The PFM Community Bank Investment Index

PFM The PFM Community Bank Investment Index An Independent, Peer Based Framework for Regional and Community Banks for Assessing Securities Portfolio Risk and Return 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 December 2016 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 ust 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 Call Report Release Date May 15 1st Quarter, March 31 ust 15 2nd Quarter, June 30 November 15 3rd Quarter, September 30 February 15 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 The PFM Community Bank Investment Index 2

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. 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: US Government Debt (Non Mortgage) 110 108 106 104 102 100 98 96 94 14 '14 Agency Debt US Municipal Debt Corporate Debt US Treasuries Private-Label ABS Dec '14 Equities Foreign Debt Characteristic Feb Apr PFMAM CBI CBI Index Index 0% 10% 20% 30% 40% 50% Return Comparison (8/15/14-11/30/16) PFMAM CBI Index Barclays U.S. Aggregate Index Jun Dec Feb Value 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 Coupon 3.29 Bloomberg Composite Rating AA PFM CBI Index characteristics as of 11/30/2016. Calculated on Bloomberg. Index Price Change Total Return Difference PFMAM CBI 4.14% 4.14% -0.39% Barclays U.S. Aggregate 4.53% 4.53% Apr Jun PFMAM CBI % Regression Analysis (8/15/14-11/30/16) 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-test 63.476 Significance 0.000 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. 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