PrefBlog

DBRS has published a newsletter highlighting Canadian bank capital levels, which is interesting in the light of their Review-Negative of non-Equity Tier 1 Capital.

They make the following rather curious statement:

DBRS believes the bank’s ability to access the capital markets for funding in good and bad times is an importantconsideration in its capital profile.

Well… has the ability of the banks to access capital markets in bad times really been tested? “Challenging” times, OK. “Difficult” times, why not? But can the past two years really be described as “bad” for Canadian banks?

They note:

The mix, quality and composition of capital are other important considerations in the overall assessment of capital. Thequality of capital has been a key rating consideration in DBRS’s assessment of Canadian banks for an extended periodof time. DBRS has a preference for common equity over hybrids, as the first loss cushion for bondholders and othersenior creditors. On average, 17% and 14% of the regulatory Tier 1 capital is made up of preferred shares andinnovative instruments, respectively, which DBRS views as reasonable. DBRS expects the quality of capital to remainrelatively steady given the recent focus by the market on “core capital,” although OSFI does allow this percentage tonow go as high as 40%, up from 30% as of November 2008.

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The Bank of Canada has released the June 2009 Financial System Review with the usual high level views of government and corporate finance.

I was most interested to see a policy recommendation in the review of the funding status of pension plans. First they state the problem:

Assets fell in 2008, largely because of the steep decline in Canadian and international equity markets. At the same time, declines in long-term bond yields caused the present value of liabilities to increase.

… and provide an illustration:

… and provide a prescription:

In this environment, plan members are concerned about pension obligations being met.

To address these issues, reforms should focus on: (i) flexibility to manage risks and (ii) proper incentives. Reforms (regulatory, accounting, and legal) should also focus on providing sponsors with the flexibility needed to actively maintain a balance between the future income from the pension fund and the payouts associated with promised benefits. Small pension funds should be encouraged to pool with larger funds to better diversify market risk as another way to help make pension funds more resilient to market volatility.

I may be a little slow, but I fail to follow the chain of logic between the premises and the conclusion that “small pension funds should be encouraged to pool with larger funds to better diversify market risk”.

This will not affect the liability side, which is based on the long Canada rate. But the Bank fails to show – or even to suggest – that the decline in assets was exacerbated by lack of diversification, that large pools are better diversified than small funds, or that pooled funds outperform small funds.

It may well be that these logical steps can be justified – but they ain’t, which makes me suspicious. The recommendation is supportive of the Ontario government’s lunatic plan to encourage the bureaucratization of the Ontario Teachers’ Pension Plan (OTPP) and OMERS, as discussed on March 31, without either mentioning the proposal or providing any of the supporting arguments that were also missing from the original.

This has the look of a quid pro quo – either institution to institution, or the old regulatory game of setting up some lucrative post-retirement consulting gigs. Even if completely straightforward and honest, the argumentation in this section is so sloppy as to be unworthy of the Bank.

Of more interest to Assiduous Readers will be the section on banks, commencing on page 29 of the PDF.

There are two things of interest here: first, for all the gloom and doom, credit losses are not as high as the post-tech-boom slowdown, let alone the recession of 1990; second, that the graph is cut off after the peak of the 1990 recession.

Why was the graph prepared in this manner? Given the Bank’s increased politicization (also evidenced by the pension plan thing) and increased regulatory bickering with OSFI, I regret that I am not only disappointed that they are not encouraging comparison with the last real recession, but suspicious that there is some kind of weird ulterior purpose. Whatever the rationale, this omission reflects poorly on the Bank’s ability to present convincing objective research.

There are a number of longer articles on the general topic of procyclicity:

• Procyclicality and Bank Capital
• Procyclicality and Provisioning: Conceptual Issues, Approaches, and Empirical Evidence
• Regulatory Constraints on Leverage: The Canadian Experience
• Procyclicality and Value at Risk
• Procyclicality and Margin Requirements
• Procyclicality and Compensation

The second article includes a chart on provisioning; not the same thing as credit losses, but a much better effort than that given in the main section of the report:

I was disappointed to see that bank capital and dynamic provisioning were discussed in the contexts of the general macro-economy and with great gobbets of regulatory discretion. I would much prefer to see surcharges on Risk Weighted Assets related to both the gross amount and the trend over time of RWA calculated by individual bank.

