Archegos: a spectacular failure in risk management by Dan diBartolomeo

Archegos: a spectacular failure in risk management

by Dan diBartolomeo

myopic view of prime brokers

example of pyramiding

The recent failure of the Archegos hedge fund/family office was a spectacular example of the persistent deficiencies in hedge fund and broker risk management. The fund went from about a $30 Billion position to total collapse, leaving at least $7 Billion in publicly announced losses associated with failed margin calls across prime brokers at Credit Suisse, Nomura, UBS, and Morgan Stanley. A fifth prime broker, Goldman Sachs, has commented only that their losses are “immaterial.”

Many investors have been left wondering how four of the world’s most sophisticated investment banks could be subject to massive losses associated with routine margin lending on a set of equity total return swaps. While not all facts have been made public, we believe that the problem arose from both weak procedures and some obvious analytical failures. Of the involved firms, Credit Suisse has already announced a change in policy to “dynamic margins” for equity return swaps. The implications of this announcement is that the prior policy was “static margin,” meaning that an investor’s deposit in a margin account did not have to grow as the value of the transaction increased.

We also know that Archegos was dealing with at least five prime brokers. It is unclear if the five firms involved were aware of the existence of very similar Archegos positions at the others. This myopic view could have allowed “pyramiding” of positions by Archegos.

Here is a simplified hypothetical example of how this pyramiding could have been accomplished.

Investor H enters a one-year total return swap with Broker C with a transaction cost of 1% for stock X for a notional amount of $100. According to the terms of the swap, if stock X goes up over the year, C owes H 99% (100-1) of the total return on $100 worth of stock X. If stock X goes down over the year, H owes C, 101% (100 +1) of the total loss on $100 worth of stock X. Investor H deposits $25 in cash with C to cover possible losses in a decline in the price of stock X as a margin deposit. Broker C can hedge their risk by buying $99 worth of stock X which drives the price of stock X up from $100 to $200. Broker C credits $99 (.99 * (200-100)) to investor H’s margin account which now has a balance of $124 ($25 + $99).

Investor H then withdraws $99 from the margin account and sets up a new account at Broker M, then sets up the identical swap transaction that H has with broker C. Since the new account is starting with $99, it can act as a margin deposit for a position of $396. Broker M can hedge their risk by buying $396 worth of X. By pyramiding positions across two brokers, H was able to use $25 to cause the two brokers to purchase $495 worth of X, driving the price of X up further. This is equivalent to financial leverage of $495/$25 or almost 20 times.

As the price of stock X keeps going up, H could again “upstream” the cash from both the accounts and set up a third account, a fourth account, and so on. This hypothetical narrative is conditional on the brokers allowing H to withdraw cash associated with “mark to market” profits before the end of the one-year term. Normally a prime broker providing this kind of facility to a hedge fund would routinely allow “mark to market profits” to be reinvested in other securities, but a large cash withdrawal would set off a lot of alarm bells. Archegos was acting like a hedge fund but was legally a family office so they might have asserted something like “we need to withdraw the cash to buy a new mega-yacht or a private island.”

In the Archegos case the amounts being invested were billions of dollars per company. With leverage of four to twenty times, a large initial transaction could certainly influence the price of a typical stock enough to set the pyramiding process in motion. With five brokers having relationships with Archegos, any pyramiding effect would also be less noticeable.

As of March 22nd, 2021 the price of ViacomCBS (VIAC) was about $100/per share, with the S&P 500 at 3940. One year earlier at the market bottom of the COVID crisis, Viacom was $12 and the S&P 500 index value was 2310. So, while the market was up about 70% from the bottom, Viacom was up 733%. Our internal estimates were that the beta of Viacom was 1.81 with a specific risk of 8.33% per month (29% per annum). Under the standard Capital Asset Pricing Model1, our expectation for the return for Viacom would be roughly 70% * 1.81 or 127%.

The unexpected return would be 733-127 or 606% over the period. Given an expected specific risk of 29%, this is a 21 standard deviation event. Assuming returns are normally distributed, the random likelihood of such an event is 3 * 10-98 (a number like .0003 but with 98 zeros). That should have been a sufficient clue to the broker risk management teams that something was wrong, and accepting Viacom shares as collateral for billions of dollars in loans was probably not the best idea. Even when we account for our risk estimates increasing through the year contract period (e.g. tripling), this is just an event that is so improbable as to immediately raise questions.

stock price moves should have raised questions

1 / Sharpe, W.F. (1964). Capital Asset Prices: A Theory of Market Equilibrium Under Conditions of Risk. Journal of Finance, Volume XIX

illiquid positions

The other big piece of this puzzle was incorrect estimation of liquidity. We know that the price of Viacom went from $100 to about $45 in a few days once brokers started to rapidly sell off the positions to salvage what value they could. The average trading volume over the prior month was about 71 Million shares or about $7 Billion per day at the $100 price. It has been publicly disclosed that the Archegos portfolio was concentrated into about half a dozen companies and reached a peak value of around $30 Billion, so the average position per company was about $5 Billion. The Viacom parcel was a bigger position with a peak value around $10 Billion, or more than 150% of a typical day’s trading volume. These magnitudes are consistent with a peak trading volume of over 500 million shares (a day in early April) during the “fire sale.”

Equity transaction cost models produced by brokers are largely empirical. Most of them are of the form presented by Kissell and Glantz. Typically, very little data is available for one day trades bigger than 25% of “average daily volume,” as traders know these trades will be very expensive to execute and avoid them. The five brokers may have believed they were the entire Archegos positions leading to the false conclusion that their internal transaction cost models were adequate (assuming they were used at all). Such myopic approaches to liquidity estimation have unfortunately been encouraged by recent SEC reporting requirements for mutual fund liquidity.

Available theoretical models of equity transaction costs assume that once a trade is outside the observed range of size, the cost of obtaining additional liquidity increases with the square of the trade size to an upper limit of 40% to 70% or more of the total position value. The observed decline of Viacom from $100 to around $45 during the unwinding of Archegos is consistent with this view.

author

Dan diBartolomeo

Dan diBartolomeo is founder and president of Northfield Information Services, Inc. He serves as PRMIA Regional Director for Boston, as well as on boards for several financial industry associations including IAQF, QWAFAFEW, BEC and CQA. Dan spent eight years as a Visiting Professor in the risk research center at Brunel University in London. In 2010, he was awarded the Tech 40 award by Institutional Investor magazine for his analysis that contributed to the discovery of the Madoff hedge fund fraud. He is currently the co-editor of the Journal of Asset Management and has authored nearly fifty research studies in peer review publications.

2 / Kissell, R. and Glantz, M. (2003). Optimal Trading Strategies: Quantitative Approaches for Managing Market Impact and Trading Risk. Amacom.