The launch effect of thematic indices: do themes move markets?

Stock market indices play a crucial role in monitoring and depicting diverse sectors of the economy. Traditionally, basket indices such as the Nifty 50 and Sensex reflect the overall market scenario. However, the evolution of investment strategies has given rise to thematic indices that focus on specific themes or trends, offering a more targeted perspective on emerging economic patterns. These indices are designed to capture longer-term structural trends, encompassing macro-economic, geopolitical, and technological shifts (Blitz, 2021). For example, themes such as capital markets, sustainability, or technology bring together firms connected by a shared economic idea rather than by sectoral classification. Notably, these indices can also be purposefully designed with narrowly defined objectives, extending their impact beyond financial performance to influence corporate social behaviour (Mehrotra et al., 2026).

Among the thematic indices in the Indian capital market, the Nifty CM stands out as a benchmark index representing the performance of the capital market ecosystem. The index was launched on September 9, 2024, to track the performance of the Nifty 500 stocks representing the capital market theme. The stocks covered are those that fall under the stock broking, clearing houses, wealth managers, depositories, asset management, and other capital market-related services. In addition to meeting the criteria of basic industry classification, the index comprises the top 20 stocks with the highest half-year average free-float market capitalisation. While the index is rebalanced quarterly, its constituents are reconstituted semi-annually. Another notable thematic index is the BSE CAPINS, which offers broader coverage by tracking companies in the capital market as well as the insurance sector. These companies are selected based on free-float market capitalisation from the BSE 500 Index. This index was rolled out on October 9, 2024. The relevance of these two indices is underscored by the expansion of India’s financial markets and insurance sector, driven by increased retail participation and innovations in financial technology.

Previous studies show that thematic index announcements can affect investor sentiment (Sadeghi, 2008), change market expectations (Sherif and Lusyana, 2017), and cause visible shifts in trading activity around the announcement dates (Bammi, 2013; Suresha et al., 2022). This makes it important to examine their impact on the Indian capital market. In this context, the objective of the present study is to examine the market’s reaction to the introduction of two capital market–themed indices: the Nifty CM and the BSE CAPINS. By investigating whether the launch of these indices affects the returns and performance of their underlying constituent stocks, the study sheds light on the nature and direction of the market response. The analysis is grounded in the semi-strong form of the Efficient Market Hypothesis (EMH), which holds that prices adjust quickly to public announcements, making any impact of the index launches observable in the immediate market response. This analysis offers valuable insights into how investors perceive thematic indices and their broader influence on investment behaviour in emerging markets like India. It also provides a basis for policymakers to improve transparency and strengthen regulatory effectiveness in capital markets.

The study focuses on market dynamics surrounding firms that are included in newly launched indices, drawing upon two strands of existing literature: index inclusion effects and new index launch effects – spanning both thematic and non-thematic index events. Seminal works such as those by Shleifer (1986) and Harris and Gurel (1986) provide foundational evidence of positive market reactions to index inclusion announcements, though primarily within the context of broad-based indices. Addressing this gap, thematic-index studies such as Sadeghi (2008) on the Malaysian Shariah Index and Mehrotra et al. (2026) on Japan’s MSCI WIN provide useful evidence on thematic index regimes outside the U.S. These insights establish a relevant conceptual foundation for analysing thematic index launches in India.

The present study contributes to the literature by showing how markets respond to thematic index introductions in an emerging economy. By comparing the Nifty CM and BSE CAPINS indices, the analysis shows that sector composition and theme-specific expectations can lead to contrasting abnormal returns, highlighting the informational role of thematic indices. The findings extend event-study research by demonstrating that such launches generate asymmetric, short-window effects shaped by investor anticipation.

The remainder of this paper is organised as follows. First, the related literature is reviewed, and hypotheses are developed. Next, the data and methodology are presented, and the empirical results are discussed. Finally, conclusions are drawn, and directions for future research are outlined.

