ASSET GROWTH OR LIQUIDITY?

Transcription

1 ASSET GROWTH OR LIQUIDITY? Seyed Hossein Raad * M. A, Student of Accounting, Branch-Islamic Azad University of Khuzestan, Iran Mohammad Ramezan Ahmadi Accounting Department Branch-Islamic Azad University of Khuzestan, Iran Ali hossein Hosseinzadeh Accounting Department, Branch-Islamic Azad University of Khuzestan, Iran *Corresponding Author Abstract This study aims at examining the correlation between asset growth and liquidity with stock return in an augmented Fama and French model within an eight-year period ( ). Results of the estimations show that the rate of correlation between liquidity and efficiency is higher than correlation between asset growth and stock return. Keywords: asset growth, liquidity, transaction size, Tehran Stock Exchange COPY RIGHT 2013 Institute of Interdisciplinary Business Research 546

2 Introduction: Capital market, particularly securities are one of the most important and sensitive formal economic elements that can have a dynamic contribution in growth of investment, production and employment. Considering the long-term economic perspective in Iran and special attention paid by higher authorities of Iran to its development, the main bases of annual budget are compiled based on development of investment and job creation. Hence, the importance of capital market is increased. Since investors are the most important variables in determining the long-term economic destiny, we need various instruments, criteria and information for providing a suitable tool in order to attend and attracting their confidence that one of these instruments is to know the sensitivity of stock return to variables such as risk premium, size, asset growth, liquidity and ratio of book value to the value of stock market. In spite of their various limitations, use of economical instruments is widely common among investors in stock exchange. In addition, it can be established a relationship between market liquidity/asset and company liquidity despite different focus of these approaches. Since the only way of responding to financial obligations is the ability for cash payment and availability of cash, the capability of the company for quick sale of its assets is very important to keep cash. Hence, if a company keeps a large part of its general assets as current asset, it can be regarded COPY RIGHT 2013 Institute of Interdisciplinary Business Research 547

3 as liquidated in comparison with other companies. In other words, a company who keeps sufficient shares of liquidated assets can be a liquidated company. The access to liquidated assets is crucial but it is not the only determinant in the company's ability to pay for financial obligations. Structure of liabilities and credit resources is highly independent of assets supply capability in market, but they affect company cash. However, cash availability is important for both approaches (Mouraski, 2008, p. 28). Theoretical literature: Usual models for predicting stock return include pricing model of capital assets, market model, Arbitrage pricing theory and factorial model. Empirical studies conducted on factors influencing stock return in different countries show that there are several variables that can predict stock return with a high accuracy. Some of these variables include company size, book value per share to the market value per share ratio, total asset growth and liquidity. Fama and French (1992) in their paper titled: Company size, ratio of liability to shareholders equity, between the profit to price per share ratio, and book value to market value ratio and beta showed that the positive relationship between Beta and return average proved in the past is the result of the negative correlation between size and Beta. When this correlation is taken into consideration the relationship between Beta and return is faded away. For other variables, they COPY RIGHT 2013 Institute of Interdisciplinary Business Research 548

4 concluded that book value to market value ratio and company size has most relationship with return. The ability to explain other variables is reduced to a great extent (almost faded away) due to these two variables. Average stock cross sectional return is readily explained by these two variables. Barber and Lion (1997) conducted a research titled: Company size, book value to market value ratio and securities return: sample excluded from financial companies. Their research was based on Fama and French s study (1992). They investigated the return of a sample of financial institutes, which Fama and French had excluded from their analyses. Evidences indicated that company size and book value to market value ratio describes significantly the cross sectional changes in securities return. In financial literature, stock liquidity is an important factor the effect of which may be examined on stock cross sectional return. Amihad and Mendelson (1986), Brennan et al. (1998, 2004), Cherida et al (2006) confirmed the negative relationship between stock return and its liquidity level. Moreover, liquidity varies over time. This means that investors are not sure how much they will spend on future transactions requiring the sale of an asset. In addition, as liquidity affects the price rate, liquidity frictions can influence the variability of its assets price (Amihad et al., 2005, p. 26). Udin (2009) examined the relationship between stock return and its liquidity via a relative measure that links the individual stock liquidity to the whole market COPY RIGHT 2013 Institute of Interdisciplinary Business Research 549

