




































INDIAN JOURNAL OF FINANCE AND BANKING 15(1) (2025), 10-18 

10 

 

                         FINANCE AND BANKING 
                                                             IJFB VOL 15 NO 1 (2025) P-ISSN 2574-6081  E-ISSN 2574-609X     

           Journal homepage: https://www.cribfb.com/journal/index.php/ijfb 

               Published by American Finance & Banking Society, USA 

TESTING SEMI-STRONG FORM MARKET EFFICIENCY: THE 

CASE OF INDIAN PHARMA SECTORS                                                            

        
 Janvi Joshi (a)1    Krunal Joshi (b)   

 

(a) Associate Professor, SJPI-GTU, Gandhinagar, India; E-mail: janvijoshi1982@gmail.com 
(b) Associate Professor, SJPI-GTU, Gandhinagar, India; E-mail: krunaljo@gmail.com 

 

 
A R T I C L E I N F O 
 

 

Article History: 
 

Received: 16th March 2025 

Reviewed & Revised: 16th March 

to 14th July 2025 

Accepted: 16th July 2025 

Published: 20th July 2025 

 
Keywords: 

 

Aggressiveness Index, Semi-Strong Market  

Efficiency, Tobin's Q 

 
JEL Classification Codes: 

 

G12, G14 

 

Peer-Review Model:  

 

External peer review was done through  

double-blind method. 
 

 

  

 
A B S T R A C T 
 
The Efficient Market Hypothesis (EMH) holds that security prices fully reflect all publicly available 

information, leaving no scope for abnormal gains from fundamental or technical analysis. Despite 

extensive research, the semi-strong form of EMH remains inconclusive in developing markets. This study 

examines the degree of semi-strong-form efficiency in the Indian pharmaceutical industry. It explores 

how effectively the stock prices of leading firms, Sun Pharmaceutical, Dr. Reddy’s Laboratories, Zydus 

Life Sciences, Cipla, and Torrent Pharmaceuticals, reflect publicly accessible information. The analysis 

covers five years from 2018–19 to 2022–23 and utilizes the Core Competency Strategic Intent (CCSI) 

model to assess the relationship between firm fundamentals and market valuation. Tobin's Q (market 

value to book value) and employee cost as a percentage of sales are considered representative indicators 

of valuation and strategic intent. Empirical results show that stock prices in this sector respond more 

rapidly to short-term, quantifiable factors such as sales performance. In contrast, long-term strategic 

elements exert a weaker effect on valuation. A numerical evaluation of Tobin's Q across firms indicates 

varying degrees of mispricing, suggesting both overvaluation and undervaluation. Overall, the study 

finds that the Indian pharmaceutical sector exhibits only partial adherence to the semi-strong form of 

market efficiency, as investors appear to prioritize immediate financial outcomes over comprehensive 

strategic fundamentals. 

 
 

© 2025 by the authors. Licensee American Finance & Banking Society, USA. This article is an open-

access article distributed under the terms and conditions of the Creative Commons Attribution (CC 

BY) license (http://creativecommons.org/licenses/by/4.0/).                           

 

INTRODUCTION 

The efficiency of financial markets remains a central concern in finance and investment research. The valuation of securities 

depends on investors' rational interpretation of publicly available information, as the accuracy and timeliness of that data 

guide decisions to buy or sell. According to the Efficient Market Hypothesis (EMH), as introduced by Fama (1970), stock 

prices should instantaneously incorporate all available information, ensuring that no investor can consistently earn abnormal 

returns. However, the practical validity of this hypothesis, particularly its semi-strong form, remains debated in both 

developed and emerging markets. In emerging economies like India, where market information asymmetry and behavioral 

biases persist, the question of whether public announcements and firm fundamentals are accurately reflected in stock prices 

remains a significant scientific question. 