The literature on index effects begins by identifying the core mechanisms through which index events influence stock prices. Extant research broadly categorises these mechanisms into demand-based, liquidity-based, and information-based hypotheses, each offering a different explanation for why stocks may experience abnormal returns around index announcements or index launches.

The price pressure hypothesis (Harris and Gurel, 1986) suggests that index events create brief demand shocks that temporarily move prices away from their fundamental value, with these effects fading quickly as they do not convey new information. In contrast, the liquidity hypothesis (Amihud and Mendelson, 1986; Beneish and Whaley, 1996; Hegde and McDermott, 2003) argues that index membership can improve trading conditions by attracting more investors, increasing turnover, and narrowing bid–ask spreads, which lowers trading costs and may lead to more persistent price effects. Beyond these demand and liquidity-based views, the information-signalling hypothesis (Denis et al., 2003; Dhillon and Johnson, 1991; Jain, 1987) suggests that index inclusion is interpreted as a signal of firm credibility, prompting investors to update their expectations about future performance and resulting in more lasting valuation changes. Taken together, these hypotheses explain why price reactions to index events may be either temporary or long-lasting.

In the context of thematic index launches such as the Nifty CM and BSE CAPINS indices, these frameworks become particularly relevant. Thematic indices not only trigger mechanical rebalancing but also shape investor perceptions of the long-term outlook for specific sectors or themes (Blitz, 2021). Given these dynamics, market reactions to index-related events have been extensively examined, and the empirical literature broadly falls into two streams. Firstly, studies examine how markets respond when individual stocks are added to existing indices. Secondly, research explores the market’s reaction to the launch of new indices. Both streams investigate how these events influence investor behaviour, stock price movements, and overall market efficiency.

Research on the addition of stocks to major indices, dating back to the 1980s, has uncovered consistent patterns in price shifts and trading volumes. Shleifer (1986) initiates this exploration by examining whether stock demand curves slope downward, focussing on S&P 500 inclusions from 1966 to 1983. Using an event study with a (−20, +20) event window around the announcement date, he reveals that stocks included after September 1976 experience a positive abnormal return of 2.8%, reflecting a notable market reaction. These price gains persist for at least ten trading days, suggesting a sustained response driven by increased demand. This evidence suggests that index inclusion significantly boosts stock prices. In a related study, Harris and Gurel (1986) investigated whether these price surges endure or fade. Their analysis of S&P 500 additions from 1973 to 1983, using a tighter event window (−10, +30), reveals a 3% price increase upon announcement. However, this uptick reverses within two weeks, supporting their price pressure hypothesis. The findings highlight the transient nature of some price effects, prompting deeper questions about the forces behind these movements.

Chen et al. (2004) extended this inquiry by exploring the role of investor attention in S&P 500 inclusions. Their study uncovers a permanent 3% abnormal return for added stocks, suggesting that inclusion enhances a stock’s visibility. The results attribute the sustained price impact to heightened investor attention. Broadening the scope to global markets, Li and Sadeghi (2009) examined inclusions in the S&P/CITIC 300 index in China from October 2004 to August 2007. They report a positive cumulative abnormal return for newly added stocks, consistent with Chen et al.’s (2004) findings of lasting price effects. The findings suggest that positive market responses to index inclusion also occur in emerging markets.

Shifting focus to sustainability indices, Cheung (2011) analyses additions to the Dow Jones Sustainability World Index (DJSWI). He finds that stocks added to the index exhibit minimal immediate changes in returns or risk following the announcement. However, a temporary cumulative abnormal return (CAR) of 0.33% emerges over the first four days post-inclusion, which subsequently dissipates. This observation aligns with Harris and Gurel’s (1986) price pressure insights while highlighting the distinct behaviour of sustainability-focused indices, where short-lived effects may reflect unique investor priorities.

