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\setlength{\itemindent}{0pt}% \setlength{\parskip}{0pt}% \setlength{\itemsep}{0pt}% \setlength{\parsep}{2pt}% \def\makelabel##1{\upshape ##1}}% } {\end{list}\end{raggedright}} \newenvironment{specHead}[2]% {\vspace{20pt}\hrule\vspace{10pt}% \phantomsection\label{#1}\markright{#2}% \pdfbookmark[2]{#2}{#1}% \hspace{-0.75in}{\bfseries\fontsize{16pt}{18pt}\selectfont#2}% }{} \def\TheFullDate{2013-01-15 (revised: 15 January 2013)} \def\TheID{\makeatother } \def\TheDate{2013-01-15} \title{The Volatility of Market Risk in Groups of Viet Nam Listed Medicine and Medical Company Groups During and after the Financial Crisis 2007-2011} \author{}\makeatletter \makeatletter \newcommand*{\cleartoleftpage}{% \clearpage \if@twoside \ifodd\c@page \hbox{}\newpage \if@twocolumn \hbox{}\newpage \fi \fi \fi } \makeatother \makeatletter \thispagestyle{empty} \markright{\@title}\markboth{\@title}{\@author} \renewcommand\small{\@setfontsize\small{9pt}{11pt}\abovedisplayskip 8.5\p@ plus3\p@ minus4\p@ 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\definecolor{GJMediumGrey}{HTML}{6D6E70} \definecolor{GJLightGrey}{HTML}{929497} \renewenvironment{abstract}{% \setlength{\parindent}{0pt}\raggedright \textcolor{GJMediumGrey}{\rule{\textwidth}{2pt}} \vskip16pt \textcolor{GJBlue}{\large\bfseries\abstractname\space} }{% \vskip8pt \textcolor{GJMediumGrey}{\rule{\textwidth}{2pt}} \vskip16pt } \usepackage[absolute,overlay]{textpos} \makeatother \usepackage{lineno} \linenumbers \begin{document} \author[1]{Dinh Tran Ngoc Huy} \affil[1]{ University of Japan} \renewcommand\Authands{ and } \date{\small \em Received: 13 December 2012 Accepted: 1 January 2013 Published: 15 January 2013} \maketitle \begin{abstract} This survey uses the sample of total 14 listed firms of related medical industry in the Viet Nam economy and especially, the stock exchange which has been affected by the global crisis during the period 2007-2011. Specifically, we perform the risk re-analysis and estimation for the listed firms in Medicine, Medical equipment and Human resource industries.First of all, using quantitative and analytical methods to estimate asset and equity beta values of three (3) groups of sub-medical listed companies in Viet Nam Medicine, Medical equipment and Human resource industries with a suitable traditional model, we found out that the beta values, in general, for most companies are acceptable, excluding a few cases. There are 57% and 71% of listed firms with lower risk, among total 14 firms, whose beta values lower than (<) 1, which is measured by equity and asset beta, accordingly. \end{abstract} \keywords{equity beta, financial structure, financial crisis, risk, asset beta, medical industry.} \begin{textblock*}{18cm}(1cm,1cm) % {block width} (coords) \textcolor{GJBlue}{\LARGE Global Journals \LaTeX\ JournalKaleidoscope\texttrademark} \end{textblock*} \begin{textblock*}{18cm}(1.4cm,1.5cm) % {block width} (coords) \textcolor{GJBlue}{\footnotesize \\ Artificial Intelligence formulated this projection for compatibility purposes from the original article published at Global Journals. However, this technology is currently in beta. \emph{Therefore, kindly ignore odd layouts, missed formulae, text, tables, or figures.}} \end{textblock*} \let\tabcellsep& \section[{Introduction}]{Introduction}\par fter the previous published article on estimated beta for listed construction company groups, here we will compare the estimated beta results of listed Viet Nam medical equipment companies to those in its supply chain activities such as medicine and human resource companies to make a comparative analysis and risk evaluation after financial crisis impacts.\par Although risk estimation can be done by using various research methods. Here, we perform a market risk analysis based on asset and equity beta of total 14 listed companies in the category of medical equipment, medicine and human resource firms. This paper emphasizes on analyzing un-diversifiable risk in the above industry in one of emerging markets: Vietnam stock market during the financial crisis 2007-2011. No research, so far, has been done on the same topic.