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\title{The Effect of Demographic Factors on the Behavior of Investors during the Choice of Investment: Evidence from Twin Cities of Pakistan}
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             \author[1]{M. Nauman  Sadiq}

             \affil[1]{  Federal Urdu University of Art, Sciences and Technology Islamabad (FUUAST),}

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\date{\small \em Received: 8 December 2013 Accepted: 2 January 2014 Published: 15 January 2014}

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\begin{abstract}
        


Investor's behaviour is influenced by many factors during investment decision making. Demographic profile of investors is also one of the decision influencing factor among others .The aim of this paper is to examine the effect of demographic factors on investors level of risk tolerance regarding the choice of investment.100 investors from twin cities of Pakistan (Rawalpindi and Islamabad) were selected as sample, chi square test and correlation was conducted to explore the effect of demographic factors on investor's level of risk tolerance regarding the choice of investment. Result of the paper showed that demographic factors of investors such as academic education, income level, investment knowledge, and investment experience effect the investors level of risk tolerance, while investors gender, marital status, occupation, and family size showed no effect on investors level of risk tolerance .These results are important for managers to advise their clients about better area of investment and risk level according to their demographic profile.

\end{abstract}


\keywords{demographic factors, investors level of risk tolerance, correlation, pakistan.}

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\let\tabcellsep& 	 	 		 
\section[{Introduction}]{Introduction}\par
ehaviour of investors in derivative markets is influence by many personal and situational factors during the choice of investment. Different researches are conducted to determine the behaviour influencing factors and attempt to understand and explain the degree to which these factors influence the decision-making process.\par
Investment involves the utilization of funds at present with the hope of better return in future. Traditional financial theories presume that investors are rational. People rationally choose between alternatives, they act rationally while making their investment decisions \hyperref[b23]{(Von Neumann, and Morgenstern, 1944)}. Later on it is explored by many researchers that Individual investor sometime make irrational decisions about their investments \hyperref[b2]{(Barberis, and Thaler, 2003)}.Different factors affect the investors behaviour during personal financial management process. Among others factors investor behaviour is also affected by demographic characteristics. Different research papers are conducted to identify the effect of demographic factors on investment decision and shown contradictory results from country to country and area to area.\par
The aim of this paper is to investigate the extent to which demographic factors affect an investor's risk tolerance attitude during decision making with the context of Pakistan. This study is primary data based collected from various respondents through a questionnaire. The respondents who were interested in investment were interacted from twin cities of Pakistan i.e. Islamabad and Rawalpindi. 
\section[{II.}]{II.} 
\section[{Literature Review}]{Literature Review}\par
Many studies are conducted to examine the effect of demographic factors on investor's level of risk tolerance during investment decision making. People having different gender, ages, income level, knowledge, marital status and occupation shows different attitudes towards decision making, some are risk seeker and some adverse risk. Brief literature about the effect of demographic factors on investor's behaviour with international evidence is given below. Male's investors are more confident in their investment decisions, they have more financial knowledge and wealth and ability to take risks (Bruce, 1995)  {\ref (Barber and Odean 2001: 261)}.When males are investing in their assets due to large income they take greater risks  {\ref (Parker, and Terry 2002)}.Some studies shown that there is no significant effect of gender on risk tolerance during financial decisions  {\ref (Schubert et al. 1999: 384-385}  
\section[{d) Marital Status}]{d) Marital Status}\par
Marital status is also an effective factor influencing the decision making of investor. Single individuals are more risk taker than married because married individuals have responsibilities for themselves and dependents \hyperref[b18]{(Roszkowski et al. 1993)}  \hyperref[b14]{(Lazzarone, 1996)}   {\ref Barber and Odean (2001: 285)}.Some studies failed to find significance association between marital status and financial risk tolerance  {\ref (McInish, 1982)}. 
\section[{e) Income Level}]{e) Income Level}\par
Income level of investor is also affects its behaviour toward investment. A person with greater wealth takes greater risk  {\ref (Terry, and Parker, 2002)}. Persons with upper level of income and millionaires tend to take higher risk as than individual with lower level of income (MacCrimmon, and Wehrung, 1986). Researcher explored that level of risk tolerance increase with the increasing level of income (Blume et al.1994)Investors invest their funds in more volatile portfolio composed of more volatile stocks when they have higher level of income \hyperref[b3]{(Barber, and Odean , 2001)}.\par
Higher level of income creates the ability of bearing the losses, so wealthier people preferred higher level of risk  {\ref (bernheim et al, 2001)}.\par
In contrast some researchers shown income level has no relationship with financial risk tolerance  {\ref (Strydom et al (2009: 18)} f) Occupation Occupation means the activity in which people engaged for pay. Those people who generate their income directly from their own business, trade, or profession leads to higher levels of risk taking as compare to the people of straight salary work for others  {\ref (MacCrimmon \& Wehrung, 1985)}.Occupational status is also affecting the level of risk taking ability; people with higher ranking occupational status are more risk seeker as compare to low ranking occupational status \hyperref[b18]{(Roszkowski et al., 1993)}.People having low risk taking ability choose low ranked professions \hyperref[b4]{(Barnewall, 1988)}. 
\section[{g) Family Size}]{g) Family Size}\par
