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             \author[1]{Md. Ariful  Islam}

             \author[2]{Md. Imtiaj  Rahman}

             \author[3]{Salahuddin  Yousuf}

             \affil[1]{  Khulna University}

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\date{\small \em Received: 6 February 2015 Accepted: 2 March 2015 Published: 15 March 2015}

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\begin{abstract}
        


This primary data based study attempts to explore the factors the investors of capital market critically consider while making their investment decisions. Study took place in Bangladesh, an economically potential developing country. A total of 125 investors were surveyed conveniently with a structured questionnaire containing 25 variables. Broad category of factors are ?Internal & Economic?, ?Internal & Supporting?, ?Internal & Regulatory?, ?Company Image?, ?Market Info?, ?External? and ?Market Situation?. Specific variables like dividend, EPS, company goodwill, industry growth, SEC regulation, and change in Govt. policy are found to be positively influential. The least influential factors are P/E ratio, price hike of necessary goods, market rumor etc.

\end{abstract}


\keywords{investor, investment decision, capital market.}

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\let\tabcellsep& 	 	 		 
\section[{Introduction}]{Introduction}\par
apital market is one of the critical components of any economy. Therefore, investment decision of the investors in the capital market is very sensitive. Different measures of stock market activities are positively correlated with measures of real economic growth across countries \hyperref[b9]{(Levine and Zervos, 1998)}. This association is particularly strong for developing countries. As an economically potential developing country, capital market is certainly a key factor for Bangladesh. Recent instability in the overall capital market of this country highly enticed the policymakers. The situation demands to analyze the decision making process of the actors in the capital market. Thus, this study attempts to explore the key factors those the investors consider while making their investment decisions in the capital market. The stock market regulatory authority and the policy makers might find the results helpful in avoiding any unexpected catastrophe, improving the stock market industry and assessing to which degree the stock market is needed to be reformed. 
\section[{II.}]{II.} 
\section[{Methodology}]{Methodology}\par
This is a survey based descriptive research. 25 key variables were considered initially. \hyperref[b10]{Malhotra (2008)} defines that there should be at least 4 or 5 times as many observations (sample size) as there are variables. Hence, a total of 125 investors from different brokerage houses of Bangladesh had been surveyed. Investors were chosen conveniently (non-probability sampling technique). A structured questionnaire was used to collect investors' responses. The respondents were asked to respond against 25 close ended statements on a 5-point Likert Scale where '1' denotes 'Strongly Disagree' and '5' denotes 'Strongly Agree'. The key variables were Dividend, Earnings per Share (EPS), Retained earnings, Price Earning (P/E) Ratio, Returned on Investment (ROI), Company News, AGM, Company Goodwill, Industry Growth, Price Hike of Necessary Goods, Market Sentiment, Agents  {\ref '}  III. 
\section[{Literature Review}]{Literature Review}\par
Investors' perception and market behavior are the key concern of the capital market analysts or researchers. Stock market's contribution on the overall economy of a country is well discussed by different scholars \hyperref[b16]{(Singh, 1997;}\hyperref[b15]{Singh, 1971;} {\ref Bhide, 1994)}. Empirical evidence linking stock market development to economic growth has been inconclusive. Though the balance of evidence is in favor of a positive relationship between stock markets and economic growth. \hyperref[b9]{Levine and Zervos (1998)} found that various measures of stock market activities are positively correlated with measures of real economic growth in different countries and this relationship is particularly strong in the developing countries. On the contrary, \hyperref[b2]{Benson (2002)} found this positive impact of capital market development largely dependent on the inclusion of higher income countries.\par
Movements of stock prices depend on number of factors. The decomposition of stock price movements is very sensitive to what assumption is made about the presence of permanent changes in either real dividend growth or excess stock return \hyperref[b1]{(Balke \& Wohar, 2006)}. \hyperref[b3]{Cochrane (1992)} and Timmerman (1995) have argued that fluctuation in stock prices can be explained by timevarying discount rates and future excess returns. \hyperref[b14]{Raihan \& Ullah (2007)}, from their study on Chittagong Stock Exchange (Bangladesh), found that stock return series do not follow random walk model in Bangladeshi capital market. Similar findings of the work of  {\ref Mobarek and Keasay (2000)} on Dhaka Stock Exchange of Bangladesh support this argument.\par
Conducting research in Dhaka Stock Exchange (DSE), \hyperref[b13]{Rahman, et al (2006)} found the negative correlation between the beta and stock return, which is reason for inefficiency of market where the assumptions behind the CAPM model is not supported. \hyperref[b20]{Wong, et al (2009)} found that when limit hits are imminent stock prices approach limit bounds at faster rates and with increased volatility and higher trade efficiency.\par
The critical challenge in this field of research is to determine the factors influence the stock price in the capital market. A large number of empirical studies had been conducted about the determinants of stock prices. Several researchers examined the relationships between stock prices and selected factors. These factors could be either internal or external. The findings of their research illustrate different outcomes depending on the scope of research. Many of these factors could be valid for all stock markets. In this section some of these studies are reviewed.\par
It is generally assumed that the emerging markets are less efficient than the developed markets. \hyperref[b13]{Rahman, et al (2006)} found the negative correlation between the beta and stock return. This is one of the reasons for inefficiency in the capital market. The movement of stock price is very sensitive to what assumption is made about the presence of permanent changes in either real dividend growth or excess stock return \hyperref[b1]{(Balke \& Wohar, 2006)}. Dividend change announcements cause a greater change in stock price when the nature of the news (good or bad) goes against the grain of the recent market direction during volatile times \hyperref[b4]{(Docking and Koch, 2005)}. After using this macroeconomic variables like gross national product (GNP), interest rate and inflation, Al-Qenae (2002) found inflation and interest rate have negative and statistically significant coefficients in almost all cases on stock prices while GNP has positive effect. \hyperref[b11]{Maysami and Koh (2000)} illustrated the connection of money supply growth, change in short and long term interest rates, inflation and variation in exchange rates with the changes in Singapore's stock market levels.\par
Udegbunam \& Eriki (2001) revealed that stock prices and inflation provides a strong support for the proposition that inflation exerts a significant negative influence on the behavior of the prices of the stocks. They also exhibited that stock prices are also strongly driven by the level of economic activity measured by interest rate, GDP, financial deregulation and money stock.  {\ref Joshep and Vezos (2006)} proclaim that interest rate and foreign exchange rate risks are important financial and economic factors affecting the value of common stocks. The results indicate a significant and negative relation between stock prices and inflation. And the output growth negatively and significantly affect stock prices. \hyperref[b18]{Tsoukalas (2003)} used industrial production, exchange rate, consumer prices and money supply as macroeconomic factors and revealed a strong relationship between stock prices with those factors. \hyperref[b5]{Ibrahim (2003)} found that the Malaysian stock price index is positively related to consumer price index, money supply and industrial production. It is negatively related to the movement of exchange rates.\par
Since consumer price index and investors' perception are two critical issues for the movement of stock prices, this study aims to explore the factors those are valued by the capital market investors.\par
IV. 
\section[{Analysis \& Discussion}]{Analysis \& Discussion}\par
25 initial variables werechosen to identify the factors affecting investment decisions in the stock market. A total of 125 investors were surveyed. Summary of their responses toward those factors are portrayed here. The above responses indicate that there are some factors to which investors are more responsive, like dividend, EPS, company goodwill, industry growth, SEC regulation, change in government policy etc. The respondents are found to be less responsive to the factors like P/E ratio; price hike of necessary goods, market rumor etc. But this is their average result. In contrast, some factors were found which has got two extreme end responses i.e. both strongly agree and strongly disagree. So it will not to be justified to leave any comment only based upon the mean result. Here the standard deviation of the response frequency is also depicted. It shows the dispersion of response from mean. The variance here is showing the responsiveness of mean in relation to standard deviation. The lesser variance is showing more representative result. Here the result of P/E ratio, ROI, price hike of necessary goods, agents' advice, market rumor, inflation, Interest rate, International situation etc. are possessing more reliable result according to variance. For a justified list of influential factors, factor analysis was performed later.\par