\par This paper is organized as follow. The research issues and literature review will be covered in next sessions 2 and 3, for a short summary. Next, methodology and conceptual theories are introduced in session 4 and 5. Session 6 describes the data in empirical analysis. Session 7 presents empirical results and findings. Then, session 8 gives analysis of risk. Lastly, session 9 will conclude with some policy suggestions. This paper also provides readers with references, exhibits and relevant web sources. \section[{II.}]{II.} \section[{Research Issues}]{Research Issues}\par We mention a couple of issues on the estimating of beta for listed medical equipment, medicine and human resource companies in Viet Nam stock exchange as following:\par Hypothesis/Issue 1: Among the three (3) companies groups, under the financial crisis impact and high inflation, the beta or risk level of listed companies in human resource industries will relatively higher than those in the rest two (2) industries.\par Hypothesis/Issue 2: Because Viet Nam is an emerging and immature financial market and the stock market still in the recovering stage, there will be a large disperse distribution in beta values estimated in the medical equipment, medicine and human resource industries.\par Hypothesis/Issue 3: With the above reasons, the mean of equity and asset beta values of these listed medical equipment companies tend to impose a high risk level, i.e., beta should higher than (>) 1. \section[{III.}]{III.} \section[{Literature Review}]{Literature Review}\par Fame, Eugene F., and French, Kenneth R., (2004) indicated in the three factor model that "value" and "size" are significant components which can affect stock returns. They also mentioned that a stock's return not only depends on a market beta, but also on market capitalization beta. The market beta is used in the three factor model, developed by Fame and French, which is the successor to the CAPM model by Sharpe, Trey nor and Linter. As Luis E. Pierre (2010) pointed, the task of estimating cost of equity in emerging markets is more difficult because of problems such as collecting data in short periods. Mo Chaudhury (2011) found out over 2007/08 crisis period, unconditional daily returns fell to negative level, unconditional volatility surged more than 200 percent, correlation between stocks weakened and the risk reduction benefit of portfolio diversification rose. Marcin, Mariusz, Marek, and Karol (2012) mentioned that the reliability and fitness of calculated betas are relevant to the valuation and investment of investors in emerging markets. And Xiaowei Kang (2012) found that combining weighted or alternative beta strategies can gain significant traction in investment community and reduce risk. Next, Wolfgang, Lukas and Ranko (2013) discovered during the financial crisis, the relation between stock returns and implied volatility exhibits differences consistent with European institutional and cultural clusters; for example, German stock market tends to be more responsive to changes in implied volatility compared to UK stock market.\par IV. \section[{Conceptual Theories a) Determinants of Equity and Asset Beta}]{Conceptual Theories a) Determinants of Equity and Asset Beta}\par There are several kinds of business risks including systematic and unsystematic risk. In financial markets, systematic risk relates to the overall risk of the whole market, is affected by some factors such as: the volatility of expected return of a single stock, interest rate fluctuations or economic crisis, cannot be avoided by diversification, and is measured by a financial metric, beta which is also called systemic risk. Market risk, indicated by beta ?, can be known by the decreasing value of an investment because of movement of market factors.\par Market risk coming from market factors can be contrasted with internal risk coming from internal factors of a company.\par Firms with beta > 1 will have the movement of stock price higher than the market benchmark. Companies whose beta values < 1 have the risk lower than the entire market risk. For example, if beta of a company is 1, 25, it means that the volatility of stock price is 25\% more than that of the entire market.\par V. \section[{Methodology}]{Methodology}\par During the period 2007-2011, the time highlighting impacts from financial crisis, we use the data from the stock exchange market in Viet Nam (HOSE and HNX and UPCOM) to estimate systemic risk results.