PFM® The PFM Community Bank Investment Index
An Independent, Peer Based Framework for Regional and Community Banks for
Assessing Securities Portfolio Risk and Return
December 2016
Authored By:
Alfred Mukunya, Director, PFM Swap Advisors LLC
Contributors:
Jonathan Sundberg, Senior Managing Consultant, PFM Asset Management LLC
Anthony Pappion, Senior Managing Consultant, PFM Asset Management LLC
From The PFM Group. The PFM Group of companies are national leaders in providing independent financial
advice, investment advisory services, and management and consulting services to local, state, and regional
governments, non-profit, and other institutional clients.
Abstract
According to the Federal Deposit Insurance Corporation
(FDIC), the market size of securities invested in by more
than 5,000 community banks stands at more than $574
billion as of September 30, 2016. A securities index
comprised of the constituent investments reported by
these banks nationwide provides investors, regulators, and
market participants a tool to assess the risk and return
profile of this universe. Sector allocation weights express
the community banking industry’s collective positioning
regarding risk and return. This index provides a benchmark
for peer comparison of investment performance. In
aggregate, it provides a consolidated view of the community
banking sector’s investments.
The PFM Asset Management LLC (PFMAM) Community
Bank Investment Index (PFM CBI Index) is a mathematical
and statistical construct that provides for powerful
quantitative and qualitative analysis, utilizing well-accepted
methods of index construction. The PFM CBI Index has
been developed and is maintained by PFMAM, part of The
PFM Group of companies.
Overview
A core purpose of banking is evaluation and decisionmaking relating to credit risk. The sheer size and politics of
the United States results in localized situations that require
a relationship banking assessment for efficient evaluation of
credit in a manner that cannot be adequately or efficiently
addressed by a national institution. Community banks
provide this localized function. The FDIC notes that the
key characteristic of a community bank is one that operates
within a limited geographic scope. Capital adequacy
requirements of community banks generally will differ, as
do their liquidity needs from national lending institutions.
Community banks make comparisons amongst each
other, and regulators also make comparisons to evaluate
performance, lending capacity, and capital adequacy. The
securities portfolio is normally a significant size of a lender’s
balance sheet, so it will display different characteristics
that should suit a community bank’s needs and purpose of
operating within its localized market, and it will need to be
compared to other community banks. Peer comparisons
are essential amongst institutions as a means of evaluating
individual and collective operating strategies, lending
practices, funding strategies, earnings, and other business
metrics. With thousands of community banks nationwide,
and a significant amount of securities investments,
community bank securities portfolios possess a uniqueness
that reflects their appetite for risk and return.
Evaluation of a community bank’s securities portfolios
generally has been qualitative and anecdotal. Using
traditional benchmark index construction, PFMAM
presents a framework that screens the securities universe
representing the community bank’s style of investing as
the industry itself actively and collectively describes. This
information is provided by the FDIC, and we believe the
PFM CBI Index will avail to community and regional banks
a useful means for quantitative and analytical approach to
portfolio evaluation.
The PFM Community Bank Investment Index | 1
Construction Rules and Methodology
(as implemented and followed by the PFM CBI Index
Committee)
The following are key definitions, rules, and general
methodology employed for the PFM CBI Index.
Consolidated Reports of Condition and Income
(Call Reports)
Every national bank, state member bank, insured state
nonmember bank, and savings association is required to
file Consolidated Reports of Condition and Income (a
Call Report) as of the close of business on the last day of
each calendar quarter. Institutions submit Call Report
data to the bank regulatory agencies for use in monitoring
the condition, performance, and risk profile of individual
institutions and the industry as a whole. Call Report data
serves a regulatory and public policy purpose by assisting
the agencies in fulfilling their missions of ensuring the
safety and soundness of financial institutions and the
financial system, the protection of consumer financial
rights, and agency-specific missions affecting national- and
state-chartered institutions, e.g., monetary policy, financial
stability, and deposit insurance.
Call Reports are the source of the most current statistical
data available for identifying areas of focus for on-site
examinations and off-site monitoring. Call Report data
contains the securities holdings of the institutions. Agencies
use Call Report data to evaluate the corporate applications
of institutions and to calculate the deposit insurance
assessments of institutions, as well as the semi-annual
assessment fees of national banks and federal savings
associations. Call Report data also is used by the public,
state banking authorities, researchers, bank rating agencies,
and the academic community.
PFMAM utilizes the securities data contained in the Call
Report for the PFM CBI Index.
