1 Introduction
The pharmaceutical industry is concerned with a special type of risk because only about 10% of developed drugs are finally placed on the market and about 20% of them allow the breakeven point to be achieved (CMR, 2007/2008; Datamonitor, 2008; Nickisch et al., 2009). Besides, the productivity of pharmaceutical research has been decreasing over the last decades (Kannt & Wieland, 2016). Product development in this industry is often outsourced, which creates many different kinds of risk, as for example knowledge losses which result from disintegration of undertakings involved in product development (Lowman et al., 2012). Sumbramanian and Dugar (2012) also emphasize the fact of outsourcing activities connected with drug discovery to countries where costs are lower, with India or China being notable examples. Such a system requires sharing knowledge and experience and risks being used by others. Korzeniowska (2020) points out the risk of the inappropriate choice of a consulting firm whose mistakes affect the producer. However, the author also admits that outsourcing in this industry is necessary because maintaining the whole research and production operations requires a well-developed system to be in place, and employing high-paid experts is often not cost-effective. All the above factors influence the valuation of a company reflected by its stock prices.
This study is original and unique because the literature usually offers research based on different fundamental values, such as financial ratios calculated for pharmaceutical companies when performance is analyzed. Authors do not consider their performance on stock exchanges. However, it is important because it is not only based on financial ratios but also on investor sentiment and behavior of market speculators who often make market prices deviate from their fundamental values based on the traditional financial analysis.
2 Literature Review
The pharmaceutical industry is thought to be highly innovative and an important contributor to GDP, and therefore there are many studies on the profitability of pharmaceutical companies in different countries (e.g., Mouri, et al., 2013; Ali, 2020). Ledley et al. (2020) compare the profitability of pharmaceutical companies with other entities from the S&P index based on using their financial statements for 2000–2018 and conclude that generally the former perform better than the latter. Fenyves et al. (2019) use return on equity to check the profitability of pharmaceutical companies in Central and Eastern Europe and find out that it has increased recently. Farhan et al. (2020) focus on the board of directors as an aspect that can affect the profitability of pharmaceutical companies alongside other factors such as financial indicators, size or age company. Barbuta-Misu (2013) shows the impact of financial leverage on the profitability of pharmaceutical companies in Romania. Lim and Rokhim (2021) find links between liquidity, sustainable growth rate and profitability measured by financial indicators such as return on equity, return on assets or earnings per share. Anghel et al. (2018) explore relationships between intellectual capital and financial performance of 24 biotech companies in 2002–2014. Basha (2014) examines the influence of crude oil prices on the financial performance of pharmaceutical companies in Jordan in 2002–2011. The paper shows a statistically significant impact of the former on the latter measured by return on assets, return on equity, or net profit margin. Farhan et al. (2019) study the relationship between liquidity and financial performance of Indian pharmaceutical companies. Nsiah and Aidoo (2015) analyze the profitability, liquidity or solvency and probability of going bankrupt of Indian companies listed on the Ghana Stock Exchange. Endri et al. (2020) analyze the financial performance of nine pharmaceutical companies from the Indonesia Stock Exchange. Like the other cited authors, they use typical financial ratios as measures of financial performance. Rehan et al. (2020) present interdependencies between the capital structure and financial performance of pharmaceutical companies in Pakistan. Mansouri and Bagheri (2015) make a ranking of pharmaceutical companies from the Tehran Stock Exchange according to their financial performance and assess them with the use of financial ratios.
Besides, the existing literature tends to focus on profitability only without comparing it to risks taken by pharmaceutical companies. The types of risks involved in pharmaceutical activity are analyzed in separate studies (Golec, Vernon, 2009; Vernon et al., 2010; Baltes et al., 2014).
This study is different in that it does not concentrate on the profitability of pharmaceutical companies themselves but treats them as portfolio investment vehicles. Thus, the perspective taken here is that of the equity investor. Although the profitability understood as financial results undoubtedly influences the profitability of direct stock investments, they can be also influenced by other factors such as technical analysis or the presence of market speculators.
3 The Methodology of the Study
The author analyzes pharmaceutical companies quoted on the Warsaw Stock Exchange operating in Poland which form the WIG-Leki index and compares their effectiveness with the WIG20TR index of 20 biggest companies on the same exchange.
