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Can the Heston Model Forecast Energy Generation? A Systematic Literature Review

Author

Listed:
  • Bianca Reichert

    (Post-Graduation Program in Industrial Engineering, Federal University of Santa Maria, Santa Maria, Brazil,)

  • Adriano Mendon a Souza

    (Department of Statistics, Federal University of Santa Maria, Santa Maria, Brazil.)

Abstract

The ability to predict the price of stock exchange assets has attracted the attention of economists and physicists around the world, as physical models are useful to predict volatility behaviors. Knowing that volatility is crucial for energy sector planning, the research aim was to investigate whether the Heston pricing model is useful to predict energy generation, trough the steps established by the systematic review protocol. In a corpus of 25 documents, it was possible to identify: Lots of financial studies, energy and demography researches; a low level of interaction among universities; the largest number of publications from Australia and China; the most important journal; and the advantages of applying Econophysics models to solve volatility problems. In conclusion, the Heston model can be applied to predict energy generation, since it is a closed-form model and capable of modeling the stochastic volatility, reversing it to the predicted value of average energy generation.

Suggested Citation

  • Bianca Reichert & Adriano Mendon a Souza, 2022. "Can the Heston Model Forecast Energy Generation? A Systematic Literature Review," International Journal of Energy Economics and Policy, Econjournals, vol. 12(1), pages 289-295.
  • Handle: RePEc:eco:journ2:2022-01-36
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    References listed on IDEAS

