BMAR

BMAR is an implementation of "Boosting Moving Average Reversion Strategy for Online Portfolio Selection: A Meta-Learning Approach" implemented in Matlab/Octave.

QUICK START

• bmar1_run.m The implementation of boosting moving average with olmar-1

• bmar2_run.m The implementation of boosting moving average with olmar-2

REFERENCES

Please consider cite the paper:

• Lin X, Zhang M, Zhang Y, et al. Boosting moving average reversion strategy for online portfolio selection: A meta-learning approach[C]//International Conference on Database Systems for Advanced Applications. Springer, Cham, 2017: 494-510.

INSTALLATION

• Just get to the directory of the codes and run the function with its name, the "opts" can be omitted.

ENVIRONMENT

The toolbox has been tested in Matlab 2012b (64-bit and 32-bit) under three major OS: Windows 7/8 (64-bit and 32-bit), Linux (Red-Hat Enterprise Linux) (64-bit and 32-bit) and Mac OS X. The toolbox is also compatable for Octave (version 3.8.0) in the Pseudo GUI (PGUI) and Command Line Interface (CLI) under three major OS: Windows 7, Linux (64-bit and 32-bit), and Mac OS X.

FOLDERS

./bmar1

./bmar2

CONTACT

Lin Xiao

E-mail: [email protected] Tsinghua University

Prof. Zhang Min

E-mail: [email protected] Tsinghua University