Investor's family size is also effects their financial risk taking behaviour. Investors having small family size are more risk taker, where increase in family size caused risk aversion (Lease, \hyperref[b15]{Lewellen, and Schlarbaum, 1977)}. 
\section[{III.}]{III.} 
\section[{Objectives of the Study}]{Objectives of the Study}\par
Following objectives were framed from the present study:\par
? Find the effect of demographic factors on investor's decisions. ? Find the nature of association between demographic factors (Education, Age, Gender, Investment knowledge, investment experience, Occupation, marital status, Income level, and family size of investors) and investor's level of risk tolerance. 
\section[{Global Journal of Management and Business Research}]{Global Journal of Management and Business Research}\par
Volume XIV Issue III Version I Year 2014 ( )C IV. 
\section[{Research Methodology}]{Research Methodology}\par
This study is primary data based involves to explored the effect of demographic factors on investors level of risk tolerance during investment decision making process. Data is collected from various respondents through a structured questionnaire. The Questionnaire contains open and close ended questions. Only those people were interacted who were interested in investment located in twin cities of Pakistan i.e. Islamabad and Rawalpindi. The total sample consisted of 100 respondents.\par
Males and females from different occupations and income levels are splits from different age groups and education levels. In this study Risk is consider as a dependent variable, while demographic factors individually checked as independent factors in relation with risk taking attitude of investors. In order to statistically check the results Chi-Square and correlation tests are used. These tests are also used by Jain, D.   
\section[{(DATA FROM QUESTIONNAIRE) a) Association between investors gender and financial risk tolerance H0:}]{(DATA FROM QUESTIONNAIRE) a) Association between investors gender and financial risk tolerance H0:}\par
There is no significant effect of gender on risk tolerance during financial decisions. H1: There is significant effect of gender on risk tolerance during financial decisions. From Table \hyperref[tab_3]{3}: It is evaluated that the computed value of chi -square is 1.544 .Where tabulated value using 5\% level of significance is 7.815.Computed value is less than tabulated value so we accept our H0 (null hypothesis) and concluded that there is no significant effect of gender on risk tolerance during financial decisions. Both male and female have same response toward financial risk tolerance.\par
Table \hyperref[tab_4]{4} is revealing that there is a negative correlation between gender and financial risk tolerance.\par
Increase in investor's gender caused negative effect on investor's ability of financial risk tolerance. 
\section[{b) Association between investors age and Financial risk tolerance H0:}]{b) Association between investors age and Financial risk tolerance H0:}\par
There is no significant effect of Age on risk tolerance during financial decisions. H1: There is significant effect of Age on risk tolerance during financial decisions.  
\section[{C}]{C}\par
From Table \hyperref[tab_6]{6}: It is evaluated that the computed value of chi -square is 21.767 .Where tabulated value using 5\% level of significance is 21.026.Computed value is greater than tabulated value so we reject our H0 (null hypothesis) and concluded that there is significant effect of Age on risk tolerance during financial decisions.\par
Table \hyperref[tab_7]{7} is revealing that negative correlation is exist between Age of investors and financial risk tolerance. An Increase in age caused negative effect on investor's ability of financial risk tolerance. 
\section[{c) Association between investors academic qualification and financial risk tolerance H0:}]{c) Association between investors academic qualification and financial risk tolerance H0:}\par
There is no significant effect of Academic qualification on risk tolerance during financial decisions. H1: There is significant effect of Academic qualification on risk tolerance during financial decisions. From Table \hyperref[tab_9]{9}: It is evaluated that the computed value of chi -square is 30.066.Where tabulated value using 5\% level of significance is 16.919.Computed value is greater than tabulated value so we reject our H0 (null hypothesis) and concluded that there is significant effect of Academic qualification on risk tolerance during financial decisions.\par
Table \hyperref[tab_10]{10} is revealing that positive correlation is exist between academic qualification and financial risk tolerance. An increase in Academic qualification caused a Positive effect on investor's ability of financial risk tolerance. 
\section[{d) Association between investors annual imcome and financial risk tolerance H0:}]{d) Association between investors annual imcome and financial risk tolerance H0:}\par
There is no significant effect of income level on risk tolerance during financial decisions H1: There is significant effect of income level on risk tolerance during financial decisions.  From Table \hyperref[tab_12]{12}: It is evaluated that the computed value of chi -square is 36.475, where tabulated value using 5\% level of significance is 21.026.Computed value is greater than tabulated value so we reject our H0 (null hypothesis) and concluded there is significant effect of income level on risk tolerance during financial decisions.\par
Table \hyperref[tab_13]{13} is revealing that Positive correlation is exist between income level of investors and financial risk tolerance. An increase in Level of income caused a positive effect on investor's ability of financial risk tolerance. 
\section[{e) Association between marital status of investors and financial risk tolerance H0:}]{e) Association between marital status of investors and financial risk tolerance H0:}\par
There is no significant effect of marital status on risk tolerance during financial decisions. H1: There is significant effect of marital status on risk tolerance during financial decisions. .620 N 100 100\par
From Table \hyperref[tab_15]{15}: It is evaluated that the computed value of chi-square is 3.423 .Where tabulated value using 5\% level of significance is 7.815.Computed value is less than tabulated value so we accept our H0 (null hypothesis) and concluded that there is no significant effect of marital status on risk tolerance during financial decisions.\par
Table \hyperref[tab_16]{16} is revealing that Positive correlation is exist between marital status and financial risk tolerance.\par
An increase in marital status caused a Positive effect on investor's ability of financial risk tolerance. 