\par First of all, we use the market stock price of total 14 listed companies in the medical equipment, medicine and human resource industries in Viet Nam stock exchange market to calculate the variability in monthly stock price in the same period; second, we estimate the equity beta for these three (3) listed groups of companies and make a comparison. Third, from the equity beta values of these listed companies, we perform a comparative analysis between equity and asset beta values of these 3 companies groups in Viet Nam. Finally, we use the results to suggest policy for both these enterprises, financial services institutions and relevant organizations.\par The (Note: The above data is at the December 12th, 2012, from Viet Nam stock exchange) .\par VI. \section[{General Data Analysis}]{General Data Analysis}\par This is a study sample of 14 firms in 3 categories of industries: medical equipment, medicine and human resource companies groups, and here are the results: the mean of equity beta is valued at 0,538 while that of asset beta is about 0,320. These data are quite acceptable values during the crisis. Additionally, the sample variance of asset beta is low (0, 1449) which is a good number, while that of equity beta is somewhat higher (0,570) showing the gap of 0,425. This shows us that the effectiveness of using financial leverage has decreased the systemic risk for the entire group.\par However, the max and min values of beta are still somewhat large. Max equity beta value is up to 2,091 that are a little bit high, compared to max asset beta value is just 1,075 that is acceptable. Looking at there is 57\% or 8 firms whose beta values lower than (<) 1 and higher than (>) 0.\par Value of equity beta varies in a range from 2,091 (max) to -0,946 (min) and that of asset beta varies in a range from 1,075 (max) to -0,163 (min). Some companies still has larger risk exposure than most of the others. There are 3 listed companies whose both equity and asset betas are lower than (<) 0, which means the stock return moves in a opposite direction to the market benchmark.\par Next, Asset beta max value is 1,075 and min value is -0,163 which show us that if beta of debt is assumed to be zero (0), the company's financial leverage contributes to a decrease in the market risk level.\par Lastly, we can see the relatively high difference between max equity and max asset beta values, which is about 1, 0153, whereas there is a smaller difference between equity and asset beta variance values which is just 0,425; so, there is certain impact on systemic risk of certain firms in term of using leverage while it indicates for most of firms that financial leverage can enable them to reduce market risk. And there is not quite big effect from financial leverage on the gap between company's beta variance values. Besides, the variance of equity and asset beta of the sample group equals to 0,0102 and 0,0014 accordingly which are much lower than the variance of the entire sample equity and asset beta of 0,57 and 0,14. The effect from financial leverage makes these beta values fluctuate a little bit less from the sample beta mean.\par We might note that equity beta values of 2 firms in this material category are the lowest compared to those of firms in the rest two (2) groups. Among three (3) industries, the systemic risk of medical equipment group companies is a bit lower than those of the rest two groups.\par Besides, the estimated equity beta mean is 0,096 and sample variance is 0,0102, which is not supporting our 2nd research hypothesis or issue that there would be a large disperse distribution in beta values estimated in this industry as well as our 3rd research hypothesis or issue that the mean of equity and asset beta values of these listed companies tend to impose a high risk level or beta should higher than (>) 1. Because of the necessity in a developing economy, the market for medicine firms is definitely established and potential although it may be affected by impacts from the financial crisis.\par The Table \hyperref[tab_5]{5} below shows us the equity and asset beta mean of 8 listed medicine companies, with values of 0,682 and 0,414, accordingly. This result means the risk is low and acceptable although the equity/asset beta values are the highest among 3 groups. This partly, maintains the public confidence of business operation of the whole industry and partly, indicates the good effect from using financial leverage.