Board of Governors of the Federal Reserve System

Figure 1. Decomposition of Cumulative Excess Returns into Risk Factors

Series: The cumulative excess returns on the KBW Bank Index.

Horizon: May 3, 2022, to June 7, 2022.

Description: A stacked bar chart with daily (business days) bars from May 3, 2022 to June 7, 2022. Bars are broken into 5 factor-predicted values, an alpha term, and a residual term, which are calculated using a one-month rolling window on specification (1) to predict the excess returns on the KBW bank index. For each bar, the components sum to the actual cumulative excess returns on the KBW index, which is also represented as a black curve overlaying the bars. Units are percentage points, and data are daily (business days). The actual cumulative excess return curve starts at about 2, decreases to about -4 by mid-May 2022, increases to about 6 at the end of May 2022, and remains about the same until the end of the series, June 7, 2022. The daily bars begin with the MKT and HML factors predicting most of the cumulative excess returns on the KBW bank index, with both factors predicting positive returns. After 2 days, these factors continue to explain most of the excess returns, but MKT takes on a negative value and HML takes a positive value until the chart nears the end of May 2022. At the end of May 2022, MKT and HML continue to explain most of the excess returns and again both take on a positive value. The alpha and residual terms remain relatively small throughout the series.

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Figure 2(a). Risk Factors and Exposures to Risk During Inter-meeting Period

Series: Cumulative Fama-French risk factors.

Horizon: May 3, 2022, to June 7, 2022.

Description: A line chart with 5 curves over May 3, 2022, to June 7, 2022. Units are percentage points and data are daily (business days). The cumulative MKT factor curve begins slightly greater than 0, peaks at about 4 on May 4, 2022, steadily decreases to about -7 by mid-May 2022, remains negative until it reaches about 0 by late-May 2022, and ends at about 1 on June 7, 2022. The cumulative SMB factor curve begins at about 0, decreases to about -5 by mid-May 2022, increases to about -1 around May 20, 2022, and remains between -1 and -2 until the end of the series when it ends at about 0. The cumulative HML factor curve begins at about 1, increases to about 10 by mid-May 2022, oscillates slightly before peaking at about 13 at the end of May 2022, and decreases to about 10 by the end of the series. The cumulative TERM factor curve begins just above 0, drops to about -1 for a day at around May 5, 2022, steadily increases to about 2 by the end of May 2022, and decreases to about 0 at the end of the series. The cumulative DEF factor curve begins just above 0, steadily decreases to about -2 by around May 20, 2022, and steadily increases to about 1 by the end of the series.

Figure 2(b). Risk Factors and Exposures to Risk During Inter-meeting Period

Series: The estimated exposure (factor loading) of KBW excess returns to each Fama-French risk factor.

Horizon: May 3, 2022, to June 7, 2022.

Description: A line chart with 5 curves over May 3, 2022, to June 7, 2022. Units are percentage points and data are daily (business days). The MKT curve begins at just under 1 and remains mostly flat as it steadily increases to just over 1 by the end of the series. The SMB curve begins at just above 0, decreases to just under 0 by May 9, 2022, increases and remains steady at about 0.5 until the end of May, and steadily decreases to just below 0 at the end of the series. The HML curve begins at about 0.5, decreases to just above 0 by May 11, 2022, steadily increases to about 0.5 by around May 24, 2022, and remains about the same through the end of the series. The TERM curve begins just below 0, increases to just above 0 by mid-May 2022, decreases to just below 0 by the beginning of June 2022, and ends at about 0. The DEF curve begins at about 0.5, increases to about 1 around May 11, 2022, decreases to about 0 by mid-May, increases to just under 1 by around May 24, 2022, and decreases to its end at about -0.5.

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Figure 3. Fraction of Value and Growth Firms by Industry

Series: The unweighted fraction of value and growth firms by 2-digit NAICS industry.

Horizon: Q4:2015 to Q4:2019.

Description: A horizontal bar chart showing the fraction of value and growth firms by industry, based on 2-digit NAICS industry classifications. The data is from Compustat, covering the period from 2015 to 2019. The chart displays the unweighted fraction of value firms (in blue) and growth firms (in red) for each industry. The x-axis represents the fraction, ranging from 0 to 0.6 (or 0% to 60%). Each industry is represented by a pair of horizontal bars, with the blue bar indicating the fraction of value firms and the red bar showing the fraction of growth firms. The fraction of value firms by industry steadily decreases from the top of the chart to the bottom, while the fraction of growth firms by industry steadily increases from the top of the chart to the bottom. Notably, the industries with the highest fraction of value firms (and lowest fraction of growth firms) are, in descending order, “Management of Companies and Enterprises,” “Finance and Insurance,” “Utilities,” “Agriculture, Forestry, Fishing and Hunting,” “Real Estate and Rental and Leasing,” “Construction,” “Transportation and Warehousing,” and “Mining, Quarying, Oil/Gas.” Industries with approximately the same fraction of value firms and growth firms are “Arts, Entertainment, and Recreation,” “Other Services (except Public Administration),” and “Wholesale Trade.” Finally, the industries with the highest fraction of growth firms (and lowest fraction of value firms) are, in ascending order, “Retail Trade,” “Educational Services,” “Information,” “Admin, Support, Other Services,” “Accommodation and Food Services,” “Manufacturing,” “Health Care and Social Assistance,” and “Professional, Scientific, and Technical Services.”

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Figure 4. Fractions and Banks’ C&I exposure to Value Firms

Series: The fraction of value firms in each 4-digit NAICS industry against banks’ committed exposure for that industry.