\section[{f) Association between investors investment knowledge and financial risk tolerance H0:}]{f) Association between investors investment knowledge and financial risk tolerance H0:}\par
There is no significant effect of investment knowledge on risk tolerance during financial decisions. H1: There is significant effect of investment knowledge on risk tolerance during financial decisions. 
\section[{Global Journal of Management and Business Research}]{Global Journal of Management and Business Research}\par
Volume XIV Issue III Version I Year 2014 ( ) ** Correlation is significant at the 0.01 level  {\ref (2-tailed)}.C\par
From Table \hyperref[tab_18]{18}: It is evaluated that the computed value of chi -square is 61.381, where tabulated value using 5\% level of significance is 21.026.Computed value is greater than tabulated value so we reject our H0 (null hypothesis) and concluded that there is significant effect of investment knowledge on risk tolerance during financial decisions.\par
Table \hyperref[tab_19]{19} is revealing that Positive correlation is exist between investment knowledge of investors and financial risk tolerance. An increase in knowledge caused a Positive effect on investor's ability of financial risk tolerance. 
\section[{g) Association between investors occupation and finanical risk tolerance H0:}]{g) Association between investors occupation and finanical risk tolerance H0:}\par
There is no significant effect of Occupation on risk tolerance during financial decisions. H1: There is significant effect of Occupation on risk tolerance during financial decisions. From Table \hyperref[tab_21]{21}: It is evaluated that the computed value of chi -square is 11.158, Where tabulated value using 5\% level of significance is 21.026.Computed value is less than tabulated value so we accept our H0 (null hypothesis) and concluded that there is no significant effect of occupation on risk tolerance during financial decisions.\par
Table \hyperref[tab_22]{22} is revealing that negative correlation is exist between occupation and financial risk tolerance.\par
An increase in occupation caused a negative effect on investor's ability of financial risk tolerance. 
\section[{h) Association between investors investment experience and financial risk tolerance H0:}]{h) Association between investors investment experience and financial risk tolerance H0:}\par
There is no significant effect of investment experience on risk tolerance during financial decisions. H1: There is significant effect of investment experience on risk tolerance during financial decisions. From Table \hyperref[tab_24]{24}: It is evaluated that the computed value of chi -square is 33.569, where tabulated value using 5\% level of significance is 21.026.Computed value is greater than tabulated value so we reject our H0 (null hypothesis) and concluded that there is significant effect of investment experience on risk tolerance during financial decisions.\par
Table \hyperref[tab_25]{25} is revealing that Positive correlation is exist between investment experience and financial risk tolerance. An increase in investment experience caused a Positive effect on investor's ability of financial risk tolerance. 
\section[{i) Association between investors family size and financial risk tolerance H0:}]{i) Association between investors family size and financial risk tolerance H0:}\par
There is no significant effect of Family size on risk tolerance during financial decisions. H1: There is no significant effect of Family size on risk tolerance during financial decisions. From Table \hyperref[tab_27]{27}: It is evaluated that the computed value of chi-square is 6.285 .Where tabulated value using 5\% level of significance is 16.919.Computed value is less than tabulated value so we accept our H0 (null hypothesis) and concluded that there is no significant effect of family size on risk tolerance during financial decisions. 
\section[{Global Journal of}]{Global Journal of}\par
Table \hyperref[tab_28]{28} is revealing that negative correlation is exist between family size and level of risk tolerance. An increase in family size caused a negative effect on investor's ability of financial risk tolerance. 
\section[{VI.}]{VI.} 
\section[{Conclusion}]{Conclusion}\par
This study concludes that there is an association between demographic characteristics and investors level of risk tolerance. Result shows that demographic factors like investor's age, academic qualification, income level, investment knowledge, and investment experience have significant effect on the behaviour of investors. There is positive correlation between investor's academic qualification, income level, and investment knowledge and investment experience with their level of risk tolerance during the choice of investments. However investor's age shows slight negative correlation. Increase in age at one point caused a negative effect on risk taking behaviour of investors.\par
Other demographic factors like investor's gender, marital status, occupation and family size have no significant effect on investor's level of financial risk tolerance.\begin{figure}[htbp]
\noindent\textbf{}\includegraphics[]{image-2.png}
\caption{\label{fig_0}}\end{figure}
  \begin{figure}[htbp]
\noindent\textbf{} \par 
\begin{longtable}{P{0.7850406504065041\textwidth}P{0.06495934959349593\textwidth}}
b) Age\tabcellsep \\
Older people tolerate more risk as compare to\tabcellsep \\
the young investors (Grable and Lytton, 1999b: 7)\tabcellsep \\
Young investor can not accurately assess about his\tabcellsep \\
work performance as compare to older one. Old people\tabcellsep \\
gain investment knowledge and experience, and make\tabcellsep \\
better investment Choices (Kumar, and Korniotis, 2011).\tabcellsep \\
In contrast some researchers found that increasing age of investors caused decrease in risk tolerance (Jiankopolos and Bernasek 2006).Further some researchers explored that investors age and financial\tabcellsep Year 2014\\
risk tolerance have no significant relationship (Al-Ajmi,\tabcellsep \\
2008: 21) (Anbar and Eker 2010: 505) Gumede (2009).\tabcellsep \\
c) Education Third demographic factor which caused a higher financial risk tolerance during decision making process is education i.e. formal attained academic training (sung, Hanna, 1996). Level of education obtained and risk tolerance have a positive relationship (Kimball et al 2007: 20) (Graham et al. 2009). Contra-dictory results are also shown by some researchers, which are exploring that no significant relationship is exist between education and risk tolerance whilst the Strydom et al (2009) Gumede (2009: 27).\tabcellsep Volume XIV Issue III Version I\\
\tabcellsep ( ) C\\
B\tabcellsep Global Journal of Management and Business Research\end{longtable} \par
 
