  This study investigates the relationship between bank efficiency and stock
market valuation using an unbalanced panel dataset of 42 listed banks in China
from 2006 to 2023. We employ a non-radial and non-oriented slack based
super-efficiency Data Envelopment Analysis (Super-SBM-UND-VRS based DEA) model,
which treats Non-Performing Loans (NPLs) as an undesired output. Our results
show that the relationship between super-efficiency and stock market valuation
is stronger than that between Return on Asset (ROA) and stock market
performance, as measured by Tobin's Q. Notably, the Super-SBM-UND-VRS model
yields novel results compared to other efficiency methods, such as the
Stochastic Frontier Analysis (SFA) approach and traditional DEA models.
Furthermore, our results suggest that bank evaluations benefit from decreased
ownership concentration, whereas interest rate liberalization has the opposite
effect.