Here a mean comparison is done to get the idea about to what extent factors are affecting male and female investors in their investment decisions. In this study, 106 male and 19 female investors are surveyed. Among them all are not agreed with same factor as a determinant of their investment decision. Here, it is found that the most important factor to male is 'dividend' whereas it is the 6 th important factor to female investors. Again, where 'industry growth' is the most important factor to female, it is the 3 rd most important factor for the male investors. Some of the factors are commonly rated by both the male and female investors. Those are: company goodwill (2 nd ), law suit file (5 th ), market sentiment (17 th ), price hike of necessary goods (23 rd ) and market rumor (25 th ). Top and least five determinants for investment for the male are given in the below table: From the survey, it is noticeable that 'company goodwill' and 'law suit file' are the common determinants among the top five important factors for both male and female investors, whereas price hike of necessary goods and market rumor are the common determinants among the least five important factors for both type of investors.\par
This study further conducted 'factor analysis'for data reduction.Factor analysisallows to reduce a large number of correlated variables to a smaller number of 'super variables'. So, factor analysis was conducted in this study with the data collected from field survey. For testing appropriateness of the factor model, Bartlett's test is used. The summary of KMO and Bartlett's Test result is presented here: The Kaiser-Meyer-Olkin (KMO) is a measure of sampling adequacy. The approximate chi-square statistic is 2067.491 with degree of freedom of 300 at the 0.05 level of significance. The appropriateness of factor analysis requires the KMO statistic to be ranging from 0.5 to 1.0. Here the value of KMO statistic is 0.685. Hence this indicates the appropriateness of factor analysis and also suggest further investigation. Here Principle Component Analysis (PCA) method is used. The above summary of "Communalities" shows that the communality (in "Initial" column) for each variable is 1.000.\par
In order to summarize the information contained in the original variables, a smaller number of factors should be extracted. Eigenvalues approach had been used here for this purpose. This table shows the eigenvalue for a factor which indicates the total variance explained by each factor. The total variance accounted for all 25 variables is 25.00 which is equal to the number of variable. Here, variable 1 has got a variance of 5.686, which is (5.686/25) or 22.745\% of the total variance. Again like the variable 1, the second variable has got a variance of 3.700, which is (3.700/25) or 14.801\% of the total variance and the first two factors has got a cumulative variance of 37.547\%. Only factors with eigenvalue greater than 1.00 are retained and other factors are discarded. An eigenvalue represents the amount of variance associated with the factors.\par
The following table reveals that the eigenvalue greater than 1.0 (default option) results in seven factors being extracted. The cumulative percentage of variance testimony the first seven factors to be accounted for 78.684\% of the variance.\par
In this approach, only factors with eigenvalues greater than 1.0 are retained. The other factors are not included in the model. It indicates the total variance attributed to that factor. Hence, only factors with a variance greater than 1 are included. Supporting factor. Factor 3 has got a high coefficient with variables V1: Dividend, V7: AGM, V22: SEC Regulations. This factor can be labeled as internal \& regulatory factor. Again factor 4 has high coefficient for variables V3: Retained earnings, V6: Company News, V8: Company Goodwill. This factor may be labeled as company image factor. The next factor i.e. factor 5 has got some highly correlated variable as well. Those are V9: Industry Growth, V15: Market Rumor. Now this factor is labeled as market info factor. Again the 6 th factor has also got some highly correlated factor. Those are V10: Price Hike of Necessary Goods, V20: International Situation. Here this factor is labeled as the external factor. And lastly the factor 7 has also got some highly correlated variables like V11: Market Sentiment, V24: Political Connectivity of Company Owner. And this factor is labeled as other factor. It can be summarized that investors are being affected in their investment decision in the major issues related to internal \& economic, internal \& supporting, internal \& regulatory, company image, market info, external and others.  \begin{figure}[htbp]
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 \begin{figure}[htbp]
\noindent\textbf{1} \par 
\begin{longtable}{P{0.15372340425531916\textwidth}P{0.07973887814313346\textwidth}P{0.023839458413926498\textwidth}P{0.009042553191489361\textwidth}P{0.008220502901353965\textwidth}P{0.08795938104448743\textwidth}P{0.012330754352030947\textwidth}P{0.09042553191489361\textwidth}P{0.018085106382978722\textwidth}P{0.007398452611218569\textwidth}P{0.01397485493230174\textwidth}P{0.01644100580270793\textwidth}P{0.06329787234042553\textwidth}P{0.008220502901353965\textwidth}P{0.007398452611218569\textwidth}P{0.022195357833655706\textwidth}P{0.008220502901353965\textwidth}P{0.026305609284332686\textwidth}P{0.011508704061895551\textwidth}P{0.02548355899419729\textwidth}P{0.013152804642166343\textwidth}P{0.045212765957446804\textwidth}P{0.013152804642166343\textwidth}P{0.012330754352030947\textwidth}P{0.03452611218568665\textwidth}P{0.018085106382978722\textwidth}P{0.019729206963249517\textwidth}}
\tabcellsep Dividend\tabcellsep Earnings Per\tabcellsep Share (EPS)\tabcellsep Retained\tabcellsep earnings\tabcellsep Price Earning\tabcellsep (P/E) Ratio\tabcellsep (ROI)\tabcellsep Company\tabcellsep News\tabcellsep AGM\tabcellsep Company\tabcellsep \multicolumn{2}{l}{Goodwill}\tabcellsep Industry\tabcellsep Growth\tabcellsep Price Hike of\tabcellsep Necessary\tabcellsep Goods\tabcellsep Market\tabcellsep Sentiment\tabcellsep \multicolumn{2}{l}{Agents'}\tabcellsep Advice\tabcellsep Available\tabcellsep Substitutes\\
N\tabcellsep \multicolumn{11}{l}{125 125 125 125 125 125 125}\tabcellsep \multicolumn{6}{l}{125 125 125}\tabcellsep \tabcellsep \multicolumn{2}{l}{125}\tabcellsep 125\tabcellsep \tabcellsep \tabcellsep 125\\
Mean\tabcellsep \multicolumn{11}{l}{4.33 4.12 3.77 2.95 3.68 3.83 3.88}\tabcellsep \multicolumn{6}{l}{4.24 4.24 2.97}\tabcellsep \tabcellsep \multicolumn{2}{l}{3.48}\tabcellsep \multicolumn{2}{l}{3.04}\tabcellsep \tabcellsep 3.08\\
\multicolumn{12}{l}{Std. Deviation .990 .725 .805 1.453 1.082 .859 .972}\tabcellsep \multicolumn{6}{l}{.712 .837 1.062}\tabcellsep \tabcellsep \multicolumn{2}{l}{.876}\tabcellsep \multicolumn{2}{l}{1.316}\tabcellsep \tabcellsep .894\\
\multicolumn{12}{l}{Variance .980 .526 .647 2.111 1.171 .738 .945}\tabcellsep \multicolumn{6}{l}{.506 .700 1.128}\tabcellsep \tabcellsep \multicolumn{2}{l}{.768}\tabcellsep \multicolumn{2}{l}{1.732}\tabcellsep \tabcellsep .800\\
Minimum\tabcellsep 1\tabcellsep \multicolumn{2}{l}{3}\tabcellsep \multicolumn{2}{l}{2}\tabcellsep \multicolumn{2}{l}{1}\tabcellsep 1\tabcellsep \multicolumn{2}{l}{2}\tabcellsep 2\tabcellsep \multicolumn{2}{l}{2}\tabcellsep \tabcellsep \multicolumn{2}{l}{2}\tabcellsep 1\tabcellsep \tabcellsep 1\tabcellsep \tabcellsep 1\tabcellsep \tabcellsep \tabcellsep 1\\
Maximum\tabcellsep 5\tabcellsep \multicolumn{2}{l}{5}\tabcellsep \multicolumn{2}{l}{5}\tabcellsep \multicolumn{2}{l}{5}\tabcellsep 5\tabcellsep \multicolumn{2}{l}{5}\tabcellsep 5\tabcellsep \multicolumn{2}{l}{5}\tabcellsep \tabcellsep \multicolumn{2}{l}{5}\tabcellsep 5\tabcellsep \tabcellsep 5\tabcellsep \tabcellsep 5\tabcellsep \tabcellsep \tabcellsep 5\\
\tabcellsep Credit Rating\tabcellsep Agency's Report\tabcellsep \tabcellsep \tabcellsep Market Rumor\tabcellsep \tabcellsep Inflation\tabcellsep Exchange Rate\tabcellsep \tabcellsep Margin Loan\tabcellsep Interest Rate\tabcellsep \multicolumn{2}{l}{International}\tabcellsep Situation\tabcellsep Website, Social\tabcellsep Blog\tabcellsep SEC Regulations\tabcellsep \tabcellsep Change in\tabcellsep Government\tabcellsep Policies\tabcellsep Political\tabcellsep \multicolumn{2}{l}{Connectivity of}\tabcellsep Company Owner\tabcellsep Law Suit File\\
N\tabcellsep \multicolumn{2}{l}{125}\tabcellsep \tabcellsep \tabcellsep \multicolumn{13}{l}{125 125 125 125 125 125 125 125}\tabcellsep \multicolumn{2}{l}{125}\tabcellsep \tabcellsep 125\tabcellsep \tabcellsep \tabcellsep 125\\
Mean\tabcellsep \multicolumn{2}{l}{3.17}\tabcellsep \tabcellsep \tabcellsep \multicolumn{15}{l}{2.69 3.89 3.55 3.02 3.75 3.34 3.57 4.13 4.07}\tabcellsep \tabcellsep 3.66\tabcellsep \tabcellsep \tabcellsep 4.12\\
\multicolumn{3}{l}{Std. Deviation .957}\tabcellsep \tabcellsep \tabcellsep \multicolumn{2}{l}{1.298}\tabcellsep \multicolumn{13}{l}{1.179 .987 1.376 1.141 1.136 1.272 .842 .805}\tabcellsep \tabcellsep \multicolumn{2}{l}{1.092}\tabcellsep \tabcellsep 1.005\\
Variance\tabcellsep \multicolumn{2}{l}{.915}\tabcellsep \tabcellsep \tabcellsep \multicolumn{2}{l}{1.684}\tabcellsep \multicolumn{13}{l}{1.391 .975 1.895 1.301 1.289 1.618 .709 .648}\tabcellsep \tabcellsep \multicolumn{2}{l}{1.193}\tabcellsep \tabcellsep 1.010\\
Minimum\tabcellsep \multicolumn{2}{l}{1}\tabcellsep \tabcellsep \tabcellsep 1\tabcellsep \tabcellsep 1\tabcellsep 1\tabcellsep \tabcellsep 1\tabcellsep 1\tabcellsep \tabcellsep \multicolumn{2}{l}{1}\tabcellsep \multicolumn{2}{l}{1}\tabcellsep 2\tabcellsep 2\tabcellsep \tabcellsep \tabcellsep 2\tabcellsep \tabcellsep \tabcellsep 1\\
Maximum\tabcellsep \multicolumn{2}{l}{5}\tabcellsep \tabcellsep \tabcellsep 5\tabcellsep \tabcellsep 5\tabcellsep 5\tabcellsep \tabcellsep 5\tabcellsep 5\tabcellsep \tabcellsep \multicolumn{2}{l}{5}\tabcellsep \multicolumn{2}{l}{5}\tabcellsep 5\tabcellsep 5\tabcellsep \tabcellsep \tabcellsep 5\tabcellsep \tabcellsep \tabcellsep 5\\
\multicolumn{4}{l}{Source: Field Survey, 2014}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \end{longtable} \par
 