\caption{\label{tab_0}}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{1} \par 
\begin{longtable}{P{0.15047846889952154\textwidth}P{0.5287081339712919\textwidth}P{0.13149920255183414\textwidth}P{0.039314194577352475\textwidth}}
\multicolumn{2}{l}{Variables}\tabcellsep Number of Investors\tabcellsep \%Age\\
Gender\tabcellsep Male\tabcellsep 73\\
\tabcellsep Female\tabcellsep 27\\
\tabcellsep Total\tabcellsep 100\tabcellsep 100\\
Age\tabcellsep Below 30 years\tabcellsep 42\\
\tabcellsep 30-40 years\tabcellsep 26\\
\tabcellsep 40-50 years\tabcellsep 18\\
\tabcellsep 50-60 years\tabcellsep 12\\
\tabcellsep 60 or Above 60 years\tabcellsep 02\\
\tabcellsep Total\tabcellsep 100\tabcellsep 100\\
Marital Status\tabcellsep Single\tabcellsep 38\\
\tabcellsep Married\tabcellsep 62\\
\tabcellsep Widow\tabcellsep 0\tabcellsep 0\\
\tabcellsep Divorced\tabcellsep 0\tabcellsep 0\\
\tabcellsep Total\tabcellsep 100\tabcellsep 100\\
Academic Qualification level\tabcellsep Below Graduation\tabcellsep 11\\
\tabcellsep Graduation\tabcellsep 43\\
\tabcellsep Post Graduation\tabcellsep 37\\
\tabcellsep Others\tabcellsep 9\tabcellsep 9\\
\tabcellsep Total\tabcellsep 100\tabcellsep 100\\
Income ( Per annum )\tabcellsep Below Rs. 160,000\tabcellsep 33\\
\tabcellsep Rs.1,60,000-Rs.3,20,000\tabcellsep 12\\
\tabcellsep Rs.3,20,000-Rs.4,80,000\tabcellsep 25\\
\tabcellsep Rs.4,80,000-Rs.6,40,000\tabcellsep 14\\
\tabcellsep Rs. 6,40,000 and Above\tabcellsep 16\\
\tabcellsep Total\tabcellsep 100\tabcellsep 100\\
Occupation\tabcellsep Student\tabcellsep 09\\
\tabcellsep Professional\tabcellsep 18\\
\tabcellsep Business\tabcellsep 14\\
\tabcellsep Service\tabcellsep 46\\
\tabcellsep Others\tabcellsep 13\\
\tabcellsep Total\tabcellsep 100\tabcellsep 100\\
Investment Experience\tabcellsep Below 1 year\tabcellsep 30\\
\tabcellsep 1-4 Years\tabcellsep 40\\
\tabcellsep 4-7 years\tabcellsep 17\\
\tabcellsep 7-10 years\tabcellsep 08\\
\tabcellsep 10 Years or Above\tabcellsep 05\\
\tabcellsep Total\tabcellsep 100\tabcellsep 100\end{longtable} \par
 
