of Ukraine, (2) the announcement of an oil import embargo on Russia by the European Union on the 31^st of May 2022 and (3) the announcement of Ukraine’s first wheat export ship departure from the port of Odesa on the 1^st of August 2022. Focusing specifically on the energy sector and the food and beverage sector of the IDX, this study will examine stock prices, AR, CAR, and TVA within these sectors.

Furthermore, beyond analyzing and evaluating market reactions, this study also assesses the market efficiency of the IDX based on the informationally efficient market hypothesis. According to this hypothesis, an efficient market promptly and accurately incorporates new information into stock prices, limiting opportunities for investors to earn AR (Fama, 1970). This study will utilize the same event study methodology to assess the market efficiency of the IDX. The stock prices will serve as indicators of market efficiency. By integrating the analysis of market reactions and market efficiency, this study aims to enhance our understanding of the interplay between geopolitical events, market reactions within the IDX, and the market efficiency of the IDX. The findings of this study will have significant implications for investors, policymakers, and financial institutions, providing them with valuable insights to navigate the IDX during geopolitical events. Investors will gain deeper insights into potential risks and opportunities within the IDX, while policymakers can proactively devise suitable strategies to manage the impact of geopolitical events, ensuring market stability and reinforcing investor confidence. Moreover, financial institutions can establish robust risk management frameworks, enabling them to accurately assess market vulnerabilities and optimize their investment strategies during such geopolitical events.

Literature Review and Hypotheses

Informationally Efficient Market Hypothesis

The informationally efficient market hypothesis is a theory stating that a market is considered efficient when the prices of its securities accurately and rapidly reflect all available information. This means that the market efficiently processes information so that prices promptly adjust to new information as it becomes available. Consequently, investors are unable to consistently gain abnormal returns (AR) by exploiting market inefficiencies caused by incomplete or delayed information. As the market becomes more informationally efficient, the chance of gaining AR decreases. There are three levels of market efficiency based on the type of information that is reflected in asset prices (Fama, 1970):

1. Weak-form efficiency: In a weak-form efficient market, all past market trading information, such as price and volume data, is already reflected in the current stock prices. This means that historical price patterns and trading data cannot provide an advantage to investors in predicting future price movements. As a result, investors cannot consistently outperform the market or gain AR by relying solely on technical analysis or historical trading information.
2. Semi-strong form efficiency: In a semi-strong form efficient market, all publicly available information, including financial statements, news, announcements, and economic data, is quickly and accurately reflected in stock prices. This means that any new information that becomes public knowledge is almost instantly incorporated into prices, leaving little room for investors to exploit the information for excess returns. Consequently, neither fundamental analysis nor the use of publicly available information alone can consistently lead to AR.
3. Strong-form efficiency: In a strong-form efficient market, all information, whether public or private, is fully and immediately reflected in stock prices. This includes not only publicly available information but also insider information. In such a market, no group of investors, including insiders, can consistently earn above-average returns based on their access to information. This implies that even if an investor has insider knowledge, they cannot exploit it to gain AR as the market has already factored in that information.

Event Study

Event study is a research methodology used to analyze the market’s reaction to publicly announced events, such as a company’s earnings announcement, a merger or acquisition, a regulatory change, or any other event that could potentially impact the market (Hartono, 2018). When an event contains information relevant to the market, the market will react upon receiving that information, and vice versa. Market reactions are typically indicated by differences in stock prices, which can be measured through abnormal returns (AR). An event can be considered to contain relevant information if it generates AR. According to Tandelilin (2019), the market will respond positively to good news and negatively to bad news, where positive market reactions generate positive AR, while negative market reactions generate negative AR. In addition to AR, the market’s reaction to an event can also be measured by trading volume activity (TVA), which reflects the sentiment and investment decisions of investors in response to the information content of the event. Increased TVA indicates a positive reaction to the information and vice versa (Hartono, 2018).

