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Working Paper
Designing Market Shock Scenarios
We propose an approach for generating financial market scenarios for stress testing financial firms' market risk exposures. This approach can be used by industry practitioners and regulators for their stress scenario design. Our approach attempts to maximize risk capture with a relatively small number of scenarios. A single scenario could miss potential vulnerabilities, while stress tests using a large number of scenarios could be operationally costly. The approach has two components. First, we model relationships among market risk factors to set scenario shock magnitudes consistently across ...
Working Paper
Evaluating Local Language Models: An Application to Bank Earnings Calls
This study evaluates the performance of local large language models (LLMs) in interpreting financial texts, compared with closed-source, cloud-based models. We first introduce new benchmarking tasks for assessing LLM performance in analyzing financial and economic texts and explore the refinements needed to improve its performance. Our benchmarking results suggest local LLMs are a viable tool for general natural language processing analysis of these texts. We then leverage local LLMs to analyze the tone and substance of bank earnings calls in the post-pandemic era, including calls conducted ...