Recent studies (e.g., Kumar & Raju, 2021; Mishra & Taneja, 2022; Gupta et al., 2023; Dutta & Sharma, 2024) 

have highlighted that market responses to financial disclosures in India vary considerably across sectors, suggesting 

incomplete efficiency. Research in developed markets has also revealed mixed evidence (e.g., Chen et al., 2021; Fernandes 

& Costa, 2022), indicating that even mature markets exhibit deviations from perfect informational efficiency. Moreover, 

advancements in algorithmic trading and digital transparency (Patel & Singh, 2023; Ali & Rehman, 2025) have reshaped 

how information influences price adjustments, underscoring the need to re-examine market efficiency in sector-specific 

contexts, such as the pharmaceutical industry. 

This study tests the semi-strong form of the EMH in the Indian pharmaceutical sector—an industry characterized 

by high research intensity, stringent regulation, and global competitiveness. Using data from five major pharmaceutical 

companies over five financial years (2018–19 to 2022–23), the research employs the Core Competency Strategic Intent 

(CCSI) model to assess the relationship between market valuation and strategic performance indicators. The central 

scientific problem addressed is whether publicly available financial and strategic information is fully and promptly 

                                                      
1Corresponding Author: ORCID ID: 0000-0003-3632-8975 

© 2025 by the authors. Hosting by American Finance & Banking Society. Peer review under the responsibility of the American Finance & Banking Society, 

USA. https://doi.org/10.46281/ijfb.v15i1.2715 
 

To cite this article: Joshi, J., & Joshi, K. (2025). TESTING SEMI-STRONG FORM MARKET EFFICIENCY: THE CASE OF INDIAN PHARMA 

SECTORS. Indian Journal of Finance and Banking, 15(1), 10-18. https://doi.org/10.46281/ijfb.v15i1.2715 

http://creativecommons.org/licenses/by/4.0/)
http://creativecommons.org/licenses/by/4.0/)
https://www.openaccess.nl/en
https://doi.org/10.46281/ijfb.v15i1.2715
https://orcid.org/0000-0003-3632-8975
https://orcid.org/0000-0001-8313-8248


Joshi & Joshi, Indian Journal of Finance and Banking 15(1) (2025), 10-18 

 

11 

integrated into stock prices. The study aims to determine the extent to which the market reflects firm fundamentals and to 

identify deviations that indicate potential over- or undervaluation of securities. 

  

LITERATURE REVIEW 

Market efficiency has remained one of the most debated concepts in financial economics for over five decades. Rooted in 

the Efficient Market Hypothesis (EMH) proposed by Fama (1970), the theory asserts that security prices fully reflect all 

available information, leaving no room for investors to achieve abnormal returns consistently. However, subsequent 

empirical studies have revealed variations in efficiency over time, across regions, and by sector, particularly in emerging 

economies such as India (Poshakwale, 1996; Gupta & Gupta, 1997; Malkiel, 2003). The Indian stock market has undergone 

a significant transformation following the establishment of the National Stock Exchange in 1992, which introduced 

electronic trading and improved transparency, yet the persistence of anomalies continues to challenge the EMH framework 

(Deshpande, 2017; Gupta & Narwal, 2022). 

Empirical investigations of market behavior have traditionally relied on weak-form and semi-strong form 

efficiency tests. Studies employing serial correlation and runs tests reported that the Bombay Stock Exchange (BSE) 

exhibited significant deviations from weak-form efficiency, suggesting that past prices could still predict future movements 

(Poshakwale, 1996; Worthington & Higgs, 2004). Similar evidence of inefficiency was observed in other developing 

markets, including Bangladesh (Ahmed, 2021), Pakistan (Habibah et al., 2017), and Saudi Arabia (Khoj & Akeel, 2020), 

where price randomness was undermined by investor sentiment and delayed information diffusion. In contrast, research on 

mature markets, such as the United States and Western Europe, indicates a closer approximation to informational efficiency 

(Malkiel, 2003; Chen et al., 2021). 

At the sectoral level, the pharmaceutical industry provides a distinct context for testing market efficiency, given its 

high reliance on innovation, regulatory compliance, and strategic investment decisions. McKinsey & Company (2020) 

identified the Indian pharmaceutical sector as the third-largest in the world, contributing significantly to global exports and 

employment. This industry's complex structure—balancing R&D intensity and market regulation—creates both information 

asymmetry and speculative opportunities. Studies by Mukhopadhyay (2007) and Dutta and Sharma (2024) identified 

macroeconomic variables such as exchange rate fluctuations, foreign investment inflows, and inflation as strong predictors 

of stock returns, implying that market prices may not fully incorporate all relevant fundamentals. 