The emphasis on regulatory infallibility is particularly distressing because it is regulators who bear responsibility for the current crisis. The banks screwed up, sure. But we expect the banks to screw up, that’s why they’re regulated. And the regulators dropped the ball.

The paper on leverage has an interesting chart:

Update, 2009-7-21:

The International Monetary Fund has released Finance & Development, June 2009, with the following articles (what follows is largely a copy-paste from their press release … sorry, not much time today!):

• Crisis Shakes Europe: Stark Choices Ahead: looks at the harsh toll of the crisis on both Europe’s advanced and emerging economies because of the global nature of the shocks that have hit both the financial sector and the real economy, and because of Europe’s strong regional and global trade links. Marek Belka, Director of the IMF’s European Department, writes in our lead article that beyond the immediate need for crisis management, Europe
  must revisit the frameworks on which the European Union is based because many have been revealed to be flawed or missing.

• Stress Test for the Euro and The Euro’s Finest Hour: In many respects, one key European institution has proved its mettle-the euro. Both Charles Wyplosz and Barry Eichengreen discuss the future of the common currency.
• The Perfect Storm: IMF
  economists rank the current recession as the most severe in the postwar period

• Preparing for a Post-Crisis World: John Lipsky, the Fund’s First Deputy Managing Director, examines the IMF’s role in a postcrisis world;
• Asset Price Booms: How Can They Best be Managed?: Giovanni Dell’Ariccia assesses what we have learned about how to manage asset price booms to prevent the bust that has caused such havoc.
• Interview: Oxford economist Paul Collier about how to help low-income countries during the current crisis,
• Start This Engine: Donald Kaberuka, President of the African Development Bank, writes about how African policymakers can prepare to take
  advantage of a global economic recovery.

• Picture This: looks at what happens when aggressive monetary policy combats a crisis;
• Back to Basics gives a primer on fiscal policy
• Data Spotlight takes a look at the recent large swings in commodity prices.

As Assiduous Readers will know, the IMF is the Venerated Regulator du jour and all right-thinking people expect it to lead us to the promised land. Those Assiduous Readers who are not Capitalist-Deviationists are urged to keep a copy with them at all times, to assist them to smartly rebut the running dog lackeys of the pro-bonus clique.

The Bank of England has released its Quarterly Bulletin 2Q09, filled with the usual charts and top-quality research.

Corporate bond liquidity, as measured by bid/offer spreads, is healing:

There is still a huge CDS basis, implying poor ability to borrow for leverage:

In addition to the general review, there are longer “Research and Analysis” articles on:

• Quantitative Easing
• Public Attitudes to Inflation and Monetary Policy
• The Economics and Estimation of Negative Equity
• Summaries of recent Boe Working Papers

Sadly, there is no chart of the decomposition of corporate bond spreads into default / default uncertainty / liquidity. It is my understanding that the system has been so stressed that they are reviewing all their embedded assumptions and calculations in their model to take a view on whether they can still trust it. A lot of quant models have blown up over the past two years!

Assiduous Readers will know I often use the Interesting External Papers section of PrefBlog as my notepad when reviewing the literature for my own purposes. And that is exactly what this post is … not so much for readers’ information, but for mine, when I want to find this stuff again!

The Bank of Canada Review of Spring 2003 contained an essay by David Longworth, Deputy Governor and life-time employee of the Bank, titled Inflation Targeting and Medium Term Planning: Some Simple Rules of Thumb:

Real long-term bond rates typically average slightly above long-term real growth rates.

Footnote: This has tended to be the case in Canada over the last 20 years. Economic theory would suggest that the real rate of return on capital would exceed the real growth rate of the economy. As long as the risk premium on private capital relative to government bonds is not too large, we would also expect that the real yield on government bonds would be slightly higher than the real growth of the economy. All this is strictly true only in a closed economy. In a small open economy, this real interest rate would reflect the world real interest rate, which in turn would reflect the real growth rate of the world economy.