Contrary to this, Oberndorfer et al. (2011) report that inclusion in sustainability indices may lead to unfavourable investor responses. Examining German firms added to the DJSI STOXX and DJSI World between 1999 and 2002 using a (−5, +5) event window, they find no significant abnormal returns for DJSI STOXX inclusions but a significant negative market reaction for the DJSI World. They argue that investors may view global sustainability inclusion as a signal of higher compliance costs, increased disclosure requirements, and possible restrictions on managerial flexibility, particularly in the more internationally prominent DJSI World. Continuing the global perspective, Febrian et al. (2013) analyse inclusions in the Jakarta Islamic Index (JII) and conventional indices like Kompas 100 and LQ45 in Indonesia from February 2007 to August 2011. Using a compact event window (−5, +5), they find that added stocks generate significant positive abnormal returns across both Islamic and conventional indices. This consistency with Li and Sadeghi’s (2009) findings reinforces the idea that market enthusiasm for index inclusions remains robust, regardless of regional or methodological differences in index construction. In the context of Islamic indices, Kassim et al. (2017) examined the FTSE Bursa Malaysia EMAS Shariah Index (FBMESI) from 2007 to 2014. Using a (AD−60, CD+60) event window, they found significant and permanent positive abnormal returns for inclusions. They attribute this to increased investor awareness and confidence from stricter Shariah screening, showing that the value of inclusion is highly dependent on the credibility and market perception of the index itself.

Hayward (2018), examining the Dow Jones North America Sustainability Index, supports these temporary effects, finding that additions have a statistically significant but short-lived impact on stock prices. The results show positive cumulative abnormal returns for up to five trading days after the announcement. Her study suggests that sustainability commitment may be regarded as an investor expectation rather than a factor that generates a positive market reward. Recent evidence from emerging markets, particularly India, shows an even weaker response. Goyal and Soni (2025) find no significant positive abnormal returns for firms added to the S&P BSE 100 ESG index. Their analysis using a market-model event study approach to measure investor reactions around the announcement day reinforces the finding that the market does not reward sustainability-index inclusion. More recent evidence from Barontini and Gioja (2025) analyses the rebalancing of MSCI ESG indices and finds that firms added to these indices experience positive abnormal returns. Their findings also indicate that these price effects may persist for several trading days, suggesting that ESG index rebalancing events convey informational value to the market. Overall, the growing body of ESG research points to a consistent trend. Sustainability index inclusion typically results in weak and diminishing price effects, even in markets where small short-term gains are observed. Table 1 presents key findings from the literature on the effects of index inclusion on stock prices in different countries.

The rise of thematic stock indices, especially those focused on areas such as Shariah compliance and sustainability, has prompted varied market responses, impacting the valuation and tradability of included stocks. Sadeghi (2008) examines the launch of the Shariah-compliant Index (SI) by Bursa Malaysia on April 17, 1999. A short-term negative market reaction is observed using a (−15, +15) day window around the index launch, with a Mean Cumulative Abnormal Return (MCAR) of −3.39% between day 0 and day 15, driven by investor scepticism and subsequent sell-offs. Over a longer timeframe, by day 135, the included stocks exhibited a significant recovery, with an MCAR of 21.73% and an 110.22% increase in trading volume. This shift reflects growing demand from a new group of investors, driving share prices upward and turning MCARs positive in the long term. Building on this strand, Sherif and Lusyana (2017) analyse the launch of the Indonesia Shariah Stock Index (ISSI) on May 12, 2011. They employ a (−20, +20) day event window to assess performance around the launch. In contrast to Sadeghi (2008)’s short-term negative response, their results show a positive CAR of +0.160% on day 20. These positive returns persist beyond the event window, indicating sustained investor confidence in the stocks added to the ISSI. This divergence from Sadeghi’s (2008) findings suggests that market reactions to Shariah-compliant index launches may vary by region or investor sentiment, prompting further investigation into contextual factors.

