A program to take in loan level data and create a model which can predict probability of default
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Updated
May 21, 2020 - Python
A program to take in loan level data and create a model which can predict probability of default
This repository contains the Python notebook used to simulate repo haircut rates for Treasury issues and Asset-Backed Securities (ABSs). It uses these simulations to test a "spike detection" algorithm, meant to gracefully enhance transparency into credit risk factors of ABSs.
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