Inception Date
The Inception Date is August 15, 2014. As of the Inception
Date, there were 5,546 institutions included in the PFM
CBI Index, and the total reported value of securities was
$531,046,906,000.
Fixing Dates
Call Report data is released on a quarterly basis, and
availability of the data determines the Fixing Dates of the
PFM CBI Index. The data is due from each institution
within 35 days of the end of each calendar quarter.
Approximately 95% of institutions have filed within 30 days.
To allow for processing time, the Fixing Dates shall be as
follows:
Fixing Date
May 15
August 15
November 15
February 15
Call Report Release Date
1st Quarter, March 31
2nd Quarter, June 30
3rd Quarter, September 30
4th Quarter, December 31
Dates of the Index Fixing Dates provide a reference point
for index users to know of any changes to the PFM CBI
Index composition. Index constituents remain the same
during the quarter. There is no reconstitution during
the interim period. This process provides a reasonable
compromise between practicality and comprehensiveness of
available data.
Sector Definitions
The following sectors are examined, as classified by the
FDIC:
• US Governments/Agencies
• Private Issue Asset-Backed Securities
• Structured Notes
•Municipals
•Corporates
• Foreign Debt
•Equities
Sub-Index Selection, Eligibility, and Mapping –
Stratified Sampling
To avail community banks the power of a benchmark
index, the PFM CBI Index is a composite index comprised
of subsector indices. PFMAM selects sub-index members
that correspond to the FDIC classifications above. The
stratification is based on the sectors provided by the FDIC.
These subsector index members must be widely available
and allow for risk/return measurement and aggregation for
the PFM CBI Index. Price availability, history, transparency,
and look-through ability to individual securities of the
sub-indices make them eligible for inclusion into the
PFM CBI Index. Performance of a sub-index plays no
role for inclusion. Each sub-index is then mapped to the
appropriate FDIC defined sector. This stratified sampling
of the PFM CBI Index relies on PFMAM experience and
expertise to stratify the index appropriately, and to select
the appropriate subsector indices that fit into the sectors.
Criteria
FDIC Bank Size
FDIC Sectors
FDIC Sector Weightings
Sub-Index Selection
Sub-Index Mapping
Update Frequency
Annually
As provided by FDIC
Quarterly, on Fixing Date
Quarterly, on Fixing Date
Quarterly, on Fixing Date
The PFM Community Bank Investment Index | 2
Characteristics of the PFM CBI Index
There are three underlying principles of the PFM CBI
Index:
1. Sector allocation weights express the industry’s
“collective wisdom” of risk versus return;
2. Provision of the best available informational
benchmark for peer comparison of investment
performance; and
3. Presentation of an agnostic view of the sector’s
investments.
The following are charts describing the PFM CBI Index,
and a comparison with a leading broad-based, fixed-income
benchmark, the Barclays US Aggregate Bond Index:
PFMAM CBI
Index
PFMAM
CBI
Index
Agency Debt
US Municipal Debt
US Government Debt (Non Mortgage)
Regression Analysis (8/15/14 - 11/30/16)
PFMAM CBI %
PFM CBI Index Committee Decision Process
This rules-based, rather than performance basis for
construction, results in a benchmark that seeks to describe
investment and style exhibited by community banks,
and does not provide for any investment decision or
recommendation.
0.5
0.4
0.3
0.2
0.1
0.0
-0.1
-0.2
-0.3
-0.4
-0.5
-1.1
-0.9
-0.7
-0.5
-0.3
-0.1
0.1
0.3
0.5
0.7
Barclays U.S. Aggregate %
Linear Beta
Range 1
Raw BETA
0.491
Adjusted BETA
0.661
ALPHA (Intercept)
0.004
R2 (Correlation2)
0.876
R (Correlation)
0.936
Standard Deviation of Error
0.039
Standard Error of ALPHA
0.002
Standard Error of BETA
0.008
t-Test63.476
Significance0.000
Last T-Value
-2.257
Last P-Value
0.012
Number of Points
572
Last Spread
1874.47
Last Ratio
0.053
PFM CBI Index vs. LBUSTRUU regression analysis, from 08/15/2014 (Inception Date) to
11/30/2016. Calculated on Bloomberg®.