The Congressional Budget Office has published its December 2007 Background Paper: How CBO Projects the Real Rate of Interest on 10-Year Treasury Notes:

This background paper summarizes CBO’s methods for calculating the natural rate of interest and applying it in projections of the real and nominal interest rates on 10-year Treasury notes.

Estimating the natural rate of interest, either over history or for projections, is a two-step procedure. First, CBO estimates the real return on capital (adjusted for taxes on profits). That estimate is based on the agency’s view of the economy’s physical production process—how capital and labor are used to produce output and generate complementary income payments to capital and labor. Because all output simultaneously generates income, data from either the income side or the product (output) side of the national income and product accounts (NIPAs), compiled by the Bureau of Economic Analysis, can be used. Second, CBO estimates an adjustment for the risk in actually realizing the return on capital. Because part of the return on capital is compensation for the risk that some firms will default and inflict losses on investors, an estimate of the real rate based on income payments from capital is higher than the natural rate. Therefore, that risk premium must be removed to yield an estimate of the natural rate. That rate is comparable to the real rate on 10-year Treasury notes, which is also free of default risk. In particular, the risk premium is based on a weighted average of separate estimates of the risk of holding equity and debt claims on capital; it also includes an adjustment for the different tax treatment of profits and interest payments generated by businesses.

Over the next 10 years, CBO projects, the natural rate of interest will decline slightly, from an estimated level of about 3.6 percent in 2006 to about 3 percent. That decline stems from a projected decline in the return on capital, much of which reflects a projected slowdown in the growth of the labor force.

CBO uses two complementary approaches for estimating the return on capital, one from the income side and the other from the product, or production, side.1 The income-based approach measures the rate of return on capital as the ratio of capital income to the capital stock. Its construction has the advantage of being independent of assumptions about production relationships or determinations of whether the economy is in or out of equilibrium. It provides a relatively smooth estimate of the return on capital over the historical and projection periods.
…
The income-side measure is estimated as the ratio of capital income to the capital stock (see Figure 2). Capital income is a domestic private-sector concept estimated as the sum of domestic corporate profits, people’s rental income, 35 percent of proprietors’ income, and interest paid by domestic businesses, using data from the NIPAs2,3 The private-sector capital stock, valued at the prices of newly produced investment goods, consists of businesses’ plant (that is, facilities) and equipment, software, inventories, housing, and land—all valued at current market prices.

The income-side measure of the return on capital has both cyclical and trend components. From 1960 to 1970 and from 1991 to 2001, the return rose during the recoveries from recessions and peaked during the expansions, before falling as the expansions matured. Across business cycles, the return has exhibited extended periods in which the underlying trend was falling (as from 1960 to 1980) and then rising (from 1980 to the late 1990s).
…
The estimate of the natural rate of interest is obtained by adjusting the real return on capital (in this instance, the income-side measure) for both tax effects and the combined risk premium (see Figure 7).

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Thomas Laubach & John C. Williams, Measuring the Natural Rate of Interest:

A key variable for the conduct of monetary policy is the natural rate of interest – the real interest rate consistent with output equaling potential and stable inflation. Economic theory implies that the natural rate of interest varies over time and depends on the trend growth rate of output. In this paper we apply the Kalman filter to jointly estimate the natural rate of interest, potential output, and the trend growth rate, and examine the empirical relationship between these estimated unobserved series. We find substantial variation in the natural rate of interest over the past four decades in the United States. Our natural rate estimates vary about one-for-one with changes in the trend growth rate. We show that policymakers’ mismeasurement of the natural rate of interest can cause a significant deterioration in macroeconomic stabilization.

FRBSF Economic Letter, 2003-10-31:

Importantly, the natural rate of interest can change, because highly persistent changes in aggregate supply and demand can shift the lines. For example, in a recent paper, Laubach (2003) finds that increases in long-run projections of federal government budget deficits are related to increases in expected long-term real interest rates; in Figure 1, an increase in long-run projected budget deficits would be represented by a rightward shift in the IS curve and a higher natural rate. In addition, economic theory suggests that when the trend growth rate of potential GDP rises, so does the natural rate of interest (see Laubach and Williams (2003) for supporting evidence).