From a behavioral finance perspective, the persistence of “rational bubbles” (Mukhopadhyay, 2007) demonstrates 

that even rational investors may participate in overpricing, anticipating that others will continue to drive prices upward. This 

phenomenon aligns with the "greater fool" theory, in which investment decisions are driven more by market expectations 

than by intrinsic value. Such patterns are evident in high-volatility sectors like pharmaceuticals, where policy shifts, patent 

approvals, and global health crises have amplified speculative behavior (Kalamen et al., 2025). 

Further evidence from global studies suggests that market irrationality differs by region and sector. Gupta and Basu 

(2011) documented weak-form inefficiency across Asian markets, while Fernandes and Costa (2022) highlighted limited 

semi-strong form efficiency even in developed economies. More recent analyses by Patel and Singh (2023) and Ali and 

Rehman (2025) argue that algorithmic trading has improved information absorption rates but has not eliminated 

inefficiencies, particularly where fundamental data are complex or delayed. 

Within the Indian context, sectoral research remains limited. Existing studies have focused mainly on aggregate 

indices rather than industry-specific analysis. The pharmaceutical sector's unique combination of innovation-driven growth 

and strategic human capital investment offers fertile ground for testing semi-strong market efficiency. Employee expenses, 

which constitute a significant share of operational costs, can serve as a proxy for strategic intent. At the same time, Tobin's 

Q ratio (Brainard & Tobin, 1968) provides a measure of market valuation relative to asset replacement value. The Core 

Competency Strategic Intent (CCSI) framework (Hamilton et al., 1998) integrates these indicators, allowing for a structured 

assessment of whether the market adequately prices firm-level fundamentals. 

Recent studies (Gupta et al., 2023) emphasize that the post-pandemic environment has magnified the gap between 

short-term performance indicators and long-term strategic fundamentals. Firms that invest aggressively in innovation and 

workforce expansion often experience delayed market recognition, suggesting partial inefficiency in the semi-strong sense. 

Thus, examining the linkage between Tobin's Q and employee expenses provides a meaningful avenue for assessing how 

efficiently public information is processed in the Indian pharmaceutical market. 

In summary, while global and regional evidence supports the semi-strong form of EMH only partially, empirical 

validation in industry-specific contexts remains scarce. The Indian pharmaceutical sector, with its high strategic intensity 

and macroeconomic importance, offers a compelling platform for investigating this theoretical gap. 

Therefore, the purpose of this study is to empirically evaluate the semi-strong form of market efficiency in the 

Indian pharmaceutical sector by analyzing the relationship between firms’ market-to-book value ratios (Tobin’s q) and 

strategic intent, measured through employee expenses as a percentage of total sales, using the Core Competency Strategic 

Intent (CCSI) model. The following hypotheses are proposed for this study: 

 

H₀: There is a positive and statistically significant association between a firm’s market-to-book value ratio (Tobin’s q) and 

its level of strategic intent, represented by the aggressiveness index (employee expenses as a percentage of sales). 

 

MATERIALS AND METHODS 

The present study examines the behaviour of stock prices in the pharmaceutical sector of India to determine whether they 

follow a random pattern or are influenced by significant factors, such as the Tobin's Q ratio. The aim is to ascertain whether 



Joshi & Joshi, Indian Journal of Finance and Banking 15(1) (2025), 10-18 

 

12 

the market adequately incorporates crucial information when valuing pharmaceutical stocks. Additionally, the study seeks 

to pinpoint instances of overvaluation or undervaluation by assessing the Company's investment aggressiveness, which 

reflects its efforts to enhance its fundamental metrics. Data analysis was conducted using publicly available information on 

the market-to-book ratio (Tobin's q) and the proportion of employee expenses to sales. The study spans five financial years, 

from 2018-19 to 2022-23, and focuses on five major pharmaceutical companies: Sun Pharma, Dr. Reddy's, Zydus Life 

Sciences, Cipla, and Torrent. Various metrics, including sales, employee cost-to-sales ratio, price-to-book ratio (Tobin's q), 

and the average market price of the stock, were analysed to assess their relationships. A summary of the data for each 

Company used in the study is provided in Table 1. Multiple correlation analysis was used to assess the strength of 

relationships among the variables discussed earlier.  The average stock price for each Company during the study period was 

used for analysis. 

