We will compare three types of prices, namely, rational (hedging) prices, geometric (growth rate) prices, and martingale (measure) prices. We will show that rational prices in the complete market theory are sometimes contrary to common sense. In the continuous-time case, we insist that the market model should differ between the small volatility case and the large volatility case.
We propose a model to quantify the effect of parameter uncertainty on the option price in the Heston model. More precisely, we present a Hamilton-Jacobi-Bellman framework which allows us to evaluate best and worst case scenarios under an uncertain market price of volatility risk. For the numerical approximation the Hamilton--Jacobi--Bellman equation is reformulated to enable the solution with a finite element method. A case study with butterfly options exhibits how the dependence of Delta on the magnitude of the uncertainty is nonlinear and highly varied across the parameter regime. Keywords: …
We design a novel calibration procedure that is designed to handle the specific characteristics of options on cryptocurrency markets, namely large bid-ask spreads and the possibility of missing or incoherent prices in the considered data sets. We show that this calibration procedure is significantly more robust and accurate than the standard one based on trade and mid-prices.
What does the financial market pricing do? A simulation analysis with a view to systemic volatility, exuberance and vagary
Biondi et al.(2012)开发了一个分析模型,以研究股票市场价格形成随时间推移的新兴动态特性,能够捕捉重要的程式化事实。这些后一种性质证明是敏感的基本信息提供的监管制度,以及对市场的信心条件之间的实际和潜在的投资者。以按市价(公允价值)计量交易证券为基础的制度虽然在市场价格和基本信号之间产生较高的线性相关性,但也涉及较高的市场不稳定性和波动性。这些制度还在市场信心空间的某些区域引发更多相关的市场繁荣和反复无常的事件,在这些区域进一步出现较低的市场流动性。
The cryptocurrency market is volatile, non-stationary and non-continuous. Together with liquid derivatives markets, this poses a unique opportunity to study risk management, especially the hedging of options, in a turbulent market. We study the hedge behaviour and effectiveness for the class of affine jump diffusion models and infinite activity Levy processes. First, market data is calibrated to stochastic volatility inspired (SVI)-implied volatility surfaces to price options. To cover a wide range of market dynamics, we generate Monte Carlo price paths using an SVCJ model (stochastic volatili…