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http://www.dem.umk.pl/dem 

D Y N A M I C  E C O N O M E T R I C  M O D E L S  
DOI: http://dx.doi.org/10.12775/DEM.2019.005  Vol. 19 (2019) 85−96 

Submitted December 7, 2019  ISSN (online) 2450-7067 

Accepted December 28, 2019 ISSN (print) 1234-3862 

Dorota Witkowska, Piotr Kuźnik  

Does Fundamental Strength of the Company Influence 
its Investment Performance? 

A b s t r a c t. The aim of our research is to find out whether the fundamental strength of the 

company affects its investment performance. The research is provided for 27 non-financial 

companies listed on the Warsaw Stock Exchange in the years 2012–2017. These companies 

belong to the stock indexes WIG20 and mWIG40 portfolios. The obtained results show that the 

proposed synthetic measure makes it possible to estimate the fundamental strength of listed 

companies, and the correlation between values of the constructed measure and rates of return 

is positive but usually statistically insignificant.  

K e y w o r d s: capital market; fundamental analysis; taxonomic measure; investment 

performance. 

J E L Classification: : C1, G11 

Introduction  

 In the process of making investment decisions, investors use different 

supporting tools such as fundamental and technical analysis. The former 

requires taking into account a number of factors that are particularly important 

in assessing the current economic and financial condition of the company and 

to consider the environment in which analyzed firm operates.  
Fundamental analysis involves assessing a firm’s equity value based on 

the analysis of published financial statements and other information without 

 
 Correspondence to: Dorota Witkowska, University of Johannesburg, College of 

Business and Economics, D Ring 414, APK, Johannesburg, South Africa, e-mail: 

mariaw@uj.ac.za. 



Dorota Witkowska, Piotr Kuźnik 

DYNAMIC ECONOMETRIC MODELS 19 (2019) 85–96 

86 

reference to the prices at which a company’s securities trade in the capital 

markets (Bauman, 1996, p.1). This analysis attempts to measure a security's 

intrinsic value by examining related economic and financial factors including 

the balance sheet, strategic initiatives, microeconomic and macroeconomic 

indicators, together with consumer behavior. Fundamental analysis is usually 

used to find long-term opportunities to invest. Studies that employ 

fundamental analysis to forecast earnings and future stock returns include Ou 

and Penman (1989a, b), Ou (1990), Greig (1992), Stober (1993), Kerstein, 

Kim (1995) Seng, Hancock (2012), Muhammad, Gohar (2018) and Bintara, 

Tanjung (2019), among others. 

 A modern approach to assessing the economic and financial condition of 

enterprises is applying the concept of fundamental strength of a company 

which bases on multidimensional comparative analysis methods. These me-

thods allow to construct aggregated measures on the basis of many different 

variables, describing the condition of the company. In other words, to examine 

the state of the enterprise, its major economic and financial factors such as 

financial liquidity, level of debt, management efficiency, profitability, etc. are 

taken into account. 

The first proposal to measure the fundamental power of the enterprise was 

so-called taxonomic measure of investment attractiveness (TMAI) proposed 

by Tarczyński (1994), and further developed by Tarczyński (2002) and 

Tarczyńska-Łuniewska (2013). TMAI is an application of a synthetic measure 

of development constructed by Hellwig (1968), which contains diagnostic 

variables describing financial situation of the company. There have been many 

attempts to construct taxonomic measures which have been used:  

(1) to evaluate the state of enterprises, e.g. Kompa (2019), 

(2) to select companies for the investment portfolio construction, e.g. 

Staszak (2017), 

(3) to find relation between financial condition of companies and their 

performance, e.g. Juszczyk (2015). 

Application of taxonomic measures to different purposes requires usage of 

different variables to their construction. 

This study aims to find our if the fundamental strength of the company 

affects its investment performance. Fundamental strength of the company is 

measured by taxonomic measure which is constructed using 15 financial 

indicators evaluated for 27 non-financial companies listed on the Warsaw 
Stock Exchange in the years 2012–2017. These companies are classified as 

big and medium size firms since they have been included in the stock indexes 

WIG20 and mWIG40 portfolios. Investment efficiency is measured by annual 

logarithmic rates of return. 



