Liquidity and firm performance the case of vietnam

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Liquidity and firm performance   the case of vietnam

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MINISTRY OF EDUCATION AND TRAINING UNIVERSITY OF ECONOMICS HOCHIMINH CITY -o0o - EÂ1 BÙI HỒNG THU LIQUIDITY AND FIRM PERFORMANCE: THE CASE OF VIETNAM MASTER OF BUSINESS ADMINISTRATION HO CHI MINH CITY, 2012 MINISTRY OF EDUCATION AND TRAINING UNIVERSITY OF ECONOMICS HOCHIMINH CITY -o0o - EÂ1 BÙI HỒNG THU LIQUIDITY AND FIRM PERFORMANCE : THE CASE OF VIETNAM MAJOR: BUSINESS ADMINISTRATION MAJOR CODE: 60.34.05 MASTER THESIS SUPERVISOR : Dr VÕ XUÂN VINH HO CHI MINH CITY, 2012 i ACKNOWLEDGEMENT I owe my deepest gratitude to my supervisor, Dr Vo Xuan Vinh, who with his wide research experience, suggested this topic to me Without his continuous support, encouragement, and enthusiasm, this research would hardly have been completed I am indebted to Dr Tran Ha Minh Quan for his immeasurable amount of support and guidance during MBA course and this thesis I would like to thank M.Sc Nguyen Thanh Trung who willingly provided me with much assistance and encouragement during MBA course I would like to thank Assistant Professor Nguyen Dinh Tho, Dr Tran Ha Minh Quan, Dr Pham Quoc Hung, Dr Nguyen Thi Mai Trang, Dr Nguyen Thi Nguyet Que for their valuable time as members of examination committee Their comments and advices are precious instruction for me to complete this thesis I also express my warmest gratitude to my professors at Faculty of Business Administration and Postgraduate Faculty, University of Economics Hochiminh City for their teaching and guidance during my MBA course I wish to thank warmly my classmates who show their teamwork spirit and willingness to help each other to complete our theses Finally, this thesis is dedicated to my beloved wife who understands, encourages, and is patient especially in the difficult period of taking care of our newborn baby during my working ii ABSTRACT This thesis aims to investigate the relation between liquidity and firm performance in Vietnam stock market The debate on this topic is still open when many papers point out that there is a positive correlation and many researches show the opposite The number of researches that support for result of positive correlation is likely to be dominant This paper shows the negative correlation between liquidity and firm performance in Vietnam stock market; however, the result is not consistent over time The paper also finds that liquidity has a negative correlation with financial leverage and this implies that highly liquid firm tends to seek capital from the banks or bond issues Besides, there is a negative correlation between liquidity and operating income on assets indicating that illiquid firm tends to focus more on corporate monitoring and has more profitability When examining the correlation further on each industry separately, we find that this correlation is only on five industries Keywords: Liquidity, firm performance, operating income to price, financial leverage, operating income on assets, Vietnam iii CONTENTS ACKNOWLEDGEMENT i ABSTRACT ii LIST OF TABLES v ABBREVIATIONS vi CHAPTER 1: INTRODUCTION 1.1 BACKGROUND 1.2 RESEARCH PROBLEM 1.3 RESEARCH OBJECTIVE 1.4 RESEARCH METHODOLOGY AND SCOPE 1.4 STRUCTURE OF RESEARCH CHAPTER 2: LITERATURE REVIEW 2.1 INTRODUCTION 2.2 LIQUIDITY 2.2.1 Bid-ask spread 2.2.2 Turnover ratio 2.2.3 Trading volume 2.2.4 Daily zero return 2.2.5 Amihud illiquidity ratio 10 2.3 FIRM PERFORMANCE 10 2.4 LIQUIDITY AND FIRM PERFORMANCE 13 CHAPTER 3: RESEARCH MODEL 18 3.1 INTRODUCTION 18 3.1 VARIABLE