5 liquidity. His study took from January 1966 to December 1995 and the intended data were collected from ordinary stocks in New York Stock Exchange and USA Stock Exchange. The study results showed that there was a negative relationship between extra return of stocks and relative measure of liquidity but this relationship was nonlinear. Results also proved that the relationship between relative measure of liquidity and extra return of stocks is negative. This result differs from that obtained by Cherida et al (2001). But this case can be explained by the nature of liquidity relative measure because this measures considers both stock liquidity and market liquidity and if investors do not pay attention to liquidity fluctuations and just to the average liquidity of market fluctuations, then the liquidity risk may not be explained by market liquidity fluctuations (Udin, 2009). In another research by Khodadadi and Nejadhosseini (2011), the relationship between accounting variables and stock return was investigated by the augmented Fama and French model. Results indicated that the relationship between asset growth and stock return is similar to the results obtained by Garry and Johnson (2010) and Cooper et al. (2008). Research Methodology: Considering the research objective, this is an applied research. The objective of applied research is to develop the applied knowledge in a certain case. In other words, applied studies lead to scientific application of knowledge. Moreover, this COPY RIGHT 2013 Institute of Interdisciplinary Business Research 550

6 study is descriptive- as it leads to more identification of current conditions and contributing to the decision making process- and it is correlational. The population consists of all companies listed on the Tehran Stock Exchange including 454companies of 39 industries. Considering the research topic, all firms having the following conditions were selected: 1. Firms which are active. 2. Firms which fiscal year ended March 20th. 3. Firms with accessible information from March 21 st, 2001 to 20, In other words, all statistical population will be used in this study. Saham 2 software and websites of Tehran Stock Exchange including sena.ir, rdis.ir, irbours.com, etc. will be used for data collection. It is noteworthy that Saham 2 software is an online software supported by Tadbirpardaz institute and provide users with data and information on companies listed on the stock exchange. The spatial domain of this research includes all companies enlisted in Tehran Stock Exchange and the temporal domain is from March 21 st, 2001 to 20, Time series regression model, cross sectional regression and descriptive methods will be used to examine the relationship between independent and dependent variables. Moreover, E-views and Excel software will be used for data analysis. COPY RIGHT 2013 Institute of Interdisciplinary Business Research 551

7 The spatial location of the object of study includes firms listed on the Tehran Stock Exchange who were active from 2001 through Table 1: A Sample of Companies Listed in Tehran Stock Exchange Year Industry Groups Num. % Auto Radio & TV Manufacture of metal Other mineral products Cement Basic metals Sugar Ceramic Rubber& plastic Machinery and equipment Electric machines Chemical Food Textiles Pharmaceutical /136 /009 /036 /063 /072 /063 /045 /063 /045 /072 /027 /072 /118 /027 /145 Total Research model and hypotheses: Three-factorial model of Fama and French is considered as one of the common models for investigation of portfolio performance based on risk-based adjusted return. In addition to three factors of market, size and ratio of book value to market value, rate of asset growth also was added as the forth factor to the model of the study. And the liquidity was added as the forth factor to model 2. COPY RIGHT 2013 Institute of Interdisciplinary Business Research 552

8 Research Hypotheses: 1- Risk premium is significantly related to stock return. 2- Company size is significantly related to stock return. 3- Book value to market value ratio (B/M ratio) is significantly related to stock return. 4- Total asset growth is significantly related to stock return. 5- Liquidity is significantly related to stock return. 6- Relationship between asset growth and stock return is more than that of the liquidity and stock return. Technical terms (conceptual and operational) 1- Relative measure of liquidity In general, liquidity is described as the ability for a large number of transactions taking place at high speed, low cost and low price effect. This definition determines some dimensions for liquidity i.e. the number of transactions, transaction speed, transaction cost and price effect (Lio, 2006). In this study, we use the relative measure of liquidity defined by Udin (2009) that considers the number of liquidity transaction. The relative measure of liquidity links the individual stock liquidity to the average market liquidity and can determine the liquidity risk. COPY RIGHT 2013 Institute of Interdisciplinary Business Research 553

9 This is defined as: RMLj,t: relative measure of stock liquidity j in month t TVj, t: turnover volume of stock j in month t ATVN-1, t: average turnover volume of all other stocks except stock j 2. Asset growth Changes in the right part of balance sheet are termed asset growth. Different indices are used to calculate asset growth. In this study, asset growth is calculated as follows (Garry & Johnson, 2010): Total asset growth= asset in n-1 year/asset in n-1 year- company asset in year n. Hypothesis testing: below: Results of model estimation by data fusion method are as shown in table Table 2. Combined data model (H4 Testing) Variable Coefficient p-value R- squared Adjusted R-squared F-statistic Prob(Fstatistic Durbin- Watson stat C RM-RF SMB HML AG COPY RIGHT 2013 Institute of Interdisciplinary Business Research 554

