gs_quant.timeseries.statistics.generate_series¶
-
generate_series
(length)[source]¶ Generate sample timeseries
- Parameters
length (
int
) – number of observations- Return type
Series
- Returns
date-based time series of randomly generated prices
Usage
Create timeseries from returns generated from a normally distributed random variables (IDD). Length determines the number of observations to be generated.
Assume random variables \(R\) which follow a normal distribution with mean \(0\) and standard deviation of \(1\)
\(R \sim N(0, 1)\)
The timeseries is generated from these random numbers through:
\(X_t = (1 + R)X_{t-1}\)
Examples
Generate price series with 100 observations starting from today’s date:
>>> prices = generate_series(100)
See also
numpy.random.normal()