\caption{\label{tab_1}Table 1 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{2} \par 
\begin{longtable}{P{0.061239193083573486\textwidth}P{0.32987512007684916\textwidth}P{0.08655139289145053\textwidth}P{0.080835734870317\textwidth}P{0.043275696445725265\textwidth}P{0.12737752161383284\textwidth}P{0.07756964457252641\textwidth}P{0.043275696445725265\textwidth}}
No\tabcellsep Variable\tabcellsep Gender\tabcellsep Mean\tabcellsep Mean Ranking\tabcellsep Gender\tabcellsep Mean\tabcellsep Mean Ranking\\
1\tabcellsep Dividend\tabcellsep Male\tabcellsep 4.37\tabcellsep 1\tabcellsep Female\tabcellsep 4.11\tabcellsep 6\\
2\tabcellsep Company Goodwill\tabcellsep Male\tabcellsep 4.2\tabcellsep 2\tabcellsep Female\tabcellsep 4.47\tabcellsep 2\\
3\tabcellsep Industry Growth\tabcellsep Male\tabcellsep 4.19\tabcellsep 3\tabcellsep Female\tabcellsep 4.53\tabcellsep 1\\
4\tabcellsep SEC Regulations\tabcellsep Male\tabcellsep 4.15\tabcellsep 4\tabcellsep Female\tabcellsep 4\tabcellsep 7\\
5\tabcellsep Law Suit File\tabcellsep Male\tabcellsep 4.11\tabcellsep 5\tabcellsep Female\tabcellsep 4.16\tabcellsep 5\\
6\tabcellsep (EPS)\tabcellsep Male\tabcellsep 4.09\tabcellsep 6\tabcellsep Female\tabcellsep 4.26\tabcellsep 3\\
7\tabcellsep Change in Government Policies\tabcellsep Male\tabcellsep 4.05\tabcellsep 7\tabcellsep Female\tabcellsep 4.21\tabcellsep 4\\
8\tabcellsep AGM\tabcellsep Male\tabcellsep 3.92\tabcellsep 8\tabcellsep Female\tabcellsep 3.68\tabcellsep 13\\
9\tabcellsep Inflation\tabcellsep Male\tabcellsep 3.87\tabcellsep 9\tabcellsep Female\tabcellsep 4\tabcellsep 8\\
10\tabcellsep Company News\tabcellsep Male\tabcellsep 3.83\tabcellsep 10\tabcellsep Female\tabcellsep 3.84\tabcellsep 11\\
11\tabcellsep Retained earnings\tabcellsep Male\tabcellsep 3.8\tabcellsep 11\tabcellsep Female\tabcellsep 3.58\tabcellsep 14\\
12\tabcellsep Interest Rate\tabcellsep Male\tabcellsep 3.72\tabcellsep 12\tabcellsep Female\tabcellsep 3.95\tabcellsep 10\\
13\tabcellsep Political Connectivity of Company Owner\tabcellsep Male\tabcellsep 3.71\tabcellsep 13\tabcellsep Female\tabcellsep 3.42\tabcellsep 19\\
14\tabcellsep (ROI)\tabcellsep Male\tabcellsep 3.7\tabcellsep 14\tabcellsep Female\tabcellsep 3.58\tabcellsep 15\\
15\tabcellsep Exchange Rate\tabcellsep Male\tabcellsep 3.5\tabcellsep 15\tabcellsep Female\tabcellsep 3.84\tabcellsep 12\\
16\tabcellsep Website, Social Blog\tabcellsep Male\tabcellsep 3.49\tabcellsep 16\tabcellsep Female\tabcellsep 4\tabcellsep 9\\
17\tabcellsep Market Sentiment\tabcellsep Male\tabcellsep 3.48\tabcellsep 17\tabcellsep Female\tabcellsep 3.47\tabcellsep 17\\
18\tabcellsep International Situation\tabcellsep Male\tabcellsep 3.32\tabcellsep 18\tabcellsep Female\tabcellsep 3.42\tabcellsep 20\\
19\tabcellsep Credit Rating Agency's Report\tabcellsep Male\tabcellsep 3.1\tabcellsep 19\tabcellsep Female\tabcellsep 3.53\tabcellsep 16\\
20\tabcellsep Available Substitutes\tabcellsep Male\tabcellsep 3.08\tabcellsep 20\tabcellsep Female\tabcellsep 3.11\tabcellsep 21\\
21\tabcellsep Margin Loan\tabcellsep Male\tabcellsep 3.08\tabcellsep 21\tabcellsep Female\tabcellsep 2.74\tabcellsep 24\\
22\tabcellsep Agents' Advice\tabcellsep Male\tabcellsep 2.99\tabcellsep 22\tabcellsep Female\tabcellsep 3.47\tabcellsep 18\\
23\tabcellsep Price Hike of Necessary Goods\tabcellsep Male\tabcellsep 2.97\tabcellsep 23\tabcellsep Female\tabcellsep 2.95\tabcellsep 23\\
24\tabcellsep P/E Ratio\tabcellsep Male\tabcellsep 2.93\tabcellsep 24\tabcellsep Female\tabcellsep 3.05\tabcellsep 22\\
25\tabcellsep Market Rumor\tabcellsep Male\tabcellsep 2.72\tabcellsep 25\tabcellsep Female\tabcellsep 2.53\tabcellsep 25\\
\multicolumn{2}{l}{Source: Field Survey, July, 2014}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \end{longtable} \par
 