Econbrowser‘s Menzie Chinn wrote a recent post asking everybody to take a deep breath and calm down a little about inflation, titled High Anxiety (about Interest and Inflation Rates):

Of course, the United States in 2009 is different than Japan in 2001. One key difference is that Japan was, and remains, a net creditor. America is a big net debtor to the rest of the world, with extremely large holdings of US Treasurys by foreign private and state actors. And so, for me, I worry more about higher real interest rates (portfolio balance effects) than higher inflation. But even here, real yields according to TIPS seems fairly low in historical perspective (and roughly comparable to those prevailing during the period characterized as “the saving glut”).

My bottom line: Think, and recollect, before panicking.

In the post, he referenced a paper by Stefania D’Amico, Don H. Kim and Min Wei (all of the Fed’s Division of Monetary Affairs), Tips from TIPS: The Informational Content of Treasury Inflation-Protected Security Prices:

We examine the informational content of TIPS yields from the viewpoint of a general 3-factor no-arbitrage term structure model of inflation and interest rates. Our empirical results indicate that TIPS yields contained a “liquidity premium” that was until recently quite large (~ 1%). Key features of this premium are difficult to account for in a rational pricing framework, suggesting that TIPS may not have been priced efficiently in its early years. Besides the liquidity premium, a time-varying inflation risk premium complicates the interpretation of the TIPS breakeven inflation rate (the difference between the nominal and TIPS yields). Nonetheless, high-frequency variation in the TIPS breakeven rates is similar to the variation in inflation expectations implied by the model, lending support to the view that TIPS breakeven inflation rates are a useful proxy for inflation expectations.

This paper was cited by Grishenko & Huang (which has been discussed on PrefBlog), who emphasize:

In a related study, the long-run averages of inflation risk premium in D’Amico, Kim, and Wei (2006) can be positive or negative depending on the different series that they use to fit the three-factor term-structure model.

Footnote: See Figures 4 through 6 in their paper.

Back to D’Amico et al.:

Specifically, we model the dynamics of nominal yields, inflation, and TIPS yields in a general no-arbitrage term structure model setting, and examine the extent to which these data are consistent with each other. Furthermore, we seek to establish some basic facts about the real term structure and the inflation risk premia implicit in nominal bond yields and to obtain an estimate of the “liquidity premium” in TIPS yields.
…
Our main results can be summarized as follows. In all the cases that we have examined, estimating the model taking TIPS yields at their face value fails to produce plausible estimates of inflation expectations or inflation risk premia. The difference between the observed TIPS yields and the model-implied real yields estimated without TIPS data indicates that the “liquidity premium” was quite large in the early years of TIPS’s existence, but has become smaller recently. This liquidity premium turns out to be difficult to account for within a simple rational pricing framework, suggesting that TIPS may not have been priced efficiently in their early years. Nonetheless, time variation in TIPS-based and model-implied breakeven rates are quite similar, suggesting that changes in the TIPS breakeven rates largely reflects changes in inflation expectations or in the investors’ attitude toward inflation risks, rather than being random movements.

They conclude:

The answer to the question of whether the TIPS breakeven rate can be taken as inflation expectation is more complicated. We find that the weekly changes in the model-implied 10-year inflation expectation tend to line up with the weekly changes in the 10-year TIPS breakeven rate. However, we also find that time variation in the inflation risk premium and the TIPS liquidity premium, the latter of which may also include other unaccounted-for effects, are often significant enough to drive a wedge between the qualitative behavior of the breakeven rates and inflation expectations. Our findings in this paper provide support for the use of TIPS breakeven rate information as a proxy for inflation expectations, but also provide a justification for caution. Indeed, in speeches that touch on inflation, policy makers often refer to the TIPS breakeven rate, but they also recognize that the interpretation of this measure is complicated by inflation risk premia and liquidity issues and then continue to monitor a large number of variables to gauge inflation expectations and underlying inflation pressures. More data and more work on TIPS modeling in the future will ndoubtedly shed more light on the informational content of TIPS prices.