\caption{\label{tab_1}Table 1 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{2} \par 
\begin{longtable}{P{0.09444444444444444\textwidth}P{0.08585858585858586\textwidth}P{0.16313131313131313\textwidth}P{0.11161616161616163\textwidth}P{0.18888888888888888\textwidth}P{0.10303030303030303\textwidth}P{0.10303030303030303\textwidth}}
\tabcellsep \tabcellsep \tabcellsep \tabcellsep RISK\tabcellsep \tabcellsep Total\\
\tabcellsep \tabcellsep Below average\tabcellsep Average\tabcellsep Above average\tabcellsep Very high\tabcellsep \\
\tabcellsep Male\tabcellsep 31\tabcellsep 28\tabcellsep 10\tabcellsep 4\tabcellsep 73\\
GENDER\tabcellsep Female\tabcellsep 12\tabcellsep 11\tabcellsep 4\tabcellsep 0\tabcellsep 27\\
Total\tabcellsep \tabcellsep 43\tabcellsep 39\tabcellsep 14\tabcellsep 4\tabcellsep 100\end{longtable} \par
 
\caption{\label{tab_2}Table 2 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{3} \par 
\begin{longtable}{P{0.2125\textwidth}P{0.085\textwidth}P{0.5525\textwidth}}
Value\tabcellsep Df\tabcellsep Sig.(2 sided)\end{longtable} \par
 
\caption{\label{tab_3}Table 3 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{4} \par 
\begin{longtable}{P{0.51\textwidth}P{0.34\textwidth}}
Gender\tabcellsep Risk\end{longtable} \par
 
\caption{\label{tab_4}Table 4 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{5} \par 
\begin{longtable}{P{0.04096385542168675\textwidth}P{0.3328313253012048\textwidth}P{0.1075301204819277\textwidth}P{0.0819277108433735\textwidth}P{0.12289156626506023\textwidth}P{0.07680722891566265\textwidth}P{0.08704819277108433\textwidth}}
\tabcellsep \tabcellsep \tabcellsep \tabcellsep RISK\tabcellsep \tabcellsep Total\\
\tabcellsep \tabcellsep Below Average\tabcellsep Average\tabcellsep Above Average\tabcellsep Very High\tabcellsep \\
\tabcellsep Below 30 years\tabcellsep 19\tabcellsep 18\tabcellsep 5\tabcellsep 0\tabcellsep 42\\
Age\tabcellsep 30-40 Years\tabcellsep 8\tabcellsep 9\tabcellsep 7\tabcellsep 2\tabcellsep 26\\
\tabcellsep 40-50 Years\tabcellsep 6\tabcellsep 10\tabcellsep 2\tabcellsep 0\tabcellsep 18\\
\tabcellsep 50-60 Years\tabcellsep 8\tabcellsep 2\tabcellsep 0\tabcellsep 2\tabcellsep 12\\
\tabcellsep 60 Years and above\tabcellsep 2\tabcellsep 0\tabcellsep 0\tabcellsep 0\tabcellsep 2\\
Total\tabcellsep \tabcellsep 43\tabcellsep 39\tabcellsep 14\tabcellsep 4\tabcellsep 100\end{longtable} \par
 