With a focus on sustainability-themed indices, Bammi (2013) examines the introduction of the BSE GREENEX, India’s first green index, announced on February 22, 2012. The results show that 70% of the included firms experience a decline in stock returns on the announcement day, with a statistically significant negative mean abnormal return. With only 30% of firms exhibiting positive returns, the findings suggest that Indian investors may not yet place significant emphasis on sustainability factors in their investment decisions. Bammi (2013) observes a short-term negative reaction consistent with Sadeghi (2008)’s results, while also identifying a lack of prolonged positive impact, implying that sustainability indices may face particular hurdles in certain markets. Further narrowing the scope to the Indian ESG indices, Suresha et al. (2022) investigated the inclusion of stocks in the BSE100 ESG and Nifty100 ESG indices. Their results show a significant decline in average abnormal return for BSE100 ESG stocks on the announcement day, consistent with Bammi’s (2013) findings. In contrast, Nifty100 ESG stocks exhibit a slight but statistically insignificant increase. In a similar vein, BSE100 ESG stocks record a significantly negative cumulative average abnormal return, whereas for Nifty100 ESG stocks, it is found to be positive but statistically insignificant. This mixed outcome extends Bammi’s (2013) insights, suggesting that investor reactions to ESG index inclusions in India vary by index and may reflect differing levels of market maturity or investor priorities.

In light of these mixed outcomes in ESG index studies, recent research shows that the launch of a thematic index can influence both stock returns and firm behaviour as companies position themselves for potential inclusion. Mehrotra et al. (2026) examined Japanese firms from 2013 to 2020 surrounding the introduction of the MSCI Empowering Women Index (WIN). They found that firms near the inclusion threshold increase women’s workforce participation by 3.5%–7.3% annually, mainly by recruiting more women into management roles, without harming short-term operating performance. This response is driven by greater customer awareness and expectations of higher institutional ownership, which trigger a positive stock market reaction, including +0.62% CAR around the announcement and +1.19% CAR from the announcement to the effective rebalancing date. The study concludes that well-designed thematic indices can encourage corporate social behaviour and improve gender diversity. Table 2 presents key findings from the literature on the effects of index launch on stock prices in different countries.

Market reactions, as documented in the literature from early studies in developed markets to recent work on thematic indices in Asia, are shown to be diverse and complex. Extant literature shows that index inclusion generally results in positive stock price movements, whereas the impact of new index launches varies with investor sentiment, market conditions, and thematic focus. This study contributes to the evolving discourse by examining the stock market response to the launch of the Nifty CM and BSE CAPINS indices in an emerging market like India. This domain remains relatively underexplored, despite the country’s expanding financial markets and rising investor engagement with thematic investment strategies. The capital-market theme is directly influenced by interest-rate expectations, monetary policy, and financial-sector regulation. A focused thematic set helps avoid confounding effects and enables a clearer assessment of theme-specific market responses.

According to the semi-strong form of the EMH, if the index launch does not provide any new or value-relevant public information, stock prices should not exhibit a statistically significant reaction. Based on this theoretical foundation, the following hypotheses are proposed:

The study employs the event study methodology described by MacKinlay (1997) to examine the stock market response to the launch of the (a) Nifty CM Index on September 9, 2024, and (b) BSE CAPINS Index on October 9, 2024. A three-day event window (−1, +1) is taken to observe stock performance prior to and subsequent to the event dates. The study focuses on short-run effects for methodological and theoretical reasons. Short event windows provide a cleaner assessment of the market’s response by reducing the influence of unrelated developments and improving causal attribution to the index launch (Campbell et al., 1997). Restricting the size of the event window reduces the likelihood of interference from closely timed announcements and enhances the precision of the estimated effects (Aït-Sahalia et al., 2012; Chen et al., 2024). Moreover, the semi-strong form of EMH suggests that markets react swiftly to public information, reinforcing the use of shorter windows to capture immediate price adjustments. Also, in the case of longer windows, the likelihood of confounding event increases, making it difficult to isolate the effect of the index launch. The analysis also excludes trading volume, as its measurement requires additional controls to distinguish information effects from normal trading patterns (Richardson et al., 1986). Given these considerations, a short event window provides a more reliable basis for assessing the immediate market reaction.

