# automatically generated by g-sorcery
# please do not edit this file

EAPI=8

REALNAME="${PN}"
LITERALNAME="${PN}"
REALVERSION="${PV}"
DIGEST_SOURCES="yes"
PYTHON_COMPAT=( python{3_11,3_12,3_13,3_14} )
DISTUTILS_USE_PEP517=standalone

inherit python-r1 gs-pypi

DESCRIPTION="RiskOptima is a powerful Python toolkit for financial risk analysis, portfolio optimization, and advanced quantitative modeling. It integrates state-of-the-art methodologies, including Monte Carlo simulations, Value at Risk (VaR), Conditional VaR (CVaR), Black-Scholes, Heston, and Merton Jump Diffusion models, to aid investors in making data-driven investment decisions."

HOMEPAGE="https://github.com/JordiCorbilla/RiskOptima"
LICENSE="MIT"
SRC_URI="https://files.pythonhosted.org/packages/source/${REALNAME::1}/${REALNAME}/${REALNAME}-${REALVERSION}.tar.gz"
SOURCEFILE="${REALNAME}-${REALVERSION}.tar.gz"
RESTRICT="test"

SLOT="0"
KEYWORDS="~amd64 ~x86"

IUSE=""
DEPENDENCIES=">=dev-python/numpy-1.26.4[${PYTHON_USEDEP}]
	>=dev-python/pandas-2.1.4[${PYTHON_USEDEP}]
	>=dev-python/scipy-1.13.1[${PYTHON_USEDEP}]
	>=dev-python/statsmodels-0.14.2[${PYTHON_USEDEP}]
	dev-python/yfinance[${PYTHON_USEDEP}]
	>=dev-python/matplotlib-3.8.4[${PYTHON_USEDEP}]
	>=dev-python/scikit-learn-1.5.1[${PYTHON_USEDEP}]
	dev-python/xgboost[${PYTHON_USEDEP}]
	>=dev-python/seaborn-0.13.2[${PYTHON_USEDEP}]
	dev-python/squarify[${PYTHON_USEDEP}]"
BDEPEND="${DEPENDENCIES}"
RDEPEND="${DEPENDENCIES}"