Stock Price

Stock price refers to the price of a stock that is valid in the stock market during a specific time period and can vary over time based on the demand and supply for the stock at that moment (Darmadji & Fakhruddin, 2012). The common types of stock prices are as follows (Widioatmodjo, 2015):

1. The nominal price is the price stated on each share of stock issued by a company, and investors are required to pay this nominal price upfront as capital. The minimum dividend that a company will pay is usually determined based on the nominal price of a stock.
2. Initial Public Offering (IPO) price is the price during the IPO set by the underwriter and the company issuing the stock. Although each share of stock has a nominal price, the IPO price may not always be the same as the nominal price stated.
3. The opening price is the price at which sellers or buyers request a stock when the stock market opens.
4. Market price is the price at a specific time period, determined by the demand and supply in the stock market during that period. The stock price can fluctuate based on the amount of demand and supply for that stock.
5. The closing price is the last price at which sellers or buyers request a stock when the stock market closes.

In addition to the demand and supply for a stock, other factors that can influence the stock price in the stock market are as follows (Alwi, 2008):

1. Internal factors originate from within the company issuing the stock, such as equity and debt-related announcements, changes in the board of directors or company management, mergers and acquisitions, announcements about business development or expansion, and announcements of the company’s financial reports.
2. External factors originate from outside the company issuing the stock, such as changes in interest rates, inflation, new economic regulations, legal claims against the company, fluctuations in currency exchange rates, political turmoil, various domestic and foreign issues, and stock trading restrictions.

Abnormal Return

Abnormal returns (AR) is the difference between the actual return of a stock and the expected return of the stock, often caused by a specific event, and can be calculated using the following formula (Hartono, 2017):

(1)ARit=Rit−E(Rit)where:

ARit = Abnormal return of stock i at time t;

Rit = Actual return of stock i at time t;

E(Rit) = Expected return of stock i at time t, which can be calculated using the capital asset pricing model as follows:

(2)E(Rit)=Rf+βi(Rm−Rf)where:

E(Rit) = Expected return of stock i at time t;

Rf = Risk-free rate;

β = Beta;

Rm = Market return.

Cumulative Abnormal Return

Cumulative abnormal returns (CAR) is the sum of abnormal returns (AR) over a specific time period and can be calculated using the following formula (Hartono, 2017):

(3)CARit=∑t1t2ARitwhere:

CARit = cumulative abnormal returns of stock i at time t;

ARit = abnormal returns of stock i at time t.

Trading Volume Activity

Trading Volume Activity (TVA) is the ratio of the total number of shares traded to the total number of shares outstanding (or available for trading) in the market over a specific time period and can be calculated using the following formula (Hartono, 2017):

(4)TVAit=∑Stock i traded at time t∑Stock i outstanding at time twhere:

TVAit = trading volume activity of stock i at time t.

Research Hypotheses

The Russia-Ukraine war has emerged as a significant geopolitical event that has garnered international attention and raised concerns about its impact on the Indonesia Stock Exchange (IDX). The escalating geopolitical tensions, economic uncertainties, rising energy and natural resource commodity prices, and trade disruptions caused by the Russia-Ukraine war have the potential to influence the performance of the IDX and trigger market reactions. Market reactions are typically indicated by differences in stock prices, which can be measured through abnormal returns (AR) (Hartono, 2018). The ability of investors to obtain AR depends on the efficiency level of the market. According to the informationally efficient market hypothesis, in an efficient market, stock prices reflect all available information accurately and rapidly, making it difficult for investors to gain AR (Fama, 1970). Conversely, in less efficient markets, stock prices may not accurately and rapidly reflect all information, providing investors with more opportunities to exploit information and gain AR until stock prices adjust. In addition to AR, market reactions to an event can also be measured through trading volume activity (TVA), which reflects investor sentiment and investment decisions in response to the information content of the event (Hartono, 2018).