\par Please refer to table \hyperref[tab_5]{5 and} Besides, the variance of beta values among these 8 firms is normal, from 0,7144 to 0,1389 for equity and asset beta, accordingly, whereas there are only one special case with beta higher than (>) 2. c) Human Resource Listed Companies Group Among 3 groups, this is the group with the 2nd smallest number of listed firms (sample size = 4) and with the 2nd lowest values of equity and asset beta mean and equity beta var of about 0, 47, 0, 28 and 0, 61 accordingly. However, the asset beta var of about 0, 2214 is the highest among 3 industries. The using of leverage has influenced these firms' risk exposure a bit less than the medicine industry. Different from firms in the medicine industries, 4 listed human resource firms has lower equity and asset beta mean and equity beta var values, estimated at 0,469 and 0,278 and 0,6075, which implies there is a more concentration in market risks among firms in this industry. The equity and asset beta values are distributed in a smaller range, from -0,199 to 1,502, and from -0,058 to 0,958 which are acceptable, esp., asset beta values are quite low, indicating the effectiveness of using financial leverage. Please refer to Exhibit 2 for more information. \section[{d) Comparison Among 3 Groups of Medical Equipment, Medicine and Human Resource Companies}]{d) Comparison Among 3 Groups of Medical Equipment, Medicine and Human Resource Companies}\par The below chart 1 shows us among the 3 groups, equity beta and asset beta values of the medical group are the lowest (0,1 and 0,3 accordingly) while those of the medicine group are the highest (0,68 and 0,71 accordingly). Assuming debt beta is 0, financial leverage has helped many listed firms in these industries lower the un-diversifiable risk.\par Furthermore, we see the equity and asset beta mean values of all 3 groups have gaps but acceptable. Therefore, it also rejects our 3rd hypothesis that the mean values of equity/asset beta of all 3 groups impose higher risks.\par Next, we can recognize from the chart that, the risk in the medicine industries higher than those in the other 2 industries. So, it rejects our 1st hypothesis.\par Last but not least, from the calculated results, variance values of asset /equity beta in the medical equipment group are lowest. In number, equity beta var is from 0,01 -0,71 and asset beta var is from 0,001-0,22 which is not big. This also rejects our 2nd hypothesis.\par Finally, if we compare beta values of three (3) above industries to those of computer and electrical group companies, we see the asset beta mean values in the medical equipment, medicine and human resource industries are a little bit lower (see exhibit 4). \section[{Global Journal of Management and Business Research}]{Global Journal of Management and Business Research} \section[{Risk Analysis}]{Risk Analysis}\par The crisis seems having no effects on medical industry because of population growth. Chart 1 : more and more similar provided services and products for consumers and patients. These risks can affect the performance and net cash flow of these companies. And prices of medical material and public utilities could increase over years. However, the medical services are vital for most of people despite of increasing medical service prices. And the medical policies are also good in term of building more hospitals and providing more high quality medical services. \section[{IX. Conclusion and Policy Suggestion a) Medical Equipment Industry}]{IX. Conclusion and Policy Suggestion a) Medical Equipment Industry}\par Even though beta mean values are fine, this is the industry which has both the lowest equity/asset beta mean values and the lowest asset /equity beta var (see chart 1). During the crisis, this industry has lower market risk and beta values of firms in the group are less fluctuated.