CONSTRUCTION 18 3.1.1 Liquidity measures 18 3.1.2 Firm performance 19 3.1.3 Control variables 20 iv 3.2 MODEL 21 CHAPTER 4: DATA AND RESEARCH METHODS 24 4.1 INTRODUCTION 24 4.2 DATA 24 4.3 RESEARCH METHODS 25 CHAPTER 5: RESULTS AND DISCUSSION 26 5.1 INTRODUCTION 26 5.1 DESCRIPTIVE STATISTICS AND CORRELATIONS 26 5.2 REGRESSION ANALYSIS RESULTS 29 5.2.1 Baseline Q specification 29 5.2.2 Baseline specification – components of Q 32 5.2.3 Baseline Q specification by industry 35 CHAPTER 6: CONCLUSIONS 37 6.1 INTRODUCTION 37 6.2 CONCLUSIONS 37 REFERENCES 40 APPENDIX A 44 APPENDIX B 45 APPENDIX C 46 v LIST OF TABLES Table 4.1: Variable definition 22 Table 6.1: Summary statistics 26 Table 6.2: Correlation matrix 27 Table 6.3: Ordinary least squares regressions for the model 29 Table 6.4: Ordinary least squares regressions for the components of Q .32 Table 6.5: Ordinary least squares regressions for Q by Industry 35 vi ABBREVIATIONS HOSE Hochiminh Stock Exchange OIP Operating income to price LEVERAGE Financial leverage OIOA Operating income on total assets LIQ_TR Liquidity measured by turnover AGE Firm‟s age BVTA Book value of total assets IDIORISK Idiosyncratic risk CUMRET Cumulative return OLS Ordinary least squares CHAPTER 1: INTRODUCTION 1.1 BACKGROUND Liquidity is one of the important factors that investors consider when they make decision on investment As defined by Amihud and Mendelson (2008), liquidity is the capacity of the assets that can be traded quickly and at low cost According to Fang et al (2009), the stock shares are the currency which commands both cash flows and control rights, the tradability of this currency plays a central role in the governance, valuation, and performance of firms The relation between liquidity and firm value is firstly documented by Amihud and Mendelson (1986) After this study, this relation draws more attention from other scholars There are many theoretical researches on this relation; most of them support the positive relation and few researches suggest negative relation In research indicating positive relation, liquidity supports the large shareholders to invest in large stake to become more majorities in voting contests; it leads to effective corporate governance (Maug, 1998), attracts the entry of the informed investors, in turn, this makes the price more informative and improve the decision of the firm managers, especially the firm with the uncertainty of cash flow in existing and future projects (Subrahmanyam and Titman, 2001; Khanna and Sonti, 2004) Moreover, liquidity makes investors trade at higher prices than more illiquid stocks (Holmstrom and Tirole, 1993), causes investors trade at a premium because liquid stocks are overvalued due to the liquidity could be a sentiment indicator (Baker and Stein, 2004), reduces managerial opportunism because investors invest on the fundamental value of the stocks (Edmans, 2009) There are few research studies on negative relation, which conclude that liquid stocks facilitate the exit of shareholders, therefore, they not want to monitor firm performance and leads to worse firm performance (Coffee, 1991), investors not want to sell when the cost of monitoring is not covered and it causes the illiquidity in stock and better firm performance (Bhide, 1993), the speculators use liquidity as a mean to make profit in manipulating price down (Goldstein and Guembel, 2008) Hence, there are many papers on both positive and negative relation between liquidity and firm performance; however, most of these papers are about the theoretical models One of the first empirical papers investigating this relation is written by Fang et al (2009) supporting the