The Anginer and Yıldızhan paper recently discussed on PrefBlog that attempted to corellate credit spreads with equity returns referenced a paper by Jing-zhi Huang and Ming Huang titled How Much of Corporate-Treasury Yield Spread is Due to Credit Risk?: A New Calibration, presented at the 14th Annual Conference on Financial Economics and Accounting:

No consensus has yet emerged from the existing credit risk literature on how much of the observed corporate-Treasury yield spreads can be explained by credit risk. In this paper, we propose a new calibration approach based on historical default data and show that one can indeed obtain consistent estimate of the credit spread across many different economic considerations within the structural framework of credit risk valuation. We find that credit risk accounts for only a small fraction of the observed corporate-Treasury yield spreads for investment grade bonds of all maturities, with the fraction smaller for bonds of shorter maturities; and that it accounts for a much higher fraction of yield spreads for junk bonds. We obtain these results by calibrating each of the models – both existing and new ones – to be consistent with data on historical default loss experience. Different structural models, which in theory can still generate a very large range of credit spreads, are shown to predict fairly similar credit spreads under empirically reasonable parameter choices, resulting in the robustness of our conclusion.

They note:

One common finding from these studies is that the average historical default loss rate for corporate bonds is typically much smaller than the observed corporate-Treasury yield spreads, and is only a small fraction of the yield spreads for investment-grade bonds. Figure 1 provides a visual summary of this finding.

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They point out:

This fact alone, however, should not lead one to automatically conclude that credit risk accounts for only a small fraction of the observed yield spreads for investment grade bonds. After all, the expected default loss rate is only part of the (promised) credit yield spread; the other part is the credit risk premium, defined as the difference between the expected realized return of a defaultable bond and that of a comparable Treasury bond. The credit risk premium is required by investors because the uncertainty of default loss should be systematic—bondholders are more likely to suffer default losses in bad states of the economy. Moreover, precisely because of the tendency for default events to cluster in the worst states of the economy, the credit risk premium can be potentially very large. In fact, some of the models considered in this paper can indeed generate credit risk premia that are large enough to explain the difference between the observed corporate yield spreads and historical default loss rate, provided that certain parameter choices are made. The key question, however, is whether any model can generate such large credit risk premia under empirically reasonable parameter choices. This question is the main focus of our paper.

They conclude:

We conclude that, for investment grade bonds (those with a credit rating not lower than Baa) of all maturities, credit risk accounts for only a small fraction—typically around 20%, and, for Baa-rated bonds, in the 30% range—of the observed corporate-Treasury yield spreads, and it accounts for a smaller fraction of the observed spreads for bonds of shorter maturities. For junk bonds, however, credit risk accounts for a much larger fraction of the observed corporate-Treasury yield spreads.

There’s an interesting paper by Deniz Anginer and Çelim Yıldızhan (both of U of Michigan), titled Pricing of Default Risk Revisited: Corporate bond spread as a proxy for default risk:

This paper explores the pricing of default risk in the cross section of equity returns using US corporate bond data during the 1986 to 2006 time period. Although financial theory suggests a positive relationship between default risk and equity returns, recent empirical papers find anomalously low returns for stocks with high probabilities of bankruptcy. In this paper we use a market based measure – corporate credit spreads – to proxy for default risk. We show that credit spreads predict corporate defaults better than previously used measures, such as, bond ratings and accounting based parameters. We do not find default risk to be significantly priced in the cross-section of equity returns. There is also no evidence of firms with high default risk delivering anomalously low returns. Our results suggest that default risk is not a priced risk factor

They review the literature:

There is now a significant body of theoretical research that shows that default-risk constitutes a considerable portion of credit spreads. Berndt, Douglas, Duffie, Ferguson, and Schranz (2005) and Saita (2006), for instance, report that the compensation demanded by investors for being exposed to credit risk, above and beyond expected default losses, is substantial. On the empirical side, Elton et al. (2001) report that default -risk related premium in credit spreads accounts for 19% to 41% of spreads depending on company rating. Driessen (2003) also finds that default risk accounts for 18% (AA rated bonds) and as high as 52% (BBB rated bonds) of the corporate spread. Huang and Huang (2003) using the Longstaff-Schwartz model find that distress risk accounts for 39%, 34%, 41%, 73%, and 93% of the corporate spread respectively for bonds rated Aa, A, Baa, Ba, and B. Longstaff, Mithal, and Neis (2005) use the information in credit-default swaps (CDS) to obtain direct measures of the size of the default and non-default components in corporate spreads. They find that the default component represents 51 percent of the spread for AAA/AA rated bonds, 56 percent for A-rated bonds, 71 percent for BBB-rated bonds, and 83 percent for BB-rated bonds.