Several previous studies have examined market reactions to the Russia-Ukraine conflict using the event study method. For instance, Richadet al. (2023) conducted a study on market reactions in the energy and non-consumer cyclical sectors of the Indonesia Stock Exchange concerning seven Russia-Ukraine war-related events. These events included the announcement of the Russian invasion of Ukraine, the US-imposed Russian oil import embargo, the Russian blockage of Ukraine’s main wheat export route, the European Union-imposed Russian oil import embargo, Indonesia’s announcement that Russia had agreed to open a wheat export sea route for Ukraine, Ukraine’s first wheat export since the war began, and the Minister of Agriculture’s announcement predicting a threefold increase in instant noodle prices. The results of their study showed significant differences in stock prices, AR, and TVA before and after some of the Russia-Ukraine war-related events they examined. These significant differences in stock prices, AR, and TVA reflected market reactions to the Russia-Ukraine war-related events. Furthermore, Yousafet al. (2022) conducted a study on market reactions in G20 member countries and several other countries, including Romania, Hungary, the Netherlands, Slovakia, Poland, and Ukraine, following the outbreak of the geopolitical conflict between Russia and Ukraine. The study focused on the announcement of Russia’s military operation in Ukraine on February 24 2022. The results of their study indicated that the announcement of Russia’s military operation in Ukraine resulted in negative and significant AR and cumulative abnormal returns (CAR) in most countries, particularly European countries and Russia. The negative and significant values of AR and CAR reflected negative and significant market reactions to the announcement of Russia’s military operation in Ukraine on the day of the event and post-event.

Drawing from the literature review and building upon the insights gained from the previous studies, this study develops the following research hypotheses:

1. H₁: There is a significant difference in stock prices on the IDX before and after the following Russia-Ukraine war-related events: a) Event 1: the announcement of Russia’s invasion of Ukraine on the 24^th of February 2022. b) Event 2: the announcement of an oil import embargo on Russia by the European Union on the 31^st of May 2022. c) Event 3: the announcement of Ukraine’s first wheat export ship departure from the port of Odesa on the 1^st of August 2022.
2. H₂: There is a significant difference in abnormal returns on the IDX before and after (a) event 1, (b) event 2, and (c) event 3.
3. H₃: There is a significant difference in cumulative abnormal returns on the IDX before and after (a) event 1, (b) event 2, and (c) event 3.
4. H₄: There is a significant difference in trading volume activity on the IDX before and after (a) event 1, (b) event 2, and (c) event 3.

Research Methodology

This study adopts a quantitative comparative study design and utilizes the event study method to analyze and evaluate market reactions on the Indonesia Stock Exchange (IDX) in response to three Russia-Ukraine war-related events as follows:

1. The announcement of Russia’s invasion of Ukraine on the 24^th of February 2022.
2. The announcement of an oil import embargo on Russia by the European Union on the 31^st of May 2022.
3. The announcement of Ukraine’s first wheat export ship departure from the port of Odesa on the 1^st of August 2022.

To investigate the presence and significance of the IDX market reaction towards these events, this study will compare and assess differences in stock prices, abnormal returns, cumulative abnormal returns, and trading volume activity as key indicators of market reactions before and after the mentioned events. Additionally, this study will utilize the same event study methodology to assess the market efficiency of the IDX. The stock prices will serve as indicators of market efficiency. The analysis will rely on secondary data collected from the IDX website and Yahoo Finance. The data analysis process will involve conducting a normality test using the Shapiro-Wilk test. For data with a normal distribution, a paired sample t-test will be employed for comparison testing. Conversely, for data that does not follow a normal distribution, a paired sample Wilcoxon signed rank test will be employed for the comparison. Both normality testing and comparison testing will be carried out using the IBM SPSS Statistics v27 software.

The event window, the period during which market reactions will be analyzed, spans 21 days, comprising 10 days before the event, the event date, and 10 days after the event. This chosen event window duration allows for capturing market reactions while avoiding confounding influences from other events. The population for this study includes all companies operating in the energy and food and beverage sectors listed on the IDX. The sample comprises a total of 53 energy companies and 57 food and beverage companies were selected using the non-probability sampling technique based on the following criteria:

1. Companies listed on the IDX operating in the energy and food and beverage sectors have conducted an Initial Public Offering (IPO) at least one year before the event window period.
2. Companies listed on the IDX operating in the energy and food and beverage sectors with actively traded stocks, i.e., stocks with prices above Rp. 50 during the event window period.

