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Ann Rutledge Copyrigt

CreditSpectrum Corp © Copyright 2017 All Rights Reserved

“WILL CHINA ABS LEAPFROG THE U.S. ABS MARKET MODEL?” A PROGRESS REPORT

INTRODUCTION

In spring 2014, I launched a study funded by Swift Institute of the leading commercial institutions driving the growth of China’s securitization (ABS) market,1 and presented a thought-experiment at SIBOS 2015 on how China’s ABS market could leapfrog the broken Western market model.

Today, as the China ABS carves out its own path, the leapfrogging scenario is stronger than ever, with an emphasis on product innovation and many young China ABS market leaders advocating for an explicit connection between ABS and Fintech. This essay is intended to amplify and update my SIBOS thesis, which touches on two of the Symposium’s four topics:

• Challenges & opportunities of FinTech (and RegTech) in the U.S. and China• Next steps in capital market liberalization and financial (de) regulation in China and the U.S.; and

To be clear, leapfrogging is not the same thing as “outsizing,” a direction in which China’s ABS market seems to be already well on its way. For example, total China ABS issuance is approximately RMB 2 Trillion, which is on par with early to mid 1990s levels in the U.S. Auto ABS issuance in China (about one-tenth of China’s total public market) is poised to exceed U.S. auto ABS issuance this year. Leapfrogging means addressing the serious moral hazard problems that led to the breakdown of the U.S. ABS market (the Global Financial Crisis, or GFC) in its third decade with critical fixes.

I believe, there are two plausible leapfrogging scenarios, and one where it does not occur:

1) China’s market microstructure undergoes a “genetic evolution” whereby a newly emerging ABS market platform develops a sui generis superior risk architecture that becomes a market standard. This is the superior design motivated by competition scenario.

2) Government authorizes the redesign of ABS market risk architecture to strengthen market discipline and lessen the dependence on intermediary credit information institutions. This is the superior policy incentives scenario.

3) The GFC revealed a dark side to ABS that promotes hidden leverage and uncompensated risk. If neither scenarios 1) nor 2) materialize there is no reason to expect China not to fall victim to a 2008-style crisis within the decade. This is the market doomed to fail scenario.

The first scenario, which sees the market as the driver of change, is plausible and likely to appeal to champions of the free market. The second scenario, nearly as plausible, is likely to appeal to champions of government planning and regulation because it affirms government’s role in balancing different moneyed interests. The third scenario (alas, also plausible) confirms the expectations of cynics.

But the winning scenario does not just depend on what our belief structures lead us to expect. It also depends also on how the forces that drive ABS growth generally play out in the Chinese environment specifically. That is the topic of the next section.

THE GLOBAL CREDIT CRISIS AND THE LAW OF ONE PRICE

For purposes of this paper, I define a “leapfrogging” market microstructure as one that creates the right conditions for competitive price formation. Theoretically, there is no need to “leapfrog” an ideal system. Economic theory and finance jointly assume market price behavior is competitive; and competitive pricing produces a single clearing asset price at the intersection of aggregate demand and supply. This is the so-called Law of One Price, which is the cornerstone of rational market pricing.

1 https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2665975

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2665975





Unfortunately, theoretical finance does not offer very much guidance on how to solve for rational prices in forward gear, i.e., from raw data. And while economists are comfortable making the assumption that rational investors seek to maximize profits, those same economists have struggled for half a century with how to model risk given that no one is indifferent in the same degree to risk.

Yet price formation does take place. So, finance theory models risk by inverting the problem—i.e., assuming the last traded price is the right price. For this to be true, markets must be able to adjust instantaneously to new information, and frictions related to information transmission and transaction costs must be assumed away. In other words, finance theory promulgates the hypothesis that markets are efficient (EMH) not because they are, but because our rational pricing models require it.