In this analysis, expected returns are estimated using the Market Model, with the Nifty 50 index serving as the market benchmark. The choice of the Market Model is justified by the observation that more complex multifactor models offer only marginal improvements in reducing the variance of abnormal returns (MacKinlay, 1997). To enhance the accuracy and statistical reliability of the expected return estimates, a 120-day estimation window is employed, which also helps mitigate potential biases arising from pre-event market trends (Dyckman et al., 1984).

The sample for the study comprises 15 stocks from the Nifty CM Index and 22 stocks from the BSE CAPINS Index, based on their composition as of the respective launch dates (refer to  Appendix,  Table A1, and  Table A2 for the complete lists). The daily adjusted closing prices of the stocks have been sourced from the CMIE Prowess database. The use of adjusted closing prices accounts for corporate actions such as dividends and stock splits, thereby offering a more accurate reflection of changes in stock value surrounding the event.

The study uses the market model framework along with parametric and non-parametric test statistics. The analytical framework is outlined in Equations (1)–(11).

The Market Model used to estimate the expected returns is specified as follows:

where,

• R_iŧ = Return of stock i at time ŧ

• R_mŧ = Return of market index (Nifty 50) at time ŧ

• α_i = Intercept for stock i

• β_i = Slope coefficient for stock i

• ϵ_iŧ = Random error term generating an abnormal return for security i at time ŧ

• ŧ= (1 … T), time index for estimation period, where T = 120 days.

• i = (1 … N), stock index

The stock’s daily actual return is computed as the percentage change in its closing price from one trading day to the next. The expected returns on the sample stocks were estimated using the ordinary least squares regression (OLS) method. OLS is a convenient and efficient method for estimating market model parameters (MacKinlay, 1997). After estimating the expected returns, the abnormal return for a stock is calculated by taking the difference between its actual return and its expected return for each day during the three-day event window. The average abnormal returns (AAR) for all firms are calculated by averaging the abnormal returns across the sample for each day during the event window (−1, +1). Additionally, the Cumulative Average Abnormal Returns (CAAR) have been obtained by aggregating average abnormal returns, i.e. over the three-day event window.

The study employs parametric test statistics to examine whether the AARs during the event period are statistically different from zero. Specifically, the study applies the conventional cross-sectional t-test, computes the test statistic for CAARs, and integrates Brown and Warner’s crude dependence adjustment to address the issue of event clustering. To ensure the robustness of the results, the study also conducted the generalised sign test, a non-parametric test based on the methodology proposed by Cowan (1992).

The conventional cross-sectional t-statistic is calculated for each day within the event window by dividing the AAR by its cross-sectional standard deviation.

The time index for the event window (t₁, t₂) is t = (t₁ … t₂), for t > T.

As outlined by MacKinlay (1997), the test statistic for CAARs is calculated as

AARs have been summed up across the event window (t_1, t₂) to arrive at CAARs, while the variance of CAAR is computed as:

where, σ²_i (t_1, t₂) is the variance of each stock during the event period computed as (t₂₋t₁ +1).

σ² $ϵ$_i. The sample variance measure of σ² $ϵ$_i has been obtained from market model regression in the estimation window.

Calendar clustering occurs when multiple events take place around the same time, leading to overlapping event windows and correlated abnormal returns. This inflates the variance of measures such as AARs, thereby reducing the accuracy of the tests. To address this issue, Brown and Warner (1980) suggest estimating the standard deviation using time-series data from the estimation period. Accordingly, a crude dependence adjustment is applied as follows:

where AAR_t and AAR_ŧ are the cross-sectional averages on each day in the event window and estimation period, respectively.

where,

In the t-test for abnormal performance in the event window (t₁, t₂) interval, the numerator of the test statistic (⁠$λ3$⁠) becomes:

The denominator is the same as shown in $λ3$⁠, divided by (t₂ − t₁+1)^1/2.