\caption{\label{tab_2}Table 2 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{3} \par 
\begin{longtable}{P{0.13392282958199359\textwidth}P{0.22684887459807074\textwidth}P{0.09839228295819935\textwidth}P{0.02733118971061093\textwidth}P{0.29790996784565915\textwidth}P{0.06559485530546624\textwidth}}
\tabcellsep Top Five\tabcellsep \tabcellsep \tabcellsep Least Five\tabcellsep \\
Mean Ranking\tabcellsep Variable\tabcellsep \multicolumn{2}{l}{Mean Mean Ranking}\tabcellsep Variable\tabcellsep Mean\\
1\tabcellsep Dividend\tabcellsep 4.37\tabcellsep 21\tabcellsep Margin Loan\tabcellsep 3.08\\
2\tabcellsep Company Goodwill\tabcellsep 4.2\tabcellsep 22\tabcellsep Agents' Advice\tabcellsep 2.99\\
3\tabcellsep Industry Growth\tabcellsep 4.19\tabcellsep 23\tabcellsep Price Hike of Necessary Goods\tabcellsep 2.97\\
4\tabcellsep SEC Regulations\tabcellsep 4.15\tabcellsep 24\tabcellsep Price Earning (P/E) Ratio\tabcellsep 2.93\\
5\tabcellsep Law Suit File\tabcellsep 4.11\tabcellsep 25\tabcellsep Market Rumor\tabcellsep 2.72\\
\multicolumn{2}{l}{Source: Field Survey, July, 2014}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \end{longtable} \par
 