Does fundamental strength of the company influence its investment performance? 

DYNAMIC ECONOMETRIC MODELS 19 (2019) 85–96 

87 

Investigation consists of several stages. In the first one synthetic measures 

of development are evaluated for all analyzed companies and years. In the 

second stage, annual rates of return for each company and the years 2012–

2017 are calculated. In the third stage, the hypothesis that fundamental 

strength of companies influences their investment performance is verified 

applying regression functions. 

1. Data and Methodology 

 The research concerns companies listed on the Warsaw Stock Exchange 

which constantly belonged to the stock indexes WIG20 and mWIG40 in the 

period from 31.12.2012 to 31.12.2017. However, companies: 

− without financial statements in the analyzed period, 

− with negative equity or zero sales revenues, 

− excluded from trading on the Warsaw Stock Exchange since 2017, 

− from the sectors defined as: banks, insurance and finance 

were excluded from investigation. Therefore, an analysis (that is carried out 

according to the above assumptions) made it possible to qualify to research 

27 non-financial companies.  

 As it was already mentioned, investigation is provided in several steps. In 

the first one synthetic measures of development are evaluated for all analyzed 

companies and years. These measures base on financial coefficients which are 

evaluated for the end of each year under consideration, using data from 

balance sheets and annual financial reports provided by selected companies. 

Taxonomic measure of investment attractiveness (TMAIit) is calculated for the 

i-th company in the t-th year as (Łuniewska and Tarczyński, 2004, p. 43):  

𝑇𝑀𝐴𝐼𝑖𝑡 = 1 −
𝑑𝑖𝑡

𝑑𝑡̅̅ ̅+2𝑆𝑑𝑡
      (1) 

where: 𝑑𝑖𝑡 – the distance (from the benchmark) of the i-th company (i = 1, 

2,…, n) in the t-th period of time (t = 1, 2,…, T), 𝑑𝑡
̅̅̅ – the average of distances 

𝑑𝑖𝑡 in time t, 𝑆𝑑𝑡  – the standard deviation of distances 𝑑𝑖𝑡 in time t. Euclidean 

distance in m-dimensional space is defined as: 

𝑑𝑖𝑡 = √
∑ (𝑧𝑗𝑡

𝑖 −𝑧𝑗𝑡
0 )2𝑚

𝑗=1

𝑚
      (2) 

where: 𝑧𝑗𝑡
𝑖  – is the standardized variable describing the j-th feature (j = 1, 2,…, 

m) in the i-th company in time t, 𝑧𝑗𝑡
0  – is the value of the j-th variable of the 

benchmark in time t, the benchmark is defined for each year and described by 



Dorota Witkowska, Piotr Kuźnik 

DYNAMIC ECONOMETRIC MODELS 19 (2019) 85–96 

88 

m variables. Standardization of all variables used for the measure construction 

is provided according to the formula: 

𝑧𝑗𝑡
𝑖 =

𝑥𝑗𝑡
𝑖 −�̅�𝑗𝑡

𝑆(𝑥𝑗𝑡)
   (3) 

where: 𝑥𝑗𝑡
𝑖  – observation of the j-th variable in the i-th company in the t-th 

year, �̅�𝑗𝑡 , 𝑆(𝑥𝑗𝑡) – average and standard deviation of the j-th variable in the t-

th year, respectively. 
 The benchmark used in the formula (2) might be either real or hypothetical 

object. Since it is difficult to determine a company which will be the pattern 

for others, the hypothetical object is usually used. Such benchmark is 

constructed from m variables as maximal value of stimulants and minimal 

values of de-stimulants i.e.: 

𝑧𝑗𝑡
0 = {

min 𝑧𝑗𝑡
𝑖  𝑖𝑓 𝑥𝑗𝑡

𝑖 𝜖𝐷

max 𝑧𝑗𝑡
𝑖  𝑖𝑓 𝑥𝑗𝑡

𝑖 𝜖𝑆
      (4) 

where: D, S, – are sets of de-stimulants and stimulants, respectively. 

