The Effect of Behavioral Finance on Stock Investment Decisions

Normality Test

Many studies especially those concentrating on the emerging stock markets and least developed economies reported that these markets were at a very high level of data nonnormality.

Normality test investigates if the sample observations are normally distributed. The test compared the values of observations distributed with normal distribution mean and standard deviation, and showed that the sample was free of outliers. The null hypothesis was that "sample distribution was normal". If the test was significant, the distribution was non-normal. The main tests for the assessment of normality were Kolmogrov-Semernov (K-S) test and Shapiro-Wilk test. Table 6 shows the results of normality test.

Variable	Kolmogrov-Semirnov			Shapiro-Wilk
Table 6 : Distributed Sample Normality Test
Variable	Statistic	df	Sig.	Statistic	df	Sig.
Loss Aversion	0.069	150	0.200	0.981	150	0.122
Overconfidence	0.073	150	0.150	0.977	150	0.061
Herding	0.060	150	0.200	0.988	150	0.200
Risk Perception	0.070	150	0.165	0.983	150	0.141
Stock Investment Decision	0.075	150	0.095	0.978	150	0.064

Table 6 reveals that all values of the test were not significant (Sig>0.05). This means that there were no outliers, and that the sample followed normal distribution.