Accessible Version
What Do Bank Stock Returns Say About Monetary Policy Transmission? Accessible Data
Figure 1. Response to MP Shocks by Bank Size and Leverage
Description: This figure consists of two scatter plots with confidence intervals (Panel a and Panel b) showing estimated stock price responses of banks to a one-standard-deviation (5 basis point) contractionary monetary policy shock. Estimates are shown across deciles of bank size and leverage.
• Panel (a): Size The x-axis represents deciles of bank size, measured by total assets, ranging from 1 (smallest) to 10 (largest). The y-axis shows the estimated stock price response to the monetary policy shock, expressed in basis points. Each decile has a blue dot indicating the estimated coefficient and a vertical dashed line representing the 90 percent confidence interval. The plot shows that banks in the smaller deciles experience less negative responses, while those in higher size deciles tend to exhibit more negative stock price responses.
• Panel (b): Leverage The x-axis represents deciles of bank leverage, measured as the ratio of total assets to net worth (NW), ranging from 1 (least leveraged) to 10 (most leveraged). The y-axis shows the estimated stock price response in basis points. Similar to panel (a), each decile has a blue dot (coefficient estimate) and a dashed vertical line (90 percent CI). More leveraged banks tend to exhibit more negative responses to monetary policy shocks.
Note: The figure shows estimated stock price responses to a one-standard-deviation (5 bp) monetary policy shock by decile of bank size measured by total assets (TA) in panel (a) and leverage measured using the ratios of total assets to net worth (NW) in panel (b). Blue dots represent the coefficient estimate $$\gamma_d^X$$ for each decile, and dashed vertical lines represent 90 percent confidence intervals. The data covers the period from February 1990 to December 2023.
Source: CRSP, Wharton Research Data Services; Compustat, Wharton Research Data Services, Jarociński and Karadi (2020), Kenneth French's Data Library; Federal Financial Institutions Examination Council, Consolidated Reports of Condition and Income for a Bank; Board of Governors of the Federal Reserve, Consolidated Financial Statements for Holding Companies (FR Y-9C).
Figure 2. Response to MP Shocks by Bank Liabilities Composition
Description: This figure consists of two scatter plots with confidence intervals (Panel a and Panel b) illustrating estimated stock price responses of banks to a one-standard-deviation (5 basis point) contractionary monetary policy shock. The estimates are displayed across deciles based on bank funding structure.
• Panel (a): Wholesale Funding Ratio The x-axis displays deciles of wholesale funding ratio, from 1 (lowest ratio) to 10 (highest ratio). The y-axis represents the estimated stock price response to the monetary policy shock in basis points. Each decile is marked by a blue dot indicating the estimated coefficient, with dashed vertical lines denoting the 90 percent confidence interval. The graph shows a pattern where banks with higher wholesale funding ratios (higher deciles) tend to have more negative responses to MP shocks.
• Panel (b): Uninsured Deposits Ratio The x-axis displays deciles of uninsured deposit ratio, from 1 (lowest) to 10 (highest). The y-axis indicates the estimated stock price response in basis points. Blue dots represent the estimated coefficients, while dashed vertical lines indicate the 90 percent confidence intervals. The chart suggests that banks with a higher proportion of uninsured deposits (top deciles) exhibit more negative responses to contractionary monetary policy shocks.
Note: The figure shows estimated stock price responses to a one-standard-deviation (5 bp) monetary policy shock by decile of banks' wholesale funding ratios in panel (a) and uninsured deposit ratios in panel (b). Blue dots represent the coefficient estimate $$\gamma_d^X$$ for each decile, and dashed vertical lines represent 90 percent confidence intervals. The data covers the period from February 1990 to December 2023.
Source: CRSP, Wharton Research Data Services; Compustat, Wharton Research Data Services, Jarociński and Karadi (2020), Kenneth French's Data Library; Federal Financial Institutions Examination Council, Consolidated Reports of Condition and Income for a Bank; Board of Governors of the Federal Reserve, Consolidated Financial Statements for Holding Companies (FR Y-9C).
Figure 3. Response to Instrumented Factors by Bank Size
Description: This figure contains two scatter plots with confidence intervals (Panel a and Panel b) illustrating how the pass-through of instrumented risk factors to bank stock returns varies across deciles of bank size.
• Panel (a): MKT Factor The x-axis represents deciles of bank size, measured as total assets in the calendar year preceding each month, from 1 (smallest) to 10 (largest). The y-axis shows the estimated pass-through (coefficient) of the instrumented market (MKT) factor. Each decile is represented by a blue dot for the coefficient estimate and a dashed vertical line indicating the 90 percent confidence interval. The chart shows a clear upward trend, where the response to the market factor increases with bank size.
• Panel (b): HML Factor The x-axis again represents deciles of lagged bank size, and the y-axis displays the estimated pass-through of the instrumented value (HML) factor. Blue dots represent estimated coefficients, and dashed lines show the 90 percent% confidence intervals. While less monotonic than Panel (a), there is a tendency for larger banks (higher deciles) to exhibit greater sensitivity to the HML factor.
Note: The figure shows the estimated pass-through of instrumented risk factors to banks’ stock returns by size deciles. Panel (a) presents results for the market factor (MKT), and Panel (b) presents results for the value factor (HML). Bank size is total assets in the calendar year preceding each month. Blue dots represent the coefficient estimate $$\gamma_d^X$$ for each decile, and dashed vertical lines represent 90 percent confidence intervals. The data covers the period from February 1990 to December 2023.
Source: CRSP, Wharton Research Data Services; Compustat, Wharton Research Data Services, Jarociński and Karadi (2020), Kenneth French's Data Library; Federal Financial Institutions Examination Council, Consolidated Reports of Condition and Income for a Bank; Board of Governors of the Federal Reserve, Consolidated Financial Statements for Holding Companies (FR Y-9C).