Category Archives: KamaKura

Fair Value and Expected Credit Loss Estimation: An Accuracy Comparison of Bond Price versus Spread Analysis Using Lehman Data

The International Financial Reporting Standard (“IFRS”) 9 and the Financial Accounting Standard Board’s (“FASB”) Current Expected Credit Loss (“CECL”) model significantly raise the accuracy bar for valuation and credit risk analytics for all organizations who report under their aegis.

In both cases, the visibility of the organization’s valuation and credit risk assessment moves from the back office or middle office, seen primarily by risk experts, to center stage under a bright spot light

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An Introduction to Stress Testing: Oil Prices, Default Probabilities and Credit Spreads

Over the last 18 months, the dramatic fall in oil prices has triggered a dramatic widening of credit spreads and default probabilities for oil-related firms. To a slightly lesser degree, the same kind of macro factor sensitivity in the credit spreads and default probabilities in firms closely associated with other basic commodities. This note explains the “reduced reduced form” modeling approach used in Kamakura’s KRIS default probability service to link forward looking macro factors to simulated default probabilities. We refer readers interested in more detail to the recent note from Kamakura “Bank of America and CCAR 2016 Stress Testing: A Simple Model Validation Example” and the references at the end of this note.

 

Bank Stock Prices And Higher Interest Rates: Lessons From Bank Of America 1974

We want to thank our readers for the very strong response to our June 17, 2015 note “Bank Stock Prices and Higher Interest Rates: Lessons from History.”  For those readers who asked “Is the correlation between Treasury yields and bank stock prices negative at other maturities besides the 10 year maturity?” we include Appendix A.  Appendix A shows that for all 9 bank holding companies studied, there is negative correlation between the bank’s stock price and Treasuries for all maturities but two.

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Interest Rate Risk: Lessons from 2 Decades of Low Interest Rates in Japan

 

In 2005, economist Richard Koo and The Economist warned that U.S. home prices were in for a collapse much like that seen in Japan after the bubble in real estate and stock prices peaked in December, 1989. “The U.S. is not Japan,” was a phrase used to dismiss any “foreign” data out of hand, much like the 1980s Japanese Minister of International Trade and Industry who stated that foreign ski makers could not compete in Japan because “Japanese snow is different.” In this note, we focus on a critical issue in many countries: what does the experience of other countries with very low interest rates tell us about what lies ahead for U.S. and European interest rates and interest rate risk analysis?

What do Berkshire Hathaway, MasterCard and Toyota Have in Common?

While the Federal Reserve’s Comprehensive Capital Analysis and Review is a key component of regulatory risk assessment, market-based risk assessments like credit spreads and modern reduced form default probabilities are more accurate and more responsive to the changes in the financial services environment.  In our March 3 ranking of major financial services firms by their funding costs, we found that 25 institutions had lower funding costs than the best of the four “too big to fail” financial institutions in the United States.

We update that analysis in this post, using all fixed rate senior non-call bond trades for financial services firms on July 20, 2015.

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Citigroup Inc. versus HSBC Holdings PLC: A Bond Market Comparison

Our analysis May 4 reported on the bond market view of HSBC Holdings PLC (HSBC). Citigroup Inc. plays a similar role in the financial services business across the Atlantic.  From a bond market perspective, how does Citigroup Inc. compare to HSBC Holdings PLC? We answer that question in this note in light of our analysis of Citigroup Inc. on October 1, 2014. 

 The first thing to note is that Citigroup Inc., not surprisingly, is much more heavily traded in the U.S. fixed rate corporate bond market, as shown in the trading of fixed-rate senior non-call debt on May 4, 2015. 

Eleven bonds of HSBC Holdings PLC and 34 bonds of HSBC USA Inc. traded, and 56 bonds of Citigroup Inc. traded. The underlying principal amount traded on the Citigroup Inc. bonds was $157 million, compared to $107 million for six HSBC Holdings PLC-related issuers.
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Calculation of the Term Structure of Liquidity Premium

Traditionally, liquidity has been defined as:

  • A Russian problem;
  • An Asian problem;
  • Someone else’s problem;
  • A broker’s problem;
  • Not something to worry about since it is guaranteed by the Central Bank; or,
  • All of the above.