positive relation between liquidity and firm performance in US stock market They use relative effective spreads as liquidity proxy and Tobin Q for measuring the firm performance The result is robust when they use alternative liquidity proxies: Amihud (2002) mean-adjusted illiquidity measure; the Lesmond et al (1999) percentage of zero daily returns liquidity measure; and the relative quoted spread Their findings support the theory of stock-price feedback effect and performance-sensitive managerial compensation causality 40 REFERENCES Amihud, Y., 2002 Illiquidity and stock returns: cross-section and time-series effects Journal of Financial Markets, 5, pp.31-56 Amihud, Y and Mendelson, H., 1986 Liquidity and Stock Returns Financial Analysts Journal, 42, pp.43-48 Amihud, Y and Mendelson, H., 2008 Liquidity, the Value of the Firm, and Corporate Finance Journal of Applied Corporate Finance, 20, pp.32-45 Baker, M and Stein, J C., 2004 Market liquidity as a sentiment indicator Journal of Financial Markets, Bekaert, G., Harvey, C R and Lundblad, C., 2006 Liquidity and Expected Returns: Lessons from Emerging Markets Bhide, A., 1993 The hidden costs of stock market liquidity Journal of Financial Economics, 34, pp.31-51 Brennan, M J., Chordia, T and Subrahmanyam, A., 1998 Alternative factor specifications, security characteristics, and the cross-section of expected stock returns Journal of Financial Economics, 49, pp.345-373 Brennan, M J and Subrahmanyam, A., 1996 Market microstructure and asset pricing: On the compensation for illiquidity in stock returns Journal of Financial Economics, 41, pp.441-464 Chan, H W and Faff, R W., 2003 An investigation into the role of liquidity in asset pricing: Australian evidence Pacific-Basin Finance Journal, 11, pp.555-572 Chordia, T., Subrahmanyam, A and Anshuman, V R., 2001 Trading activity and expected stock returns Journal of Financial Economics, 59, pp.3-32 Coffee, J C., 1991 Liquidity versus control: The institutional investor as corporate monitor Columbia Law Review, 91, pp.1277-1368 Connolly, T., Conlon, E J and Deutsch, S J., 1980 Organizational Effectiveness: A Multiple-Constituency Approach The Academy of Management Review, 5, pp.211217 41 Datar, V T., Naik, N Y and Radcliffe, R., 1998 Liquidity and stock returns: An alternative test Journal of Financial Markets, 1, pp.203-219 Demsetz, H and Lehn, K., 1985 The Structure of Corporate Ownership: Causes and Consequences Journal of Political Economy, 93, pp.1155-1177 Edmans, A., 2009 Blockholder Trading, Market Efficiency, and Managerial Myopia Journal of Finance, Forthcoming Eleswarapu, V R and Reinganum, M R., 1993 The seasonal behavior of the liquidity premium in asset pricing Journal of Financial Economics, 34, pp.373-386 Etzioni, A 1964 Modern Organizations, Englewood Cliffs, Prentice-Hall Fang, V W., Noe, T H and Tice, S., 2009 Stock market liquidity and firm value Journal of Financial Economics, 94, pp.150-169 Goldstein, I and Guembel, A., 2008 Manipulation and the Allocational Role of Prices Review of Economic Studies, 75, pp.133–164 Gompers, P A., Ishii, J L and Metrick, A., 2003 Corporate governance and equity prices Quarterly Journal of Economics, 118, pp.107-155 Gutierrez, R C and Prinsky, C A., 2007 Momentum, reversal, and the trading behaviors of institutions Journal of Financial Markets, 10, pp.48-75 Hitt, M A., 1988 The Measuring of Organizational Effectiveness: Multiple Domains and Constituencies Management International Review, 28, pp.28-40 Holmstrom, B and Tirole, J., 1993 Market Liquidity and Performance Monitoring The Journal of Political Economy, 101, pp.678-709 Kaplan, S N and Zingales, L., 1997 Do