Category: Research

Designing More Efficient CDS Auctions

Professor Haoxiang Zhu

Credit default swaps (CDS) are an important derivative class. According to the Bank for International Settlements, as of June 2013, CDS contracts have $24 trillion notional amount outstanding and $725 billion market value globally.

A CDS contract is a default insurance contract written on a firm, loan or sovereign country. Buyers of protection (CDS buyers) pay periodic premiums on a notional amount of debt to sellers of protection (CDS sellers), until the contract expires or default occurs, whichever is earlier. For example, if a bond investor wishes to insure against the default of $100 million corporate bonds, and a five-year CDS contract on that bond is quoted at 500 basis points (5%) per year, then the CDS buyer pays $5 million per year to the CDS seller for five years. If the bond defaults within five years, the CDS seller pays the CDS buyer the loss given default. The question is: What are the recovery value and default compensation?

The market uses CDS auctions to determine the recovery value of a defaulted bond. For example, the auction-determined recovery rate of Greece debt is 21.5 cents per euro. So, CDS sellers pay CDS buyers 78.5 (=100-21.5) cents per euro of debt insured. In addition to settling CDS contracts, CDS auctions also give investors an opportunity to trade defaulted bonds at zero bid-ask spread. Given the sheer size of CDS markets and high-profile defaults in the recent recession, it is important that CDS auctions deliver unbiased prices and efficient allocations. But do they?

In a recent research paper with Professor Songzi Du of Simon Fraser University, we find that the current design of CDS auctions leads to systematically biased prices and inefficient allocations.

To understand why the auction design is biased and inefficient, we need to understand the auction procedure itself. A CDS auction consists of two stages. In the first stage, investors who have CDS positions submit market orders (called “physical requests”) to buy or sell the defaulted bonds. An investor’s market order on the bond must be in the opposite direction of his CDS position, and no larger in magnitude. The sum of these market orders, called “open interest,” is sold in the second stage, which is a uniform-price auction. Importantly, only one-sided limit orders are allowed in the second stage. If the open interest is to buy, only limit sell orders are allowed; if the open interest is to sell, only limit buy orders are allowed. The market-clearing price in the second stage is the “official” recovery rate of the defaulted bond for settling CDS.

From 2006 to November 2013, this auction procedure has settled more than 140 defaults, including those of Lehman Brothers, Fannie Mae, General Motors, and Greece, among others.

Through a formal auction model, we show that the biased design comes from the restrictions imposed on the two stages of CDS auctions. To get the intuition, consider a CDS buyer. A CDS buyer naturally wishes to sell the defaulted bonds to minimize the uncertainty in the auction final price; he can eliminate this price risk by selling an amount equal to his CDS position. If this CDS buyer also has a low value for owning the bonds (for information or hedging motives), he would want to sell more. But the auction procedure forbids him from selling these additional quantities. A supply to sell is therefore suppressed in the first stage. In the second stage, this supply is suppressed again if the open interest is to sell (as only buy limit orders are allowed). Information from a suppressed demand cannot come into the price. Therefore, price is systematically biased, and allocations of bonds are inefficient.

This is not the end of the story. In an earlier version of the same research paper, we show that, if CDS traders are large, they also have a strong incentive to manipulate the final price auction price—to get favorable settlement payments on their CDS positions. Manipulation also leads to price biases.

The administrators of CDS auctions are aware of the biased prices; as a remedy, they impose a price cap or a price floor, depending on dealers’ quotes and the direction of the open interests. But this measure is imperfect and can backfire. We find that although a price cap or floor can correct price biases, it can also make bond allocations even less efficient.

What is a better solution then? We show that a simple, unconstrained double auction delivers better price discovery and allocative efficiency. A double auction for settling CDS is similar to the open and close auctions on stock exchanges. Since double auctions have done well in equity markets, why not consider it for CDS auctions?

For details of this research, see Songzi Du and Haoxiang Zhu, “Are CDS Auctions Biased and Inefficient?”. An earlier version of this paper is summarized by FT Alphaville (part 1, part 2).

Haoxiang  Zhu is Assistant Professor of Finance at the MIT Sloan School of Management

Stimulus or austerity: an economist’s search for answers

New finance faculty member Jonathan Parker examines the effects of 2008 stimulus payments

Professor Jonathan Parker

In February 2008, Congress passed a $100 billion stimulus bill aimed at shoring up an an economy on the edge of freefall.

The stimulus awarded a tax rebate of up to $600 per person or $1,200 per couple in hopes that recipients would spend the money and prop up the sagging economy.