\caption{\label{tab_3}Table 3 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{4} \par 
\begin{longtable}{P{0.119683908045977\textwidth}P{0.2760057471264368\textwidth}P{0.05862068965517241\textwidth}P{0.05373563218390805\textwidth}P{0.2833333333333333\textwidth}P{0.05862068965517241\textwidth}}
\tabcellsep Top Five\tabcellsep \tabcellsep \tabcellsep Least Five\tabcellsep \\
Mean Ranking\tabcellsep Variable\tabcellsep Mean\tabcellsep Mean Ranking\tabcellsep Variable\tabcellsep Mean\\
1\tabcellsep Industry Growth\tabcellsep 4.53\tabcellsep 21\tabcellsep Available Substitutes\tabcellsep 3.11\\
2\tabcellsep Company Goodwill\tabcellsep 4.47\tabcellsep 22\tabcellsep Price Earning (P/E) Ratio\tabcellsep 3.05\\
3\tabcellsep Earnings Per Share (EPS)\tabcellsep 4.26\tabcellsep 23\tabcellsep Price Hike of Necessary Goods\tabcellsep 2.95\\
4\tabcellsep Change in Government Policies\tabcellsep 4.21\tabcellsep 24\tabcellsep Margin Loan\tabcellsep 2.74\\
5\tabcellsep Law Suit File\tabcellsep 4.16\tabcellsep 25\tabcellsep Market Rumor\tabcellsep 2.53\\
\multicolumn{2}{l}{Source: Field Survey, July, 2014}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \end{longtable} \par
 
