https://github.com/dmorgankx/optionpricing
https://github.com/dmorgankx/optionpricing
Last synced: about 2 months ago
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- Host: GitHub
- URL: https://github.com/dmorgankx/optionpricing
- Owner: dmorgankx
- Created: 2019-07-29T08:30:31.000Z (almost 6 years ago)
- Default Branch: master
- Last Pushed: 2020-06-24T08:16:34.000Z (almost 5 years ago)
- Last Synced: 2024-08-03T17:12:44.471Z (11 months ago)
- Language: HTML
- Size: 6.85 MB
- Stars: 4
- Watchers: 3
- Forks: 8
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
- awesome-q - dmorgankx/optionpricing
README
# Option Pricing in kdb+/q
This repository contains q scripts which can be used to generates Asian and European option prices using Black Scholes, Monte Carlo and Quasi-Monte Carlo methods. The methods demonstrated follow the work presented in the paper [S. Kucherenko et. al 2007](http://www.broda.co.uk/gsa/wilmott_GSA_SK.pdf). The scripts also include wrappers for the C++ pseudo-random and Sobol sequence number generators, along with the functions required to produce both cumulative and inverse cumulative normal distributions.
## Requirements
- [JupyterQ](https://github.com/KxSystems/jupyterq) - this produces a tree dependency for kdb+, Python and embedPy
- Sobol C++ library - `SobolSeq1024` function provided within the library, with max dimension of 1024.
- [matplotlib](https://matplotlib.org/)
**Note**: Before running any of the code, make sure that `$QHOME` is defined.
## Installation
To create the shared object files for the number generators and distribution functions the below must be run:
__Linux__:
```
make && make install && make clean
```
__Windows__ (within `build`):
```
call build.bat
```
**Note**: `build.bat` runs with Visual Studio 2017. To run with 2019 replace line 9 with:
```
call "C:\Program Files (x86)\Microsoft Visual Studio\2019\BuildTools\VC\Auxiliary\Build\vcvars64.bat"
```
For other versions, please modify file accordingly.
## Loading
Examples of option pricing using all of the techniques provided in the library can be run using the Jupyter notebook provided or by running the below script:
```q
q)\l op.q
q)loadfile`:init.q
q)loadfile`:q/run.q
```
Note that `run.q` can be multi-threaded.