Michael Zang serves as a Senior Quant/Model Developer at Fannie Mae, where he leverages his extensive expertise in quantitative analysis and model development to drive innovative solutions in the fixed income market. With a strong focus on empirical credit and default modeling, Michael plays a...
Michael Zang serves as a Senior Quant/Model Developer at Fannie Mae, where he leverages his extensive expertise in quantitative analysis and model development to drive innovative solutions in the fixed income market. With a strong focus on empirical credit and default modeling, Michael plays a pivotal role in developing sophisticated econometric models that enhance the predictive accuracy of prepayment and default risks associated with various structured products, including RMBS, CMBS, and CLOs. His hands-on experience with programming languages such as C++, C#, and Python enables him to create robust algorithms that analyze complex datasets, ensuring that Fannie Mae remains at the forefront of the evolving financial landscape.
Michael's current projects involve the development of advanced roll rate and transition models, which are essential for understanding borrower behavior and credit risk dynamics in a fluctuating interest rate environment. His proficiency in time series analysis and signal processing allows him to extract meaningful insights from historical data, informing strategic decisions that mitigate risk and optimize portfolio performance. Additionally, his expertise in data mining and finance equips him with the tools necessary to navigate the intricacies of interest rate derivatives and agency MBS, further solidifying his role as a key contributor to Fannie Mae's mission of providing liquidity and stability to the housing market.
As a thought leader in the field, Michael is committed to continuous learning and innovation, staying abreast of industry trends and emerging technologies that can enhance model accuracy and efficiency. His collaborative approach and ability to communicate complex quantitative concepts make him a valuable asset to cross-functional teams, driving impactful results in a competitive financial environment.
