Lending Club Data Analysis and Algorithms
lcbt.py is a Genetic Algorithm which analyses the Lending Club data and searches for the best criteria and lending club filters to reduce default rates and maximize (NAR) Net Annual Return
The inspiration comes from David M. Patierno PHP implementation
http://blog.dmpatierno.com/post/3161338411/lending-club-genetic-algorithm
Lending Club Data can be found here and is automatically downloaded if it cannot be found https://www.lendingclub.com/info/download-data.action
Lending Club Data field descriptions are here http://www.lendingclub.com/kb/index.php?View=entry&EntryID=253
Here are the usage models
C:\pypy-2.0.2\pypy.exe lcbt.py
C:\Python27\python.exe -O lcbt.py
C:\Python32\python.exe -O lcbt.py
Best performance with linux + pypy + zmqpy
[iteration 190/4096 6.16 sec/iter] 1024 loans (48/mo.) test at 15.63% APY. 45 loans defaulted (4.00%, $21.30 avg loss) 11.9808% net APY
[iteration 53/4096 49.54 sec/iter] 1013 loans (50/mo.) test at 15.51% APY. 40 loans defaulted (3.00%, $21.15 avg loss) 12.2170% net APY
Some of the performance figures on my laptop
##New version using bit vectors##
[iteration 1955/4096 24.13 sec/iter] 1010 loans (48/mo.) test at 15.90% APY. 43 loans defaulted (4.00%, $22.24 avg loss) 12.1523% net APY
[iteration 4/4096 114.57 sec/iter] 2203 loans (87/mo.) test at 12.58% APY. 119 loans defaulted (5.00%, $21.49 avg loss) 8.0941% net APY
##First version
[iteration 76/4096 43.89 sec/iter] 1037 loans test at 19.54% APY. 2 loans defaulted (0.00%, $22.67 avg loss) 20.0333% net APY
[iteration 1/4096 176 secs/iter] 1356 loans test at 15.56% APY.3 loans defaulted (0.00%, $20.62 avg loss) 15.3609% net APY
[iteration 3/4096 186.94 sec/iter] 1377 loans test at 17.07% APY. 2 loans defaulted (0.15%, $23.00 avg loss) 17.0613% net APY
- Verify based on www.lendstats.com
- Python Lending Club API http://python-lendingclub.readthedocs.org/en/latest/
$ curl -O http://python-distribute.org/distribute_setup.py
$ curl -O https://raw.githubusercontent.com/pypa/pip/master/contrib/get-pip.py
$ ./pypy-2.1/bin/pypy distribute_setup.py
$ ./pypy-2.1/bin/pypy get-pip.py
$ ./pypy-2.1/bin/pip install pygments
$ ./pypy-2.1/bin/pip install zmqpy
$ ./pypy-2.1/bin/pip install pyzmq
C:\\Users\gczajkow\boost\boost_1_53_0>.\b2 toolset=msvc-12.0 install --prefix=C:\\Users\gczajkow\boost\boost_1_53_0.release