Finance theory further requires market completeness—investors can take short or long positions—as well as no-arbitrage conditions—when prices are too high, sellers will establish a short position that will drive the price down and when prices are too low buyers will drive the price up. Alas, theoretical finance failed the ABS market spectacularly during the GFC, or perhaps the ABS market failed theoretical finance. Otherwise we could not raise inconvenient questions like these—

• Financial value is computed as the time value of expected future cash flows, and all ABS securities are built from expected future cash flows of a defined collateral pool, so why did rating agencies invent so many different criteria and methodologies—for auto loan, equipment lease, aircraft and credit card etc., asset-backed securities; residential and commercial mortgage-backed securities; collateralized loan, bond and debt obligations, credit linked notes, asset-backed commercial paper, structured investment vehicles, and many other sub-types, as if they represented different valuation problems, when in fact they were just different instances of the same problem?

• Secondary market liquidity in these sectors was negligible from the earliest days of the ABS market until the Crisis, yet investor interest in re-securitizations was high from 2004 – 2007—but why? Re-securitizations were backed by the very same securities investors didn’t want to trade.

The fact that we can ask both questions tends towards the view that price competition in the ABS market was stifled by inefficient information transmission. Ratings seem to have filtered out vital security information by creating distinctions without differences, and by drowning signals of credit performance with noise. At least, that is the hypothesis on which I base this analysis. For a more general treatment of why ABS needs to be rated fundamentally differently from corporate bond analysis, please see Appendix A.

LEAPFROGGING, FROM THE BOTTOM-UP OR THE TOP-DOWN?

Can China’s ABS market leapfrog the Western ABS market model by breaking down artificial walls between different ABS product markets (or primary and secondary markets) by imposing uniform risk standards and benchmarks governing structured securities backed by all asset types in the primary and secondary markets? In this paper, I assume information monopolists prefer to operate in opaque rather than rather transparent information systems so they can play “unfair games,” i.e., where one side has better access to critical information about the structure of investment payoffs than the other side, and profit. Or, as the Chinese saying goes, 浑水摸鱼: grasp for fish in muddy waters.

Bottom-Up

In U.S. ABS markets, credit rating agencies and ABS underwriters are both information monopolists. Credit rating agencies have a bird’s eye view of the whole securities market, access to nonpublic data, and knowledge of their own secret processes. To a lesser extent, ABS underwriters have the same price discovery edge as the credit rating agencies, as well as the power to price securities. By keeping investors somewhat in the dark, they control price discovery. Their edge enables them to structure ABS with one-sided payoffs without detection or prosecution.

Posit that the information monopolists’ lock on the ABS origination process is due in part to how ABS is traded OTC, which is less efficient for price discovery than a centralized exchange-traded model. A bottom-up critical fix would be





to redesign ABS market microstructure so credit rating agencies and ABS underwriters have less control over the design, packaging, distribution and pricing of structured securities than under the current model.

China’s ABS market today is, too, characterized by splintering, for example, between regulatory jurisdictions, and between public and private offering markets. Nevertheless, China has a greater diversity of ABS distribution channels than the U.S. There is negotiated trading in accordance with Interbank Market rules; or ABS underwriters can list public ABS deals on Shanghai and Shenzhen exchanges; and private ABS deals can be listed on the Inter-OTC market. These alternative markets have proven especially hospitable to innovation.

Moreover, new platforms in China are competing to host commercial trade. Although they are not credit rating agencies or underwriters, these parties are trying to assume the role of information monopolist by leveraging new data, proprietary systems, strategies and idiosyncratic know-how. Presently they tend to specialize along one of two lines, as data firms focused on disseminating secondary market data and research firms, and Fintech firms offering proprietary primary market structuring tools and developing secondary market trading capabilities. These are privately financed firms or networks embedded in China’s online bank and Fintech industries, with large campuses in Hangzhou (near the Shanghai) or Shenzhen (near Hong Kong), with hooks into China’s financial markets. Some have links into the establishment cross-border U.S.-China lobby (the Structured Finance Industry Group, SFIG, and China Securitization Forum, CSF). Others have little to no connection with the “old order.”