Stimulants are variables whose rise in quantity indicates an increase of 

economic and financial standing of the enterprise whereas de-stimulants are 

variables with the opposite direction of influence. 

In the second stage, annual logarithmic rates of return are calculated, 

according to the formula:  

𝑅𝑖𝑡 = 𝑙𝑛 (
𝑦𝑖𝑡

𝑦𝑖𝑡0
)       (5) 

where 𝑦𝑖𝑡, 𝑦𝑖𝑡0 – quotations of share price of the i-the company on the last 

and the first day of Warsaw Stock Exchange quotation in the t-the year (t = 

2012, 2013,…,2017), respectively.  

In the third stage, the hypothesis that fundamental strength of companies 

influences their investment performance is verified, applying Pearson 

correlation coefficients and regression functions. In other words, the relations 

between logarithmic annual rates of return from shares of considered 

companies and values of synthetic measure TMAI (for current and lagged 

dependencies) are estimated. 

2. Evaluation of Companies Based on Taxonomic Measure 

 To evaluate the fundamental strength of companies, it is necessary to 

apply numerous indicators that are of particular importance when assessing 

the current state of the enterprise and its further development prospects. In the 



Does fundamental strength of the company influence its investment performance? 

DYNAMIC ECONOMETRIC MODELS 19 (2019) 85–96 

89 

construction of the aggregated measures, the selection of diagnostic variables 

is extremely important since it determines the quality of evaluation and signals 

the proper functioning of companies, taking into account their economic and 

financial situation (Tarczyński and Łuniewska, 2004). 

Table 1.  TMAI values of selected companies for the years 2012–2017 

Company 
 

TMAI Value 

2012 2013 2014 2015 2016 2017 Average 

AMREST 0.15 0.13 0.18 0.11 0.11 0.08 0.13 
ASSECOPOL 0.36 0.39 0.36 0.19 0.24 0.20 0.29 
BOGDANKA 0.30 0.31 0.27 0.11 0.27 0.38 0.27 
BORYSZEW 0.14 0.15 0.18 0.10 0.16 0.15 0.15 

BUDIMEX 0.23 0.35 0.12 0.19 0.27 0.29 0.24 
CCC 0.27 0.32 0.20 0.15 0.11 0.19 0.21 

CDPROJECT 0.45 0.32 0.35 0.28 0.41 0.34 0.36 
CIECH –0.04 0.18 0.19 0.15 0.24 0.25 0.16 

CYFRPLSAT 0.27 0.35 0.18 0.14 0.16 0.16 0.21 
ECHO 0.21 0.29 0.36 0.35 0.33 0.23 0.29 
ENEA 0.24 0.42 0.36 0.14 0.23 0.21 0.27 

EUROCASH 0.07 0.12 0.08 0.05 0.05 –0.06 0.05 
GTC 0.09 –0.10 –0.04 0.18 0.16 0.27 0.09 

INTERCARS 0.16 0.21 0.20 0.11 0.14 0.11 0.15 
KERNEL 0.32 0.26 0.12 0.11 0.22 0.22 0.21 

KETY 0.28 0.34 0.29 0.18 0.25 0.22 0.26 
KGHM 0.42 0.37 0.23 0.01 0.06 0.13 0.20 
KRUK 0.22 0.06 0.10 0.13 0.16 0.18 0.14 

LOTOS 0.09 0.10 0.14 0.05 0.15 0.20 0.12 
LPP 0.28 0.32 0.24 0.14 0.17 0.23 0.23 

NETIA 0.08 0.15 0.18 0.08 0.09 0.04 0.10 
ORANGEPL 0.16 0.17 0.18 0.11 0.06 0.07 0.13 

ORIBS 0.34 0.44 0.46 0.23 0.38 0.31 0.36 
PGE 0.28 0.31 0.37 0.11 0.23 0.18 0.25 

PGNIG 0.25 0.32 0.33 0.21 0.25 0.25 0.27 
PKNORLEN 0.18 0.18 0.13 0.14 0.24 0.27 0.19 
TAURONPE 0.23 0.25 0.23 0.09 0.05 0.09 0.16 

Note: Bold letters denote the State Treasury companies.  