investment-cash flow sensitivities provide useful measures of financing constraints? The Quarterly Journal of Economics, 112, pp.169-216 Khanna, N and Sonti, R., 2004 Value creating stock manipulation: feedback effect of stock prices on firm value Journal of Financial Markets, 7, pp.237-270 Kudla, R J., 1980 The Effects of Strategic Planning on Common Stock Returns The Academy of Management Journal, 23, pp.5-20 42 Lee, C M C., 1993 Market Integration and Price Execution for NYSE-Listed Securities The Journal of Finance 48, pp.1009-1038 Lesmond, D A., Ogden, J P and Trzcinka, C A., 1999 A New Estimate of Transaction Costs The Review of Financial Studies, 12, pp.1113–1141 Liu, W., 2006 A liquidity-augmented capital asset pricing modelstar, open Journal of Financial Economics, 82, pp.631-671 Maug, E., 1998 Large Shareholders as Monitors: Is There a Trade-Off between Liquidity and Control? The Journal of Finance, 53, pp.65-98 Mehran, H., 1995 Executive compensation structure, ownership, and firm performance Journal of Financial Economics, 38, pp.163-184 Merton, R C., 1987 A Simple Model of Capital Market Equilibrium with Incomplete Journal of Finance, 42, pp.483-510 Montgomery, C A., Thomas, A R and Kamath, R., 1984 Divestiture, Market Valuation, and Strategy The Academy of Management Journal, 27, pp.830-840 Murphy, G B., Trailer, J W and Hill, R C., 1996 Measuring Research Performance in Entrepreneurship Journal of Business Research, 36, pp.15-23 Parhizgari, A M and Gilbert, G R., 2004 Measures of organizational e ectiveness: private and public sector performance Omega, 32, pp.221 – 229 Pastor, L and Stambaugh, R F., 2003 Liquidity risk and expected stock returns The Journal of Political Economy, 111, pp.642-685 Shin, H.-H and Stulz, R M., 2000 Firm Value, Risk, and Growth Opportunities NBER Working Paper, 7808 Spiegel, M and Wang, X 2005 Cross-sectional Variation in Stock Returns: Liquidity and Idiosyncratic Risk Yale University and Penn State University Steers, R M., 1975 Problems in the Measurement of Organizational Effectiveness Administrative Science Quarterly, 20, pp.546-558 Subrahmanyam, A and Titman, S., 2001 Feedback from Stock Prices to Cash Flows The Journal of Finance,, 56, pp.2389-2413 43 Venkatraman, N and Ramanujam, V., 1986 Measurement of Business Performance in Strategy Research: A Comparison of Approaches The Academy of Management Review, 11, pp.801-814 Zammuto, R F., 1984 A Comparison of Multiple Constituency Models of Organizational Effectiveness The Academy of Management Review, 9, pp.606-616 44 APPENDIX A components of Tobin’s Q where Q Tobin‟s Q Ve: market value of Equity, Vl: market value of Liabilities, OpInc: operating income, Assets: total assets, OIP: operating income to price, LEVERAGE: financial leverage, OIOA: operating income on assets 45 APPENDIX B Industry Classification Industry Code Industry name A Agriculture, forestry and fisheries B Mining C Processing and manufacturing Production and distribution of electricity, gas, water heater, D water steam and air conditioning Water supply, operation and management waste disposal, waste E water F Construction Wholesale and retail; repairing automobiles, motorcycles and G other motors H Transportation and logistics I Accommodation and food services J Information and telecommunication K Finance, banking and insurance L Real estate M Professional activities, science and technology N Operating and administrative support services R Entertainment services 46 APPENDIX C Multiple Regression Results Dependent Variable: Q Method: Least Squares Date: 04/24/12 Time: 23:28 Sample: 573 Included observations: 573 Variable Coefficient Std Error