Corporate Debt
US Treasuries
Private-Label ABS
Equities
Foreign Debt
0%
10%
20%
30%
40%
50%
CharacteristicValue
Maturity (Years from Today)
5.84
Yield to Worst
2.27
Yield to Maturity
2.45
Modified Duration
4.18
Option-Adjusted Duration
4.34
Contribution to Duration
4.34
Option-Adjusted Convexity
-0.30
Option-Adjusted Spread (OAS)
32.67
Coupon3.29
Bloomberg Composite Rating
AA
PFM CBI Index characteristics as of 11/30/2016. Calculated on Bloomberg®.
Return Comparison (8/15/14 - 11/30/16)
110
PFMAM CBI Index
108
Barclays U.S. Aggregate Index
106
104
102
100
98
96
94
Aug
‘14
Oct
'14
Dec
'14
Feb
'15
Apr
'15
Jun
'15
Aug
'15
Oct
'15
Dec
'15
Feb
'16
Apr
'16
Total Return
Jun
'16
Aug
'16
Oct
'16
Index
Price Change
PFMAM CBI
Barclays U.S. Aggregate
4.14%4.14%-0.39%
4.53%
4.53%
Difference
Applications of the PFM CBI Index
(a) Historical and Trend Assessment. The PFM CBI
Index provides a snapshot of the community bank
sector’s profile of a significant portion of its balance
sheet. Historical and trend analysis can be performed to
provide information on community bank investments.
(b)Sector Allocation Assessment. The PFM CBI Index
can be seen as providing a snapshot of risk versus
return across securities holdings held by community
banks. Portfolio managers have lacked relevant or
appropriate benchmarks for overall guidance, relying
on broad-based market indices and anecdotal trends
rather than quantitative benchmarks that would reflect
a community bank’s risk return profile. Since this basket
of securities provides an objective descriptor of the risk
return profile of the community banks, it is a powerful
comparison tool that can be used by an individual bank.
It forms the cornerstone for an independent, peer-based
framework for regional and community banks to assess
a securities portfolio’s risk and return. It allows banks to
gauge their performance against others in the industry.
At a glance, a bank portfolio manager can assess how
overweight or underweight they are in a given sector
with respect to their peers, or the collective.
PFM CBI Index vs Barclays US Aggregate Bond Index (ticker LBUSTRUU) historical returns, from
08/15/2014 (Inception Date) to 11/30/2016. Calculated on Bloomberg®.
The PFM Community Bank Investment Index | 3
(c) Individual Portfolio Assessment. Access to the PFM
CBI Index can allow for performance measurement on
an ongoing basis. There are several fixed-income indices
used by investors, but PFMAM knows of none that
track the community banks’ collective investment style
and preferences. The PFM CBI Index recognizes the
unique investment profile of community and regional
banks and provides the appropriate benchmark for
securities investments.
Advanced Portfolio Construction
(a) Portfolio Optimization using Linear Programming.
Maximizing yield on a conservative fixed-income
portfolio of investment-grade securities can be
challenging with limited time, tools, and resources, as
well as additional constraints imposed by regulators and
bank boards. Using the PFM CBI Index, an institution
can apply a disciplined and quantitative approach to
portfolio construction that would extend the stratified
sampling performed with the PFM CBI Index. Given
a finite amount of dollars to invest in a portfolio, an
objective function when selecting from a universe of
securities is maximizing return while staying within
constraints as identified by the PFM CBI Index.
Out of this comes the ability to develop a Research
Allocation Model Portfolio (“RAMP”), representing a
basket that mimics or closely tracks to the PFM CBI
Index. A bank can seek to optimize portfolio returns
given its individual constraints, while staying within
acceptable bounds of volatility or comparable returns
of peers within the PFM CBI Index. In other words,
a community bank can seek to maximize yield of its
portfolio subject and remain within an appropriate risk
budget relative to other peer investment portfolios. The
fact that the PFM CBI Index is developed independently
means the resulting portfolio analytics reports that
describe a portfolio can be very useful in providing
management, boards, Asset-Liability Committee
(ALCO), and regulators an independent view of a bank’s
portfolio in comparison to the industry at-large. A bank
or bank subsidiary can design an effective investment
strategy that implicitly takes into consideration a peer
comparison, or alternatively, simply use the PFM CBI
Index as an ongoing gauge of where the portfolio stands
with respect to its peers.
(b)Portfolio Optimization using Quadratic
Programming. Instead of an objective that only
maximizes the expected return of a portfolio when
selecting a basket of securities from a universe, the
quadratic programming objective also minimizes
the difference between the expected total return of
the portfolio and its benchmark. This optimization
approach also is called “variance minimization”
because this risk-return trade-off is in the objective.
