Analyzing Financial Health of the SMES Listed in the AERO Market of Bucharest Stock Exchange Using Principal Component Analysis

Round 1

Reviewer 1 Report

Authors aimed to build a composite financial index for measuring the financial 13 health of the companies listed on the AERO market of the Bucharest Stock Exchange.

The presented topic is interesting, but very limited locally to companies in Romania. There is a risk that it will not find interest on the part of readers. I strongly suggest that it would be worthwhile to extend the research to several European countries from the indicated sector.

The method has been described in a transparent manner and the results have been presented in an adequate manner.

The summary is very simple and does not bring conclusions and implementation of the method used. I also suggest to indicate a limitation in the presented study.

 

Author Response

Dear Reviewer,

 

Thank you for carefully reviewing our paper and for your valuable comments and suggestions. We made the changes required and performed a general revision. Hope now the manuscript meets the quality criteria and formal requirements.

Best regards,

prof.univ.habil. Diana Sabău-Popa

Author Response File: Author Response.pdf

Reviewer 2 Report

The main purpose of this paper is to determine the key factors in evaluating the financial health of the companies listed on the Bucharest Stock Exchange using the principal component analysis (PCA) method for panel data. The authors have built a composite financial index using rates of return, liquidity, management of 25 companies listed on the AERO market for the period 2011-2018. Their results show a positive and statistically significant relation between Solvency and the three rates (rates of return, of liquidity, respectively of management).

 

This is an interesting paper which makes contributions towards related literature. I list my comments as follows.

1. The authors should reconsider your purpose. Why do we need to build a composite financial index? If we want to diagnose the financial health of small and medium-sized companies, we can use solvency rate directly. Since the solvency rate is so easy to calculate, is there any necessary to build a new and complex index to measure the financial health? This research only shows the relation between current index and current solvency rate. The contribution should be using this new index to predict the future solvency rate. I suggest the authors to proof the predictive power of the new index.

2. You choose the principal component analysis method to develop a financial index. What is the advantage or disadvantage to use the PCA method? The authors should explain in more detail.

3. Data

Empirical results of the study are based on only 25 firms and 3 industries. You should explain how those samples can represent all small and medium-sized economies well.

4. Empirical Models

(1) In Line 335, the title of Table 6 is incorrect. Regression models in Table 6 use panel data instead of cross-sectional data.

(2) The average of day’s sales in receivables and average payable days outstanding are different in different industry. We can’t say that the longer average rotation time of current suppliers (DRF) means less financial health in different industry. The authors should use industry dummy variables as one kind of control variables.

(3) In Line162, the authors mention that “…If the Average rotation time of current suppliers (DRF) is smaller than the Average duration of short-term receivables rotation (DRC), this reflects an unfavorable situation for the company, ie it pays its suppliers in a shorter period of time than it receives the money from customers, which leads to a short-term cash deficit.” It is not necessary an unfavorable situation. The company might pay the money to suppliers in a shorter period of time in order to get a cheaper price. It is a useful management strategy. I suggest the authors to build your model based on financial theorems.

(4) This paper uses short-term debts (DS), long-term debts (DL) and total debts (DT) as control variables in Model (1), (2), (5) and (6). The lager company would have more debts. The size effect has powerful influence on those three variables. You should consider this point.

(5) Financing leverage (L) is the other control variable in Model (3) and (4). In Table 1, we can find that solvency rate (RSG) = Total Assets / (DS+DL) = TA/ DT. According to accounting identity, we also know that Asset = Debt + Equity. In other words, solvency rate (RSG) = TA/ DT = (DT + Equity) / DT = 1+ (Equity/DT) = 1+ financing leverage (L). In fact, the dependent and independent variable are the same in Model (3) and (4).

(6) The independent variables should be uncorrelated with each other in the regression model. The authors show a negative and statistically significant relation between financial health index and financing leverage in Model (7). However, financial health index and financing leverage are independent variables in Model (4). You show the assumption of multiple linear regression is violated by yourself.

All of your models have serious problems. I suggest the authors to adjust your empirical models and variables.

5. In Line 160, it is not a complete sentence.

6. In Line 385, I can’t find explanations of Model (6) and (7).

7. There are a lot of grammar errors. I suggest the authors to recheck your manuscript carefully.

 

I hope that my comments will help the authors to improve the quality of the paper.

Author Response

Dear Reviewer,

 

Thank you for carefully reviewing our paper and for your valuable comments and suggestions. We made the changes required and performed a general revision. Hope now the manuscript meets the quality criteria and formal requirements.

Best regards,

prof.univ.habil. Diana Sabău-Popa

 

Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report

The authors have already revised the manuscript according to previous comments. I list my other comments as follows:

1. The authors mention the technique used to select the companies and industries for this article and explain the method of clustered sampling in detail in the cover letter. I suggest you to put this description in your paper.
2. Some conclusions of financial healthy for SMEs in Table 6 are not correct.

        For example:

• The mean Z-score of Arteca is 0.09 when you use a t-test with zero. Arteca also has a positive, 1.99, and significant t-value. We can know that the mean Z-score of Arteca is significantly greater than zero. However, Arteca also has a negative, -3.28, and significant t-value when you use a t-test with 0.25. It means that the mean Z-score of Arteca is significantly lower than 0.25. We should conclude that Arteca is a SFH firm.
• ConexPrahova has a negative, -0.34, and insignificant t-value. We have no evidence to support Z-score is greater than 0.5. Why could you conclude ConexPrahova is a GFH firm?

You should care about the sign of t-value. It is a serious problem. I suggest the authors to use this way to recheck Table 6 and Table 8.

3. The companies come from only 3 industries in this research. The results in Table 7 show that they are not significantly different between 3 sectors. According to the outcome, empirical results of industry dummies could be mentioned just in the footnote and with untabulated way. Table 7 uses regressions without dummies.
4. On the one hand, Total Debts is insignificant in all models. On the other hand, Total Debts is influenced by the firm size. I suggest the authors to remove it from Table 7. Keeping only model (6) and (2) but without Total Debts in Table 7.
5. You should recheck zit or zij in Line 408 and 409.

Author Response

Dear Reviewer,

 

Thank you for carefully reviewing our paper and for your valuable comments and suggestions. We made the changes required and performed a general revision. Hope now the manuscript meets the quality criteria and formal requirements.

We made the changes required (marked in blue) and performed a general revision. Hope now the manuscript meets the quality criteria and formal requirements.

 

Best regards,

prof. univ. habil. Diana Sabău-Popa

Author Response File: Author Response.pdf