 Synthetic measures of development (TMAI) are constructed employing 15 

financial indicators belonging to four groups: 

1. profitability ratios: return on assets ratio (ROA), return on equity 

ratio (ROE) and return on sales ratio (ROS); 

2. liquidity ratios: current ratio, acid-test ratio (quick ratio) and cash 

ratio; 



Dorota Witkowska, Piotr Kuźnik 

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3. efficiency (activity) ratios: average collection period, average 

payment period, fixed asset turnover ratio, asset turnover ratio and 

inventory turnover ratio; 

4. leverage (debt) ratios: debt ratio, debt to EBITDA ratio, interest 

coverage ratio and long-term debt to equity ratio.  

Obtained TMAI values for considered companies in the years 2012–2017 are 

presented in Table 1. 

 According to (Łuniewska and Tarczyński, 2006, p. 95), the level of 

synthetic measures for companies with strong foundational and being 

attractive in terms of investment is determined by TMAI in the range of 0.3–

0.5. Analysing values of constructed measure in Table 1, it may be noticed 

that in each of the audited periods there are several companies in good 

economic and financial condition, for which TMAI values equal 0.3 and 

above. Namely for rounded measure values, there are 15 such firms in 2013, 

11 companies in 2012, 9 enterprises in 2014, 6 companies in 2017, 5 

enterprises in 2016, and 2 firms in 2015 (i.e. there are only 48 such cases, and 

among them only in 33 cases TMAI is bigger than 0.3). It means that the 

majority of companies under study are characterized by weak economic and 

financial results in the years 2015–2017 (i.e. in more than 70% of all analysed 

cases).  

 Among analysed companies only four of them can be classified into the 

group of the best companies, i.e. CDPROJEKT in all analysed years, ORBIS 

together with BOGDANKA in five years and ECHO in four years. Ten 

enterprises are characterized by values of the synthetic measure below 0.3 in 

all years of investigation, which means low investment attractiveness and 

fundamental strength. Other companies show low values of TMAI in three 

and more years (among six considered years).  

 CDPROJEKT obtains the highest value of taxonomic measure of 

investment attractiveness in 2012 (TMAI= 0.45) and keeps the TMAI value 

above 0.3 in five following years, that proves its strong financial situation and 

proper management. The second place in 2012, in terms of investment 

attractiveness, belongs to KGHM company, which in the following years does 

not perform well, and keeps the last place in the constructed ranking for 2015. 

The years 2013 and 2014 are favourable for ORBIS, which seems to be of the 

best financial standing, and the values of aggregate measures equal 0.44 and 

0.46, respectively. TMAI values for ORBIS in the considered period 2012–
2017, are regularly in the range between 0.3 and 0.5, with the exception of 

2015, when the measure decreases to 0.23.  

 Definitely unfavourable results in 2013 and 2014, in terms of TMAI, 

belong to GTC, which is the weakest among all companies in both years. In 



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2015, ECHO reaches the highest TMAI level, while in the following year the 

first place is taken by CDPROJEKT again, whereas TAURONPE turns out to 

be the least attractive investment. BOGDANKA is the highest ranked 

company in the ranking in 2017, while EUROCASH characterizes by the 

lowest TMAI level among all companies. 

