3 papers
q-fin.ST2026
Reflexivity as Prompt: Does Awareness of Self-Reinforcing Market Dynamics Improve LLMs as Financial Market Forecasters?
Eugene Park
We study how frontier large language models (LLMs) behave as financial forecasters during boom-bust market cycles when made progressively aware of Soros's theory of reflexivity. St…
cs.CL2025
Medical Hallucinations in Foundation Models and Their Impact on Healthcare
Yubin Kim, Hyewon Jeong, Shan Chen +24
Hallucinations in foundation models arise from autoregressive training objectives that prioritize token-likelihood optimization over epistemic accuracy, fostering overconfidence an…
q-fin.ST2023
Principal Component Analysis and Hidden Markov Model for Forecasting Stock Returns
Eugene W. Park
This paper presents a method for predicting stock returns using principal component analysis (PCA) and the hidden Markov model (HMM) and tests the results of trading stocks based o…