 

RESULTS AND DISCUSSIONS 

Of the five firms analyzed, four demonstrated a strong positive correlation between annual Revenue and market valuation 

(see Table 2). For instance, Cipla exhibited a correlation coefficient of 0.925 between Revenue (in crores) and its average 

stock price, suggesting that the market responded to readily available data such as revenue figures, which aligns with the 

assumptions of semi-strong market efficiency. However, when evaluating the relationship between the Market-to-Book 

Ratio (here, Tobin's q) and the firm's strategic posture (measured by the Aggressiveness Index), the correlation was negative, 

indicating a lack of alignment between the two variables. In Cipla's case, the correlation between Tobin's Q and strategic 

intent stood at -0.690. 

In several instances, while there was a strong positive link between the average market price and Revenue, the 

association between Tobin's Q and strategic intent was clearly negative. For example, Sun Pharma's stock price-to-revenue 

correlation was 0.867, while its strategic intent-to-q ratio reflected a weaker negative association (r = -0.165). This pattern 

suggests that market participants tend to rely more on simple, accessible financial indicators, such as Revenue, rather than 

on more abstract or delayed signals, such as strategic direction or internal firm intent. 

 

Table 1. Data of selected sample companies (FY 2018-19 to 2022-23) 

 
Firm Name Financial Year Revenue (in 

Crores) 

Market-to-Book 

Ratio (MV/BV) 

Staff Expenses (in Crores) Staff Cost as a Percentage 

of Revenue" 

Sun Pharma 2018-19 26,415 5.32 1625 0.062 

2019-20 29,065 5.03 1571.34 0.054 

2020-21 32,837 3.46 1702.77 0.052 

2021-22 33,498 5.73 1805.9 0.054 

2022-23 38,654 8.93 2000.78 0.052 

Dr Reddy 2018-19 14,281 2.75 1843 0.129 

2019-20 15,448 3.29 1931.9 0.125 

2020-21 17,517 3.32 2030.2 0.116 

2021-22 19,047 4.25 2270.1 0.119 

2022-23 21,545 3.71 2434.6 0.113 

Zydus Life 

Science 

2018-19 11,904 5.01 26.48 0.002 

2019-20 13,165 4.14 30.91 0.002 

2020-21 14,253 2.43 31.68 0.002 

2021-22 14,403 3.54 163.83 0.011 

2022-23 15,265 2.7 163.56 0.011 

Cipla 2018-19 15,155 3.1 1785.94 0.118 

2019-20 16,362 2.7 1839.84 0.112 

2020-21 17,131 1.96 1911.08 0.112 

2021-22 19,159 3.3 1703.58 0.089 

2022-23 21,763 3.65 1729.16 0.079 

Torrent 

 

 

 

 

2018-19 5,982 4.64 826.07 0.138 

2019-20 7,672 6.59 1014.06 0.132 

2020-21 7,939 6.52 1061.76 0.134 

2021-22 8,004 7.13 1097.12 0.137 

2022-23 8,508 7.46 1097.93 0.129 

Source: Authors’ compilation 

 

Table 2 illustrates that the correlation between Revenue (in Crores) and stock prices is generally stronger than that 

between the Market-to-Book Ratio and strategic investment behaviour, which is intended to capture future potential or 

intrinsic firm value. 

Even if strategic intent does not exhibit a positive correlation with Tobin's Q within the same accounting period, 

its effects may be more visible in subsequent periods. Table 3 explores this by analyzing the relationship between the 

Aggressiveness Index and Tobin's Q with a one-year time lag. The results indicate that firms like Sun Pharma and Torrent 

show a meaningful positive association, while others continue to display weak or negative relationships. 

