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Imperfect Hedging in Defaultable Markets and Insurance Applications
2016
In this thesis, we study the impact of random times to model and manage unpredictable risk events in the financial models. First, as a generalization of the classical Neyman-Pearson lemma, we show how to minimize the probability of type-II-error when the null hypothesis, alternative and the significance level all are revealed to us randomly. This randomness arises some measurability requirements that we have dealt with them by using a measurable selection argument. Then, we consider a
doi:10.7939/r3862bk6t
fatcat:pv27rk2hdfaatlakrhnepffcvq