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Don founded Kamakura Corporation in April 1990 and currently serves as its chairman and chief executive officer where he focuses on enterprise wide risk management and modern credit risk technology. His primary financial consulting and research interests involve the practical application of leading edge financial theory to solve critical financial risk management problems. Don was elected to the 50 member RISK Magazine Hall of Fame in 2002 for his work at Kamakura. Read More

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Sep 13

Written by: Donald van Deventer
9/13/2014 4:10 AM 

On September 9, we compared the marginal cost of wholesale funding for Bank of America Corporation (BAC) with the U.S. Dollar Cost of Funds IndexTM, a proxy for the marginal cost of funding for the 4 largest U.S. deposit-taking banks. We found that Bank of America’s marginal cost of funds was 0.134% higher than the composite of the 4 “Too Big to Fail” banks and about 0.30% higher than Wells Fargo & Co. (WFC). A number of readers asked “what does this mean to Warren Buffett?” Accordingly, in this note we compare the marginal cost of funding for two Berkshire Hathaway (BRK.A)(BRK.B) legal entities with the U.S. Dollar Cost of Funds Index, Bank of America Corporation, and Wells Fargo & Co. We keep tongue firmly in cheek for the entirety of this exercise.

Conclusion: Our tongue in cheek analysis shows that management at both Bank of America Corporation and Wells Fargo & Co. can lower their marginal funding costs to a significant degree by either emulating Mr. Buffett’s management strategies or by replacing the implicit guarantee of the U.S. government with an explicit guarantee from Berkshire Hathaway.

The Analysis
Step one in today’s analysis is to report the composite credit spreads of the four “too big to fail” banks underlying the U.S. Dollar Cost of Funds Index TM. The big four banks represented 4 of the 17 most heavily traded bond issuers in the United States in this chart of fixed-rate non-call senior debt issues. For information on bond types excluded from the construction of the index, please see the note on the index below. Here is a summary of trading volume on September 10, 2014: 



There were 2,011 trades in 294 bond issues representing $908 million in principal of the four reference banks underlying the U.S. Dollar Cost of Funds Index. By contrast, there were only 137 trades in 16 issues of Berkshire Hathaway Inc. and Berkshire Hathaway Finance Corporation for a total volume of about $11 million. We use the term “Berkshire Hathaway” in this note to refer to both legal entities. Within the U.S. Dollar Cost of Funds Index, there is variation in credit quality among the four banks, which we have noted in other posts. For purposes of this note, however, we focus on the composite index alone. The credit spreads fitted to the September 10, 2014 trade data are shown here:



At the common “on the run” maturities, the U.S. Dollar Cost of Funds Index is summarized here, both in terms of credit spreads and yields. 



At the five year point, the composite marginal costs of funds for the big four banks is a credit spread of 0.834% and an all-in yield of 2.624%, compared to a 1.79% yield on the five year Treasury as reported by the U.S. Department of the Treasury.

Comparison of Berkshire Hathaway Credit Spreads with the U.S. Dollar Cost of Funds Index, September 10, 2014
Next, we follow the same credit spread calculation procedures used in the U.S. Dollar Cost of Funds Index for Berkshire Hathaway, using observable bond trades on September 10, 2014. We calculate the difference between the trade-weighted average credit spreads and the U.S. Dollar Cost of Funds credit spreads for the identical maturities for all observable bond trades of Berkshire Hathaway with at least $1 million in trading volume. The bonds used are senior non-call fixed rate debt issues reported by TRACE via Market Axess. The results are shown in this table: 



On a simple average basis, equally weighting each issue, Berkshire Hathaway’s average funding differential versus the U.S. Dollar Cost of Funds Index is a credit spread advantage of 0.337% below the marginal cost of funds composite for the too big to fail banks. While some argue that the too big to fail banks are the beneficiaries of a funding subsidy because of an implicit guarantee from the U.S. government, the data makes it clear that a guarantee by Berkshire Hathaway would be more valuable still.

Comparing the Marginal Cost of Wholesale Funds for BAC and WFC
Next, we look at the updated marginal cost of funding for two key Berkshire Hathaway investments, Wells Fargo & Co. and Bank of America Corporation. First, we look at the spreads on Wells Fargo & Co. (WFC) bond issues and compare them with the U.S. Dollar Cost of Funds Index. Using a simple average of the difference, we find that Wells Fargo & Co. has a marginal cost of funds 0.215% BELOW the U.S. Dollar Cost of Funds Index. Bank of America Corporation, by contrast, has a marginal cost of funds 0.114% above the U.S. Dollar Marginal Cost of Funds index. This represents an advantage for Wells Fargo & Co. of 0.215% + 0.114% = 0.329% over the marginal cost of funds for Bank of America, about 1 basis point higher than we found two days ago. Ironically, the marginal cost of funds for Berkshire Hathaway, at 0.337% below the U.S. Cost of Funds Index, is lower than the marginal cost of both banks in which Warren Buffett has invested. Berkshire Hathaway has a marginal funding cost advantage of 0.337% - 0.215 = 0.122% over Wells Fargo and 0.337% - (-0.114%) =0.451% over Bank of America Corporation. Mr. Buffett can earn a return on assets of 0.451% just by issuing bonds and investing the proceeds in the bonds of Bank of America Corporation. This is a better ROA than many bankers have achieved over the last decade.

