R: A package for generating time series data using fractals
fractalrock-package
R Documentation
A package for generating time series data using fractals
Description
Simulating stock market prices and returns can be accomplished using a number
of techniques. Most commonly, geometric brownian motion (aka a random walk) is used to simulate stock prices. Using this technique results in a normal
distribution of price returns. As an alternative technique, it is possible to
generate price series using fractals. The advantage is that price returns
tend to have volatility that clusters, similar to actual returns.
The basic principle driving fractal generation of time series is that data is
generated iteratively based on increasing levels of resolution. The initial
series is defined by a so-called initiator pattern and then generators are
used to replace each segment of the initial pattern. Regular, repeatable
patterns can be produced by using the same seed and generators. By using a set of generators, non-repeatable time series can be produced. This technique is
the basis of the fractal time series process in this package.
At a later date, implementation of the [modified] rescaled range statistic
will be included to provide more analytical insight into the time series data
produced by this package.
Details
Package:
fractalrock
Type:
Package
Version:
1.1.0
Date:
2013-02-04
License:
GPL-3
To generate a set of asset prices, the function getPortfolioPricesis the most direct way to accomplish this. An xts object will be returned with
one time series per 'asset' provided. In addition, the dates will be coerced
to fit a given business day calendar based on timeDate.
Investigation into fractals via this package is best accomplished by calling the
underlying fractal function. This function produces raw values
useful for analysis of the fractal generation process.
Author(s)
Brian Lee Yung Rowe <r@zatonovo.com>
References
M. Frame, B. Mandelbrot, N. Neger. Fractal Geometry. 2009.
http://classes.yale.edu/fractals/