Top-Down

Another salient difference in how the U.S. and Chinese ABS markets are organized is that government has an explicit and expansive role in ABS market organization and regulation. First and foremost, as my Swift paper spells out, China’s ABS market is the brainchild of China’s top financial policy makers. In fact, my efforts to identify commercial leaders to carry the market forward in 2014 were somewhat thwarted by the aggressive leading role played by government. Today, although explicit forms of intervention have lessened, government still calls the tune.

For example, the original transaction-by-transaction approval process morphed into a less invasive registration process at the end of 2014. But government still exerts a strong influence over how much and what type of ABS to originate. Real estate is currently frowned on while public-private partnerships are supported. Government also can censor the ideas behind financial products. For example, securitization originally was permitted while re-securitization and synthetic securitization were not. Today, credit default swaps are now sanctioned under certain conditions. And as the supply of qualified assets for ABS gets used up in ABS, such restrictions may be further lowered (as happened in the U.S.).

Government’s central role in deciding to deploy capital in its economy gives it greater scope to experiment with innovative deregulation through capital market design. There is a precedent for this in Chinese policy-makers’ willingness to foster experimentation with online banking, block chain and Bitcoin initiatives. China - and yes, U.K., Malaysia, Australia, Singapore, Hong Kong, Canada, Saudi Arabia etc. - are also ahead of U.S. bank regulators in developing meaningful Fintech policy responses.

With regard to the crossover between Fintech and ABS, which has peculiar financial properties of not quite money and not quite a debt security, one exciting frontier for innovation would be to bring ABS into the block chain environment and treat it as a “risky coin” that comes into the money as the collateral amortizes. Leaving aside the costs of using block chain, the capital treatment for ABS coins is much less onerous than the capital treatment of corporate debt, which ABS is not. (Again, see Appendix A.)

In sum, this is an opportunity for risk standardization from the top-down. China’s government might consider taking the lead to impose fixed benchmarks that map value of “risky coins” to ratings on the “risky securities.” As the terminal value of the “ABS coin” becomes more certain, its security ratings reflect the impact of increased certainty with upgrades (or downgrades). The lagging ratings problem is eliminated as the associated hurdle rate is updated to reflect current risk at each point in time. Capital efficiency is improved, and potentially liquidity increases.





Moreover this idea of an overlay of a numerical benchmark on alphanumeric ratings is not new. Moody’s Investors Service used such a benchmarking system in the 1980s and 1990s, but only for establishing primary market ratings. The novelty aspect relates to issuing ABS securities as “coins” in designated block-chain exchanges, where information vetting is shared among block chain users, and information monopolists have a diminished role. This seems to me to be the strongest argument for government to experiment with a top-down system of quality standards in ABS—that, as the de facto information monopolist in China’s capital markets, the Chinese government would want to impose controls limiting the development of information monopolies that have threatened the order of global credit markets on more than one occasion.

LEAPFROGGING SIDEWAYS. OR, ENTROPY: ENEMY OF PROGRESS

While the last two scenarios are plausible in their own way, so is the third whereby China follows the U.S. model into Crisis. Here, the key risks are neither inertia nor moral hazard (although China certainly is vulnerable to both) but the surprising nonlinear effects of market evolution.

The U.S. ABS market evolution was a tragedy in three acts, as my Swift paper set forth in some detail. In Act 1, securitization caught on fast because it offered the market a funding arbitrage—a way to save money relative to on-balance sheet loans or bonds by choosing to securitize. In most cases, the cost of funds can be lowered because of the presence of incremental information and measures.

When Act 2 followed, other types of asset besides private contracts started to be repackaged using securitization techniques. It was still possible to squeeze out a pricing arbitrage using the waterfall-modeling techniques of ABS, but the funding arbitrages were not as dramatic as they originally had been because pricing between the two markets was undergoing dramatic changes. At this stage of market development, assets may be perceived to be getting scarcer and there are pressures to repackage existing ABS securities, or to create synthetic structures. If the benchmarks for repackaging and structuring are correct, arbitrage trading is making pricing in the market fairer.