The generalised sign test, as presented by Cowan (1992), examines whether the number of stocks with positive cumulative abnormal returns (CARs) during the event window exceeds the expected frequency under normal market conditions. The null hypothesis is rejected if the proportion of firms with positive abnormal returns in the event window is significantly higher than that observed during the T-day estimation period. The expected frequency is determined based on the proportion of positive abnormal returns in the estimation window.

where, S_iŧ = 1 if AR_it > 0, 0 otherwise; and the generalised sign test statistic is:

In this context, $w$ represents the count of stocks within the event window where the cumulative abnormal return, CAR_i (t₁, t₂), is positive. The test statistic is based on a normal approximation of the binomial distribution with parameter p.

The results reveal distinct patterns in both AAR and CAAR for the two index launches, with the Nifty CM Index demonstrating largely negative abnormal returns, while the BSE CAPINS Index reflects a favourable market reaction. The analysis delves into the underlying data to better understand the nature of these initial investor reactions. This section examines the results of the computed test statistics for the Nifty CM and BSE CAPINS indices, highlighting index-specific effects. It also discusses the broader implications of these findings.

The launch of the Nifty CM Index appears to trigger a negative market reaction, as indicated by abnormal returns estimated using the market model. As presented in Table 3, the three-day event window (−1, +1) shows a negligible negative AAR of −0.100% on the day preceding the launch, suggesting no significant anticipatory trading activity. On the event day, however, the AAR declines sharply to −1.237%, followed by a continued negative return of −0.641% on the subsequent day, resulting in a CAAR of −1.978% over the event window (Figure 1).

Table 3 shows that the conventional T-statistic is significant at the 5% level on day 0 and remains significant at the 10% level on day +1 during the three-day event window. However, after applying a crude adjustment for clustering, the results continue to indicate a negative effect on each day of the window, though without statistical significance. In Table 4, the test statistic for CAARs is found to be statistically significant at the 10% level, underscoring a sustained negative response overall during the event window.

Table 4 presents the results of the generalised sign test, which evaluates whether the three-day event window reflects a consistent trend in abnormal returns across stocks. The test statistic of −1.938 leads to rejection of the null hypothesis at the 10% level. The negative sign indicates that a greater proportion of firms experienced negative cumulative abnormal returns (CARs) during the event window compared to the estimation period, implying a negative market reaction to the index launch.

The launch of the BSE CAPINS Index elicits a positive market response, particularly on the day before and the day of the announcement. As shown in Table 5, during the three-day event window (−1, +1), AAR on the day before the launch stands at 0.764%, reflecting mild optimism surrounding the announcement. On the event day, AAR peaks at 1.932%, indicating a strong and enthusiastic market reaction. However, this was followed by a decline on the day after the launch, with AAR falling to −0.468%. Overall, the event window yields a CAAR of 2.229%, as illustrated in Figure 2.

The results indicate that the cross-sectional T-statistic is highly significant at the 1% level on the event day, while the post-event day (+1) shows significance at the 10% level, although with a reversal in sign. However, after applying the crude adjustment to account for potential cross-sectional correlation, the significance levels diminish. Despite this, Brown and Warner’s (1980) statistic remains significant at the 5% level on the event day, suggesting a positive market reaction to the launch (Table 5).

Table 6 shows that the CAAR is positive and significant at the 1% level. The generalised sign test for the three-day event window also rejects the null hypothesis at the 1% level. The positive sign of the test statistic indicates that the proportion of firms with positive CARs during the event window exceeds the proportion of negative abnormal returns observed in the estimation period, reflecting an overall positive market reaction to the launch of the BSE CAPINS Index.

