First, using = is not a nice practice. Use <- instead (or assign()).
Then format your script properly so as to look pretty: using spaces helps!
Also, having exponential and 'e' named variables can be confusing.
Using non-vectorized for loops is also not a good practice, since they are slow.
To answer the question, you do not have enough variance because the series is converging, because of its functional form, which is
$$ x_{t+1} = \dfrac{e^{0.3 \cdot x_t + \epsilon} - 1}{e^{0.3 \cdot x_t + \epsilon} + 1 }, \qquad x_0 = 0$$
Try this:
beta <- 0
out_matrix <- matrix(NA, 400, 1)
epsilon <- rnorm(1)
for (i in 1:400) {
ifelse( i == 1,
out_matrix[i] <- beta,
out_matrix[i] <- ( ( exp( 0.3 * out_matrix[i-1] + epsilon ) - 1 ) / ( exp(0.3 * out_matrix[i-1] + epsilon ) + 1 ) )
)
}
out_matrix
plot.ts(out_matrix)
my_time_series <- ts(rnorm(400))creates a time series of length 400. Please clarify your question (which program you are using and how do you define your time series). – Konstantinos Jun 15 '15 at 00:28