Jonathan Parker, one of MIT Sloan’s newest professors, said he believes the 2008 Economic Stimulus Act offers a promising opportunity to study a vexing question: Is household stimulus effective and good public policy?

“My research suggests that the stimulus payments did increase spending, and the extent to which they did informs us about the effects of similar policies on the economy.” Parker said. “We now have a reasonable idea about the spending responses to hitting the Fiscal Cliff or to a proposed tax change.”

“Whether the stimulus bill was good public policy, some will say ’yes,’ others will say ’no,’” he said. “That’s one of the things I’m studying.”

Parker joins MIT Sloan from Northwestern’s Kellogg School of Management, where he wrote several papers examining the impact of stimulus spending. He says at MIT he expects to continue to study stimulus spending versus austerity.

“My view is there is not a great case for either,” Parker said. “A convincing quantitative picture is still murky. A requisite for clarifying that picture is a better understanding of how firms and households behave. That’s what I’m continuously chasing.”

Parker’s path

This fall, Parker returns to MIT, where he received his doctorate in 1996. He joins an impressive roster of finance faculty at MIT Sloan, which is home to Nobel laureate Robert Merton and 2012 Time 100 honoree Andrew Lo.

“It’s a great institution with fantastic colleagues, from the grad students to the most senior faculty member,” Parker said. “It’s an exciting place to be.”

It is also a personal homecoming for Parker, who was born in Portland, Ore., but raised in the Boston suburb of Newton.

As a child, Parker couldn’t avoid being influenced by the academic life. Both parents worked at Boston University—his mother was an administrator, his father a professor of ancient Near Eastern languages and religion specializing in the ancient language Ugaritic.

While he didn’t choose economics until college, Parker’s studies began at the kitchen table.

“My mother was continuously coming up with mechanisms to make sure things were reasonably fairly divided between me and my brother,” he said. For instance, one brother sliced a piece of cake and the other brother got to pick which slice he got. “There’s something about that in economics, determining allocations in reasonable ways, understanding incentives, and thinking about how to make mechanisms that efficiently allocate resources,” said Parker.

His parents sent him to the rigorous Roxbury Latin School in the West Roxbury neighborhood of Boston. Parker went on to earn a bachelor’s in economics and mathematics from Yale University in 1988, and later a PhD in economics from MIT. The longtime headmaster at Roxbury Latin, F. Washington “Tony” Jarvis, an Episcopal priest who oversaw the school from 1974 to 2004, left a lasting impression.

“He was an inspirational figure for thinking about living for more than a house in the suburbs and the 2.5 kids and a minivan,” Parker said. “It was about doing something bigger, better, and beneficial to other people rather than measuring success in life by income.”

Work and public service

Parker studies household economics and asset pricing—the big economic questions that touch on people’s everyday lives.

After posts at the University of Michigan and the University of Wisconsin, Parker taught at Princeton University.

In 2009, while at Northwestern, Parker was tapped to join a team of economists charged with devising a way to attach values to the assets in the government’s Troubled Asset Relief Program (TARP) portfolio. It was critical to find ways to help the government pin values to assets to protect taxpayers. There were many challenges, Parker said.

“How do we value claims the government holds against AIG, Citigroup, and most of the smaller banks in the U.S.?” Parker asked. “Many of the claims on these institutions held by the U.S. government—and so taxpayers—were not traded in the marketplace, so how do you figure out their worth? Given that some may not pay the government back, and the government controls policies that influence whether they will be able to, how do you price the risk in these banks?”

Parker’s work studying the efficacy of stimulus spending started at Princeton with the tax rebates of 2001, and continued at Northwestern. There he set out in several studies to measure exactly what households did with their stimulus checks, and why, with an eye toward influencing future policy.

In 2012, Parker wrote “The Economic Stimulus Payments of 2008 and the Aggregate Demand for Consumption,” with Christian Broda of Duquesne Capital Management. The pair used consumer purchase scans to see how the tax rebates were spent.

What they learned was that after rebates arrived, households raised spending 10 percent in the first week and 4 percent in the following seven weeks, then the spending trailed away. Almost all consumer spending was by households with incomes of $35,000 or less and with two months or less of liquid assets.

Parker said it is tough to sell stimulus programs if households believe they don’t work and are costly because they add to the nation’s long-term debt.

“The $64,000 question is, ’What do we do now—with the US debt to GDP as high as it is and a perceived need to increase spending for demand?’” Parker said. “There’s a tough trade-off because household spending reflects not just cash flow, but also future concerns about who’s going to pay, and will there be a default crisis?”