    as
    1. Przemyslaw S. Stilger & Ngoc Quynh Anh Nguyen & Tri Minh Nguyen, 2021. "Empirical performance of stochastic volatility option pricing models," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 8(01), pages 1-22, March.
    2. Aria, Massimo & Cuccurullo, Corrado, 2017. "bibliometrix: An R-tool for comprehensive science mapping analysis," Journal of Informetrics, Elsevier, vol. 11(4), pages 959-975.
    3. Adrian Dragulescu & Victor Yakovenko, 2002. "Probability distribution of returns in the Heston model with stochastic volatility," Quantitative Finance, Taylor & Francis Journals, vol. 2(6), pages 443-453.
    4. Salvador, Beatriz & Oosterlee, Cornelis W., 2021. "Corrigendum to ``Total value adjustment for a stochastic volatility model. A comparison with the Black–Scholes model''," Applied Mathematics and Computation, Elsevier, vol. 406(C).
    5. Francesco Mainardi, 2020. "On the Advent of Fractional Calculus in Econophysics via Continuous-Time Random Walk," Mathematics, MDPI, vol. 8(4), pages 1-9, April.
    6. Leng, Na & Li, Jiang-Cheng, 2020. "Forecasting the crude oil prices based on Econophysics and Bayesian approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 554(C).
    7. Li, Jiang-Cheng & Li, Yun-Xian & Tang, Nian-Sheng & Mei, Dong-Cheng, 2016. "The roles of mean residence time on herd behavior in a financial market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 350-357.
    8. Zhu, Song-Ping & Lian, Guang-Hua, 2015. "Pricing forward-start variance swaps with stochastic volatility," Applied Mathematics and Computation, Elsevier, vol. 250(C), pages 920-933.
    9. Darren Shannon & Grigorios Fountas, 2021. "Extending the Heston Model to Forecast Motor Vehicle Collision Rates," Papers 2104.11461, arXiv.org, revised May 2021.
    10. Heston, Steven L, 1993. "A Closed-Form Solution for Options with Stochastic Volatility with Applications to Bond and Currency Options," The Review of Financial Studies, Society for Financial Studies, vol. 6(2), pages 327-343.
    11. Xin‐Jiang He & Wenting Chen, 2021. "A semianalytical formula for European options under a hybrid Heston–Cox–Ingersoll–Ross model with regime switching," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 343-352, January.
    12. Ioannis Kyriakou & Panos K. Pouliasis & Nikos C. Papapostolou, 2016. "Jumps and stochastic volatility in crude oil prices and advances in average option pricing," Quantitative Finance, Taylor & Francis Journals, vol. 16(12), pages 1859-1873, December.
    13. Gilles Daniel & Nathan Joseph & David Bree, 2005. "Stochastic volatility and the goodness-of-fit of the Heston model," Quantitative Finance, Taylor & Francis Journals, vol. 5(2), pages 199-211.
    14. Shenghui Wang & Rob Koopman, 2017. "Clustering articles based on semantic similarity," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(2), pages 1017-1031, May.
    15. Xavier Gabaix, 2016. "Power Laws in Economics: An Introduction," Journal of Economic Perspectives, American Economic Association, vol. 30(1), pages 185-206, Winter.
    16. Schwartz, Eduardo S, 1997. "The Stochastic Behavior of Commodity Prices: Implications for Valuation and Hedging," Journal of Finance, American Finance Association, vol. 52(3), pages 923-973, July.
    17. Saqib Mehmood & Amin Qureshi & Anders S. Kristensen, 2020. "Risk Mitigation of Poor Power Quality Issues of Standalone Wind Turbines: An Efficacy Study of Synchronous Reference Frame (SRF) Control," Energies, MDPI, vol. 13(17), pages 1-14, August.
    18. Long Teng & Matthias Ehrhardt & Michael Günther, 2016. "On The Heston Model With Stochastic Correlation," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 19(06), pages 1-25, September.
    19. Pan, Shouzheng & Yan, Hai & He, Jia & He, Zhengbing, 2021. "Vulnerability and resilience of transportation systems: A recent literature review," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 581(C).
    20. Cox, John C & Ingersoll, Jonathan E, Jr & Ross, Stephen A, 1985. "An Intertemporal General Equilibrium Model of Asset Prices," Econometrica, Econometric Society, vol. 53(2), pages 363-384, March.
    21. Vincenzo Russo & Valentina Lagasio & Marina Brogi & Frank J. Fabozzi, 2020. "Application of the Merton model to estimate the probability of breaching the capital requirements under Basel III rules," Annals of Finance, Springer, vol. 16(1), pages 141-157, March.
    22. Zhou, Wei & Zhong, Guang-Yan & Leng, Na & Li, Jiang-Cheng & Xiong, De-Ping, 2019. "Dynamic behaviors and measurements of financial market crash rate," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 527(C).
    23. Jaume Masoliver & Josep Perello, 2006. "Extreme times for volatility processes," Papers physics/0609136, arXiv.org, revised May 2007.
    24. Salvador, Beatriz & Oosterlee, Cornelis W., 2021. "Total value adjustment for a stochastic volatility model. A comparison with the Black–Scholes model," Applied Mathematics and Computation, Elsevier, vol. 391(C).
    25. Zhong, Guang-Yan & He, Feng & Li, Jiang-Cheng & Mei, Dong-Cheng & Tang, Nian-Sheng, 2019. "Coherence resonance-like and efficiency of financial market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    26. Dong, Yang & Wen, Shu-hui & Hu, Xiao-bing & Li, Jiang-Cheng, 2020. "Stochastic resonance of drawdown risk in energy market prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    27. Lin, Sha & He, Xin-Jiang, 2021. "A closed-form pricing formula for forward start options under a regime-switching stochastic volatility model," Chaos, Solitons & Fractals, Elsevier, vol. 144(C).
    28. He, Xin-Jiang & Zhu, Song-Ping, 2016. "An analytical approximation formula for European option pricing under a new stochastic volatility model with regime-switching," Journal of Economic Dynamics and Control, Elsevier, vol. 71(C), pages 77-85.
    29. Richmond, Peter & Sabatelli, Lorenzo, 2004. "Langevin processes, agent models and socio-economic systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 336(1), pages 27-38.
    30. Paulo Ferreira & Éder J.A.L. Pereira & Hernane B.B. Pereira, 2020. "From Big Data to Econophysics and Its Use to Explain Complex Phenomena," JRFM, MDPI, vol. 13(7), pages 1-10, July.
    31. Lorella Fatone & Francesca Mariani & Maria Cristina Recchioni & Francesco Zirilli, 2009. "An explicitly solvable multi‐scale stochastic volatility model: Option pricing and calibration problems," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 29(9), pages 862-893, September.
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    More about this item

    Keywords

    Electricity; Stock Exchange; Stochastic Volatility; Systematic Review;
    All these keywords.

    JEL classification:

    • A12 - General Economics and Teaching - - General Economics - - - Relation of Economics to Other Disciplines
    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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