Even the Bard has commented on liquidity with the rather pithy ‘put money in thy purse’!

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Apple Inc. Bonds: How Much for the World’s Number One Brand?

Apple Inc. (AAPL) ranks number 1 on the Forbes “most valuable brand” rankings. What does it cost, in terms of brand premium, to buy the bonds of Apple Inc.?  We answer that question in this note. We last reviewed Apple Inc. on January 20, 2014. In this note, we turn to the U.S. dollar bonds issued by Apple Inc. and compare its current default probabilities and credit spreads with those on all heavily traded corporate fixed-rate bonds on March 3, 2015. A total of 307 trades were reported on 14 fixed-rate bond issues of Apple Inc. with trading volume of $145.2 million on March 3. Apple Inc. was the 11th most actively traded corporate bond issuer on March 3. We use this information for three purposes: to evaluate the risk and return on the firm’s bonds, to evaluate the firm’s credit risk-adjusted dividend yield, and to reach a conclusion on investment grade status by the modern “Dodd-Frank” definition.

Conclusion:   The passion that equity and bond investors have shown for the common stock and bonds of the world’s number one brand is easy to understand.  Apple Inc. literally has the lowest default probabilities of its peer group at every maturity from 1 month to 10 years.  The firm is as close to the best bond rating as one is able to come in the 2015 environment.  If there is any bad news for bond investors in Apple Inc., it’s that bond prices have been bid up so strongly that the firm’s bonds offer just average value, as measured by the ratio of credit spread to default probability.   There were 148 heavily traded bond issues that offered better value by this criterion than the best Apple Inc. bond on March 3.  For investors with long memories, you will recall that the 1 year default probability of Apple Inc. rose above 3.50% in 1997-1998. Euphoria can be misleading at times.

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Stressed Out: A Bond Market Risk Ranking Of Leading Financial Institutions

On March 13, 2014, we pointed out the many reasons why the Federal Reserve-mandated stress testing process will be a less accurate measure of financial institutions’ risk than the market’s price on those institutions’ promise to pay a dollar in the future.  The market place considers all scenarios, not just three as in the Fed’s CCAR stress tests.  The market place invests cold hard cash to price various financial institutions’ promises to pay.  In the stress testing process, those who prepare the stress tests are often in a conflict of interest position, since it normally serves them best financially if the CCAR results are prepared on the sunny side of the street.

In this note, we update our results from March 13, 2014 with the bond market assessments of financial institutions whose bonds were traded in the U.S. corporate bond market on Friday, January 23.  We use 1,281 trades on the bonds of 51 different legal entities in the financial services industry with underlying principal of $1.4 billion to rank those firms by riskiness.  We rank the institutions by credit spread and by spread to the U.S. Dollar Cost of Funds Index.

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Basel III Counterparty Credit Metrics

 Basel III Counterparty Credit Metrics

Click here for a *.pdf version of this document.

EXECUTIVE SUMMARY
An important element of Basel III is the definition of minimum capital adequacy requirements for counterparty credit exposures (derivative instruments, long settlement transactions, securities financing transactions, and counterparty master agreements where the counterparty to the transaction is a credit-risky entity) held by banks.

Basel III defines two forms of capital adequacy requirements for counterparty credit exposures. The first form specifies the minimum capital required to cover potential future losses from counterparty defaults in terms of the probability of counterparty default (PD), the loss rate given default (LGD) on a defaulted exposure, the exposure at default (EAD) of the exposure, and the effective maturity (M) of the exposure. The second form specifies the minimum capital required to cover potential future losses from future changes in the credit quality of the counterparty that result in changes in the credit spreads for the counterparty’s credit exposures.

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Business and Credit Cycles

While often attempted history proves that one cannot repeal the business and credit cycle.  The cycle always seems to be the same although the triggers and environment may be different.  Losses peak, loan demand and supply dry up, the appetite for risk evaporates while households and businesses begin the process of repairing their respective balance sheets.  Slowly investors start stretching for yield and lenders (banks, shadow banks and capital markets) begin to ease credit terms, soon followed by increased usage of leverage.  A review of the Federal Reserve Senior Credit Officer Survey bears out this cycle.