Finally, in Act 3, the pressure for gain is intense. The emphasis shifts to benchmark arbitrage where it is possible to make money by selecting (an asset rated by) one benchmark with lapsed standards and buying (an asset rated by) a nominally equivalent benchmark that is constituted by more rigorous standards. An example from the pre-GFC market was buying an RMBS, repackaging it for sale in a CDO, where the standards were less rigorous, and booking a gain.

This kind of arbitrage opportunity only exists when the conventional quality measures are not homogeneous. The danger of scenarios like this materializing is real, notwithstanding that China appears to be lagging the U.S. in developing an analytical layer. For, it is all too easy to conclude the U.S. experience could not be repeated in China before temptation sets in.

APPENDIX A: UNDERSTANDING ABS ANALYTICALLY

China needs high money velocity and ample quantities of credit to realize its ambitious national economic and social goals. The securitization (“ABS”) market is a natural alternative channel of credit—a second “expressway” for transporting debt capital to harder-to-reach destinations. But ABS has two properties that make it more valuable than as a complement corporate debt:

(1) The principle of underwriting for ABS is more forward-looking and tangible than for corporate bonds, being based on the accounts receivable rather than revenue projections.

(2) The dollar value of ABS is countable, if risky. Dollars available to repay future corporate bond come from future revenues, which are uncertain and hence uncountable.

To highlight these distinctions, consider the global beverage franchise Starbucks. If we based a corporate credit analysis on the mean and variance of coffee-units Starbucks sells by the hour through its various branches and netted out associated expected future expenses, its rating should be closer to AAA than the current A1 rating by Moody’s.





Starbucks’ cash flows are well suited for the granularity of ABS analysis. Nevertheless, revenues are not receivables. Starbucks revenue may exceed or fail estimates, but no one is legally obligated to buy its beverages. This is not to say Starbucks could never be AAA by an ABS style corporate credit analysis, but the mechanics of the analysis would need to be adapted to fit the essential problem of ranking corporate balance sheet risk.

Like art versus science, the difference between the two approaches is only partly methodological. It is also essential. Good corporate credit research goes beyond linear extrapolation to draw on analogy, experience and insight in pursuit of patterns that can narrow future uncertainty. The enemy of incisive corporate credit analysis is mindless, mechanical process application. By contrast, overreliance on human judgment is the enemy of superior and reliable ABS analysis. ABS analysis standardizes uncertainty by focusing on marginal future cash flows and grading their risk. Its power lies in the objective, consistent, disciplined adherence to methodology and process.

I. What is lacking in the U.S. ABS market model

The fair price of a bond is its discounted future cash flows at the appropriate hurdle rate for the risk. The hurdle rate can be found on a Bloomberg or Reuters screen by look-up on yield-spread curves based on term structure and rating. Corporate credit risk is conventionally considered to change slowly. To reflective its relative risk we assign a static credit risk premium, rc.

But unlike enterprise credit risk, ABS undergoes natural credit transitions due to risk amortization in tandem with the amortization of the principal balance. Its hurdle rate changes as a function of time. The bond pricing formula must be adjusted to a more generic case involving the lifecycle, i.e.—

P ≡∑i=1

n

( C (i)

( 1+r f +r c( i))i ) (1)

In primary market ABS analysis, ratings are issued based on the percentage of capital contingently available to different tranches to make up payment shortfalls. Here, the rating reflects payment risk. Thereafter, the default distribution is not updated, so the risk premium is backward looking. If the original rating improves, capital is locked up in the structure. If the original rating is too generous, the signal is delayed for months or years. This is a serious shortcoming of the U.S. model.

