New answers tagged time-series
3
You need to get the open of the first candle, the high and low over all candles in the time frame and the close of the last candle.
R has a package for this, your language of choice might have it as well.
1
The number of up moves of the stock $S$ after 100 days follows binomial distribution.
To calculate expected value of the stock we have to weight values by probability mass function.
After 100 days we have $k$ up moves of $1+10\%$ and $100-k$ down moves of $1-10\%$ i.e. the value of the stock is $S_0*(1+10\%)^k*(1-10\%)^{(100-k)}$
with probability ${100}\...
3
It is not negative returns that are an issue.
Assume the following prices in two periods:
$P_o = 100$ ; $P_1 = 99$
Standard percent calc:
$$\frac{P_1}{P_0}-1 = -0.01$$ which is -1% .
Using the natural logarithm you get
$$ln(99)-ln(100) = -0.01005$$ which is essentially identical.
Negative prices are an issue - but these are not observed for many economic ...
4
Providing an example:
I believe the best way to verify how the roots of the characteristic equation relates to covariance stationarity of the time-series process, is through an example in the form of an AR(1) process. In a vague sense, using the lag-operator in order to obtain the characteristic equation, offers a transformation of the Autoregressive process ...
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