This cyclical nature of credit and default risk can clearly be seen from the history of the Kamakura Troubled Company Index going back to its introduction in 1990.

 

http://www.kamakuraco.com/MartinMZorn/tabid/397/EntryId/744/Business-and-Credit-Cycles.aspx

Low Rate and Negative Rate Model Validation for Interest Rate Risk and Asset and Liability Management

The author wishes to thank his colleague, Managing Director for Research Prof. Robert A. Jarrow, for twenty years of guidance and helpful conversations on this critical topic.

As zero interest rate policies and negative interest rates ripple through world financial markets, many legacy interest rate risk systems and asset and liability management systems have been unable to keep pace. In this note, we use 100,000 scenarios from a modern 9 factor Heath, Jarrow and Morton interest rate simulation from Kamakura Corporation to illustrate the model validation issues that arise when one admits that negative interest rates have a probability that is not zero.

The model validation procedures we outline are used by Kamakura in both its Kamakura Risk Information Services macro factor scenario sets and in Kamakura Risk Manager (“KRM”). KRM has allowed users to simulate and analyze negative interest rates for more than 20 years.

Negative Interest Rates: An International Perspective
Even with negative interest rates making the headlines in European markets daily, one sometimes hears the phrase “It can’t happen in the United States.” The same phrase, of course, was used to deny the possibility that home prices could fall in the United States prior to the 2006-2010 financial crisis. Negative interest rates have already been observed in the secondary market for U.S. Treasury securities, as confirmed by this phrase quoted from the February 17 version of the U.S. Department of the Treasury yield reporting web page:

 

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Trends in Sovereign Credit Risk Assessment

The Asian Institute of Chartered Bankers has just published “A Best Practice Approach to Modeling Sovereign Defaults” in the December 2014 issue of its Banking Insight magazine. Since the article, which I co-authored with my colleagues Suresh Sankaran and Dr. Clement Ooi, was targetted toward the Asia market, it is helpful to emphasize some of the most important points in modeling sovereign default risk from a world-wide perspective. There are three key points in modeling sovereign default risk that we explain in the rest of this article:

  • The credit default swap market is a very problematic source of credit information and, at best, it is reliable only for a short list of reference names.
  • The conflict of interest faced by legacy rating agencies is even more extreme in the sovereign case than it is in the well-documented corporate and structured products markets.
  • Modern statistical modeling techniques are best practice and the only realistic alternative to the credit default swap market and legacy credit ratings.

We outline the reasons for these assertions in the rest of this note. Read more

 

Stress Testing: The Use and Abuse of “Intuitive Signs” on Credit Model Coefficients

In the past week, I have spoken with many regulators and bankers on the proper role of intuition in the econometric estimation of credit models for the Federal Reserve’s Comprehensive Capital Analysis and Review 2015. In our review ofbest practices for stress testing , value at risk, and credit value at risk on October 20, 2014, there was no role for “intuition,” just for science. The same is true for our November 13, 2014 update of model validation procedures for CCAR 2015

Why? In quotes from Kathryn Schultz, Nobel Prize Winner Daniel Kahneman, and Professors King and Soneji below, we explain that the very DNA of human beings leads us to be overconfident in our own intellectual powers. Rather than relying on modern econometric methods, most humans would rather guess an answer and would normally be supremely confident in its accuracy.

 

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Bond Market Stress Test: 25 Financial Institutions Have Lower Credit Spreads than the Best “Too Big to Fail” Bank

The Federal Reserve will announce the results of the “DFAST” stress tests on March 5. On March 13, 2014, we pointed out the many reasons why the Federal Reserve-mandated stress testing process will be a less accurate measure of financial institutions’ risk than the market’s price on those institutions’ promise to pay a dollar in the future. The market place considers all scenarios, not just three as in the Fed’s CCAR stress tests. The market place invests cold hard cash to price various financial institutions’ promises to pay.