Happiness is picking up credit for free:

there is much variation in credit spreads within a rating group. The correlation between credit spreads and ratings is only 45%. AA bonds have an average credit spread of 77.51 basis points with a standard deviation of 98 basis points. A one standard deviation move in credit spreads would firmly take this bond’s rating to a BBB rating which is 6 rating levels down from AA. These results indicate that measuring default risk through company ratings can yield misleading results.

Mind you, I’m a little suspicious of their methodology:

Table 11 reports summary statistics for credit spreads by rating category. The benchmark risk-free yield is the yield of the closest maturity treasury. We include only straight fixed-coupon corporate bonds for the January 1974-December 2006 time period. Bonds for financial firms are excluded. The spreads are given in annualized yield in basis points and ratings in this sample come from Standard and Poor’s.

That’s a long time-frame, with a very wide variety of market conditions. I suspect that disaggregating the data would reduce the variance of spreads within a rating category considerably. Fortunately for my willingness to consider their results, the corellation between credit spreads and equity returns was examined using portfolios that were rebalanced monthly.

… and the authors conclude:

In this paper we examine the pricing of default risk in equity returns. Our contribution to this literature is two-fold. First, ours is the first paper to use bond spreads to measure the ex-ante probability of default risk. This measure has several advantages over others that have been used in the literature. It is available in high frequency, it is model and assumption free and reflects the market consensus of the credit quality of the underlying firm. Most importantly in section 3.2 we show that credit spread drives out the significance of most of the other measures in hazard rate regressions that are used to predict corporate defaults. Second, contrary to previous findings, we show that default risk is not priced negatively in the cross section of equity returns. Portfolios sorted on credit spreads do not deliver significant positive or negative returns after controlling for the well known risk factors. Cross-sectional regressions also show no anomalous relationship between credit spreads and equity returns. We find that credit ratings are priced negatively in the cross-section, but credit spreads are not, even though credit spreads predict bankruptcies better than bond ratings. Our findings challenge the previous studies that have found an anomalous relationship between credit risk and equity returns. We believe that our analysis is the right step towards finding a more appropriate measure of systematic default risk that can explain the cross section of equity returns in line with the rational expectations theory.

The Investment Industry Association of Canada has released its First Quarter Report on Equity New Issues and Trading:

Financial institutions shifted from issuing new common shares in the fourth quarter of 2008 to preferred shares in the first quarter of 2009. During Q4/08 the financial sector issued $7.7 billion of common equity, accounting for 72% of common share issuance, whereas in Q1/09 only $2.5 billion or 32% was from the financial sector. As a result, total common equity issuance witnessed a 26% pullback from the previous quarter, while preferred shares surged over threefold and reached record highs of $4.4 billion in financings in Q1/09. Q1’s preferred share issuance equaled 65% of all of 2008’s preferred share issuance (Chart 2).

The FDIC has released its 1Q09 Quarterly Banking Profile, stuffed with the usual facts ‘n’ figures. Headlines are:

• Highest Earnings in Four Quarters are 61 Percent Lower than a Year Ago
• Loss Provisions Continue to Weigh Heavily on Earnings
• Lower Funding Costs Lift Large Bank Margins
• Charge-Offs Continue to Rise in All Major Loan Categories
• Noncurrent Loans Rise by $59.2 Billion
• Reserve Building Continues
• Industry Capital Registers Largest Quarterly Increase Since 2004
• Downsizing at a Few Large Banks Causes $302-Billion Decline in Industry Assets
• Deposit Share of Funding Rises Even as Total Deposits Decline
• Twenty-One Failures is Highest Quarterly Total Since 1992