The study reveals a significant negative market response following the launch of the Nifty CM, evidenced by a 1.237% decline in abnormal returns on the event day. Under the semi-strong form of the EMH, this suggests that the market quickly incorporated the public information about the index launch into prices. The observed pattern aligns with the classic “buy the rumour, sell the news” behaviour. The informed investors, anticipating the positive implications of index inclusion, might have acted on expectations ahead of the public announcement, driving up the prices during the pre-event period. Once the information became public, the market promptly adjusted as investors booked profits, resulting in a decline that continued throughout the event period. This behaviour is consistent with the findings of Brunnermeier (2001) and Kadan et al. (2015), who document similar trading patterns during anticipation-driven events.

This short-term reaction aligns with the price pressure hypothesis, which suggests that temporary buying and selling around index events can move prices briefly without affecting fundamentals (Harris and Gurel, 1986). The sharp fall in AAR on day 0 and the further decline on day +1 may reflect investors unwinding their pre-event positions and creating temporary downward pressure. This behaviour is also consistent with the information cost hypothesis, which states that greater public availability of theme-specific information reduces informed traders’ advantage and leads them to close positions (Merton, 1987).

A comparable short-term negative market reaction is also reported by Sadeghi (2008), who examined the launch of a Shariah-compliant index in Malaysia. The study attributes the decline to investor scepticism and initial selloffs. These results can also be viewed through the lens of information-asymmetry theory. Haider (2025) shows that thematic index announcements introduce new public signals about constituent firms, which abruptly reduce the informational advantage of informed traders. When this public information arrives at the moment of index launch, private information gains disappear, prompting traders to unwind pre-event positions. This mechanism, consistent with semi-strong EMH, reinforces the “sell the news” pattern observed for Nifty CM, as prices adjust quickly to the new theme-specific information.

Grau-Vera and Rubio (2024) also demonstrate that thematic indices generally exhibit no significant risk-adjusted performance (alpha), as their constituents tend to be small, weakly profitable, and highly sensitive to adverse economic shocks. The negative reaction to Nifty CM likely reflects a market realisation of these underlying risks, where the capital market’s theme is perceived as inherently cyclical and vulnerable to downturns. Moreover, under EMH, investors might consider possible downsides of index inclusion, such as stricter regulations and higher compliance costs linked to being part of a sector-focused index. These factors may reduce investors’ expectations of future returns, thereby contributing to the negative abnormal returns recorded during the event window.

In contrast, the launch of the BSE CAPINS Index generated a strong positive market reaction on the event day. This market behaviour may be influenced by investor optimism toward capital markets and insurance, as these sectors are seen as key beneficiaries of financial development and policy support in India. Thematic composition of the index appeared to attract investor attention, contributing to an upward revaluation of constituent stocks around the event day. The positive reaction to BSE CAPINS may also reflect the presence of insurance stocks, which are considered relatively stable and supported by long-term structural growth. This created a more favourable investor perception than the Nifty CM, which may have been seen as more sensitive to short-term market conditions and influenced by prior investor expectations. The market’s swift response to this public information aligns with the semi-strong form of EMH. Although prices declined on the third day due to profit-booking, this reflects how markets adjust to evolving investor expectations. Despite the short-term dip, the overall market reaction during the three-day event window remained positive. The initial positive reception of the BSE CAPINS Index can be contrasted with the findings of Suresha et al. (2022) concerning ESG indices in India. They observed a significant decline in BSE100 ESG AARs on the announcement day, but only a minor, insignificant rise for Nifty100 ESG stocks. This mixed outcome from Suresha et al. (2022), alongside the divergent reactions to Nifty CM and BSE CAPINS, underscores that investor sentiment and market responses to new thematic indices can vary significantly depending on the specific theme, perceived benefits, and current market conditions.

To provide a broader context, the reactions to the Nifty CM and BSE CAPINS launch events can be compared with those observed for other thematic indices in India. For instance, the Nifty India Tourism Index generated strong optimism when it was rolled out, and an Exchange-Traded Fund (ETF) was created to track it. However, the ETF’s early performance was modest and volatile, showing that market enthusiasm for new themes does not always translate into significant immediate returns (Motilal Oswal Financial Services Limited, 2024).