In the stress testing process, those who prepare the stress tests are often in a conflict of interest position, since it normally serves them best financially if the CCAR results are prepared on the sunny side of the street. In this note, we update our results from January 27, 2015 with the bond market assessments of financial services firms whose bonds were traded in the U.S. corporate bond market on Monday, March 2. Many of the firms whose bonds are traded are not subject to the stress testing process, so a bond market analysis gives us a broader and more comprehensive risk assessment. We use 5,383 trades on the bonds of 127 different legal entities in the financial services industry with underlying principal of $1.8 billion to rank those firms by riskiness. We rank the institutions by credit spread, by spread to the U.S. Dollar Cost of Funds Index, and by “best value,” which we define as the ratio of credit spread to matched maturity default probability.

Conclusion:  25 financial institutions led by Berkshire Hathaway Finance Corporation (BRK.A) (BRK.B) have a better spread to the U.S. Dollar Cost of Funds Index TM than the best of the four “too big to fail” financial institutions in the United States, which we define as the grouping including Bank of America Corporation (BAC), Citigroup Inc. (C), JPMorgan Chase & Co. (JPM) and Wells Fargo & Co. (WFC).

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Liquidity At Risk – A stochastic look at cashflows

It has been clearly established that when customers default, it results in liquidity risk; when there is a fraud within the organisation, it impacts liquidity, when there is funding concentration, there is clear evidence of illiquidity if the funders do not renew credit lines, and when markets change, it changes the liquidity profile of an organization.

Liquidity is a second order risk, and one does not manage second order risks without adequately monitoring, measuring and controlling primary risks. If an organisation controls credit risk, it is, in part, controlling liquidity risk.

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Kamakura Reports Significant Decline in Corporate Credit Quality during December 2014

NEW YORK, January 5, 2015: Kamakura Corporation reported Monday that the Kamakura troubled company index ended the month of December at 6.42%, an increase of 1.31% from the end of November. The index reflects the percentage of the Kamakura 34,000 public firm universe that has a default probability over 1.00%. An increase in the index reflects declining credit quality while a decrease reflects improving credit quality.

As of the end of December, the percentage of the global corporate universe with default probabilities between 1% and 5% was 5.03%, up 0.92% from November; the percentage of the universe with default probabilities between 5% and 10% was 0.95%, up 0.27%; the percentage between 10% and 20% was 0.31%, up 0.6%; while the percentage of companies with default probabilities over 20% was 0.13%, up 0.06 from the previous month.

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Stress Testing: The Use and Abuse of Lagged Default Probabilities in “Forbidden” Credit Models

As the Federal Reserve’s 2015 Comprehensive Capital Analysis and Review stress testing exercise moves to its conclusion, a steady stream of well-intended but incorrect models are coming into public view. In particular, many analysts have been using lagged default probabilities as inputs to their 13 quarter stress tests, a modeling strategy that ProfessorsJoshua Angrist and Jorn-Steffen Pischke label “forbidden models” in their classic econometrics text “ Mostly Harmless Econometrics: An Empiricist’s Companion” (2009).

We explain why such models, however well intended, are usually invalid and unacceptable from a model validation point of view using quotes from Angrist and Pischke.

 

Read more at http://www.kamakuraco.com/Blog/tabid/231/EntryId/729/Stress-Testing-The-Use-and-Abuse-of-Lagged-Default-Probabilities-in-Forbidden-Credit-Models.aspx

Cisco Systems Inc. vs. Google Inc. vs. Apple Inc.: A Bond Battle

Cisco Systems Inc. (CSCO) has launched the largest U.S. bond offering since last September, raising $8 billion in seven tranches. This note compares the risk and return on Cisco Systems Inc. bonds with those of Google Inc. and Apple Inc., featured in yesterday’s Kamakura bond analysis.

See the detailed Article at  http://www.kamakuraco.com/Blog/tabid/231/EntryId/613/Cisco-Systems-Inc-vs-Google-Inc-vs-Apple-Inc-A-Bond-Battle.aspx