\caption{\label{tab_5}Table 5 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{6} \par 
\begin{longtable}{P{0.20238095238095236\textwidth}P{0.08095238095238094\textwidth}P{0.5666666666666667\textwidth}}
Value\tabcellsep Df\tabcellsep Sig. (2-sided)\end{longtable} \par
 
\caption{\label{tab_6}Table 6 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{7} \par 
\begin{longtable}{P{0.36428571428571427\textwidth}P{0.48571428571428565\textwidth}}
Age\tabcellsep Risk\end{longtable} \par
 
\caption{\label{tab_7}Table 7 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{8} \par 
\begin{longtable}{P{0.3801242236024845\textwidth}P{0.1531055900621118\textwidth}P{0.04223602484472049\textwidth}P{0.12142857142857141\textwidth}P{0.07391304347826086\textwidth}P{0.07919254658385093\textwidth}}
\tabcellsep \tabcellsep \tabcellsep Risk\tabcellsep \tabcellsep Total\\
\tabcellsep \multicolumn{2}{l}{Below average Average}\tabcellsep Above average\tabcellsep Very high\tabcellsep \\
Qualification Level Below graduation\tabcellsep 11\tabcellsep 0\tabcellsep 0\tabcellsep 0\tabcellsep 11\\
Graduation\tabcellsep 20\tabcellsep 19\tabcellsep 3\tabcellsep 1\tabcellsep 43\\
Post Graduation\tabcellsep 9\tabcellsep 18\tabcellsep 7\tabcellsep 3\tabcellsep 37\\
Others\tabcellsep 3\tabcellsep 2\tabcellsep 4\tabcellsep 0\tabcellsep 9\\
Total\tabcellsep 43\tabcellsep 39\tabcellsep 14\tabcellsep 4\tabcellsep 100\end{longtable} \par
 
\caption{\label{tab_8}Table 8 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{9} \par 
\begin{longtable}{P{0.306\textwidth}P{0.187\textwidth}P{0.051\textwidth}P{0.306\textwidth}}
\tabcellsep Value\tabcellsep Df\tabcellsep Sig. (2-sided)\\
Pearson Chi-Square\tabcellsep 30.066\tabcellsep 9\tabcellsep .000\end{longtable} \par
 
\caption{\label{tab_9}Table 9 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{10} \par 
\begin{longtable}{P{0.5884615384615385\textwidth}P{0.26153846153846155\textwidth}}
Education\tabcellsep Risk\end{longtable} \par
  {\small\itshape [Note: ** . Correlation is significant at the 0.01 level(2-tailed).]} 
\caption{\label{tab_10}Table 10 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{11} \par 
\begin{longtable}{P{0.043896713615023474\textwidth}P{0.4309859154929577\textwidth}P{0.08380281690140844\textwidth}P{0.06384976525821597\textwidth}P{0.09577464788732394\textwidth}P{0.05985915492957747\textwidth}P{0.07183098591549296\textwidth}}
\tabcellsep \tabcellsep \tabcellsep \tabcellsep Risk\tabcellsep \tabcellsep Total\\
\tabcellsep \tabcellsep Below average\tabcellsep Average\tabcellsep Above average\tabcellsep Very high\tabcellsep \\
\tabcellsep Below Rs. 160,000\tabcellsep 23\tabcellsep 8\tabcellsep 2\tabcellsep 0\tabcellsep 33\\
Income\tabcellsep Rs.1,60,000-Rs.3,20,000\tabcellsep 6\tabcellsep 6\tabcellsep 0\tabcellsep 0\tabcellsep 12\\
\tabcellsep Rs.3,20,000-Rs.4,80,000\tabcellsep 7\tabcellsep 11\tabcellsep 6\tabcellsep 1\tabcellsep 25\\
\tabcellsep Rs.4,80,000-Rs.6,40,000\tabcellsep 3\tabcellsep 10\tabcellsep 1\tabcellsep 0\tabcellsep 14\\
\tabcellsep Rs. 6,40,000 and Above\tabcellsep 4\tabcellsep 4\tabcellsep 5\tabcellsep 3\tabcellsep 16\\
Total\tabcellsep \tabcellsep 43\tabcellsep 39\tabcellsep 14\tabcellsep 4\tabcellsep 100\end{longtable} \par
 
\caption{\label{tab_11}Table 11 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{12} \par 
\begin{longtable}{P{0.3\textwidth}P{0.18333333333333335\textwidth}P{0.06666666666666667\textwidth}P{0.3\textwidth}}
\tabcellsep Value\tabcellsep Df\tabcellsep Sig. (2-sided)\\
Pearson Chi-Square\tabcellsep 36.475\tabcellsep 12\tabcellsep .000\end{longtable} \par
 