Results

Descriptive Statistics of the Energy Sector

Table I shows that the mean values of average stock prices and ATVA increased after event 1, i.e., by 4.1% and 73.5%, respectively. However, the mean values of AAR and CAR decreased, both by 14.1%. Moreover, the highest maximum values for average stock prices, AAR, CAR, and ATVA, occurred after event 1, i.e., Rp. 46,827.50, 0.0493, 0.49305, and 0.11310308, respectively. Conversely, the lowest minimum value for ATVA occurred before event 1, i.e., 0.00000006. The lowest minimum values for average stock prices, AAR, and CAR occurred after event 1, i.e., Rp. 50.50, −0.06441, and −0.64406, respectively.

Table I. Energy Sector—Event 1

	N	Minimum	Maximum	Mean
Average stock price before	53	52.40	46,250.00	2,307.2708
Average stock price after	53	50.50	46,827.50	2,402.4719
AAR before	53	−0.05683	0.04837	−0.0121665
AAR after	53	−0.06441	0.04931	−0.0145364
CAR before	53	−0.56833	0.48366	−0.1216651
CAR after	53	−0.64406	0.49305	−0.1453640
ATVA before	53	0.00000006	0.03949905	0.0049089471
ATVA after	53	0.00000016	0.11310308	0.0085186552

Table II shows that the mean values of average stock prices and ATVA increased after event 2, i.e., by 5.7% and 2.95%, respectively. However, the mean values of AAR and CAR decreased, both by 54.1%. The highest maximum value for average stock prices occurred after event 2, i.e., Rp. 36,560.00. On the other hand, the highest maximum values for AAR, CAR, and ATVA occurred before event 2, i.e., 0.02146, 0.21465, and 0.03257141, respectively. The lowest minimum values for average stock prices, ATVA, AAR, and CAR, occurred before event 2, i.e., Rp. 55.20, 0, −0.06946, and −0.69464, respectively.

Table II. Energy Sector—Event 2

	N	Minimum	Maximum	Mean
Average stock price before	53	55.20	34,710.00	2,250.0100
Average stock price after	53	57.20	36,560.00	2,377.7970
AAR before	53	−0.06946	0.02146	−0.0164602
AAR after	53	−0.05918	0.01265	−0.0253582
CAR before	53	−0.69464	0.21465	−0.1646016
CAR after	53	−0.59181	0.12648	−0.2535816
ATVA before	53	0	0.03257141	0.00429077
ATVA after	53	0.00000053	0.03150596	0.00441732

Table III shows that the mean value of average stock prices increased after event 3, i.e., by 3.1%. On the contrary, the mean values of ATVA, AAR, and CAR decreased by 15.2% and 57.6% respectively. The highest maximum value for average stock prices occurred after event 3, i.e., Rp. 35,185.40. However, the highest maximum values for ATVA, AAR, and CAR occurred before event 3, i.e., 0.02562111, 0.04313, and 0.43127, respectively. The lowest minimum values for average stock prices and ATVA occurred before event 3, i.e., Rp. 53.50 and 0, respectively. Conversely, the lowest minimum values for AAR and CAR occurred after event 3, i.e., −0.06767 and −0.67673, respectively.