His research so far doesn’t give a clear answer—stimulus or austerity. But then again, no one has the answer yet.

“Economists who get on TV and say ’I’m sure we should do more stimulus’ or claim that the only way forward is austerity, they are not getting there from the academic evidence they’ve read,” Parker said. “They’re getting there from somewhere else.”

“I’m always humbled by how little we know,” Parker said. “The world is infinitely more complex than our economic models. So we’re continuously learning. Some of the biggest questions in economics are still up for grabs.”

 

Can Financial Engineering Cure Cancer?

Professor Andrew Lo

There is growing consensus that the bench-to-bedside process of translating biomedical research into effective therapeutics is broken. In a paper published in the October 2012 issue of Nature Biotechnology, my coauthors, Jose-Maria Fernandez and Roger M. Stein, and I suggest that this is caused in large part by the trend of increasing risk and complexity in the biopharma industry. This trend implies that the traditional financing vehicles of private and public equity are becoming less effective for funding biopharma because the needs and expectations of limited partners and shareholders are becoming less aligned with the new realities of biomedical innovation. The traditional quarterly earnings cycle, real-time pricing, and dispersed ownership of public equities imply constant scrutiny of corporate performance from many different types of shareholders, all pushing senior management toward projects and strategies with clearer and more immediate payoffs, and away from more speculative but potentially more transformative science and translational research.

We propose a new framework for simultaneously investing in multiple biomedical projects to increase the chances that a few will succeed, thus generating enough profit to more than make up for all the failures. Given the outsized cost of drug development, such a “megafund” will require billions of dollars in capital; but with so many projects in a single portfolio, our simulations suggest that risk can be reduced enough to attract deep-pocketed institutional investors, such as pension funds, insurance companies, and sovereign wealth funds.

A key innovation of this proposal is to tap into public capital markets directly through securitization, using structured debt securities as well as traditional equity to finance the cost of basic biomedical research and clinical trials. Securitization is a common financing method in which investment capital is obtained from a diverse investor population by issuing debt and equity that are claims on a portfolio of assets—in this case biomedical research. Debt financing is an important feature because the bond market is much larger than the equity market, and this larger pool of capital is needed to support the size of the portfolios required to diversify the risk of the drug development process. In addition, this vast pool of capital tends to be more patient than the longest-horizon venture capital fund.

Our findings suggest that bonds of different credit quality can be created, which could appeal to a broad set of short-term and long-term investors. The results from the simulations we ran indicate that a megafund of $5 billion to $15 billion may be capable of yielding average investment returns in the range of 9 percent to 11 percent for equity holders, and 5 percent to 8 percent for bondholders. These returns may be lower than traditional venture capital hurdle rates, but are more attractive to large institutional investors.

To calibrate and test our simulation of the investment performance of a hypothetical cancer drug megafund, we accessed the databases of hundreds of anti-cancer compounds assembled by Deloitte Recap LLC and the Center for the Study of Drug Development at Tufts University School of Medicine. These simulations not only yielded attractive investment returns on average, but also implied that many more drugs would be successfully developed and brought to market. Such an outcome would be particularly welcome given the current scarcity of investment capital in the life sciences industry despite the growing burden of disease. One in two men and one in three women in the United States will develop cancer at some point in their lifetimes, making this one of the major priorities facing society.

We acknowledge that our analysis is only the first of many steps needed to create a private-sector solution to the funding gap in the life sciences industry. The practical challenges of creating a megafund would require unprecedented collaboration among medical researchers, financial engineers, and biopharma practitioners. Support from charitable organizations and the government also could play a critical role in expediting this initiative. In an extension of this simulation, we show that the impact of such support can be greatly magnified in the form of guarantees rather than direct subsidies. The MIT Laboratory for Financial Engineering will be hosting a conference at MIT in June where representatives from all the major stakeholder communities will be invited to explore these ideas together.

Finally, our proposal is clearly motivated by financial innovations that played a role in the recent financial crisis, so it is natural to question the wisdom of this approach. Despite Wall Street’s mixed reputation in recent years, we are convinced that securitization can be used responsibly to address a host of pressing social challenges. With lessons learned from the crisis and proper regulatory oversight, financial engineering can generate significant new sources of funding for the biopharma industry, even in this difficult economic climate. Raising billions of private-sector dollars for biomedical research may seem ill timed and naive—but given the urgency of cancer, diabetes, heart disease, and other medical challenges, the question is not whether we can afford to invest billions more at this time, but rather whether we can afford to wait.