Pricing autocallables under local-stochastic volatility

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Cite
Farkas, Walter, et al. “Pricing Autocallables under Local-Stochastic Volatility”. Frontiers of Mathematical Finance, vol. 1, no. 4, 2022, pp. 575-10, https://doi.org/10.3934/fmf.2022008.
Farkas, W., Ferrari, F., & Ulrych, U. (2022). Pricing autocallables under local-stochastic volatility. Frontiers of Mathematical Finance, 1(4), 575-610. https://doi.org/10.3934/fmf.2022008
Farkas, Walter, Francesco Ferrari, and Urban Ulrych. “Pricing Autocallables under Local-Stochastic Volatility”. Frontiers of Mathematical Finance 1, no. 4 (2022): 575-610. https://doi.org/10.3934/fmf.2022008.
Farkas W, Ferrari F, Ulrych U. Pricing autocallables under local-stochastic volatility. Frontiers of Mathematical Finance. 2022;1(4):575-610.
Citations
Title Journal Journal Categories Citations Publication Date
Accelerated American option pricing with deep neural networks

 Quantitative Finance and Economics
  • Social Sciences: Finance
 2023
Citations Analysis
Category Category Repetition
Social Sciences: Finance1
The category Social Sciences: Finance 1 is the most commonly referenced area in studies that cite this article. The first research to cite this article was titled Accelerated American option pricing with deep neural networks and was published in 2023. The most recent citation comes from a 2023 study titled Accelerated American option pricing with deep neural networks. This article reached its peak citation in 2023, with 1 citations. It has been cited in 1 different journals. Among related journals, the Quantitative Finance and Economics cited this research the most, with 1 citations. The chart below illustrates the annual citation trends for this article.
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