Table III. Energy Sector—Event 3

	N	Minimum	Maximum	Mean
Average stock price before	53	53.50	32,680.00	2,275.3815
Average stock price after	53	54.00	35,185.40	2,345.7408
AAR before	53	−0.04995	0.04313	−0.0125906
AAR after	53	−0.06767	0.01393	−0.0198489
CAR before	53	−0.49946	0.43127	−0.1259059
CAR after	53	−0.67673	0.13928	−0.1984892
ATVA before	53	0	0.02562111	0.00331709
ATVA after	53	0.00000021	0.01805265	0.00281369

Descriptive Statistics of the Food and Beverage Sector

Table IV shows the mean values of the average stock prices experienced an increase after event 1, i.e., by 4.0%. In contrast, the mean values of both average abnormal returns (AAR) and cumulative abnormal returns (CAR) experienced a decrease of 30.4%. Moreover, the mean value of the average trading volume activity (ATVA) also decreased by 11.0%. Furthermore, for the maximum values, the highest maximum value of average stock prices occurred after event 1, i.e., by Rp. 11,491.24. However, the highest maximum values of AAR, CAR, and average ATVA occurred before event 1, i.e., by 0.08968, 0.89684, and 0.09403500, respectively. On the other hand, for the minimum values, the lowest minimum value of the ATVA occurred before event 1, i.e., by 0.00000061. Conversely, the lowest minimum values of average stock prices, AAR, and CAR occurred after event 1, i.e., by Rp. 74.70, −0.05494, and −0.54945, respectively.

Table IV. Food and Beverage Sector—Event 1

	N	Minimum	Maximum	Mean
Average stock price before	53	83.50	10,441.99	1,716.9174
Average stock price after	53	74.70	11,491.24	1,785.5815
AAR before	53	−0.05437	0.08968	−0.0148647
AAR after	53	−0.05494	0.03103	−0.0193858
CAR before	53	−0.54368	0.89684	−0.1486474
CAR after	53	−0.54945	0.31027	−0.1938581
ATVA before	53	0.00000061	0.09403500	0.00360612
ATVA after	53	0.00000159	0.06618424	0.00322369

Table V shows the mean values of the average stock prices experienced an increase after event 2, i.e., by 2.7%. On the contrary, the mean value of the ATVA decreased by 39.9%. Moreover, the mean values of both AAR and CAR also decreased by 32.5%. Furthermore, for the maximum values, the highest maximum values of average stock prices, ATVA, AAR, and CAR, occurred before event 2, i.e., at Rp. 12,115.60, 0.00946, 0.09462, and 0.05044238, respectively. On the other hand, for the minimum values, the lowest minimum values of average stock prices, ATVA, AAR, and CAR occurred after event 2, i.e., at Rp. 68.30, 0.00000056, −0.04948, and −0.49485, respectively.

Table V. Food and Beverage Sector—Event 2

	N	Minimum	Maximum	Mean
Average stock price before	53	68.60	12,115.60	2,018.6094
Average stock price after	53	68.30	11,296.67	2,074.0120
AAR before	53	−0.04056	0.00946	−0.0163572
AAR after	53	−0.04948	0.00912	−0.0216729
CAR before	53	−0.40563	0.09462	−0.1635717
CAR after	53	−0.49485	0.09123	−0.2167286
ATVA before	53	0.00000114	0.05044238	0.0025066390
ATVA after	53	0.00000056	0.02195861	0.0015057639

Table VI shows the mean values of the average stock prices experienced a decrease of 9.2%, ATVA decreased by 29.1%, and both AAR and CAR decreased by 27.0% after event 3. Furthermore, for the maximum values, the highest maximum values of average stock prices and ATVA occurred before event 3, i.e., by Rp. 11,607.50 and 0.02205793, respectively. However, the highest maximum values of AAR and CAR occurred after the announcement of event 3, i.e., by 0.01679 and 0.16791, respectively. On the other hand, for the minimum values, the lowest minimum value of average stock prices occurred before the announcement of event 3, i.e., by Rp. 66.00. Conversely, the lowest minimum values of ATVA, AAR, and CAR occurred after the announcement of event 3, i.e., by 0.00000036, −0.04878, and −0.48778, respectively.