 ORBIS and CDPROJEKT have the highest average values of TMAI 

which for both companies over the six examined years are above 0.36. These 

two firms should be classified as companies with strong fundamental and 

being attractive for investment. Other companies achieve much worse results 

thus their investment attractiveness is at an average level. It is worth 

mentioning that among the State Treasury companies, ENEA from the energy 

sector and PGNIG, belonging to the WIG-OIL&GAS industry index, keep the 

highest place in the created ranking of companies. The least level of 

taxonomic measure of investment attractiveness is observed for EUROCASH. 

The company fares by far the worst in the period under review, reaching an 

average TMAI of 0.05. It is worth mentioning that the TMAI negative values 

presented in Table 1 are irrelevant since values of the measure depend on the 

normalization formula (1), which is the special case of the formula presented 

by Tarczyński (1994, p. 177).  

3. Rates of Return of Analyzed Listed Companies 

 Annual logarithmic rates of return, calculated for all companies, are 

presented in Table 2. It is visible, that average annual rates of return in the 

years 2015–2017 are below 20% (only 14% in 2015) whereas they are over 

20% in three first years of investigation (25% in 2014).  

 The rates of return of companies listed on the Warsaw Stock Exchange 

were characterized by high volatility in the period 2012–2017. Among the 

selected companies, there are those that systematically generated positive 

returns on the capital employed by investors, e.g. BUDIMEX, INTERCARS, 

CCC, KĘTY, KRUK, ORBIS. The shares of CCC brought on average 31.66% 

of profit per year. In the case of KRUK, the return was 30.43%, while 

investors obtained 17.92% on shares of ORBIS. 

 The highest rate of return in 2012 is recorded by LPP (83.76%), while 

ORANGEPL generated the lowest value i.e. 25.01% losses. CDPROJEKT 
achieved the highest rate of return among all selected enterprises in 2013 

(104%). The main factor was the high sales of the popular game series 

translating into high and positive financial flows of the company. 

CDPROJEKT was keeping the leader position in 2016 and 2017, and also 

achieved the highest average rate of return over the entire period (48.75%). 



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CIECH company was successful in 2014 and 2015 (70.23%). The highest 

losses were generated by GTC (i.e. 32.37% in 2014) and BOGDANKA (i.e. 

101.18% in 2015). Other raw material and energy companies, e.g. KGHM, 

ENEA, PGE and TAURONPE, did not avoid losses in 2015. 

 Taking into consideration average returns obtained by analyzed 

companies, it is visible that CDPROJECT keeps the first place (48.75% 

average annual rate of return) and is followed by CCC (31.66%), AMREST 

(30.97%) and KRUK (30.42%). ORBIS, which is a leader in the TMAI 

classification, achieved average returns of 17.92% over the entire period but 

it did not generate losses in any year. There are 7 companies which generated 

negative average annual rates of returns. Among them ORANGEPL had the 

lowest average rate of return from shares in all years 2012–2017. On average, 

it generated losses of 12.96% per year. 

Table 2.  Logarithmic rate of return for the years 2012–2017 

Company 
 

Annual Rate of Return (%) 

2012 2013 2014 2015 2016 2017 Average 

AMREST 40.83 –6.66 10.54 63.23 45.29 32.58 30.97 
ASSECOPOL –1.96 6.55 16.45 15.74 0.44 –14.86 3.73 
BOGDANKA 29.06 –3.32 –21.56 –101.18 73.85 –2.18 –4.22 
BORYSZEW –4.73 –21.51 13.63 –18.10 53.31 14.07 6.11 

BUDIMEX 5.51 69.28 15.74 35.08 6.40 12.63 24.11 
CCC 47.23 48.27 14.72 5.49 39.66 34.57 31.66 

CDPROJECT 16.06 104.00 –4.91 28.24 85.73 63.41 48.75 
CIECH 24.43 33.55 35.27 70.23 –33.54 –1.40 21.42 

CYFRPLSAT 19.60 18.78 18.37 –11.82 16.40 2.31 10.61 
ECHO 40.15 28.27 4.95 –2.01 74.11 –4.83 23.44 
ENEA –11.57 –12.03 14.98 –26.48 –17.35 20.79 –5.28 