The launch of the Nifty CM Index and the subsequent decline in stock prices highlight key risks for retail investors. Unlike institutional players with access to advanced insights, retail investors often rely on basic market cues. Many investors may have entered the market anticipating gains following the launch, but experienced losses as prices declined. It serves as a reminder for the investors to adopt a thoughtful approach, guided by informed decision-making. The launch effects of capital market-related thematic indices also have broader implications for market transparency and efficiency. They can improve information flow, analyst coverage, and investor attention, but may also trigger short-term stock price volatility and speculative trading, especially in markets with high information asymmetry (Haider, 2025). Beyond immediate price reactions, they may reshape market linkages, volatility spillovers, and portfolio risk management (Majumder, 2025). Again, with the introduction of the BSE CAPINS Index, a similar trend was observed. While the event day saw a sharp rise in prices, profit-booking led to a quick reversal. Retail investors who bought during the surge may have ended up with unexpected losses. This pattern shows that markets often react in anticipation of announcements and correct soon afterwards. It also supports the literature suggesting that thematic indices tend to attract retail investors who are influenced by the recent performance and appealing stories. Funds built on niche themes often perform poorly after launch, once the initial hype fades (Blitz, 2021). These observations align with broader evidence cautioning retail investors about the volatility of Indian equity markets. This highlights the importance of retail investors exercising caution, focussing on long-term goals, and conducting proper research rather than relying on initial sentiment.

Given the influence of thematic indices on corporate decisions and market reactions (Mehrotra et al., 2026), policymakers should ensure greater transparency and clearly defined inclusion criteria. They should also review how index performance is reported, particularly the use of synthetic historical data that can artificially inflate returns (Blitz, 2021). Thematic indices backed by institutional or government-linked investors can shape corporate behaviour by encouraging firms to adopt socially beneficial practices such as improving gender diversity or strengthening environmental sustainability (Haider, 2025; Mehrotra et al., 2026). The varied responses to thematic indices in India and other emerging markets highlight the complexity of investor behaviour. Policymakers should consider these factors when regulating thematic products to ensure that the regulations achieve their purpose and support market stability.

This study examines the short-run market impact of the launch of the Nifty CM Index and the BSE CAPINS Index. By analysing stock price movements, it assesses whether the introduction of these indices influences investor behaviour and overall market dynamics. A three-day event window is employed to capture the market’s immediate response while reducing the effect of unrelated external factors. The study is guided by the semi-strong form of the EMH, which predicts that markets react quickly to public announcements. The focus on short-window abnormal returns tests whether index launch information is immediately incorporated into prices, thereby linking the empirical approach to established efficiency theory.

The findings indicate that the introduction of the Nifty CM Index leads to short-term fluctuations in stock returns but does not produce a sustained positive impact. Investors exhibit brief trading adjustments following the launch, yet broader market trends remain largely unchanged. In contrast, the launch of the BSE CAPINS Index elicits a strong positive response on the event day. Although there is a slight decline in returns following the announcement, the cumulative performance over the event window suggests an overall favourable market reception. The positive reaction to BSE CAPINS likely reflects the relative stability of its insurance constituents, in contrast to Nifty CM, which may be viewed as more sensitive to short-term market conditions and influenced by prior investor sentiment. Given the behavioural differences observed across themes, effective oversight by policymakers remains crucial for safeguarding overall market stability.

While the study provides meaningful insights into how markets react to the launch of thematic indices, it is subject to certain limitations. The analysis relies primarily on parametric tests and focuses on a short-term event window, without considering factors such as trading volume and market liquidity. The short event window limits the study’s ability to capture longer-term behavioural patterns. Since early reactions may differ from medium- or long-term responses, the findings may not fully generalise to broader time horizons or varying market conditions. Future research could build on these findings by exploring the long-term effects of index launches, incorporating measures of investor sentiment, and examining the impact of periodic index reconstitution. It could also explore spillovers across sectors, market linkages, and hedging strategies linked to thematic indices.

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