\caption{\label{tab_4}Table 4 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{5} \par 
\begin{longtable}{P{0.5454166666666667\textwidth}P{0.17\textwidth}P{0.13458333333333333\textwidth}}
\multicolumn{2}{l}{Kaiser-Meyer-Olkin Measure of Sampling Adequacy.}\tabcellsep .685\\
\tabcellsep Approx. Chi-Square\tabcellsep 2067.491\\
Bartlett's Test of Sphericity\tabcellsep Df\tabcellsep 300\\
\tabcellsep Sig.\tabcellsep .000\end{longtable} \par
 
\caption{\label{tab_5}Table 5 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{6} \par 
\begin{longtable}{P{0.85\textwidth}}
Investors' Investment Decisions in Capital Market: Key Factors\end{longtable} \par
 
\caption{\label{tab_6}Table 6 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{7} \par 
\begin{longtable}{P{0.18426573426573425\textwidth}P{0.08767482517482518\textwidth}P{0.10104895104895105\textwidth}P{0.14414335664335665\textwidth}P{0.03566433566433567\textwidth}P{0.07132867132867134\textwidth}P{0.11739510489510488\textwidth}P{0.10847902097902098\textwidth}}
\tabcellsep \tabcellsep \tabcellsep \multicolumn{2}{l}{Initial Eigenvalues}\tabcellsep \tabcellsep \tabcellsep \\
\multicolumn{6}{l}{Component Total \% of Variance Cumulative \% Component Total}\tabcellsep \multicolumn{2}{l}{\% of Variance Cumulative \%}\\
1\tabcellsep 5.686\tabcellsep 22.745\tabcellsep 22.745\tabcellsep 14\tabcellsep .383\tabcellsep 1.531\tabcellsep 92.309\\
2\tabcellsep 3.700\tabcellsep 14.801\tabcellsep 37.547\tabcellsep 15\tabcellsep .358\tabcellsep 1.433\tabcellsep 93.741\\
3\tabcellsep 2.990\tabcellsep 11.959\tabcellsep 49.506\tabcellsep 16\tabcellsep .259\tabcellsep 1.034\tabcellsep 94.775\\
4\tabcellsep 2.191\tabcellsep 8.766\tabcellsep 58.272\tabcellsep 17\tabcellsep .217\tabcellsep .866\tabcellsep 95.642\\
5\tabcellsep 1.666\tabcellsep 6.666\tabcellsep 64.937\tabcellsep 18\tabcellsep .203\tabcellsep .810\tabcellsep 96.452\\
6\tabcellsep 1.337\tabcellsep 5.347\tabcellsep 70.285\tabcellsep 19\tabcellsep .180\tabcellsep .722\tabcellsep 97.174\\
7\tabcellsep 1.100\tabcellsep 4.399\tabcellsep 74.684\tabcellsep 20\tabcellsep .160\tabcellsep .641\tabcellsep 97.814\\
8\tabcellsep .873\tabcellsep 3.493\tabcellsep 78.177\tabcellsep 21\tabcellsep .148\tabcellsep .591\tabcellsep 98.405\\
9\tabcellsep .830\tabcellsep 3.319\tabcellsep 81.496\tabcellsep 22\tabcellsep .123\tabcellsep .493\tabcellsep 98.898\\
10\tabcellsep .777\tabcellsep 3.108\tabcellsep 84.604\tabcellsep 23\tabcellsep .116\tabcellsep .465\tabcellsep 99.362\\
11\tabcellsep .549\tabcellsep 2.197\tabcellsep 86.801\tabcellsep 24\tabcellsep .092\tabcellsep .370\tabcellsep 99.732\\
12\tabcellsep .504\tabcellsep 2.016\tabcellsep 88.817\tabcellsep 25\tabcellsep .067\tabcellsep .268\tabcellsep 100.000\\
13\tabcellsep .490\tabcellsep 1.961\tabcellsep 90.778\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
\multicolumn{4}{l}{Extraction Method: Principal Component Analysis}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \end{longtable} \par
 
\caption{\label{tab_7}Table 7 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{8} \par 
\begin{longtable}{P{0.06868686868686869\textwidth}P{0.32196969696969696\textwidth}P{0.22323232323232325\textwidth}P{0.2361111111111111\textwidth}}
\tabcellsep \multicolumn{3}{l}{Extraction Sums of Squared Loadings}\\
Component\tabcellsep Total\tabcellsep \% of Variance\tabcellsep Cumulative \%\\
1\tabcellsep 5.686\tabcellsep 22.745\tabcellsep 22.745\\
2\tabcellsep 3.700\tabcellsep 14.801\tabcellsep 37.547\\
3\tabcellsep 2.990\tabcellsep 11.959\tabcellsep 49.506\\
4\tabcellsep 2.191\tabcellsep 8.766\tabcellsep 58.272\\
5\tabcellsep 1.666\tabcellsep 6.666\tabcellsep 64.937\\
6\tabcellsep 1.337\tabcellsep 5.347\tabcellsep 70.285\\
7\tabcellsep 1.100\tabcellsep 4.399\tabcellsep 74.684\end{longtable} \par
 