The study period starts in January 2017 and ends in June 2021. Such a choice derives from the fact that some companies were not quoted before January 2017, and consequently a longer timeframe would not consider all the pharmaceutical companies which comprised the WIG-Leki index at the time the study was conducted. WIBOR was used as a risk-free interest rate from the end of the study period. If there were no quotations on the day concerned, the previous date was considered. The literature does not give a clear answer to the question if the risk-free interest rate should be taken from the beginning or from the end of the study period, or changed during the period (Bernando & Ledoit, 2000). WIBORs were downloaded from www.stooq.com for standard periods and interpolated linearly for the required periods. The data were divided into four study periods depending on the market trends of the WIG20 Total Return index:
2 January 2017–23 February 2020 – horizontal trend, the risk-free rate is a three-year WIBOR = 1.84%,
24 February 2020–15 March 2020 – bear market, the risk-free rate is a three-week WIBOR = 1.61%,
16 March 2020–13 June 2021 – bull market, the risk-free interest rate is a one-and-a half-year WIBOR = 0.31%,
2 January 2017–13 June 2020 – the whole analyzed period, the risk – free interest rate is a four-and-a-half-year WIBOR = 1.87%.
Effectiveness (or performance) is understood as the relationship between excess return and risk understood in different ways. Both traditional and alternative risk measures are used. The following companies which make up the WIG-Leki index on 15 June 2021 (end of the study period) are analyzed:
Bioton S.A.,
Biomed Lublin S.A.,
Celon Pharma S.A.,
PZ Cormay S.A.,
KRKA Polska Sp. z o.o.,
Mabion S.A.,
Master Pharm S.A.,
Pharmena S.A.,
Sopharma A.D.
Besides, the performance of the WIG-Leki index is analyzed. It reflects the general effectiveness of all pharmaceutical companies which make it up . At the beginning, the statistical analysis was performed. Such distribution features were calculated as mean, standard deviation, skewness, and kurtosis. Weekly data for companies and indexes were downloaded from www.stooq.com. In the case of missing data when there were no quotations available for a company for one week because of no transactions (Sopharma AD and KRKA Polska Sp. z o.o.), quotations from the previous period were taken.
The methods of investment performance valuation can be divided into two groups:
Standard efficiency measures. In this group, the Sharpe ratio is used (Sharpe, 1975).
Alternative efficiency measures. Here, maximum drawdown measures such as Calmar ratio, Sterling ratio, Burke ratio are applied (Young, 1991; Burke, 1994).
The Sharpe ratio was designed by William Sharpe to compare the performance of mutual funds. The author compared returns and risks of 34 investment funds between 1954 and 1963 and ranked them from the best to the worst (Sharpe, 1966). The Sharpe ratio is often depicted in the following way (Francis, 2000, p. 709):
where:
– the average value of return on the portfolio of i assets
σ(ri) – the standard deviation of return on the portfolio of i assets
rf – risk-free interest rate
In the following years, the Sharpe ratio started to be used for other assets or portfolios. It is a relative performance measure of the investment and can be applied to make a comparison between several assets. It cannot be used to measure the performance of a single asset. The same rule applies to other ratios used in this study.
Moving on to alternative measures, the Calmar ratio is depicted as (Young 1991, p. 40; Eling & Schuhmacher 2007, p. 6):
where:
rf – risk-free interest rate
MDi – the lowest rate of return on i assets in the assumed period.
As seen from the formula, the Calmar ratio takes into account the lowest return on asset in the analyzed period. It presents the worst-case scenario from the past, which is its advantage. On the other hand, it has the disadvantage of high sensitivity to random returns resulting from low-probability events. The required efficiency is when it is maximized. In order to diminish the sensitivity of the Calmar ratio, the Sterling ratio is applied. It considers the average level of N maximum negative returns. It is defined (Kestner, 1996, pp. 44–46; Eling & Schuhmacher, 2007, p. 6):
As with the previously discussed measures, the Sterling ratio is also designed so that higher values are required.
Another alternative ratio used in the study is the Burke ratio. In this case, the excess return is related to the square root of the sum of N powered lowest returns achieved in the examined period. Mathematically, it can be presented in the following way (Burke, 1994, p. 56; Eling & Schuhmacher 2007, p. 6):
The design of the Burke ratio shows that similarly to the performance measures presented earlier, maximum values are required.
3 Research Results
The different performance measures applied for the purposes of the analysis are depicted in Tables 10.3 to 10.6. As shown, they do not always lead to the same conclusions. Thus, only these situations are considered here in which all of them show identical results. This additionally means that conclusions on the investment effectiveness of pharmaceutical companies are based on the consideration of different attitudes to risk. Thanks to such methodology, results are more reliable. Descriptive statistics for the companies and indexes examined are depicted in Table 10.1.
Main statistics for analyzed indexes and companies
Source: Author’s calculations on the basis of data downloaded from Stooq (2021)
In Table 10.1, apart from such measures as variance, standard deviation or mean, which were later used in the calculations of performance measures, skewness and kurtosis were calculated. They show the third and the fourth central moment of the distribution, whereas the mean and the standard deviation are the first and the second. In other words, they provide additional information concerning risk associated with investments in particular entities. The higher the kurtosis, the higher the risk, so the investment efficiency is lower at the same rate of return. As far as skewness is concerned, its positive values are desired to minimize risk.
