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 (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.

This is a survey based descriptive research. 25 key variables were considered initially. 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 ' III.

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 (Singh, 1997;Singh, 1971;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. 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, Benson (2002) found this positive impact of capital market development largely dependent on the inclusion of higher income countries.

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 (Balke & Wohar, 2006). Cochrane (1992) and Timmerman (1995) have argued that fluctuation in stock prices can be explained by timevarying discount rates and future excess returns. 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 Mobarek and Keasay (2000) on Dhaka Stock Exchange of Bangladesh support this argument.

Conducting research in Dhaka Stock Exchange (DSE), 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. 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.

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.

It is generally assumed that the emerging markets are less efficient than the developed markets. 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 (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 (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. 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.

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. 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. 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. 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.

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.

IV.

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.

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.

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.

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.

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.

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.