10 Results obtained from combined model show that F statistic is ; therefore, with a confidence coefficient of 95% it can be said that variables all assuming the value zero simultaneously is rejected and the model is significant. Durbin Watson statistic is , therefore error terms assuming correlation is rejected at the 5% significance level. The adjusted coefficient of determination of the model is 0/144074, i.e. 14% of dependent variables are explained by independent variables. According to the results of model estimation, the value of the explanatory variable coefficient of the asset growth coefficient is and is significant at the 5% significance level. Therefore, H1 is not rejected at the 95% significance level Results of the model estimate by data fusion method are as shown in table below: Table 3. Combined data model (H5 Testing) Variable Coefficient p-value R- squared Adjusted R-squared F-statistic Prob(Fstatistic Durbin- Watson stat C RM-RF SMB HML RML COPY RIGHT 2013 Institute of Interdisciplinary Business Research 555

11 Results obtained from combined model show that F statistic is ; therefore, with a confidence coefficient of 95% it can be said that variables all assuming the value zero simultaneously is rejected and the model is significant. Durbin Watson statistic is , therefore error terms assuming correlation is rejected at the 5% significance level. The adjusted coefficient of determination of the model is 0/139168, i.e. 13.9% of dependent variables are explained by independent variables. According to the results of model estimation, the value of the explanatory variable coefficient of the liquidity coefficient is and is significant at the 5% significance level. Therefore, H1 is not rejected at the 95% significance level. By comparison of the results of H4 and H5 and, also, using these two factors together via Fama and French model, it is concluded that the rate of correlation between liquidity and stock return is higher (32%) and there is a relationship between asset growth and stock return (10%). Applied recommendations: In addition to examine the changes in economic macro and micro variables including domestic products growth, exchange rate, periodic structure of interest rates and industrial productions, investors must pay attention to other factors such as company asset growth, liquidity level, company size and changes in other accounting items of the company in their decision criteria. Variables studied in this COPY RIGHT 2013 Institute of Interdisciplinary Business Research 556

12 research are significantly related with only a number of companies listed on the Tehran Stock Exchange. Investors, by identifying these companies, can make decisions to or not to invest in the above-mentioned companies' stocks. Stock exchange agencies must consider the relationship of changes in variables studied in companies listed on the Tehran Stock Exchange and to guide investors for selecting optimal portfolio. Limitations of the study: The researcher must explain the limitations of the study clearly and exactly. If researchers describe their study limitations, many incorrect interpretations will not be offered due to lack of limitations of the study. Thus, the limitations of the present study are summarized below: 1. Difficulty in getting information required by the study in financial information of companies listed on the Tehran Stock Exchange resulted in excluding many companies from the research statistical sample. 2. Since the statistical population of this research includes the firms enlisted on the Tehran Stock Exchange, the generalization of results to companies excluded from the stock exchange will encounter limitations. COPY RIGHT 2013 Institute of Interdisciplinary Business Research 557

13 References Amihud, Y. Mendelson, H. and Pedersen, L.H., Liquidity and asset prices. [pdf] America: nowpublishers. Available at: Amihud, Y. and H. Mendelson (1986), Asset pricing and the bid-ask spread. Journal of Financial Economics 17, Barber, Brand M., and John d. Lyon(1997), firm Size, Book- to Market Ratio, and Security Returns: A Holdout sample of financial firms, The Journal of finance 52,pp Brennan, M.J., Chordia, T. and Subrahmanyam, A., Alternative factor specifications, security characteristics, and the crosssection of expected stock returns. Journal of Financial Economics, 49, PP Chordia, T., and S. Lakshmanan, Earnings and price momentum. Journal of Financial Economics 80: Chordia, T., A. Subrahmanyam and V. R. Anshuman (2001), Trading activity and expected stockreturns. Journal of Financial Economics 59, Cooper, M.J., Gulen, H., Schill, M.J., Asset growth and the crosssection of stock returns. Journal of Finance 63, Fama, E., French, K., The cross-section of expected stock returns. Journal of Finance, 47(2), pp COPY RIGHT 2013 Institute of Interdisciplinary Business Research 558

14 Morawski, J, Investment decisions on illiquid assets: A Search Theoretical Approach to Real Estate Liquidity. [pdf] Germany: Gabler GWV Fachverlage GmbH. Available at: Nejadhooseini, M, Asset growth and the crosssection of stock returns. Philip G. Jessica J. (2010), The relationship between Asset Growth and the cross section of stock returns. Journal of Banking&Finance35 pp Uddin, M., Reexamination of stock liquidity risk with a relative measure. Studies in Economics and Finance, 26, PP COPY RIGHT 2013 Institute of Interdisciplinary Business Research 559