Based on these observations, the null hypothesis stating a positive association between Tobin's Q and strategic 

intent is rejected. The evidence supports the view that investors operating under bounded rationality may prioritize easily 

interpretable figures, such as Revenue or profits, while undervaluing more complex strategic indicators. This highlights a 

market tendency to price stocks based on straightforward and publicly visible information, potentially overlooking more 

nuanced or future-oriented signals embedded in strategic decisions. 



Joshi & Joshi, Indian Journal of Finance and Banking 15(1) (2025), 10-18 

 

13 

The observed influence likely applies across all firms in the sample, as a significant segment of the pharmaceutical 

sector is subject to external factors, including global economic shifts, supply-and-demand imbalances, and unforeseen events 

such as natural disasters. As previously mentioned, such discrepancies may lead to stock mispricing, creating arbitrage 

opportunities. The Core Competency Strategic Intent (CCSI) model provides a valuable framework for analyzing a firm's 

fundamentals and assessing whether its stock is undervalued or overvalued. This presents a potential extension of the study. 

 

Table 2. Interrelationship Matrix of Key Financial Indicators by Firm 

 
    Revenue  Market-to-

Book  

Staff Cost as a Percentage of Revenue 

(Strategic Intent) 

Sun Pharma Market-to-Book 0.636 
  

Staff Cost as a Percentage of Revenue -0.793 -0.165 
 

Market Price (average of stock) 0.867 0.832 -0.408 

Dr Reddy Market-to-Book 0.757 
  

Staff Cost as a Percentage of Revenue -0.913 -0.623 
 

Market Price (average of stock) 0.749 0.819 -0.823 

Zydus Life 

Science 

Market-to-Book -0.896 
  

Staff Cost as a Percentage of Revenue 0.718 -0.368 
 

Market Price (average of stock) 0.547 -0.425 0.731 

Cipla Market-to-Book 0.576 
  

Staff Cost as a Percentage of Revenue -0.976 -0.690 
 

Market Price (average of stock) 0.925 0.537 -0.933 

Torrent Market-to-Book 0.984 
  

Staff Cost as a Percentage of Revenue -0.712 -0.659 
 

Market Price (average of stock) 0.822 0.819 -0.395 

Source: Authors’ compilation 

 

Table 3. Correlation Results of the Aggressiveness Index of 2018-19 with Tobin's Q of 2020-21 

 

Source: Authors’ compilation 

 

Currently, the model includes only one strategic intent indicator, Staff Cost as a Percentage of Revenue, but it holds 

flexibility for future enhancement. Additional variables such as customer retention rates or advertising-to-revenue ratios 

could also be integrated into the model and tested alongside the Market-to-Book Ratio (Tobin’s q). This would allow for a 

more comprehensive evaluation of strategic positioning and market valuation. 

Figures 1 through 4 track the movement of Tobin's Q and the Aggressiveness Index (used here to denote strategic 

intent based on staff expenditure) over several financial years. In these visuals, the Aggressiveness Index is standardized to 

1, while the Market-to-Book Ratio reflects the average market valuation per share across the corresponding fiscal year. Both 

axes are uniformly scaled to ensure consistency and ease of comparison. Yearly average values were used to examine the 

co-movement of Tobin's Q and strategic intent indicators, as shown in Table 4 for the 2018–19 to 2022–23 period. These 

transition plots (Figures 1–4) are instrumental for investors in evaluating how firm positioning evolves and assist in 

identifying both current and prospective valuation scenarios. The framework is especially valuable for medium-term 

investment planning. For instance, Figure 1 highlights that both Torrent and Sun Pharma significantly ramped up their staff-

related investments to scale operations, with Torrent also achieving a relatively higher Market-to-Book Ratio. Other firms, 

by contrast, trailed in either metric. 