EUROCASH 39.92 10.14 –20.72 26.53 –18.88 –37.26 –0.05 
GTC 15.43 –28.43 –32.37 29.97 13.70 20.78 3.18 

INTERCARS 6.48 79.09 17.25 6.15 15.64 11.29 22.65 
KERNEL –2.88 –56.15 –29.10 54.98 30.20 –28.09 –5.17 

KETY 37.53 45.30 30.72 14.22 27.23 12.59 27.93 
KGHM 69.46 –39.28 –4.04 –50.67 39.68 19.32 5.75 
KRUK 1.78 63.04 28.45 46.83 31.93 10.48 30.42 

LOTOS 54.04 –15.04 –22.13 5.72 34.84 42.85 16.71 
LPP 83.76 69.27 –20.80 –25.99 2.88 45.55 25.78 

NETIA –20.04 20.81 13.56 6.47 –7.37 24.27 6.28 
ORANGEPL –25.01 –15.46 –11.49 –17.98 –12.79 4.96 –12.96 

ORIBS 3.63 9.87 12.16 36.50 19.80 25.55 17.92 
PGE –0.78 –7.22 17.19 –27.97 –21.41 13.08 –4.52 

PGNIG 24.45 0.94 –11.49 17.48 12.35 14.08 9.63 
PKNORLEN 33.25 –15.58 21.06 35.14 26.01 24.42 20.72 
TAURONPE –5.23 –3.62 18.35 –52.41 –1.05 6.78 –6.19 

Note: Bold letters denote the State Treasury companies.  



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4. Relationship Between Fundamental Strength of Companies 
and their Investment Performance 

 Supporters of fundamental analysis claim that profits from capital 

investments can be achieved by investing in companies characterized by good 

economic and financial conditions. Assuming that the taxonomic measure of 

investment attractiveness (1) properly describes financial standing of 

companies and annual rate of return (5) is a good measure of firm 

performance, we apply Pearson correlation coefficients and linear regression 

functions to verify the existence of positive relationship between both 

phenomena. The research is conducted for the following 16 relations between: 

 (1) values of average returns and average values of synthetic measures, 

 (2)–(7) values of rates of return in the years: 2012, 2013, 2014, 2015, 

2016, 2017 and values of synthetic measures in the same years, 

 (8) values of rates of return in the whole period 2012–2017 and values of 

synthetic measures in the six-years period, 

 (9) values of rates of return in the five-years period 2013–2017 and values 

of TMAI in the period 2012–2016 (i.e. TMAI is lagged by one year), 

 (10)–(14) values of rates of return in the period 2013, 2014, 2015, 2016, 

2017 and values of synthetic measures lagged by one, 

 (15) values of rates of return in 2012–2017 and values of TMAI in the six-

years period for the companies with the highest average annual returns i.e. 

CDPROJECT, CCC, AMREST and KRUK, 

 (16) values of rates of return in 2012–2017 and values of TMAI in the six-

years period for companies with the highest values of taxonomic measure i.e. 

CDPROJECT, BOGDANKA, ORBIS and ECHO.  

Values of Pearson correlation coefficients and characteristics of the regression 

models are presented in Table 3. 

 Based on the results in Table 3, it is visible that the relation between 

fundamental strength of the company and its performance is positive (except 

for the lagged TMAI in 2015) but usually statistically insignificant. Only 

correlations between both phenomena, observed for the whole period of 

analysis and rates of return from 2016 for both current and lagged values of 

TMAI, are statistically significant. Pearson correlation coefficient obtained 

for four companies which were selected as the ones with the highest values of 

taxonomic measure is quite high i.e. 0.31 but it is not statistically significant. 

In general, values of Pearson coefficient are low and do not excide 0.36, 

therefore also determination coefficients of regression functions are not bigger 

than 0.13.  

 



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DYNAMIC ECONOMETRIC MODELS 19 (2019) 85–96 

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Table 3.  Relations between TMAI and rates of return. 