Correlation coefficients depicted in Table 10.2 show that returns on WIG20TR are highly correlated with returns on the WIG-Leki index and the majority of pharmaceutical companies returns only during the period 24 February 2020 to 15 March 2020. Simultaneously, all correlation coefficients are insignificant. In other periods, they are low. Thus, pharmaceutical companies could be used as diversifying assets for WIG20TR. Given also that many pharmaceutical companies had higher performance measures than WIG20TR, it can be concluded that they are a good option for an investor on the Warsaw Stock Exchange.
Correlation coefficients between WIG20TR return and examined entities. Bolded values are significant at p<0,05
Source: Author’s calculations on the basis of data downloaded from Stooq (2021)
Data depicted in Table 10.3 show that during the period 2 January 2017 to 23 February 2020, there were four pharmaceutical companies which achieved better results than the WIG20TR index. These were: Celon Pharma S.A., Sopharma A.D., KRKA Polska Sp.z o.o., Mabion S.A. All the measures applied show the same results.
Performance measures for companies and indexes in 02 January 2017– 23 February 2020
Source: Author’s calculations on the basis of data downloaded from Stooq (2021)
In the period 24 February to 15 March 2020, the market saw sharp declines, so all performance measures are negative. However, some pharmaceutical companies go down less than the WIG20TR index. As data gathered in Table 10.4 show, different measures give slightly different results; however, all of them support the conclusion that at least three pharmaceutical companies performed better than the WIG20TR index. These were companies such as PZ Cormay S.A., Pharmena S.A., Sopharma S.A.
Performance measures for companies and indexes from 24 February 2020 to 15 March 2020
Source: Author’s calculations on the basis of data downloaded from Stooq (2021)
Between 16 March 2020 and 13 June 2021, there was one company, KRKA Polska Sp.z o.o., which achieved better results than WIG20TR measured with all the risk-return ratios applied. However, if one considers only alternative measures, not the Sharpe ratio, it can be concluded that four pharmaceutical entities showed a better relationship between the excess rate of return and risk than the WIG20TR index treated as a benchmark. These were WIG-Leki index, Bioton S.A., Biomed Lublin S.A., and KRKA Polska Sp.z o.o. (see table 10.5).
Performance measures for companies and indexes in the period 16 March 2020 to 13 June 2021
Source: Author’s calculations on the basis of data downloaded from Stooq (2021)
As Table 10.6 suggests, throughout the analyzed period 2 January 2017 to 13 June 2021, WIG-Leki index and three companies performed better than the WIG20TR index: Biomed Lublin S.A., Celon Pharma S.A., and KRKA Polska Sp.z o.o.
Performance measures for companies and indexes in 2 January 2017–13 June 2021
Source: Author’s calculations on the basis of d ata downloaded from Stooq (2021)
To sum up, while different results are produced in different periods of time, there are many pharmaceutical companies which deliver better results than the WIG20TR index in all the periods except in the immediate wake of the COVID-19 pandemic when all world markets slumped. All in all, in order to successfully use pharmaceutical companies as part of an investment portfolio, it is necessary to make the right choice of companies as well as the right prediction of the market situation. In general, pharmaceutical companies are advised to be used as portfolio diversification instruments because of their low or average correlation with the WIG20TR index during typical market conditions and possible higher investment efficiency than the benchmark.
4 Conclusions, Applicability, and Limitations of the Study
The results of the study may be helpful both for investors and market makers seeking to optimize their investment decisions. It is different from existing ones because the literature devoted to pharmaceutical companies often provides research based on fundamental values of pharmaceutical companies when performance is analyzed. Authors do not consider their performance on stock exchanges based on the relationship between the excess rate of return and risk. In contrast, an approach such as that adopted in this study addresses vital aspects because stock market performance is not only based on financial analysis but also on investor sentiment and behavior of market speculators who often make market prices go away from their fundamental values.
The imitation of the study is that it is an index that had to be used as a benchmark. Thus, if an investor plans to build a diversified portfolio consisting of both WIG20TR index stocks and pharmaceutical companies’ stocks, it would be necessary either to buy a basket of stocks replicating the index or to use futures contracts. In the latter case, the basis risk arises. It is understood as differences between index and futures contracts quotations which may make the final result slightly different than for the index itself. Apart from that, index design changes over time, so portfolio changes must be made from time to time, which may affect investment performance.
However, there are no doubts that some pharmaceutical companies quoted on the Warsaw Stock Exchange should be considered in portfolio diversification because of their both low and medium correlation with the benchmark used as well as better performance for some of them in all time periods, except for the one at the beginning of the COVID-19 pandemic which triggered a panic in financial markets globally.
Further studies could include portfolio optimization in order to assess what shares of stocks from the pharmaceutical index in the whole portfolio would be desired to minimize risk or maximize the rate of return.
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