t-Statistic Prob C LIQ_TR LN_AGE LN_BVTA CUMRET IDIORISK 3.143143 -0.216644 -0.001600 -0.127713 0.666514 3.458104 0.559292 0.036975 0.063528 0.034886 0.121092 0.919589 5.619861 -5.859208 -0.025187 -3.660836 5.504185 3.760489 0.0000 0.0000 0.9799 0.0003 0.0000 0.0002 R-squared Adjusted R-squared S.E of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic) 0.137195 0.129587 1.032251 604.1627 -828.2242 18.03186 0.000000 Mean dependent var S.D dependent var Akaike info criterion Schwarz criterion Hannan-Quinn criter Durbin-Watson stat 1.443563 1.106427 2.911777 2.957336 2.929549 1.501784 Dependent Variable: Q Method: Least Squares Date: 04/24/12 Time: 23:29 Sample: 573 IF YEAR = 2007 Included observations: 85 Variable Coefficient Std Error t-Statistic Prob C LIQ_TR LN_AGE LN_BVTA CUMRET IDIORISK 0.028955 -0.366959 0.112587 0.078366 -1.465701 18.01503 3.019523 0.302423 0.267668 0.195138 0.608046 3.329907 0.009589 -1.213396 0.420623 0.401594 -2.410509 5.410070 0.9924 0.2286 0.6752 0.6891 0.0183 0.0000 R-squared Adjusted R-squared S.E of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic) 0.281242 0.235751 1.689463 225.4886 -162.0736 6.182355 0.000069 Mean dependent var S.D dependent var Akaike info criterion Schwarz criterion Hannan-Quinn criter Durbin-Watson stat 2.707168 1.932552 3.954672 4.127094 4.024025 2.110730 47 Dependent Variable: Q Method: Least Squares Date: 04/24/12 Time: 23:30 Sample: 573 IF YEAR = 2008 Included observations: 127 Variable Coefficient Std Error t-Statistic Prob C LIQ_TR LN_AGE LN_BVTA CUMRET IDIORISK 1.393793 -0.156125 0.008066 0.001575 0.390884 -0.918366 0.883568 0.105441 0.086237 0.058559 0.237352 1.551563 1.577460 -1.480683 0.093533 0.026896 1.646848 -0.591897 0.1173 0.1413 0.9256 0.9786 0.1022 0.5550 R-squared Adjusted R-squared S.E of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic) 0.038719 -0.001003 0.699263 59.16514 -131.7004 0.974746 0.436109 Mean dependent var S.D dependent var Akaike info criterion Schwarz criterion Hannan-Quinn criter Durbin-Watson stat 1.157913 0.698912 2.168511 2.302882 2.223104 1.931638 Dependent Variable: Q Method: Least Squares Date: 04/24/12 Time: 23:30 Sample: 573 IF YEAR =2009 Included observations: 152 Variable Coefficient Std Error t-Statistic Prob C LIQ_TR LN_AGE LN_BVTA CUMRET IDIORISK 2.138365 -0.137089 0.080823 -0.074575 0.691276 0.409652 0.802643 0.040460 0.084876 0.049090 0.155056 1.269308 2.664153 -3.388293 0.952241 -1.519144 4.458244 0.322737 0.0086 0.0009 0.3425 0.1309 0.0000 0.7474 R-squared Adjusted R-squared S.E of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic) 0.180899 0.152848 0.701813 71.91099 -158.7964 6.448853 0.000019 Mean dependent var S.D dependent var Akaike info criterion Schwarz criterion Hannan-Quinn criter Durbin-Watson stat 1.349229 0.762501 2.168373 2.287737 2.216863 0.138526 48 Dependent Variable: Q Method: Least Squares Date: 04/24/12 Time: 23:31 Sample: 573 IF YEAR =2010 Included observations: 209 Variable Coefficient Std Error t-Statistic Prob C LIQ_TR LN_AGE LN_BVTA CUMRET IDIORISK 4.045450 -0.090847 -0.084330 -0.163298 1.307107 0.034403 0.432515 0.033973 0.054475 0.026497 0.177841 1.028211 9.353310 -2.674063 -1.548066 -6.162805 7.349846 0.033459 0.0000 0.0081 0.1232 0.0000 0.0000 0.9733 R-squared Adjusted R-squared S.E of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic) 0.310281 0.293293 0.502455 51.24951 -149.6700 18.26456 0.000000 Mean dependent var S.D dependent var Akaike info criterion Schwarz criterion Hannan-Quinn criter Durbin-Watson stat 1.171841 0.597692 1.489665 1.585617 1.528459 1.325334 Dependent Variable: OIP Method: Least Squares Date: 04/24/12 Time: 23:32 Sample: 573 Included