Table VI. Food and Beverage Sector—Event 3

	N	Minimum	Maximum	Mean
Average stock price before	53	68.60	12,115.60	2,018.6094
Average stock price after	53	68.30	11,296.67	2,074.0120
AAR before	53	−0.04056	0.00946	−0.0163572
AAR after	53	−0.04948	0.00912	−0.0216729
CAR before	53	−0.40563	0.09462	−0.1635717
CAR after	53	−0.49485	0.09123	−0.2167286
ATVA before	53	0.00000114	0.05044238	0.0025066390
ATVA after	53	0.00000056	0.02195861	0.0015057639

Comparative Analysis of the Energy Sector

Based on the comparative test results presented in Table VII, H_1a, H_1b and H_1c for the energy sector are accepted, indicating there is a significant difference in stock prices in the energy sector on the IDX before and after events 1, 2, and 3. These comparative test results support the findings of a previous study by Nerlinger and Utz (2022), which showed that the geopolitical conflict between Russia and Ukraine has led to significant differences in stock prices of the energy sector in 75 countries worldwide, indicated by a positive and statistically significant value of the cumulative average abnormal return (CAAR), where a positive and significant CAAR value reflects an increase in the stock prices of the energy sector.

Table VII. Energy Sector—Stock Price

Event	z-value	p-value
Event 1	−2.063b	0.039
Event 2	−2.257b	0.024
Event 3	−2.678b	0.007

Based on the comparative test results presented in Table VIII, H_2b and H_2c for the energy sector are accepted, but H_2a is rejected, indicating there is a significant difference in AR in the energy sector on the IDX before and after events 2 and 3, but no significant difference before and after event 1. These comparative test results support the findings of previous study by Huka and Kelen (2022) as well as the findings of previous research by Kusumaet al. (2022), which showed no significant difference in AR in the energy sector on the IDX before and after the announcement of Russia’s invasion of Ukraine on February 24 2022.

Table VIII. Energy Sector—Abnormal Returns

Event	t-value	p-value
Event 1	0.849	0.399
Event 2	4.320	<0.001
Event 3	3.860	<0.001

Based on the comparative test results presented in Table IX, H_3b and H_3c for the energy sector are accepted, but H_3a is rejected, indicating there is a significant difference in CAR in the energy sector on the IDX before and after events 2 and 3, but no significant difference before and after event 1. These comparative test results support the findings of previous study by Ahmedet al. (2022), which showed no significant difference in CAR in the energy sector of the STOXX Europe 600 index before and after the onset of the geopolitical crisis between Russia and Ukraine, marked by the announcement of Russia’s recognition of the independence of two pro-Russian separatist regions in eastern Ukraine, namely Donetsk and Luhansk, on Monday, the 21^st of February 2022.

Table IX. Energy Sector—Cumulative Abnormal Returns

Event	t-value	p-value
Event 1	0.849	0.399
Event 2	4.320	<0.001
Event 3	3.860	<0.001

Based on the comparative test results presented in Table X, H_4a and H_4c for the energy sector are accepted, but H_4b is rejected, indicating there is a significant difference in TVA in the energy sector on the IDX before and after events 1 and 3, but no significant difference before and after event 2. These comparative test results support the findings of a previous study by Amelya (2022), which showed a significant difference in TVA in the oil and gas sector in 7 countries, namely Saudi Arabia, the United States, Canada, the United Arab Emirates, Nigeria, Kuwait, and Norway, before and after the announcement of Russia’s invasion of Ukraine.

Table X. Energy Sector—Trading Volume Activity

Event	z-value	p-value
Event 1	−3.368b	<0.001
Event 2	−0.828b	0.408
Event 3	−2.288b	0.022

Comparative Analysis of the Food and Beverage Sector

Based on the comparative test results presented in Table XI, H_1b for the food and beverage sector is accepted, but H_1a and H_1c are rejected, indicating there is a significant difference in stock prices in the food and beverage sector on the IDX before and after events 2, but no significant difference in stock prices before and after event 1 and 3. These comparative test results support the findings of a previous study by Herninta and Rahayu (2021), which showed significant differences in stock prices of the food and beverage sector on IDX before and after the announcement of the first positive COVID-19 cases in Indonesia, which reflects the IDX’s market reaction.