Horizon: Q4:2015 to Q4:2019.

Description: Figure 4 is a scatter plot titled "Fractions and Banks' C&I exposure to Value Firms". The plot shows the relationship between the fraction of value firms in different industries and banks' committed exposure to those industries. The x-axis represents "Committed exposure", ranging from 0 to 0.1 (or 0% to 10%). The y-axis represents "Fraction value", ranging from 0.2 to 0.6 (or 20% to 60%). Each point on the plot represents a 4-digit NAICS industry category, based on Compustat data from 2015 to 2019. All dots representing industries where the fraction of value firms is less than the fraction of growth firms (red triangles) are clustered in the bottom left corner of the chart. Dots representing industries where the fraction of value firms is greater than or equal to the fraction of growth firms (blue circles) show a positive relationship beginning in the middle-left of the chart and extending to the top-right. Most of these exist in the left-half of the chart---there is one dot at just past 0.06 and one dot just past 0.1. NAICS industries with a fraction of value firms greater than or equal to the fraction of growth firms and committed exposure greater than 0.018 are labeled with their 4-digit NAICS code. In ascending order of committed exposure, these are: 5241, 2111, 2211, 5222, 5311, 5239, 5221, 5259.

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Figure 5(a). Fraction of Bank Stock Prices Unexplained by Risk Factors

Series: The fraction of stock return movements for three bank indexes that could not be explained by the five Fama-French factors following the NYCB turmoil on January 31, 2024.

Horizon: January 31, 2024 to February 14, 2024.

Description: Panel (a) is a line graph showing the fraction of bank stock prices unexplained by risk factors for three indexes following the NYCB turmoil beginning on January 31st, 2024. The x-axis spans from January 31 to February 14, 2024, with daily data points. The y-axis represents the fraction, ranging from 0.0 to 0.7. Three lines are plotted: (i) KBW Regional (dashed red line): Starts around 0.15, rises sharply to about 0.4 by February 1, and continues to fluctuate between 0.4 and 0.55 for the rest of the period, ending at about 0.55 on February 14. (ii) KBW Regional (modified) (solid purple line): Follows a similar pattern to KBW Regional but with slightly lower values, starting near 0 and ending around 0.5. (iii) KBW (solid black line): Remains relatively stable throughout the period, fluctuating between 0.1 and 0.2, with a slight increase towards the end. The KBW Regional and KBW Regional (modified) indexes show a much higher fraction of unexplained stock price movements compared to the KBW index, indicating a greater impact of the NYCB turmoil on regional banks.

Figure 5(b). Fraction of Bank Stock Prices Unexplained by Risk Factors

Series: The fraction of stock return movements for three bank indexes that could not be explained by the five Fama-French factors following the closure of SVB on March 10, 2023.

Horizon: March 10, 2023 to March 24, 2023.

Description: Panel (b) is a line graph depicting the fraction of bank stock prices unexplained by risk factors for three indexes following the closure of SVB on March 10th, 2023. The x-axis spans from March 10 to March 24, 2023, with data points every few days. The y-axis represents the fraction, ranging from 0.0 to 0.7. Three lines are plotted: (i) KBW Regional (dashed red line): Starts around 0.15, drops to nearly 0 by March 14, then rises to about 0.15 by March 24. (ii) KBW (modified) (solid blue line): Begins at about 0.2, rises to peak at around 0.25 on March 16, then declines to about 0.15 by March 24. (iii) KBW (solid black line): Starts around 0.15, drops to nearly 0 by March 22, then rises slightly to about 0.1 by March 24. In this panel, the KBW (modified) index shows the highest fraction of unexplained stock price movements, while the KBW Regional and KBW indexes follow similar patterns but with lower values. This suggests that the SVB closure had a broader impact on the banking sector beyond just regional banks.

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Figure 6(a). Exposure to the NYCB Shock

Series: Individual bank’s stock price changes against their sensitivity to the NYCB shock.

Horizon: January 30, 2024, to March 5, 2024.

Description: Panel (a) is a scatter plot showing the changes in stock prices against sensitivity to the NYCB shock for individual banks. The x-axis represents the "Sensitivity to NYCB shock," ranging from -0.05 to 0.2. The y-axis shows the "Change in stock price (in %)" from January 30, 2024, to March 5, 2024, ranging from -30% to 10%. Two types of banks are represented: (i) KBW Regional banks (red dots); (ii) KBW banks (blue dots). Dots representing KBW banks are mostly located in the top left of the chart, with a slight negative relationship. Dots representing KBW regional banks are all located on the positive side of the x-axis, and have a significant negative relationship.

Figure 6(b). Exposure to the NYCB Shock

Series: The exposure of each bank to nonfarm nonresidential loans against their sensitivity to the NYCB shock.

Horizon: January 30, 2024, to March 5, 2024.

Description: Panel (b) is a scatter plot illustrating the exposure of banks to nonfarm nonresidential loans against their sensitivity to the NYCB shock. The x-axis represents the "Sensitivity to NYCB shock," ranging from -0.05 to 0.2. The y-axis shows the "Exposure to Nonfarm Nonresidential" loans, ranging from 0 to 40%. Two types of banks are represented: (i) KBW Regional banks (red dots); (ii) KBW banks (blue dots). Dots representing KBW banks are mostly located in the bottom left of the chart, with a slight positive relationship. Dots representing KBW regional banks are all located on the positive side of the x-axis and have a significant positive relationship.

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