\par After difficulties in the crisis (see exhibit 1), financial services industries, the government and central banks have certain efforts and policies to support businesses and internal investors, and stabilize inflation. \section[{b) Medicine Industry}]{b) Medicine Industry}\par Generally speaking, this is the industry which has the highest values of equity/asset beta mean and equity beta varies, among 3 groups (0, 68, 0, 41 and 0, 71). The using of financial leverage can be a reason to reduce market risk. The market is well established. \section[{c) Human Resource Industry}]{c) Human Resource Industry}\par Through our comparative analysis on asset beta values, this is the industry which has the lower market risk exposure than that of the medicine industry when we consider values of asset beta var. Also the beta variance shows a small dispersion and smaller than, esp., medicine firms, under leverage impacts.\par In general, our empirical findings state that they are not in favor of our 1st and 2nd and 3rd hypotheses or research issues.\par In short, although Viet Nam is an emerging market with imperfect financial system, the beta values estimated are at acceptable level with 57\% firms in the research sample while just a few companies' beta values are risky (about 21\% firms).\par Additionally, it indicates the higher the using of financial leverage, the lower the beta values. In reality, there are 57\% of VN medical equipment, medicine and human resource firms (8 among 14 firms) which has 0< equity beta<1 and 71\% of total firms (10 among 14 firms) with 0 1\tabcellsep 3\tabcellsep 36,44\%\tabcellsep 21\%\\ \tabcellsep total\tabcellsep 14\tabcellsep 47,1\%\tabcellsep 100\%\\ \tabcellsep Asset Beta\tabcellsep No. of firms\tabcellsep Financial leverage (average)\tabcellsep Ratio\\ \tabcellsep <0\tabcellsep 3\tabcellsep 76,09\%\tabcellsep 21\%\\ \tabcellsep 0 1\tabcellsep 1\tabcellsep 9,72\%\tabcellsep 7\%\\ \tabcellsep total\tabcellsep 14\tabcellsep 43,0\%\tabcellsep 100\%\\ VII.\tabcellsep \multicolumn{2}{l}{Empirical Research Findings}\tabcellsep \\ \tabcellsep and Discussion\tabcellsep \tabcellsep \\ \multicolumn{3}{l}{a) Medical Equipment Listed Companies Group}\tabcellsep \\ \multicolumn{4}{l}{During the crisis 2007-2011, the market for}\\ \multicolumn{4}{l}{these companies still exists, but has certain difficulties}\\ \multicolumn{2}{l}{because of increasing input prices.}\tabcellsep \tabcellsep \end{longtable} \par \caption{\label{tab_2}Table 2 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{3} \par \begin{longtable}{P{0.28813559322033894\textwidth}P{0.08644067796610169\textwidth}P{0.07563559322033898\textwidth}P{0.1548728813559322\textwidth}P{0.136864406779661\textwidth}P{0.10805084745762711\textwidth}} Order No.\tabcellsep Company stock code\tabcellsep Equity beta\tabcellsep Asset beta beta = 0) (assume debt\tabcellsep Note\tabcellsep Financial leverage\\ 1\tabcellsep DNM\tabcellsep 0,168\tabcellsep 0,056\tabcellsep APC as comparable\tabcellsep 66,6\%\\ 2\tabcellsep JVC\tabcellsep 0,025\tabcellsep 0,003\tabcellsep DNM as comparable\tabcellsep 88,5\%\\ \multicolumn{2}{l}{Note : Raw data, not adjusted.}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ \multicolumn{4}{l}{(Source : Viet Nam stock exchange data)}\tabcellsep \tabcellsep \end{longtable} \par \caption{\label{tab_3}Table 3 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{4} \par \begin{longtable}{P{0.2653658536585366\textwidth}P{0.2197560975609756\textwidth}P{0.22390243902439025\textwidth}P{0.14097560975609758\textwidth}} Statistic results\tabcellsep Equity beta\tabcellsep Asset beta beta = 0) (assume debt\tabcellsep Difference\\ MAX\tabcellsep 0,168\tabcellsep 0,056\tabcellsep 0,1118\\ MIN\tabcellsep 0,025\tabcellsep 0,003\tabcellsep 0,0220\\ MEAN\tabcellsep 0,096\tabcellsep 0,029\tabcellsep 0,0669\\ VAR\tabcellsep 0,0102\tabcellsep 0,0014\tabcellsep 0,0088\\ \tabcellsep Note: Sample size : 2\tabcellsep \tabcellsep \\ b) Medicine Listed Companies Group\tabcellsep \tabcellsep \tabcellsep \end{longtable} \par \caption{\label{tab_4}Table 4 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{5} \par \begin{longtable}{P{0.16817204301075267\textwidth}P{0.038387096774193545\textwidth}P{0.08408602150537633\textwidth}P{0.3655913978494624\textwidth}P{0.038387096774193545\textwidth}P{0.0310752688172043\textwidth}P{0.1243010752688172\textwidth}} 2013\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ ear\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ Y\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ Volume XIII Issue VII Version I\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ ( )\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ Global Journal of Management and Business Research\tabcellsep Order No. 1 2 3 