Table XI. Food and Beverage—Stock Price

Event	z-value	p-value
Event 1	−0.506b	0.613
Event 2	−2.072b	0.038
Event 3	−0.020b	0.984

Based on the comparative test results presented in Table XII, H_2a, H_2b and H_2c for the food and beverage sector are accepted, indicating there is a significant difference in AR in the food and beverage sector on the IDX before and after events 1, 2 and 3. These comparative test results support the findings of a previous study by Seoet al. (2013), which showed a significant difference in AR in the food and beverage sector before and after food safety-related events.

Table XII. Food and Beverage—Abnormal Returns

Event	z-value	p-value
Event 1	−2.117b	0.034
Event 2	4.338	<0.001
Event 3	3.203	0.002

Based on the comparative test results presented in Table XIII, H_3a, H_3b and H_3c for the food and beverage sector are accepted, indicating there is a significant difference in CAR in the food and beverage sector on the IDX before and after events 1, 2 and 3. These comparative test results support the findings of a previous study by Seoet al. (2013), which showed a significant difference in CAR in the food and beverage sector before and after food safety-related events.

Table XIII. Food and Beverage—Cumulative Abnormal Returns

Event	z-value	p-value
Event 1	−2.117b	0.034
Event 2	4.338	<0.001
Event 3	3.203	0.002

Based on the comparative test results presented in Table XIV, H_4c for the food and beverage sector is accepted, but H_4a and H_4b are rejected, indicating there is a significant difference in TVA in the food and beverage sector on the IDX before and after events 1, but no significant difference in TVA before and after event 1 and 2. These comparative test results support the findings of a previous study by Zuhroh and Putri (2021) as well as the findings of previous research by Jatmiko (2021), which showed no significant difference in TVA in the food and beverage sector on the IDX before and after the announcement of the first positive COVID-19 cases in Indonesia.

Table XIV. Food and Beverage—Trading Volume Activity

Event	z-value	p-value
Event 1	−0.314b	0.754
Event 2	−0.401b	0.688
Event 3	−2.483b	0.013

Discussion

The presented comparative test results indicate that Russia-Ukraine war-related events, namely event 1 (the announcement of Russia’s invasion of), event 2 (the announcement of an oil import embargo on Russia by the European Union on the 31^st of May 2022), and event 3 (the announcement of Ukraine’s first wheat export ship departure from the port of Odesa on the 1^st of August 2022), triggered market reactions across the energy and food and beverage sectors on the Indonesia Stock Exchange (IDX).

In the energy sector, the hypotheses (H_1a, H_1b, H_1c) concerning stock prices were accepted, indicating a significant difference in stock prices before and after all three events. This suggests that these events prompted significant reactions within the market, likely due to their potential to disrupt global energy markets and supply chains. Additionally, abnormal returns (AR) and cumulative abnormal returns (CAR) in the energy sector (H_2b, H_2c, H_3b, H_3c) were found to be significantly different before and after events 2 and 3, but not before and after event 1. This suggests that events related to the oil import embargo and Ukraine’s wheat export elicited a stronger market reaction compared to the announcement of Russia’s invasion of Ukraine. Moreover, trading volume activity (TVA) in the energy sector (H_4a, H_4c) demonstrated a significant difference before and after events 1 and 3, but not event 2. This suggests that events related to Russia’s invasion and Ukraine’s first wheat export provoked a more pronounced market reaction compared to the oil import embargo event.

In the food and beverage sector, the results showed that the hypothesis (H_1b) regarding stock prices was accepted for event 2, indicating a significant difference in stock prices before and after the announcement of the oil import embargo. However, hypotheses H1a and H1c were rejected, indicating no significant difference in stock prices before and after events 1 and 3 in this sector. This suggests that the food and beverage sector displayed a significant reaction to the oil import embargo event, possibly due to the embargo’s direct effect on trade relationships and supply chains, particularly those related to oil, which might have triggered a ripple effect on other sectors, including food and beverages. AR and CAR for the food and beverage sector (H_2a, H_2b, H_2c, H_3a, H_3b, H_3c) were found to be significantly different before and after all three events. This indicates that these three events prompted a strong reaction within the market. Regarding TVA in the food and beverage sector, there was a significant difference before and after event 3 (H_4c), while no significant differences were observed before and after events 1 and 2. This suggests that Ukraine’s first wheat export elicited a more pronounced market reaction in comparison to the other two events.

