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# CITATION file created with {cffr} R package
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cff-version: 1.2.0
message: 'To cite package "SVDNF" in publications use:'
type: software
license: GPL-3.0-only
title: 'SVDNF: Discrete Nonlinear Filtering for Stochastic Volatility Models'
version: 0.1.11
doi: 10.32614/CRAN.package.SVDNF
abstract: Implements the discrete nonlinear filter (DNF) of Kitagawa (1987) <https://doi.org/10.1080/01621459.1987.10478534>
  to a wide class of stochastic volatility (SV) models with return and volatility
  jumps following the work of Bégin and Boudreault (2021) <https://doi.org/10.1080/10618600.2020.1840995>
  to obtain likelihood evaluations and maximum likelihood parameter estimates. Offers
  several built-in SV models and a flexible framework for users to create customized
  models by specifying drift and diffusion functions along with an arrival distribution
  for the return and volatility jumps. Allows for the estimation of factor models
  with stochastic volatility (e.g., heteroskedastic volatility CAPM) by incorporating
  expected return predictors. Also includes functions to compute filtering and prediction
  distribution estimates, to simulate data from built-in and custom SV models with
  jumps, and to forecast future returns and volatility values using Monte Carlo simulation
  from a given SV model.
authors:
- family-names: Arsenault-Mahjoubi
  given-names: Louis
  email: larsenau@sfu.ca
- family-names: Bégin
  given-names: Jean-François
- family-names: Boudreault
  given-names: Mathieu
repository: https://CRAN.R-project.org/package=SVDNF
date-released: '2024-10-29'
contact:
- family-names: Arsenault-Mahjoubi
  given-names: Louis
  email: larsenau@sfu.ca