observations: 573 Variable Coefficient Std Error t-Statistic Prob C LIQ_TR LN_AGE LN_BVTA CUMRET IDIORISK 0.141303 0.004859 -0.004929 0.000610 0.010940 -0.241314 0.125900 0.008323 0.014300 0.007853 0.027259 0.207005 1.122342 0.583833 -0.344669 0.077683 0.401345 -1.165741 0.2622 0.5596 0.7305 0.9381 0.6883 0.2442 R-squared Adjusted R-squared S.E of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic) 0.002893 -0.005900 0.232366 30.61446 26.22509 0.329034 0.895492 Mean dependent var S.D dependent var Akaike info criterion Schwarz criterion Hannan-Quinn criter Durbin-Watson stat 0.118902 0.231683 -0.070594 -0.025035 -0.052822 1.669893 49 Dependent Variable: LEVERAGE Method: Least Squares Date: 04/24/12 Time: 23:34 Sample: 573 Included observations: 573 Variable Coefficient Std Error t-Statistic Prob C LIQ_TR LN_AGE LN_BVTA CUMRET IDIORISK 1.303070 -0.045037 -0.002245 -0.046123 0.193426 -0.214428 0.116668 0.007713 0.013252 0.007277 0.025260 0.191825 11.16907 -5.839148 -0.169430 -6.337975 7.657478 -1.117830 0.0000 0.0000 0.8655 0.0000 0.0000 0.2641 R-squared Adjusted R-squared S.E of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic) 0.163576 0.156200 0.215327 26.28929 69.86218 22.17721 0.000000 Mean dependent var S.D dependent var Akaike info criterion Schwarz criterion Hannan-Quinn criter Durbin-Watson stat 0.588218 0.234411 -0.222905 -0.177346 -0.205133 1.014274 Dependent Variable: OIOA Method: Least Squares Date: 04/24/12 Time: 23:35 Sample: 573 Included observations: 573 Variable Coefficient Std Error t-Statistic Prob C LIQ_TR LN_AGE LN_BVTA CUMRET IDIORISK 0.167458 -0.010862 0.005865 -0.005743 0.067212 -0.091358 0.048042 0.003176 0.005457 0.002997 0.010402 0.078990 3.485666 -3.420045 1.074846 -1.916622 6.461786 -1.156576 0.0005 0.0007 0.2829 0.0558 0.0000 0.2479 R-squared Adjusted R-squared S.E of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic) 0.084407 0.076333 0.088668 4.457750 578.2614 10.45419 0.000000 Mean dependent var S.D dependent var Akaike info criterion Schwarz criterion Hannan-Quinn criter Durbin-Watson stat 0.083409 0.092259 -1.997422 -1.951863 -1.979650 1.323111 50 Dependent Variable: Q Method: Least Squares Date: 04/24/12 Time: 23:38 Sample: 573 IF IND = "A" Included observations: 21 Variable Coefficient Std Error t-Statistic Prob C LIQ_TR LN_AGE LN_BVTA CUMRET IDIORISK 3.868958 -0.783111 -0.480190 -0.028552 1.672273 16.21114 6.437347 0.598426 0.370888 0.479748 1.088655 10.09150 0.601017 -1.308618 -1.294704 -0.059514 1.536091 1.606415 0.5568 0.2104 0.2150 0.9533 0.1453 0.1290 R-squared Adjusted R-squared S.E of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic) 0.389431 0.185909 1.302862 25.46173 -31.82058 1.913453 0.151666 Mean dependent var S.D dependent var Akaike info criterion Schwarz criterion Hannan-Quinn criter Durbin-Watson stat 2.555004 1.443982 3.601960 3.900395 3.666728 2.268668 Dependent Variable: Q Method: Least Squares Date: 04/24/12 Time: 23:38 Sample: 573 IF IND = "B" Included observations: 17 Variable Coefficient Std Error t-Statistic Prob C LIQ_TR LN_AGE LN_BVTA CUMRET IDIORISK -3.618429 -0.306064 1.692736 -0.033279 1.538565 31.69372 4.740364 0.297483 0.586026 0.273863 1.168694 4.676491 -0.763323 -1.028845 2.888498 -0.121516 1.316482 6.777243 0.4613 0.3256 0.0147 0.9055 0.2148 0.0000 R-squared Adjusted R-squared S.E of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic) 0.872785 0.814960 1.440948 22.83964 -26.63187 15.09351 0.000132 Mean dependent var S.D dependent var Akaike info criterion Schwarz criterion Hannan-Quinn criter Durbin-Watson stat 2.773427 3.349769 3.839044 4.133119 3.868275 2.377375 51 Dependent Variable: Q Method: Least Squares