 

Table 4. Computed Values for Visualizing Tobin's Q and Aggressiveness Index over Time 

 
Financial Year Firm 

Name 

Revenue 

(in Crores) 

Market-to-

Book Ratio 

Staff Cost as 

a Percentage 

of Revenue 

Aggressiveness 

Index 

Staff Expenses (in Crores) 

2018-19 Sun 

Pharma 

26415 5.32 0.06 0.68 1625 

Dr Reddy 14281 2.75 0.13 1.44 1843 

Zydus 11904 5.01 0.00 0.02 26.48 

Cipla 15155 3.1 0.12 1.31 1785.94 

Torrent 5982 4.64 0.14 1.54 826.07 

Average 
  

0.09 
  

2019-20 Sun 

Pharma 

29065 5.03 0.05 0.63 1571.3 

Dr Reddy 15448 3.29 0.13 1.47 1931.9 

Zydus 13165 4.14 0.00 0.03 30.91 

Cipla 16362 2.7 0.11 1.32 1839.84 

Company Correlation between Tobin's Q and Aggressiveness Index 

Sun Pharma 0.95 

Dr Reddy 0.16 

Zydus -0.13 

Cipla 0.52 

Torrent 0.88 



Joshi & Joshi, Indian Journal of Finance and Banking 15(1) (2025), 10-18 

 

14 

Torrent 7672 6.59 0.13 1.55 1014.06 

Average 
  

0.09 
  

2020-21 Sun 
Pharma 

32837 3.46 0.05 0.62 1702.77 

Dr Reddy 17517 3.32 0.12 1.40 2030.2 

Zydus 14253 2.43 0.00 0.03 31.68 

Cipla 17131 1.96 0.11 1.34 1911.08 

Torrent 7939 6.52 0.13 1.61 1061.76 

Average 
  

0.08 
  

2021-22 Sun 
Pharma 

33498 5.73 0.05 0.66 1805.9 

Dr Reddy 19047 4.25 0.12 1.45 2270.1 

Zydus 14403 3.54 0.01 0.14 163.83 

Cipla 19159 3.3 0.09 1.08 1703.58 

Torrent 8004 7.13 0.14 1.67 1097.12 

Average 
  

0.08 
  

2022-23 Sun 

Pharma 

38654 8.93 0.52 3.05 20078 

Dr Reddy 21545 3.71 0.11 0.66 2434.6 

Zydus 15265 2.7 0.01 0.06 163.56 

Cipla 21763 3.65 0.08 0.47 1729.16 

Torrent 8508 7.46 0.13 0.76 1097.93 

Average 
  

0.17 
  

Source: Authors’ compilation 

 

As seen in Figure 2, Torrent displayed a notably stronger Aggressiveness Index than its peers, several of which 

lagged on both indicators or excelled in only one. Given its fundamental positioning in the model, Torrent stands out as a 

strong growth stock. In Figure 3, Torrent and Dr. Reddy consistently maintained favorable values for both strategic intent 

and valuation, reinforcing their suitability for medium-term investment. Conversely, Sun Pharma appears to have 

streamlined its operations, as reflected in a lower Tobin's Q. This could imply upside potential over the next 2–3 years. 

Figure 4 indicates that both Torrent and Dr. Reddy continued to lead in workforce investment, an indicator of 

business expansion. A prudent fund manager should recognize that internal management, equipped with confidential 

strategic insights, likely responds to evolving market demands through deliberate staffing and investment decisions. With 

this in mind, both Torrent and Dr. Reddy, supported by robust fundamentals, are well-positioned to attract medium-term 

investors. Sun Pharma, too, made notable improvements in its Aggressiveness Index. 

Following the onset of the COVID-19 pandemic in 2021, there was a surge in activity within the pharmaceutical 

space. As reflected in Figure 5, the market has recalibrated its valuation of Sun Pharma accordingly. This figure also reveals 

that firms generally realigned their Tobin's Q values post-pandemic. Among them, Torrent emerges as undervalued, offering 

a compelling case for medium-term investment consideration. 

 

 
 

Figure 1. CCSI Matrix for 2018-19 FY 

 

 

 

0

1

2

3

4

5

6

0 0.3 0.6 0.9 1.2 1.5 1.8M
V

/B
V

Aggresivness Index

2018-19 



Joshi & Joshi, Indian Journal of Finance and Banking 15(1) (2025), 10-18 

 

15 

 
 

Figure 2. CCSI Matrix for 2019-20 FY 

 

 

 

 

 

 
 

Figure 3. CCSI Matrix for 2020-21 FY 

 

 

 

 