\caption{\label{tab_8}Table 8 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{9} \par 
\begin{longtable}{P{0.34136\textwidth}P{0.09928\textwidth}P{0.33455999999999997\textwidth}P{0.07479999999999999\textwidth}}
\tabcellsep \multicolumn{2}{l}{Rotation Sums of Squared Loadings}\tabcellsep \\
Components\tabcellsep Total\tabcellsep \% of Variance\tabcellsep Cumulative \%\\
1\tabcellsep 4.519\tabcellsep 18.075\tabcellsep 18.075\\
2\tabcellsep 3.125\tabcellsep 12.501\tabcellsep 30.576\\
3\tabcellsep 2.462\tabcellsep 9.849\tabcellsep 40.425\\
4\tabcellsep 2.373\tabcellsep 9.491\tabcellsep 49.916\\
5\tabcellsep 2.086\tabcellsep 8.345\tabcellsep 58.261\\
6\tabcellsep 2.084\tabcellsep 8.336\tabcellsep 66.597\\
7\tabcellsep 2.022\tabcellsep 8.087\tabcellsep 74.684\\
\multicolumn{2}{l}{Through the above table, the rotation of sums of}\tabcellsep \multicolumn{2}{l}{absolute value indicates that the factor and the variable}\\
\multicolumn{2}{l}{squared loading is done. The following table (Table 10)}\tabcellsep are closely related.\tabcellsep \\
shows the rotated factor matrix.\tabcellsep \tabcellsep \multicolumn{2}{l}{Here, in this study, Varimax procedure had}\\
\multicolumn{2}{l}{This matrix represents correlation between the}\tabcellsep \multicolumn{2}{l}{been used for rotation. Summary of rotated component}\\
\multicolumn{2}{l}{factors and the variables. A coefficient with a large}\tabcellsep \multicolumn{2}{l}{matrix is presented here}\end{longtable} \par
 
\caption{\label{tab_9}Table 9 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{10} \par 
\begin{longtable}{P{0.4005354752342704\textwidth}P{0.06372155287817939\textwidth}P{0.06599732262382864\textwidth}P{0.06542838018741633\textwidth}P{0.06599732262382864\textwidth}P{0.06315261044176707\textwidth}P{0.06258366800535475\textwidth}P{0.06258366800535475\textwidth}}
\tabcellsep \tabcellsep \tabcellsep \tabcellsep Component\tabcellsep \tabcellsep \tabcellsep \\
\tabcellsep 1\tabcellsep 2\tabcellsep 3\tabcellsep 4\tabcellsep 5\tabcellsep 6\tabcellsep 7\\
V1: Dividend\tabcellsep -.133\tabcellsep -.210\tabcellsep .855\tabcellsep .063\tabcellsep -.017\tabcellsep .158\tabcellsep .074\\
V2: Earnings Per Share (EPS)\tabcellsep -.080\tabcellsep .843\tabcellsep .059\tabcellsep .075\tabcellsep -.010\tabcellsep -.280\tabcellsep .121\\
V3: Retained earnings\tabcellsep -.037\tabcellsep -.194\tabcellsep -.179\tabcellsep .569\tabcellsep .210\tabcellsep -.030\tabcellsep -.440\\
V4: Price Earning (P/E) Ratio\tabcellsep -.821\tabcellsep -.161\tabcellsep -.164\tabcellsep .176\tabcellsep .087\tabcellsep .152\tabcellsep -.114\\
V5: Returned on Investment (ROI)\tabcellsep -.591\tabcellsep -.591\tabcellsep -.132\tabcellsep .198\tabcellsep -.012\tabcellsep -.036\tabcellsep .125\\
V6: Company News\tabcellsep .008\tabcellsep -.078\tabcellsep .286\tabcellsep .652\tabcellsep -.156\tabcellsep -.011\tabcellsep .096\\
V7: AGM\tabcellsep .095\tabcellsep .334\tabcellsep .786\tabcellsep -.177\tabcellsep .038\tabcellsep -.204\tabcellsep .157\\
V8: Company Goodwill\tabcellsep .038\tabcellsep -.014\tabcellsep -.113\tabcellsep .694\tabcellsep -.099\tabcellsep .044\tabcellsep .035\\
V9: Industry Growth\tabcellsep .032\tabcellsep .246\tabcellsep .238\tabcellsep .290\tabcellsep -.596\tabcellsep .113\tabcellsep .152\\
V10: Price Hike of Necessary Goods\tabcellsep -.329\tabcellsep .011\tabcellsep -.257\tabcellsep .000\tabcellsep .232\tabcellsep -.617\tabcellsep .392\\
V11: Market Sentiment\tabcellsep -.023\tabcellsep .105\tabcellsep .186\tabcellsep .122\tabcellsep -.080\tabcellsep -.096\tabcellsep .840\\
V12: Agents' Advice\tabcellsep .285\tabcellsep .533\tabcellsep -.437\tabcellsep -.239\tabcellsep .154\tabcellsep .341\tabcellsep -.258\\
V13: Available Substitutes\tabcellsep -.471\tabcellsep -.081\tabcellsep -.165\tabcellsep .353\tabcellsep .435\tabcellsep -.369\tabcellsep .068\\
V14: Credit Rating Agency's Report\tabcellsep -.013\tabcellsep .804\tabcellsep -.009\tabcellsep -.116\tabcellsep -.072\tabcellsep .362\tabcellsep -.030\\
V15: Market Rumor\tabcellsep .375\tabcellsep .197\tabcellsep .180\tabcellsep -.161\tabcellsep .752\tabcellsep -.098\tabcellsep .122\\
V16: Inflation\tabcellsep .696\tabcellsep .010\tabcellsep .033\tabcellsep .260\tabcellsep .258\tabcellsep .210\tabcellsep -.229\\
V17: Exchange Rate\tabcellsep .744\tabcellsep -.023\tabcellsep -.273\tabcellsep -.010\tabcellsep .074\tabcellsep .292\tabcellsep -.038\\
V18: Margin Loan\tabcellsep .018\tabcellsep -.623\tabcellsep .127\tabcellsep .181\tabcellsep .605\tabcellsep .223\tabcellsep .060\\
V19: Interest Rate\tabcellsep .683\tabcellsep -.064\tabcellsep -.055\tabcellsep -.282\tabcellsep .283\tabcellsep .363\tabcellsep -.013\\
V20: International Situation\tabcellsep .263\tabcellsep -.007\tabcellsep -.100\tabcellsep .087\tabcellsep -.008\tabcellsep .826\tabcellsep .071\\
V21: Website, Social Blog\tabcellsep .656\tabcellsep .266\tabcellsep -.003\tabcellsep .042\tabcellsep .102\tabcellsep .226\tabcellsep -.324\\
V22: SEC Regulations\tabcellsep -.019\tabcellsep -.027\tabcellsep .606\tabcellsep .578\tabcellsep .052\tabcellsep .013\tabcellsep .329\\
V23: Change in Government Policies\tabcellsep .698\tabcellsep -.173\tabcellsep -.177\tabcellsep .242\tabcellsep -.255\tabcellsep .032\tabcellsep .108\\
V24: Political Connectivity of Company\tabcellsep -.214\tabcellsep -.450\tabcellsep .169\tabcellsep .001\tabcellsep .265\tabcellsep .096\tabcellsep .680\\
Owner\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
V25: Law Suit File\tabcellsep .608\tabcellsep -.312\tabcellsep -.024\tabcellsep .361\tabcellsep .365\tabcellsep .249\tabcellsep -.157\\
\multicolumn{2}{l}{Extraction Method: Principal Component Analysis;}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
\multicolumn{5}{l}{Rotation Method: Varimax with Kaiser Normalization; Rotation converged in 10 iterations}\tabcellsep \tabcellsep \tabcellsep \end{longtable} \par
 