Date: 04/24/12 Time: 23:38 Sample: 573 IF IND = "C" Included observations: 232 Variable Coefficient Std Error t-Statistic Prob C LIQ_TR LN_AGE LN_BVTA CUMRET IDIORISK 0.995475 -0.188620 0.019312 0.050544 0.757839 -0.415898 0.917202 0.049014 0.084468 0.059659 0.154140 1.240696 1.085338 -3.848283 0.228628 0.847216 4.916546 -0.335214 0.2789 0.0002 0.8194 0.3978 0.0000 0.7378 R-squared Adjusted R-squared S.E of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic) 0.144626 0.125702 0.867554 170.0989 -293.1923 7.642366 0.000001 Mean dependent var S.D dependent var Akaike info criterion Schwarz criterion Hannan-Quinn criter Durbin-Watson stat 1.466727 0.927826 2.579244 2.668383 2.615193 1.132909 Dependent Variable: Q Method: Least Squares Date: 04/24/12 Time: 23:39 Sample: 573 IF IND = "D" Included observations: 27 Variable Coefficient Std Error t-Statistic Prob C LIQ_TR LN_AGE LN_BVTA CUMRET IDIORISK 3.218501 -0.750969 0.259749 -0.207625 -0.187766 12.54189 2.347330 0.312804 0.329445 0.169040 0.881773 6.771343 1.371133 -2.400768 0.788444 -1.228263 -0.212942 1.852201 0.1848 0.0257 0.4392 0.2329 0.8334 0.0781 R-squared Adjusted R-squared S.E of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic) 0.341058 0.184167 0.769761 12.44316 -27.85335 2.173853 0.095989 Mean dependent var S.D dependent var Akaike info criterion Schwarz criterion Hannan-Quinn criter Durbin-Watson stat 1.458572 0.852227 2.507656 2.795619 2.593282 0.736632 52 Dependent Variable: Q Method: Least Squares Date: 04/24/12 Time: 23:39 Sample: 573 IF IND = "F" Included observations: 39 Variable Coefficient Std Error t-Statistic Prob C LIQ_TR LN_AGE LN_BVTA CUMRET IDIORISK -0.849516 -0.144445 0.062734 0.163564 0.675241 -2.870542 1.616439 0.082269 0.169047 0.103118 0.293857 2.066045 -0.525548 -1.755766 0.371104 1.586194 2.297858 -1.389390 0.6027 0.0884 0.7129 0.1222 0.0280 0.1740 R-squared Adjusted R-squared S.E of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic) 0.257830 0.145380 0.540200 9.629934 -28.06424 2.292839 0.067977 Mean dependent var S.D dependent var Akaike info criterion Schwarz criterion Hannan-Quinn criter Durbin-Watson stat 1.047860 0.584343 1.746884 2.002817 1.838711 1.176644 Dependent Variable: Q Method: Least Squares Date: 04/24/12 Time: 23:39 Sample: 573 IF IND = "G" Included observations: 80 Variable Coefficient Std Error t-Statistic Prob C LIQ_TR LN_AGE LN_BVTA CUMRET IDIORISK 5.089380 -0.124468 -0.034205 -0.281836 0.614305 -0.041322 0.903921 0.047821 0.100362 0.069478 0.180829 1.536030 5.630338 -2.602804 -0.340813 -4.056479 3.397160 -0.026902 0.0000 0.0112 0.7342 0.0001 0.0011 0.9786 R-squared Adjusted R-squared S.E of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic) 0.436797 0.398743 0.480077 17.05509 -51.69196 11.47827 0.000000 Mean dependent var S.D dependent var Akaike info criterion Schwarz criterion Hannan-Quinn criter Durbin-Watson stat 1.066655 0.619129 1.442299 1.620951 1.513926 1.455947 53 Dependent Variable: Q Method: Least Squares Date: 04/24/12 Time: 23:40 Sample: 573 IF IND = "H" Included observations: 47 Variable Coefficient Std Error t-Statistic Prob C LIQ_TR LN_AGE LN_BVTA CUMRET IDIORISK 6.272022 -0.253659 -0.064350 -0.326360 0.744460 -0.578337 1.247095 0.079820 0.158297 0.077518 0.254060 2.235488 5.029304 -3.177881 -0.406513 -4.210113 2.930248 -0.258707 0.0000 0.0028 0.6865 0.0001 0.0055 0.7972 R-squared Adjusted R-squared S.E of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic) 0.448307 0.381028 0.596933 14.60948 -39.23090 6.663349 0.000126 Mean dependent var S.D dependent var Akaike info criterion Schwarz criterion Hannan-Quinn criter Durbin-Watson stat 1.203846 0.758735 1.924719 