Skip to main content

Estimates the Risk Neutral Density and Historical Density of an underlying and suggests trading intervals based on the Pricing Kernel.

Project description

spd_trading

This package estimates the Risk Neutral Density (RND) and Historical Density (HD) of an underlying and suggests a trading strategy based on the Pricing Kernel:

The RND is estimated by Rookley's Method, which uses the option table of one trading day. risk_neutral_density.Calculator.get_rnd

The HD is estimated by a GARCH(1,1) Model, which uses a timeseries of the underlying. historical_density.Calculator.get_hd

The package is part of a Master Thesis, which will be published after grading [1]_. The thesis explains the theoretical background in more detail and gives more references. Furthermore an actual trading strategy was implemented and backtested on real data (BTC options March-September 2019).

The concious desicion of not implementing the actual strategy in the package is due to the high responsibility that would come with publishing such a risky tool. However, the construction of strategies based on the kernels are explained and analyized in the thesis as well.

Installation

Via pip

    pip install spd_trading

Or via download from git:

    pip install git+https://github.com/franwe/localpoly#egg=spd-trading

Note that in order to avoid potential conflicts with other packages it is strongly recommended to use a virtual environment (venv) or a conda environment.

See image in README.md in GitHub repo.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

spd_trading-0.1.0.tar.gz (14.8 kB view details)

Uploaded Source

Built Distribution

spd_trading-0.1.0-py3-none-any.whl (17.7 kB view details)

Uploaded Python 3

File details

Details for the file spd_trading-0.1.0.tar.gz.

File metadata

  • Download URL: spd_trading-0.1.0.tar.gz
  • Upload date:
  • Size: 14.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/3.10.0 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.60.0 CPython/3.7.6

File hashes

Hashes for spd_trading-0.1.0.tar.gz
Algorithm Hash digest
SHA256 2dfb018a5e320ad826af7619790c614ba2ab7b167eca8f5f78d52a2291a01bd2
MD5 4e313ccc4a853e1829bed756b0a618a4
BLAKE2b-256 7483997b7d63d5080fab480fd9124890410dc5ff569b221b7c90edcc1b80c10b

See more details on using hashes here.

File details

Details for the file spd_trading-0.1.0-py3-none-any.whl.

File metadata

  • Download URL: spd_trading-0.1.0-py3-none-any.whl
  • Upload date:
  • Size: 17.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/3.10.0 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.60.0 CPython/3.7.6

File hashes

Hashes for spd_trading-0.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 4daa9ec377ed86617c4e323af3eece0b3842a495bdc22098eb88a22073f476fc
MD5 0190a3ebf5851b73820918e9204f861c
BLAKE2b-256 2e2452aecd7ac75d42c9ddd0ce43adfe912e92d124ffa84d3e0983679fe17fa1

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page