GARCH option pricing with volatility derivatives

Oh, Dong Hwan; Park, Yang-Ho

doi:10.1016/j.jbankfin.2022.106718

Cited by 5 publications

(1 citation statement)

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“…Furthermore, research has found systematic biases in the Black-Scholes model for pricing stock index options, particularly when options are out of the money. Additionally, the joint estimation of stock returns and volatility derivatives using the GARCH option pricing approach has proven highly beneficial, highlighting the utility of volatility derivatives in GARCH option valuation [4].…”

Section: Literature Reviewmentioning

confidence: 99%

Volatility, Uncertainty, and Option Pricing

Liu

2024

AEMPS

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Amidst global and Chinese uncertainties, this paper delves into stock market volatility and option pricing within the current economic policy context. Focusing on China's stock market, it calculates returns and volatility changes in key indices, analyzing differences among indices and funds, along with temporal variations. Shared data characteristics and reflections on new market trends emerge. Employing methods such as the GARCH model, Black-Scholes formula, and Monte Carlo algorithm, it analyzes volatility and option pricing using extensive annual and monthly data. Visualizations showcase market change patterns. The study defines volatility as a measure of financial asset price fluctuation extent, reflecting asset risk. Higher volatility indicates pronounced price fluctuations and uncertainty, while lower volatility signifies smoother fluctuations and greater certainty. Merging data with volatility's significance, the study probes China's securities market uncertainty, investigating the link between option pricing and volatility. It concludes by identifying the connection between volatility, uncertainty, and option pricing, pointing to future research directions and challenges. Future work will track the latest market trends to enrich understanding.

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Section: Literature Reviewmentioning

confidence: 99%