Since the Credit Crisis, ratings have become more dynamic. This is due in part to settlements in which certain rating agencies have committed to improving their rating architecture, in part to depressed yields that are driving investors down the capital structure and back in time via the secondary market. Slowly, the ABS secondary market is inching towards dynamic price adjustment, but these adjustments are subjective. They are still decoupled from risk. Hence their relationship to intrinsic value is random.

For ratings and prices to keep pace with intrinsic value at all points in time, the forward default curve must be modeled as a logistic function, for example—

D ( t )= Dr1+b e−c(t−t0 ) (2)

D(t) is the cumulative static pool default rate modeled as a function of time. Dr is the expected default rate, b is a scale parameter, c is a measure of correlation between defaults, and t0 is the curve’s inflection point, where burnout begins. Crucially, the first and second central moments of the forward default curve, D(t), must be sampled in the model to reflect the option-adjusted security risk of each security in the capital structure.

II. The pure ABS framework is China’s best funding choice





As the Starbucks analogy shows, corporate credit and ABS are differently constituted. But they are also more than complementary markets. The pure form of ABS (pure ABS) is cybernetic. It promotes greater capital efficiency and velocity than traditional on-balance sheet corporate debt finance. For any borrower with a stable cash cycle shifting to pure ABS (ABS that follows the ABS rules) as a debt funding strategy has more than microeconomic benefits for the company in question—it has macroeconomic benefits for the entire financial system.

(1) Pure ABS reduces financial system entropy.

It standardizes corporate payment uncertainty into measures of risk that can be more precisely audited. It allows risk to be paired more precisely with capital cushion to attain targeted returns. With pure ABS, every new transaction is structured according to the condition of its collateral and deals with superior collateral can support more leverage. Whenever real economic expansion outpaces risk, receivables turn faster and more stably. More receivables can be refinanced in highly rated (“AAA”) securities. Credit expands to meet demand without contributing to systemic risk. When the boom phase ends and aggregate demand contracts, the evidence of financial strain will show up in the performance of the new receivables, and a smaller portion will be financeable at AAA yields. Borrowers that are genuinely in need of funding are willing to pay marginally more to obtain working capital, but opportunistic borrowing will decrease. Leverage in the macro-economy will contract.

In the aggregate, implementation of a pure ABS framework will allow financial system leverage to rise and fall in step with collateral quality, and move incrementally closer towards policy targets. Over the long run this automated stabilization micro-mechanism should bring China’s currency, leverage and growth targets into a sustainable long-run equilibrium.

(2) Pure ABS frees up the capital of value-generating enterprises for reward or reinvestment.

Much like the expiration of value (risk) in options, ABS security risk declines as the collateral pool pays down. Decreasing risk is due in part to amortization of scheduled principal, prepaid principal receipts and write-downs every period, as well as the repayment of senior securities ((deleveraging).

Who gets the residual after senior expenses and principal amounts are paid? If the original structure was acceptable to all parties and secondary market performance is in line with original repayment scenarios, all parties have been fairly compensated as per the Indenture. Any cash left over is “free” to be redistributed. How? That is a choice. To date, the American market has chosen to ignore the question of who deserves the free cash by failing to fix the model and preserving the stealth transfer of wealth.

How much “free cash” could be available for redistribution without increasing systemic risk? Up to 33% of the original capital reserves in a well-structured deal. So, for example, if required capital is 8% and China’s 2016 debt is USD 18 trillion, then up to USD 0.475 Trillion could be released into the economy. Everyone in the economy is better off financially—not just the transaction parties.

Call this mechanism the risk-calibrated capitalization of the domestic balance sheet. Risk-calibrated capitalization is a far more powerful, effective and safe stimulus mechanism than turning a blind eye to a borrower’s high levels of loan impairment. Even though most firms probably could escape the jaws of bankruptcy, having to finance impaired loans severely caps their long-term growth potential.

Risk

For China not to adopt pure ABS and apply it rigorously to the primary and secondary markets, the risk is that capital diversion that started as a trickle turns into a flood as a handful of players learn how to profit from the cracks in the framework. This is how the U.S.-style Credit Tsunami began.

