Pricing Bermudan Callable Derivatives with Default, Collateral Margining, Funding and Investment Costs

A. Amin
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Abstract

In this research note, we price Bermudan structured derivatives including the consequences of default, collateral margining, funding and investment costs. We use LSA Monte Carlo method for finding MTM for collateral margining along all simulation points. We also find 'default MTM' using LSA which helps us calculate cash flows in case of default. Finally we do a third sweep of LS Monte Carlo to calculate 'final MTM' in which we find the price of the derivative while simultaneously calculating funding/investment costs as they themselves depend upon future value of 'final MTM'. All three sets of LSA Monte carlo take just 5-10 seconds for 50K-100K paths and most of the cost associated with computations is in simulation of OIS rates, and Stochastic basis and calculation of basis functions used later for regressions. We also model correlations between default intensities and between default intensities and OIS/Basis rates with an intention to model wrong/Right way risk to some degree. We also give formulas for calculation of survival probabilities/Default Discount Rates in our setting. We also model credit migrations by mapping default probability bands from rating agencies on default intensities.
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定价百慕大可赎回衍生品违约,抵押品保证金,融资和投资成本
在这份研究报告中,我们为百慕大结构性衍生品定价,包括违约后果、保证金、融资和投资成本。我们使用LSA蒙特卡罗方法来寻找沿所有模拟点的抵押品边际的MTM。我们还使用LSA找到了“默认MTM”,这有助于我们计算违约情况下的现金流量。最后,我们对LS蒙特卡罗进行第三次扫描,以计算“最终MTM”,其中我们找到衍生品的价格,同时计算融资/投资成本,因为它们本身取决于“最终MTM”的未来价值。对于50K-100K的路径,这三组LSA蒙特卡罗算法只需要5-10秒,与计算相关的大部分成本是在OIS率的模拟、随机基和基函数的计算上,之后用于回归。我们还对违约强度之间以及违约强度与OIS/Basis利率之间的相关性进行建模,目的是在一定程度上对错误/正确的方式风险进行建模。我们还给出了计算生存概率/违约折现率的公式。我们还通过映射评级机构对违约强度的违约概率带来模拟信用迁移。
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