Random Portfolio Dataset and Generator

Random variance-covariance matrix generation for portfolio optimization problems

View the Project on GitHub sertalpbilal/randomportfolio

Random Portfolio Dataset and Generator

This page includes a randomly generated portfolio dataset and its generator package. Refer to the links on the left-hand side to download the version you want.

The python script provides a simplified way to generate random variance-covariance matrix for portfolio optimization problems.

The implementation follows the paper of Hirschberger et al. to generate the random variance-covariance matrix (Q). The code also provides return rates (mu) batch sizes (M) and face values (P) in respective folders. It provides a basis that can be modified for any purpose.

Usage

Inside /src folder, call

randomportfolio.py [-h] -n ASSET -f FILENAME [-s SEED] [-e PARAM_E]
                        [-v PARAM_V] [-b PARAM_E_BAR]

Arguments:
  -h, --help            show help message and exit
  -n ASSET, --asset ASSET
                        number of assets
  -f FILENAME, --filename FILENAME
                        file name
  -s SEED, --seed SEED  seed number
  -e PARAM_E, --param_e PARAM_E
                        the e parameter for the method
  -v PARAM_V, --param_v PARAM_V
                        the v parameter for the method
  -b PARAM_E_BAR, --param_e_bar PARAM_E_BAR
                        the e-bar parameter for the method

Example

> python randomportfolio.py -n 200 -f RD1 -s 1122015
Random Portfolio
----------------
Parsing info...
Generating root...
Saving to file...
All done!

Randomly generated data can be found under /data/Q, /data/M, /data/mu, and /data/P

Reference

Hirschberger, Markus, Yue Qi, and Ralph E. Steuer. "Randomly generating portfolio-selection covariance matrices with specified distributional characteristics." European Journal of Operational Research 177.3 (2007): 1610-1625.

License

MIT License

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

Citation

DOI

@Misc{sertalp2016randomportfolio,
  Title                    = {Random Portfolio Dataset Generator},
  Author                   = {Sertalp B. \c{C}ay},
  HowPublished             = {\url{http://sertalpbilal.github.io/randomportfolio/}},
  doi = {10.5281/zenodo.53204},
  url = {http://dx.doi.org/10.5281/zenodo.53204}
}