III. Elements of the Pure ABS framework

Constraints of the pure ABS framework are parsimonious indeed—

1. The axioms of arithmetic must apply;





2. The conventional balance sheet constraints must apply;3. ABS pricing and rating must be based on the actual collateral and waterfall;4. A priori elements applied at origination may not be changed ad hoc in the life of the transaction.

But, these constraints must be in force at all times.

(1) Axioms of Arithmetic

That analysts and structurers need to apply the operations of arithmetic (addition, multiplication, distribution and order) freely to do ABS seems obvious, but certain key operations are not permitted under FASB’s securitization framework (see SFAS 140 Appendix B, September 2000)—specifically, partitioning the accounts receivable on the balance sheet into vintages.

FASB’s current expected credit loss standard (CECL) is a reversal of its position on receivables analysis, but not its position that accounting objects are not numbers in the mathematical sense. But cash flow valuations are numbers in the mathematical sense. To not be able to use the axioms of arithmetic on them is to agree to an unacceptable level of opacity in ABS analysis.

(2) Balance Sheet and Other Cardinal Constraints

A balance sheet is a periodic snapshot of an entity’s key operating, investment and financial elements. All going-concern balance sheets exhibit asset-liability principal and interest parity. If these constraints are regularly violated, the entity is or will soon be insolvent.

Like other financial transactions, an ABS must be structured so the asset-liability parity conditions hold for the expected (base) case. I.e., each transaction party is receiving a fair yield for the risk they bear given all that can be known from the time of loan origination until now. A fair risk-adjusted return is also known as risk-certainty equivalence.

An “unfair game” is one that favors one transaction party with a paper gain when the deal closes. I.e., the position benefits from a positive discounted net present value (NPV) at the risk-calibrated hurdle rate. One or more transaction parties take a paper loss: the position has a negative NPV at the risk-calibrated hurdle rates. The following are garden variety violations of asset-liability parity conditions:

The seller receives an inflated price for the collateral and the buyer pays too much-receives too little yield-for the base case value of the security cash flow stream at closing

The securities are not adequately credit-enhanced to cushion the impact of risky collateral cash flows because the non-cash forms of credit enhancement (excess spread, over-collateralization, subordination, non-cash reserve funds, triggers) are not properly valued at closing.

Non-credit elements of protection to the transaction such as swaps, caps or CDS are not properly valued at closing.

The discount rate is based on ratings that violate parity conditions or the ratings do not violate parity conditions but the market ignores the ratings.

Ratings or yields fail to adjust in response to endogenous or exogenous changes in the risk level.

(3) Pricing and rating of collateralized securities are determined periodically on the basis of the actual collateral pool and current application of the waterfall;

Mischief happens in the ABS market when the analysis is anchored to something other than the real pool and exact structure. Inadequate analysis is the rule rather than the exception.

Pool quality is not fully known up front so it must be estimated. This makes the analysis vulnerable to the use of false proxies.

Uncertainty about pool quality disappears with the passage of time. Failure to update the pool in real time detracts from precision and can mislead.

Pool performance can also be biased by use of parameters that are outside the collateral pool, for example, arbitrary default rates, correlation, recovery assumptions, pool payment speeds. Parameters that deviate from





the pool’s actual properties give rise to estimation biases that can result in misrated and mispriced securities. Bias is narrowed by measuring the pool directly.

At closing, the transaction structure is fully known but rarely modeled. Excel is rarely adequate to model all the structural features. Most commercial providers of transaction structuring software take shortcuts or introduce process logic that has bugs. These defects may not be apparent to the user, but they bias the analysis.

(4) A priori elements applied at origination may not be changed ad hoc in the life of the transaction

Once the structuring rules, the rating scale, choice of pricing index and other a priori elements are set at origination, they should not be changed. Otherwise, just as in the Credit Crisis, ABS devolves into a game of bait-and-switch.

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