Conclusion
Our tongue in cheek analysis shows that management at both Bank of America Corporation and Wells Fargo & Co. can lower their marginal funding costs to a significant degree by either emulating Mr. Buffett’s management strategies or by replacing the implicit guarantee of the U.S. government with an explicit guarantee from Berkshire Hathaway.

Appendix

Background on the U.S. Dollar Cost of Funds IndexTM
Measuring the marginal cost of funds for a financial institution is a critical calculation from both a management perspective and a regulatory perspective. From a management perspective, if one’s own firm faces a funding disadvantage versus a group of banks who are “too big to fail,” that has dramatic implications for corporate strategy. From a regulatory perspective, favoring a group of financial institutions with an implicit guarantee of survival can create an anti-competitive subsidy as an unintended consequence. In this section, we explain the U.S. Dollar Cost of Funds IndexTM from Kamakura Corporation which makes quantification of funding advantages and disadvantages a practical daily reality.

Background on the U.S. Dollar Cost of Funds Index
On a typical day in the U.S. corporate bond market, there are significant bond trades in fewer than 20 of the 6,730 banks insured by the U.S. Federal Deposit Insurance Corporation. Moreover, there have been trades in only 14 U.S. banking legal entities in the credit default swap market since July 2010. That means for the overwhelming majority of financial institutions, an arm’s length benchmark for marginal funding costs is the only alternative since there is literally no trading in their own name. For many years, the interest rate swap curve was used as this benchmark for transfer pricing, asset and liability management, and internal probability assessment by the majority of large banks. With the unveiling of the Libor scandal and the associated prolonged period of negative interest rate swap spreads to the U.S. Treasury yield curve, the swap curve has lost credibility as a reliable benchmark for the marginal cost of funds.

For this reason, a new benchmark is needed that has these characteristics:

  • It should realistically measure the marginal cost of new funds to the financial institutions with the largest trading volume.
  • It should be based on public information that is readily verifiable by any investor or other market participant.
  • It should be based on actual trades, not estimates of trading costs.
  • It should be a calculation that can be done without the input of information or the cooperation of any of the financial institutions named in Libor-related lawsuits.
  • It should be based on such a large volume of trades that manipulation of the benchmark would be difficult, if not impossible.
  • It should be a composite of data relating to a number of financial institutions so that no one institution’s cost of funds is used as the benchmark.
  • The calculation methodology should be transparent and replicatable by any third party.
  • The calculation agent should not be a legal entity or other organization directly or indirectly controlled by the group of financial institutions named in Libor-related lawsuits.

The U.S. Dollar Cost of Funds IndexTM from Kamakura Corporation
Kamakura Corporation has created just such an index, labeled the “U.S. Dollar Cost of Funds Index.TM” The U.S. Dollar Cost of Funds Index TM measures the trade-weighted cost of funds for the largest deposit-taking U.S. bank holding companies. The index is a credit spread, measured in percent and updated daily, over the matched maturity U.S. Treasury yield on the same day. The current bank holding companies used in determining the index are Bank of America Corporation (BAC), Citigroup Inc. (C), JPMorgan Chase & Co. (JPM), and Wells Fargo & Company (WFC). The index is an independent market-based alternative to the Libor-swap curve that has traditionally been used by many banks as an estimate of their marginal cost of funds. Kamakura Corporation is the calculation agent, and the underlying bond price data is provided by TRACE and the U.S. Department of the Treasury. The National Association of Securities Dealers launched the TRACE ( Trade Reporting and Compliance Engine) in July 2002 in order to increase price transparency in the U.S. corporate debt market. The system captures information on secondary market transactions in publicly traded securities (investment grade, high yield and convertible corporate debt) representing all over-the-counter market activity in these bonds. For each of the reference names used in the calculation of the index, Kamakura Corporation assembles bond data as follows:

  • All bond trades of that reference name are gathered from TRACE.
  • All bonds which are not fixed rate debt issues are dropped.
  • All bonds which are not “non-call” (other than “make whole” calls) are dropped
  • All bonds which do not pay interest semi-annually are dropped.
  • All “survivorship option” bonds are dropped.
  • All bonds with a changing interest rate or principal amount tied to any index are dropped. This eliminates structured products.

The result is a large number of straight non-call fixed rate senior debt issues which traded that day. This contrasts with the Libor calculation procedure in which there are zero trades for $0 on 0 instruments.

Assembling the Composite Index
The composite credit spread is then calculated as follows:

  1. The traded-weighted average yield is calculated for each of the underlying bonds.
  2. The matched-maturity U.S. Treasury yield is interpolated from the “on the run”
  3. maturities published by the U.S. Department of the Treasury.
  4. The trade-weighted credit spread for each issue is calculated by subtracting the interpolated matched maturity Treasury yield from the trade-weighted average yield.
  5. Since the spread varies by years to maturity, a curve is fit to all observable bonds using a cubic function of the years to maturity t on each issue.

Credit spread = a + bt + ct2 + dt3

The coefficients a, b, c, and d are calculated using ordinary least squares

The terms, trading volume, and pricing for each underlying bond, the matched maturity U.S. Treasury yields, the coefficients of the index function for that day, and the “on the run” values of the index are provided by Kamakura Corporation to index clients.

Copyright ©2014 Donald van Deventer

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