\caption{\label{tab_12}Table 12 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{13} \par 
\begin{longtable}{P{0.51\textwidth}P{0.34\textwidth}}
Income\tabcellsep Risk\end{longtable} \par
 
\caption{\label{tab_13}Table 13 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{14} \par 
\begin{longtable}{P{0.1481651376146789\textwidth}P{0.10137614678899083\textwidth}P{0.1481651376146789\textwidth}P{0.10137614678899083\textwidth}P{0.16376146788990825\textwidth}P{0.09357798165137615\textwidth}P{0.09357798165137615\textwidth}}
\tabcellsep \tabcellsep \tabcellsep \tabcellsep Risk\tabcellsep \tabcellsep Total\\
\tabcellsep \tabcellsep Below average\tabcellsep Average\tabcellsep Above average\tabcellsep Very high\tabcellsep \\
Marital Status\tabcellsep Single\tabcellsep 17\tabcellsep 14\tabcellsep 7\tabcellsep 0\tabcellsep 38\\
\tabcellsep Married\tabcellsep 26\tabcellsep 25\tabcellsep 7\tabcellsep 4\tabcellsep 62\\
Total\tabcellsep \tabcellsep 43\tabcellsep 39\tabcellsep 14\tabcellsep 4\tabcellsep 100\end{longtable} \par
 
\caption{\label{tab_14}Table 14 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{15} \par 
\begin{longtable}{P{0.3122448979591837\textwidth}P{0.17346938775510204\textwidth}P{0.05204081632653061\textwidth}P{0.3122448979591837\textwidth}}
\tabcellsep Value\tabcellsep Df\tabcellsep Sig. (2-sided)\\
Pearson Chi-Square\tabcellsep 3.423\tabcellsep 3\tabcellsep .331\end{longtable} \par
 
\caption{\label{tab_15}Table 15 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{16} \par 
\begin{longtable}{P{0.6611111111111111\textwidth}P{0.18888888888888888\textwidth}}
Marital Status\tabcellsep Risk\end{longtable} \par
 
\caption{\label{tab_16}Table 16 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{17} \par 
\begin{longtable}{P{0.85\textwidth}}
Risk\end{longtable} \par
 
\caption{\label{tab_17}Table 17 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{18} \par 
\begin{longtable}{P{0.3\textwidth}P{0.18333333333333335\textwidth}P{0.06666666666666667\textwidth}P{0.3\textwidth}}
\tabcellsep Value\tabcellsep Df\tabcellsep Sig. (2-sided)\\
Pearson Chi-Square\tabcellsep 61.381\tabcellsep 12\tabcellsep .000\end{longtable} \par
 
\caption{\label{tab_18}Table 18 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{19} \par 
\begin{longtable}{P{0.08769841269841269\textwidth}P{0.44523809523809527\textwidth}P{0.17539682539682538\textwidth}P{0.14166666666666666\textwidth}}
\tabcellsep \tabcellsep Knowledge\tabcellsep Risk\\
\tabcellsep Pearson Correlation\tabcellsep 1\tabcellsep .592**\\
Knowledge\tabcellsep Sig.(2tailed)\tabcellsep \tabcellsep .000\\
\tabcellsep N\tabcellsep 100\tabcellsep 100\\
\tabcellsep Pearson Correlation\tabcellsep .592**\tabcellsep 1\\
Risk\tabcellsep \tabcellsep \\
\tabcellsep Sig.(2tailed)\tabcellsep .000\\
\tabcellsep N\tabcellsep 100\tabcellsep 100\end{longtable} \par
 
\caption{\label{tab_19}Table 19 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{20} \par 
\begin{longtable}{P{0.0855704697986577\textwidth}P{0.22818791946308725\textwidth}P{0.11979865771812079\textwidth}P{0.19395973154362417\textwidth}P{0.03993288590604027\textwidth}P{0.0855704697986577\textwidth}P{0.09697986577181208\textwidth}}
\tabcellsep \tabcellsep \tabcellsep Risk\tabcellsep \tabcellsep \tabcellsep Total\\
\tabcellsep \tabcellsep Below average\tabcellsep \multicolumn{2}{l}{Average Above average}\tabcellsep Very high\tabcellsep \\
\tabcellsep Student\tabcellsep 5\tabcellsep 3\tabcellsep 1\tabcellsep 0\tabcellsep 9\\
Occupation\tabcellsep Professional\tabcellsep 5\tabcellsep 10\tabcellsep 3\tabcellsep 0\tabcellsep 18\\
\tabcellsep Business\tabcellsep 4\tabcellsep 5\tabcellsep 3\tabcellsep 2\tabcellsep 14\\
\tabcellsep Service\tabcellsep 21\tabcellsep 17\tabcellsep 6\tabcellsep 2\tabcellsep 46\\
\tabcellsep Others\tabcellsep 8\tabcellsep 4\tabcellsep 1\tabcellsep 0\tabcellsep 13\\
Total\tabcellsep \tabcellsep 43\tabcellsep 39\tabcellsep 14\tabcellsep 4\tabcellsep 100\end{longtable} \par
 