The constraints are still a part of the overall
optimization approach. The concept of a Tracking
Error is introduced. This measures how closely a
portfolio follows the index to which it is benchmarked.
Replicating a benchmark would result in a tracking
error of zero, and no incremental return above the
benchmark. The Tracking Error is used in reporting
performance and controlling risk, and can be used as
a target for the portfolio optimization process. The
Tracking Error Volatility (TEV) measures the volatility
of the difference between the performance of a portfolio
and the performance of its chosen benchmark. A low
TEV indicates a passively managed portfolio, while a
high TEV — either positive or negative — indicates an
actively managed portfolio.
Conclusion
PFMAM recognizes that regional and community banks are
subject to unique restrictions and regulatory requirements,
and therefore have additional considerations in meeting the
objectives to seek yield, liquidity and safety when making
their securities investment allocation decisions. PFMAM
uses FDIC information and independent mappings in the
construction of the PFM CBI Index to aid these banks
in their endeavor. In contrast, national bank institutions
have the resources and tools to perform advanced
portfolio optimization; for example, they use classic linear
programming or quadratic programming methods for fixed
income investment analysis in seeking to maximize yield or
return on a portfolio, subject to a set of prescribed criteria.
Their large portfolios allow for the scale and provide the
resources to perform this dedicated analysis. Conversely,
smaller institutions will often perform this analysis
anecdotally, without any corresponding or rigid benchmark
to compare to peers for use when making their decisions.
PFMAM acknowledges that our clients in the regional
and community banking sector are devoted to building
communities, and we strive to support them in achieving
this by making tools available to help them manage risk and
preserve principle. We are proud to say that the PFM CBI
Index is such a tool, providing new insight and capability
for better portfolio management.
The PFM Community Bank Investment Index | 4
REFERENCES
Federal Deposit Insurance Corporation (FDIC). www.fdic.gov.
FDIC. (2012, Dec.). “FDIC Community Banking Study.”
https://www.fdic.gov/regulations/resources/cbi/report/cbi-full.pdf
Kumar, A. (2009). “Portfolio Optimization.” New York, NY: Barclays Capital Research Publications.
Kumar, A. and Lazanas, A. (2009). “Barclays Capital Portfolio Optimizer – User Guide” New York, NY:
Barclays Capital Research Publications.
Lazanas, A. (2011). “A Portfolio Manager’s Guide to Multi-Factor Fixed Income Risk Models and Their Applications.”
New York, NY: Barclays Capital Research Publications.
Mossavar-Rahmani, S. (1997). “Indexing Fixed Income Assets.” In Frank J. Fabozzi (Ed.),
The Handbook of Fixed Income Securities (5th ed.). Chicago, IL: Irwin Professional Publishing.
Peifer, D. B. (1997). “A Sponsor’s View of Benchmark Portfolios.” In Frank J. Fabozzi (Ed.),
The Handbook of Fixed Income Securities (5th ed.). Chicago, IL: Irwin Professional Publishing.
Reifel, M. Bloomberg Finance, L.P. (2013). “Portfolio Construction in Port <GO> Trade Simulation and Portfolio Optimization User Guide.” A Bloomberg White Paper.
Reilly, F. K. and Wright, D. J. (2013). “Bond Market Indexes.” In F. Fabozzi and S. Mann (Eds.),
The Handbook of Fixed Income Securities (8th ed.). The McGraw-Hill Companies, Inc.
This guidance is not a substitute for reading and understanding relevant professional literature, related entity governing documents, and
transaction level documentation. The views expressed within this material constitute the perspective and judgment of PFM Asset Management
LLC (PFMAM) at the time of distribution and are subject to change. Opinions presented are not necessarily indicative of future events. Information
contained herein is based on data obtained from recognized statistical services, issuer reports or communications, or other sources, believed to
be reliable. No representation is made as to its accuracy or completeness. This material is intended for informational purposes. It should not be
construed as an offer to purchase/sell any investment.
PFMAM is registered with the Securities and Exchange Commission (SEC) under the Investment Advisers Act of 1940 and provides independent
investment advisory services to state and local governments, not-for-profit organizations, and other institutional investors. PFMAM is a leading
money manager in the United States, and currently has more than $105 billion in assets under management and advisement as of September 30,
2016, including $66.2 billion in assets under discretionary management and $39.1 billion in assets under non-discretionary advisement. A copy of
our Form ADV, Parts 2A & B is available upon request.
The PFM Community Bank Investment Index | 5