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arXiv 2009.14764q-fin.MFq-fin.CP
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带随机漂移和扩散的局部波动率模型的校准

Calibrating Local Volatility Models with Stochastic Drift and Diffusion

Orcan Ogetbil, Narayan Ganesan, Bernhard Hientzsch

AI总结:

本研究针对三类局部波动率相关模型提出蒙特卡洛校准算法,推导对应SDE系统、给出校准条件与步骤,在外汇场景下验证了算法的收敛性与准确性。

摘要:

我们针对三类模型提出了蒙特卡洛校准算法:带随机利率的局部波动率模型、带确定性利率的随机局部波动率模型,以及带随机利率的随机局部波动率模型。针对每类模型,我们详细推导了对应的随机微分方程(SDE)系统,并列出了校准所需的输入数据和步骤。我们给出了在已知欧式期权价格、随机利率模型参数及相关性的条件下,局部波动率存在的条件。这些模型设定于外汇场景中,汇率的漂移项由本国和外国两个随机短期利率的差值给出,二者均由G1++过程建模;对于随机波动率,我们用CIR过程对汇率的方差建模。我们还开展了测试,证明了所提算法的收敛性与准确性。

英文摘要:

We propose Monte Carlo calibration algorithms for three models: local volatility with stochastic interest rates, stochastic local volatility with deterministic interest rates, and finally stochastic local volatility with stochastic interest rates. For each model, we include detailed derivations of the corresponding SDE systems, and list the required input data and steps for calibration. We give conditions under which a local volatility can exist given European option prices, stochastic interest rate model parameters, and correlations. The models are posed in a foreign exchange setting. The drift term for the exchange rate is given as a difference of two stochastic short rates, domestic and foreign, each modeled by a G1++ process. For stochastic volatility, we model the variance for the exchange rate by a CIR process. We include tests to show the convergence and the accuracy of the proposed algorithms.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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