0

1

2

3

4

5

6

7

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8M
V

/B
V

Aggresivness Index

2019-20 

0

1

2

3

4

5

6

7

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2

M
V

/B
V

Aggresivness Index

2020-21 

14,253 Zydus

17,517 Dr reddy

7,939 Torrent

17,131 Cipla

32837 Sun Pharma 



Joshi & Joshi, Indian Journal of Finance and Banking 15(1) (2025), 10-18 

 

16 

 
 

Figure 4. CCSI Matrix for 2021-22 FY 

 

Figure 5. CCSI Matrix for 2022-23 FY 

CONCLUSIONS 

The primary purpose of this study was to evaluate the semi-strong form of the Efficient Market Hypothesis (EMH) in the 

context of the Indian pharmaceutical industry, using publicly available information, including earnings announcements and 

strategic indicators. The empirical findings demonstrate that the Indian pharmaceutical market exhibits only partial 

efficiency. Stock prices tend to respond more strongly to immediately quantifiable variables, such as sales, rather than to 

strategic investments reflected in employee expenditures. This suggests that the market still favors short-term, tangible 

outcomes over long-term value creation factors. 

The analysis of Tobin's Q and the Aggressiveness Index indicates a weak or negative correlation between firm 

aggressiveness and market valuation. In contrast, the positive correlation between sales and market prices suggests that 

investors respond more consistently to observable performance indicators. Among the firms analyzed, Torrent 

Pharmaceuticals and Dr. Reddy’s Laboratories displayed stronger fundamentals and consistent growth, positioning them as 

relatively undervalued and potentially favorable options for medium-term investors. 

0

1

2

3

4

5

6

7

8

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2M
V

/B
V

Aggresivness Index

2021-22 

33,498 Sun pharma

14,403  Zydus 19,159 Cipla

Dr. reddy 

8,004 Torrent

0

1

2

3

4

5

6

7

8

9

0 0.5 1 1.5 2 2.5 3 3.5 4M
V

/B
V

Aggresivness Index

2022-23



Joshi & Joshi, Indian Journal of Finance and Banking 15(1) (2025), 10-18 

 

17 

This paper makes a unique contribution by applying the Core Competency Strategic Intent (CCSI) model to assess 

the linkage between human capital investment and market valuation in the Indian pharmaceutical sector. The findings 

enhance theoretical understanding of market semi-efficiency and provide a practical decision-making framework for 

portfolio and fund managers seeking to identify undervalued securities in information-sensitive markets. 

From a managerial perspective, the results underscore the importance of transparent, timely disclosure of fundamental 

performance metrics to enhance market confidence and valuation accuracy. However, the study is limited to five years 

(2018–2023) and a small set of firms, which constrains the generalizability of its results. 

Future research could extend this analysis to other high-growth sectors, integrate additional indicators such as R&D 

expenditure and brand valuation, and employ time-series econometric models to capture dynamic efficiency patterns. A 

broader comparative study across industries and post-pandemic market phases could provide deeper insights into the 

evolving nature of informational efficiency in emerging economies like India. 

 

 
Author Contributions: Conceptualization, J.J. and K.J.; Methodology, J.J.; Software, J.J.; Validation, J.J.; Formal Analysis, J.J. and K.J.; Investigation, 

J.J.; Resources, J.J.; Data Curation, J.J.; Writing – Original Draft Preparation, J.J. and K.J.; Writing – Review & Editing, J.J. and K.J.; Visualization, J.J.; 
Supervision, K.J.; Project Administration, J.J.; Funding Acquisition, J.J. and K.J. Authors have read and agreed to the published version of the manuscript. 

Institutional Review Board Statement: Ethical review and approval were waived for this study, due to that the research does not deal with vulnerable 
groups or sensitive issues. 

Funding: The authors received no direct funding for this research. 

Acknowledgments: The authors sincerely thank the anonymous reviewers for their thoughtful comments and constructive suggestions that greatly 
improved the quality of this paper. 

Informed Consent Statement: Informed consent was obtained from all subjects involved in the study. 

Data Availability Statement: The data presented in this study are available on request from the corresponding author. The data are not publicly available 
due to restrictions. 

Conflicts of Interest: The authors declare no conflict of interest.                                                                                                                                                                                                                                   

 

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