/PyfengForPapers

Python Code for Quantitative Finance Papers

Primary LanguageJupyter NotebookGNU General Public License v3.0GPL-3.0

PyfengForPapers

PyfengForPapers hosts a collection of the Py notebooks (.ipynb) that use PyFENG package to reproduce the results of financial engineering papers. This repository aims to help researchers by providing a replication for published papers. The installation of PyFENG is required.

PyFENG Installation

  • For the first-time installation, 
    pip install pyfeng
  • For an upgrade, 
    pip install --upgrade pyfeng
  • If running on your modified implementation,
    • Make a local copy of PyFENG repository by forking or download.
    • Make necessary modifications.
    • Uncomment the following lines in the beginning of notebook file. Then, the local PyFENG will be used. 
      %load_ext autoreload
%autoreload 2
      import sys
sys.path.insert(sys.path.index('')+1, 'PATH_TO_LOCAL_PYFENG')

List of Implemented Papers

  • Notebook | Choi J, Huh J & Su N (2024). Tighter 'uniform bounds for Black–Scholes implied volatility' and the applications to root-finding. Operations Research Letters, 57, 107189. DOI:10.1016/j.orl.2024.107189 [arXiv]
  • Notebook | Choi J & Seo BK (2023). Option pricing under the normal SABR model with Gaussian quadratures. [arXiv]
  • Notebook | Choi J & Chen R (2022). Improved iterative methods for solving risk parity portfolio. Journal of Derivatives and Quantitative Studies, 30(2), 114-124. DOI:10.1108/JDQS-12-2021-0031 (Open Access) [arXiv].
  • Notebook | Choi J et al. (2022). A Black-Scholes user's guide to the Bachelier model. Journal of Futures Markets, 42(5), 959-980. DOI:10.1002/fut.22315 [arXiv]
  • Notebook | Choi J & Wu L (2021). A note on the option price and 'Mass at zero in the uncorrelated SABR model and implied volatility asymptotics.' Quantitative Finance, 21, 1083. DOI:10.1080/14697688.2021.1876908 [arXiv]
  • Notebook | Choi J & Wu L (2021). The equivalent constant-elasticity-of-variance (CEV) volatility of the stochastic-alpha-beta-rho (SABR) model. Journal of Economic Dynamics and Control, 128, 104143. DOI:10.1016/j.jedc.2021.104143 [arXiv]
  • Notebook | Krekel M, de Kock J, Korn R, & Man TK (2004). An analysis of pricing methods for basket options. Wilmott Magazine, 2004(7), 82–89.
  • Notebook | Several SABR Model papers by Antonov and co-authors.
    • Antonov A, & Spector M (2012). Advanced analytics for the SABR model. [SSRN]
    • Antonov A, Konikov M, & Spector M (2013). SABR spreads its wings. Risk, 2013(Aug), 58–63.
    • Antonov A, Konikov M, & Spector M (2019). Modern SABR Analytics. Springer International Publishing. DOI:10.1007/978-3-030-10656-0
  • Notebook | Choi J, Liu C, & Seo BK. (2019). Hyperbolic normal stochastic volatility model. Journal of Futures Markets, 39(2), 186–204. DOI:10.1002/fut.21967 [arXiv]
  • Notebook | Ball CA, Roma A (1994). Stochastic Volatility Option Pricing. Journal of Financial and Quantitative Analysis 29:589–607. DOI:10.2307/2331111
  • Notebook | Schöbel R, Zhu J (1999). Stochastic Volatility With an Ornstein–Uhlenbeck Process: An Extension. Review of Finance 3:23–46. DOI:10.1023/A:1009803506170
  • Coming Soon | Choi J (2018). Sum of all Black-Scholes-Merton models: An efficient pricing method for spread, basket, and Asian options. Journal of Futures Markets, 38:627–644. DOI:10.1002/fut.21909
  • Notebook | Barone-Adesi G, Rasmussen H, Ravanelli C (2005). An option pricing formula for the GARCH diffusion model. Computational Statistics & Data Analysis 49:287–310. DOI:10.1016/j.csda.2004.05.014
  • Notebook | Baldeaux J (2012). Exact simulation of the 3/2 model. International Journal of Theoretical and Applied Finance, 15:1250032. DOI:10.1142/S021902491250032X