Collectively, the comparative test results highlight the varying reactions observed within both the energy and food and beverage sectors on the IDX to Russia-Ukraine war-related events. The energy sector consistently displayed strong reactions across all three Russia-Ukraine war-related events, as evidenced by significant changes in stock prices, abnormal returns, cumulative abnormal returns, and trading volume activity. This indicates a uniform reaction to Russia-Ukraine war-related events. In contrast, the food and beverage sector exhibited a reaction that was more specific to each event, primarily reflected in abnormal and cumulative abnormal returns. This implies that the food and beverage sector’s reaction is linked to event-specific factors associated with the Russia-Ukraine war-related events, such as supply chain disruptions and shifts in international trade dynamics due to trade embargoes. Nevertheless, despite the varying reactions of the energy sector and the food and beverage sector to different Russia-Ukraine war-related events, there is still a commonality in their more pronounced reaction towards event 3.

Conclusion

The findings of this study reveal that Russia-Ukraine war-related events had an impact on the Indonesia Stock Exchange (IDX), triggering both immediate and subsequent market reactions across the energy and food and beverage sectors. Of particular note is the diverse nature of these reactions across various events within these sectors. A more pronounced market reaction was observed following event 3 (the announcement of Ukraine’s first wheat export ship departure from the port of Odesa on 1st August 2022) compared to event 2 (the announcement of an oil import embargo on Russia by the European Union) and event 1 (the announcement of Russia’s invasion of Ukraine). This difference could be attributed to event 3 being a significant diplomatic breakthrough since the war’s start, involving multiple countries worldwide. Russia’s blockade of Ukrainian ports for months necessitated intervention from numerous nations to enable Russia’s participation in the wheat and grain export agreement with Ukraine, facilitated by Turkey and the United Nations. In contrast, event 2 represents the European Union’s (EU) intervention effort to halt the Russia-Ukraine war, involving solely EU member countries, and event 1 involved only Russia and Ukraine. Given these findings, it is evident that Russia-Ukraine war-related events involving multiple countries or entities exert a greater impact on the energy and food and beverage sectors within the IDX, leading to more pronounced market reactions. Additionally, the findings of this study also reveal that the IDX exhibits a level of semi-strong form market efficiency. This is evident from the differences in stock prices within the IDX before and after Russia-Ukraine war-related events, indicating adjustments to stock prices in response to newly available information concerning these events. Consequently, stock prices in the IDX reflect all publicly available information.

The implications of these findings span across multiple domains. Investors can capitalize on these insights to make well-informed decisions that effectively manage risk and maximize returns. Simultaneously, policymakers can utilize these insights to tailor policies that address sector-specific vulnerabilities and opportunities stemming from geopolitical events. This targeted approach enhances both risk management and overall economic stability. Correspondingly, financial institutions can harness these insights to refine their risk management strategies and provide more accurate investment recommendations, thereby navigating uncertainties with greater resilience. Furthermore, this study serves as a catalyst for further exploration. Future studies could delve into a more comprehensive examination of sub-sectors within the energy and food and beverage sectors, dissecting their distinct responses to geopolitical events. Additionally, extending the analysis to encompass a wider spectrum of events from diverse geopolitical contexts or additional sectors could yield deeper insights into the varying market reactions observed. In conclusion, this study sheds light on the interplay between geopolitical events, market reactions within the IDX, and the market efficiency of the IDX. The findings of this study contribute to a deeper understanding of how geopolitical events shape financial markets, especially the IDX, offering opportunities for more informed decision-making, strategic adaptation, and risk mitigation in an ever-evolving economic landscape.