\caption{\label{tab_10}Table 10 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{11} \par 
\begin{longtable}{P{0.16196275071633237\textwidth}P{0.4931948424068767\textwidth}P{0.19484240687679083\textwidth}}
Factor\tabcellsep Variables\tabcellsep Surrogate Variables\\
Factor 1 (Internal \& Economic)\tabcellsep V4: Price Earning (P/E) Ratio\tabcellsep V4: Price Earning (P/E) Ratio (-0.821)\\
\tabcellsep V5: Returned on Investment (ROI)\tabcellsep \\
\tabcellsep V13: Available Substitutes\tabcellsep \\
\tabcellsep V16: Inflation\tabcellsep \\
\tabcellsep V17: Exchange Rate\tabcellsep \\
\tabcellsep V19: Interest Rate\tabcellsep \\
\tabcellsep V21: Website, Social Blog\tabcellsep \\
\tabcellsep V23: Change in Government Policies\tabcellsep \\
\tabcellsep V25: Law Suit File\tabcellsep \\
Factor 2 (Internal \& Supporting)\tabcellsep V2: Earnings Per Share (EPS)\tabcellsep V2: Earnings Per Share (EPS) (0.843)\\
\tabcellsep V12: Agents' Advice\tabcellsep \\
\tabcellsep V14: Credit Rating Agency's Report\tabcellsep \\
\tabcellsep V18: Margin Loan\tabcellsep \\
Factor 3 (Internal \& Regulatory)\tabcellsep V1: Dividend\tabcellsep V1: Dividend (0.855)\\
\tabcellsep V7: AGM\tabcellsep \\
\tabcellsep V22: SEC Regulations\tabcellsep \\
Factor\tabcellsep Variables\tabcellsep Surrogate Variables\\
Factor 4 (Company Image)\tabcellsep V3: Retained earnings\tabcellsep V8: Company Goodwill (0.694)\\
\tabcellsep V6: Company News\tabcellsep \end{longtable} \par
 
\caption{\label{tab_11}Table 11 :}\end{figure}
 			\footnote{© 2015 Global Journals Inc. (US)} 		 		\backmatter  			 
\subsection[{Global Journal of Management and Business Research}]{Global Journal of Management and Business Research}\par
Volume XV Issue IV Version I Year ( )\par
Therefore V4 would be selected as surrogate variable under factor 1 since it has the highest factor loading. V2, V12, V14, V18 have high loading on factor 2 and among the 4 variables V2 has the highest loading. So EPS (V2) can be selected as the surrogate variable for factor 2. Again among the high loading variables V1, V7, V22 the highest loading is by V1 (Dividend) which in turns becomes the surrogate variable for factor 3.\par
In this way the surrogate variable of factor 4, factor 5, factor 6 and factor 7 is respectively V8 (Company Goodwill), V15 (Market Rumor), V20 (International Situation) and V11 (Market Sentiment), as those are the highest loading among the high loadings \hyperref[b8]{(Khan, 2006)}.\par
V. 
\subsection[{Findings And Conclusion}]{Findings And Conclusion}\par
Key factors like dividend, EPS, company goodwill, industry growth, SEC regulation and change in government policy are having higher mean score. At the same time,factors with lower mean score are P/E ratio, price hike of necessary goods, market rumor etc. The core factors identified through factor analysis through which investors' investment decision can be affected. This study was conducted based on a developing country's capital market. The research outcome would be more effective if the study was conducted in a comparative manner with three different types of economy, i.e. under developed economy, developing economy and developed economy. Yet, this study is expected to contribute to the researches on capital market behavior. The key investment factors identified by this research will help the policymakers to their endeavor to reform the capital market.			 			  				\begin{bibitemlist}{1}
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