Number of the relation 1 2 3 4 5 6 7 8 

Constant Number of 
observations 

27 27 27 27 27 27 27 162 

Correlation  

Pearson coefficients 0.26 0.09 0.17 0.27 0.28 0.36 0.31 0.22 

Regression functions  

Constant a 0.03 0.14 0.01 –0.06 –0.16 –0.02 0.00 0.00 
Slope factor b 0.50 0.21 0.53 0.46 1.53 1.15 0.69 0.63 
t-statistics ta 0.34 1.22 0.05 –0.69 –0.95 –0.17 0.03 0.00 
t-statistics tb 1.35 0.45 0.86 1.38 1.46 1.94 1.64 2.91 

𝑅2 0.07 0.01 0.03 0.07 0.08 0.13 0.10 0.05 

Number of the relation 9 10 11 12 13 14 15 16 

Number of observations 135 27 27 27 27 27 24 24 

Correlation  

Pearson coefficients 0.00 0.11 0.24 –0.27 0.33 0.18 0.15 0.31 

Regression functions  

Constant a 0.12 0.06 –0.05 0.27 0.00 0.06 0.28 –0.29 
Slope factor b 0.00  0.37 0.38 –0.94 1.41 0.39 0.38 1.56 
t-statistics ta 2.03 0.34 –0.57 1.62 0.01 0.65 1.73 –0.84 
t-statistics tb 0.01 0.54 1.25 –1.40 1.74 0.89 0.71 1.52 

𝑅2 0.00 0.01 0.06 0.07 0.11 0.03 0.02 0.09 

Note: Bold numbers denote significant relations at the significance level 0.05.  

Conclusions 

 An ongoing assessment of the company's operations is necessary to 

company management and providing development perspectives. For this 

purpose, the state of the enterprise is examined in terms of its economic and 

financial condition. In our research we applied linear ordering method to 

evaluate the fundamental strength of the company. In majority of research, 

ratios describing financial liquidity, level of debt, management efficiency and 

profitability are taken into account to construct taxonomic measure of 

investment attractiveness, and such financial indicators were used in this 

study. 

 The aim of our research was to find out if the fundamental strength of the 

company affects its investment performance. In order to achieve that goal, we 
constructed the synthetic measure determining the fundamental strength of 

public companies that are characterized by good economic and financial 

condition and market value. Then we checked if the statistically significant 

relation between values of aggregated measure and annual rates of return 

exists. 



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DYNAMIC ECONOMETRIC MODELS 19 (2019) 85–96 

96 

 The obtained results show that in all cases (but one) correlation between 

taxonomic measures and logarithmic rates of return is positive. However, 

statistically significant relationship between TMAI values and the rates of 

return from the shares of the analyzed public companies is observed only for 

the whole period of investigation 2012–2017 and for 2016 for both current 

and lagged relations.  

 In other words, the statement, that fundamental strength of companies 

affects their investment performance, seems to be confirmed although our 

study also shows that there are other factors influencing rates of returns and 

correlation between both phenomena is usually not strong. These results are 

consistent with study (Juszczyk, 2015) although in this research different set 

of companies, considered periods and variables were applied for the 

taxonomic measure construction. However, lack of significant relations for 

lagged TMAI values (except one year) shows weak forecasting properties of 

constructed synthetic measure which cannot be used in the initial selection of 

companies for the investment portfolio. Our results contradict (Staszak, 2017) 

who obtained promising results applying constructed by him TMAI to 

investment portfolio determination. But in his research, portfolios were built 

using only companies being leaders in the rankings of considered companies. 

Taking that fact in consideration, we notice the similarity to our results since 

correlation between fundamental strength and returns evaluated for four 

companies, selected as the most attractive for investors, is relatively high. 

References  

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	Introduction
	1. Data and Methodology
	2. Evaluation of Companies Based on Taxonomic Measure
	3. Rates of Return of Analyzed Listed Companies
	4. Relationship Between Fundamental Strength of Companies and their Investment Performance
	Conclusions
	References