4\tabcellsep Company stock code AMV APC DBM DBT\tabcellsep \multicolumn{3}{l}{Companies (as of Dec 2012) Equity beta Asset beta (assume debt beta = 0) 1,191 1,075 0,419 0,383 comparable Note DLV as 2,091 0,765 PGT as comparable 0,661 0,192 PGT as comparable}\tabcellsep Financial leverage 9,7\% 8,6\% 63,4\% 70,9\%\\ \tabcellsep 5\tabcellsep DCL\tabcellsep 0,840\tabcellsep 0,374\tabcellsep PGT as comparable\tabcellsep 55,4\%\\ \tabcellsep 6\tabcellsep DDN\tabcellsep -0,946\tabcellsep -0,163\tabcellsep \tabcellsep 82,8\%\\ \tabcellsep 7\tabcellsep DHG\tabcellsep 0,592\tabcellsep 0,432\tabcellsep \tabcellsep 27,2\%\\ \tabcellsep 8\tabcellsep DHT\tabcellsep 0,610\tabcellsep 0,251\tabcellsep \tabcellsep 58,8\%\end{longtable} \par {\small\itshape [Note: (Source : Viet Nam stock exchange data).C 30]} \caption{\label{tab_5}Table 5 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{6} \par \begin{longtable}{P{0.14655172413793105\textwidth}P{0.2637931034482759\textwidth}P{0.2686781609195402\textwidth}P{0.17097701149425287\textwidth}} Statistic results\tabcellsep Equity beta\tabcellsep Asset beta (assume debt beta = 0)\tabcellsep Difference\\ MAX\tabcellsep 2,091\tabcellsep 1,075\tabcellsep 1,0153\\ MIN\tabcellsep -0,946\tabcellsep -0,163\tabcellsep -0,7831\\ MEAN\tabcellsep 0,682\tabcellsep 0,414\tabcellsep 0,2685\\ VAR\tabcellsep 0,7144\tabcellsep 0,1389\tabcellsep 0,5756\\ \tabcellsep \multicolumn{2}{l}{Note: Sample size : 8}\tabcellsep \end{longtable} \par \caption{\label{tab_6}Table 6 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{} \par \begin{longtable}{} \end{longtable} \par \caption{\label{tab_7}}\end{figure} \begin{figure}[htbp] \noindent\textbf{7} \par \begin{longtable}{P{0.14655172413793105\textwidth}P{0.16120689655172413\textwidth}P{0.37126436781609196\textwidth}P{0.17097701149425287\textwidth}} Statistic results\tabcellsep Equity beta\tabcellsep Asset beta (assume debt beta = 0)\tabcellsep Difference\\ MAX\tabcellsep 1,502\tabcellsep 0,958\tabcellsep 0,5436\\ MIN\tabcellsep -0,199\tabcellsep -0,058\tabcellsep -0,1412\\ MEAN\tabcellsep 0,469\tabcellsep 0,278\tabcellsep 0,1914\\ VAR\tabcellsep 0,6075\tabcellsep 0,2214\tabcellsep 0,3861\\ \tabcellsep \tabcellsep Note: Sample size : 4\tabcellsep \end{longtable} \par \caption{\label{tab_8}Table 7 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{} \par \begin{longtable}{P{0.188\textwidth}P{0.488\textwidth}P{0.018\textwidth}P{0.031999999999999994\textwidth}P{0.05399999999999999\textwidth}P{0.034\textwidth}P{0.036\textwidth}} 2013\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ ear\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ Y\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ Volume XIII Issue VII Version I\tabcellsep \tabcellsep \tabcellsep \tabcellsep Ex hib i it\tabcellsep \\ ( ) C\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ Global Journal of Management and Business Research\tabcellsep \multicolumn{6}{l}{Exhibit 2 : Estimating beta results for Viet Nam Listed Human Resource Companies (as of Dec 2012) Order No. Company stock code Equity beta Asset beta (assume debt beta = 0) Note Financial leverage 1 CMS -0,063 -0,016 VCM as comparable 74,4\%}\\ \tabcellsep 2\tabcellsep ILC\tabcellsep 0,635\tabcellsep 0,226\tabcellsep SDA as comparable\tabcellsep 64,5\%\\ \tabcellsep 3\tabcellsep SDA\tabcellsep 1,502\tabcellsep 0,958\tabcellsep \tabcellsep 36,2\%\\ \tabcellsep 4\tabcellsep VCM\tabcellsep -0,199\tabcellsep -0,058\tabcellsep \tabcellsep 71,1\%\end{longtable} \par \caption{\label{tab_9}}\end{figure} \footnote{© 2013 Global Journals Inc. (US)} \footnote{T h g 1 -0 6 T h g 4 -0 6 T h g 7 -0 6 T h g 1 0 -0 6 T h g 1 -0 7 T h g 4 -0 7 T h g 7 -0 7 T h g 1 0 -0 7 T h g 1 -0 8 T h g 4 -0 8 T h g 7 -0 8 T h g 1 0 -0 8 T h g 1 -0 9 T h g 4 -0 9 T h g 7 -0 9 T h g 1 0 -0 9 T h g 1 -1 0 T h g 4 -1 0 T h g 7 -1 0} \backmatter \par Acquirers? An Analysis of Trading in Stock -Financed Acquisitions, Journal of Financial Research. \begin{bibitemlist}{1} \bibitem[Kashyap and Zingales ()]{b6}\label{b6} ‘2007-8 Financial Crisis: Lessons from Corporate Finance’. Anil K Kashyap , Luigi Zingales . \textit{Journal of Financial Economics} 2010. \bibitem[7% 9%-12% 9%-10% 6,88% 5 ()]{b14}\label{b14} 2\% 17.000. \textit{7\% 9\%-12\% 9\%-10\% 6,88\% 5}, 2009. 2008. 2007. 8 p. . 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