2.160908 2.013599 1.535831 Dependent Variable: Q Method: Least Squares Date: 04/24/12 Time: 23:40 Sample: 573 IF IND = "K" Included observations: 18 Variable Coefficient Std Error t-Statistic Prob C LIQ_TR LN_AGE LN_BVTA CUMRET IDIORISK 6.225305 0.165791 -0.186049 -0.288166 1.368257 -0.227111 1.316956 0.115794 0.214318 0.076067 0.335987 4.674526 4.727041 1.431779 -0.868096 -3.788328 4.072351 -0.048585 0.0005 0.1777 0.4024 0.0026 0.0015 0.9620 R-squared Adjusted R-squared S.E of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic) 0.836661 0.768603 0.382821 1.758625 -4.608340 12.29334 0.000222 Mean dependent var S.D dependent var Akaike info criterion Schwarz criterion Hannan-Quinn criter Durbin-Watson stat 0.923515 0.795824 1.178704 1.475495 1.219628 0.822377 54 Dependent Variable: Q Method: Least Squares Date: 04/24/12 Time: 23:43 Sample: 573 IF IND = "L" Included observations: 43 Variable Coefficient Std Error t-Statistic Prob C LIQ_TR LN_AGE LN_BVTA CUMRET IDIORISK 1.576150 -0.103250 -0.240661 0.035170 0.246446 2.338473 2.657755 0.195723 0.306921 0.163874 0.379386 3.079229 0.593038 -0.527530 -0.784111 0.214618 0.649591 0.759434 0.5568 0.6010 0.4380 0.8312 0.5200 0.4524 R-squared Adjusted R-squared S.E of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic) 0.076525 -0.048268 1.087829 43.78478 -61.40321 0.613215 0.690356 Mean dependent var S.D dependent var Akaike info criterion Schwarz criterion Hannan-Quinn criter Durbin-Watson stat 1.614499 1.062489 3.135033 3.380782 3.225658 1.578971 Dependent Variable: Q Method: Least Squares Date: 04/24/12 Time: 23:43 Sample: 573 IF IND = "Other" Included observations: 31 Variable Coefficient Std Error t-Statistic Prob C LIQ_TR LN_AGE LN_BVTA CUMRET IDIORISK 4.154442 0.077245 0.354510 -0.326363 0.439255 3.268060 3.352998 0.131664 0.257084 0.227286 0.469203 2.762320 1.239023 0.586684 1.378964 -1.435910 0.936173 1.183085 0.2268 0.5627 0.1801 0.1634 0.3581 0.2479 R-squared Adjusted R-squared S.E of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic) 0.371295 0.245554 0.874063 19.09966 -36.48019 2.952851 0.031440 Mean dependent var S.D dependent var Akaike info criterion Schwarz criterion Hannan-Quinn criter Durbin-Watson stat 1.427622 1.006303 2.740657 3.018203 2.831130 1.651728 ... the increase of volume of liquidity attracts the entry of the informed investors, in turn, it makes the price more informative and leads to the improvement of the decision of the firm managers,... leads the firm to cancel the project investment, and it results in the decrease of the firm value The above papers suggest the following hypotheses: H1: Liquidity has positive effect on firm performance. .. turnover ratio and of trading volume, and the coefficients of variation of the turnover ratio and of trading volume (Chordia et al., 2001), the Pastor and Stambaugh (2003) liquidity measure, the Amihud

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Mục lục

  • BÌA

  • ACKNOWLEDGEMENT

  • ABSTRACT

  • CONTENTS

  • LIST OF TABLES

  • ABBREVIATIONS

  • CHAPTER 1: INTRODUCTION

    • 1.1 BACKGROUND

    • 1.2 RESEARCH PROBLEM

    • 1.3 RESEARCH OBJECTIVE

    • 1.4 RESEARCH METHODOLOGY AND SCOPE

    • 1.4 STRUCTURE OF RESEARCH

    • CHAPTER 2: LITERATURE REVIEW

      • 2.1 INTRODUCTION

      • 2.2 LIQUIDITY

        • 2.2.1 Bid-ask spread

        • 2.2.2 Turnover ratio

        • 2.2.3 Trading volume

        • 2.2.4 Daily zero return

        • 2.2.5 Amihud illiquidity ratio

        • 2.3 FIRM PERFORMANCE

        • 2.4 LIQUIDITY AND FIRM PERFORMANCE

        • CHAPTER 3: RESEARCH MODEL

          • 3.1 INTRODUCTION

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