School of Statistics and Mathematics, Shandong University of Finance and Economics, Jinan, China.
School of Insurance, Shandong University of Finance and Economics, Jinan, China.
PLoS One. 2023 Sep 28;18(9):e0292324. doi: 10.1371/journal.pone.0292324. eCollection 2023.
This paper investigates the pricing problem of quanto options with market liquidity risk using the Bayesian method. The increasing volatility of global financial markets has made liquidity risk a significant factor that should be taken into consideration while evaluating option prices. To address this issue, we first derive the pricing formula for quanto options with liquidity risk. Next, we construct a likelihood function to conduct posterior inference on model parameters. We then propose a numerical algorithm to conduct statistical inferences on the option prices based on the posterior distribution. This proposed method considers the impact of parameter uncertainty on option prices. Finally, we conduct a comparison between the Bayesian method and traditional estimation methods to examine their validity. Empirical results show that our proposed method is feasible for pricing and predicting quanto options with liquidity risk, particularly for parameter estimations with a small sample size.
本文运用贝叶斯方法研究了具有市场流动性风险的定量期权定价问题。全球金融市场波动性的增加使得流动性风险成为评估期权价格时需要考虑的一个重要因素。为了解决这个问题,我们首先推导出了具有流动性风险的定量期权的定价公式。然后,我们构建了一个似然函数,以便对模型参数进行后验推断。接下来,我们提出了一种数值算法,根据后验分布对期权价格进行统计推断。该方法考虑了参数不确定性对期权价格的影响。最后,我们将贝叶斯方法与传统估计方法进行了比较,以检验其有效性。实证结果表明,我们提出的方法对于具有流动性风险的定量期权的定价和预测是可行的,特别是对于小样本量的参数估计。