\caption{\label{tab_20}Table 20 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{21} \par 
\begin{longtable}{P{0.3\textwidth}P{0.18333333333333335\textwidth}P{0.06666666666666667\textwidth}P{0.3\textwidth}}
\tabcellsep Value\tabcellsep Df\tabcellsep Sig. (2-sided)\\
Pearson Chi-Square\tabcellsep 11.158\tabcellsep 12\tabcellsep .515\end{longtable} \par
 
\caption{\label{tab_21}Table 21 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{22} \par 
\begin{longtable}{P{0.6071428571428571\textwidth}P{0.24285714285714283\textwidth}}
Occupation\tabcellsep Risk\end{longtable} \par
 
\caption{\label{tab_22}Table 22 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{23} \par 
\begin{longtable}{P{0.07544378698224852\textwidth}P{0.3118343195266272\textwidth}P{0.11065088757396449\textwidth}P{0.07544378698224852\textwidth}P{0.12071005917159763\textwidth}P{0.07544378698224852\textwidth}P{0.08047337278106509\textwidth}}
\tabcellsep \tabcellsep \tabcellsep \tabcellsep Risk\tabcellsep \tabcellsep Total\\
\tabcellsep \tabcellsep Below average\tabcellsep Average\tabcellsep Above average\tabcellsep Very high\tabcellsep \\
\tabcellsep Less than 1 Years\tabcellsep 17\tabcellsep 9\tabcellsep 4\tabcellsep 0\tabcellsep 30\\
Experience\tabcellsep 1-4 Years\tabcellsep 14\tabcellsep 19\tabcellsep 7\tabcellsep 0\tabcellsep 40\\
\tabcellsep 4-7 Years\tabcellsep 6\tabcellsep 8\tabcellsep 2\tabcellsep 1\tabcellsep 17\\
\tabcellsep 7-10 Years\tabcellsep 2\tabcellsep 2\tabcellsep 1\tabcellsep 3\tabcellsep 8\\
\tabcellsep 10 years or Above\tabcellsep 4\tabcellsep 1\tabcellsep 0\tabcellsep 0\tabcellsep 5\\
Total\tabcellsep \tabcellsep 43\tabcellsep 39\tabcellsep 14\tabcellsep 4\tabcellsep 100\end{longtable} \par
 
\caption{\label{tab_23}Table 23 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{24} \par 
\begin{longtable}{P{0.3\textwidth}P{0.18333333333333335\textwidth}P{0.06666666666666667\textwidth}P{0.3\textwidth}}
\tabcellsep Value\tabcellsep Df\tabcellsep Sig. (2-sided)\\
Pearson Chi-Square\tabcellsep 33.569\tabcellsep 12\tabcellsep .001\end{longtable} \par
 
\caption{\label{tab_24}Table 24 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{25} \par 
\begin{longtable}{P{0.6071428571428571\textwidth}P{0.24285714285714283\textwidth}}
Experience\tabcellsep Risk\end{longtable} \par
 
\caption{\label{tab_25}Table 25 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{26} \par 
\begin{longtable}{P{0.85\textwidth}}
Year 2014\\
Volume XIV Issue III Version I\\
( ) C\\
Management and Business Research\end{longtable} \par
 
\caption{\label{tab_26}Table 26 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{27} \par 
\begin{longtable}{P{0.3122448979591837\textwidth}P{0.17346938775510204\textwidth}P{0.05204081632653061\textwidth}P{0.3122448979591837\textwidth}}
\tabcellsep Value\tabcellsep Df\tabcellsep Sig. (2-sided)\\
Pearson Chi-Square\tabcellsep 6.285\tabcellsep 9\tabcellsep .711\end{longtable} \par
 
\caption{\label{tab_27}Table 27 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{28} \par 
\begin{longtable}{P{0.6233333333333333\textwidth}P{0.22666666666666666\textwidth}}
Family Size\tabcellsep Risk\end{longtable} \par
 
\caption{\label{tab_28}Table 28 :}\end{figure}
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\end{bibitemlist}
 			 		 	 
\end{document}