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March 5, 2024

How Deep is Your Bench? Recent Benchmark Manipulation Antitrust Cases

Author(s): Jeffrey Armstrong

As litigations involving LIBOR, ISDAfix, Forex and various commodity benchmarks indicate, benchmarks that serve as reference rates and the underlying prices used to generate them can be susceptible to manipulation. In the US, the manipulations can constitute violations of antitrust laws or securities and commodity exchange laws that protect investors, asset managers, pension funds, hedge funds and other market participants from artificial prices not aligned with competitive market forces and sound trading strategies.

This post reviews some of the recent benchmark manipulation litigations that have alleged antitrust violations as well as provides insight into some of the factors related to benchmark manipulation. Benchmarks typically serve as reference prices or rates used by buyers and sellers in contracts for both real assets, like commodity supply contracts, and financial instruments/financial contracts, like swaps, futures or options derivatives. An example of benchmark manipulation could be a regular polling by a third party of manufacturers’ transaction prices to compute an average price (the benchmark) who respond with non-representative purchases or sales to push the average up or down.

The Manipulation and Demise of LIBOR

The well-known London Interbank Offered Rate or “LIBOR” benchmark (defunct since June 2023) relied on daily surveys of money center banks in London for quoted rates on overnight and short-term interbank loans. The submitting banks’ rate quotes were then compiled to generate a daily LIBOR benchmark rate announced to the market around 12 noon London time.

The daily LIBOR became a more fragile benchmark and one of the more scrutinized financial benchmarks as the pool of actual interbank loans, particularly in US dollars known as Eurodollar loans, diminished over time. With fewer actual loan transactions to observe market rates plus the hundreds of trillions of dollars in financial market products whose values were tied to the LIBOR benchmark, the survey-based LIBOR became more susceptible to manipulation and less verifiably tethered to actual loan costs. For these reasons, the Financial Conduct Authority (“FCA”), the regulator of the UK’s financial markets and capital markets, decided to cease LIBOR publication altogether.

Every other developed economy and many developing economies have followed the FCA’s lead to cease publication of their LIBOR-equivalent financial benchmark. The new benchmark replacement rates adopted by each economy are too numerous to review in this post. However, the new financial benchmarks suffer from some of the same deficiencies (or create new ones) that led to the demise of LIBOR or fail to satisfactorily resolve weaknesses similar to those that have spurred benchmark manipulation disputes in other markets. While the LIBOR manipulation scandal is essentially over, allegations of manipulation of other benchmarks will no doubt continue.

Commodity Market Benchmarks

In non-financial products such as physical commodities, many price benchmarks rely on sparse spot-market transaction data. Such spot trades are typically not conducted on an open, transparent exchange and could be susceptible to market abuse. Rather, trading is conducted in more opaque venues such as over-the-counter (“OTC”) markets, e.g., Forex, or in thinly traded markets such as fertilizer (see discussion below). Often, the underlying price information and published benchmarks rely on Price Reporting Agencies (“PRAs”) like Platts.

These limitations alone do not necessarily imply the benchmarks are flawed or biased. But in some situations, commodity benchmarks may not rely at all on actual transactions but rather on quoted prices or even price indications (non-firm quotes) from surveys of market participants, a weakness of LIBOR that was eventually exploited and led to its demise.

An Econ One study analyzed the spot market prices of US fertilizer, which surged in late 2021. Spot trading in fertilizer, like many other real assets, is not conducted on an open transparent trading platform like a centralized exchange. The chart below shows how wholesale fertilizer prices moved in relation to natural gas (the key input to nitrogen fertilizer production). Interestingly, the price-cost gap was fairly stable from 2016 – 2019 (the distance between the solid blue line and solid red line), then the gap substantially widened in 2022.

Chart showing U.S. Producer Price Indexes for Nitrogen and Natural Gas 2016-2023

While prices of fertilizer and natural gas have since fallen from their peak, the wholesale price of fertilizer remains above its average over 2016 – 2019 by roughly $100 per ton more (comparing the solid blue to the dashed blue line in the shaded area of the chart). By contrast, natural gas prices (the Henry Hub spot price) have fallen back to their pre-COVID levels (solid red line versus dashed red line). At $100 per ton and roughly 12 million tons of nitrogen fertilizer consumed by the US agriculture sector each year, this amounts to $1.2 billion in higher annual costs.

The fertilizer price surge caught the attention of federal and state agriculture regulators as well as the Iowa State Attorney General. While the trends do not necessarily signify improper market activity, they underscore the importance of ongoing scrutiny of financial and commodity benchmarks, even at times when prices are no longer at extreme peaks and may appear to have settled to normal levels. For example, Econ One analyses suggest that higher market concentration levels in US fertilizer production appear to be one of the structural drivers of the price-cost gap discussed above.

Benchmarks for Financial Derivatives

Returning to financial benchmarks, one of the latest and active antitrust litigations alleging benchmark manipulation as well as market manipulation shows that valuable economic evidence of collusion can be developed through data and econometric analyses.

A class action filed by buyside investors alleged the benchmark price used to settle Credit Default Swaps was manipulated by dealer banks (see In Re Credit Default Swaps Auctions Litigation). A Credit Default Swap or “CDS” gives bond investors price protection in the event that the bond issuer defaults or enters bankruptcy. The loss in value of the bonds is compensated for through the settlement of the CDS swap following an auction that values the covered bonds and generates a benchmark price from quotes submitted into the auction.

The econometric evidence presented in Plaintiffs’ Complaint was based on a regression model that analyzed actual benchmark prices generated by the auctions used to determine the swap settlement payments. The econometric model employed techniques known as pooled cross-sectional time-series analysis and implemented widely-accepted statistical tests to demonstrate Defendants’ caused each others’ collusive pricing behavior during a live auction that manipulated the benchmark.

In summarizing Plaintiffs’ empirical evidence of collusion, the judge incorporated an excerpt from the Complaint that, as he understood Plaintiffs’ “econometric analyses,” attempted to:

“show that Defendants have been consistently engaged in a multiyear bid-rigging and price-fixing scheme to artificially skew the final auction price in whichever direction suits their own financial interests.” (Memorandum Opinion and Order at p. 24).

The judge then ruled:

“the Court agrees with Plaintiffs that the statistical allegations, standing alone, allege a plausible antitrust conspiracy sufficient to deny the [Defendants’] Motion as to these claims.” (Memorandum Opinion and Order at pp. 66-67)

Benchmarks are vital market price information for investors, market participants and the performance of the economy.  The issues discussed in this post are of paramount importance to investigating potential benchmark manipulation, including possible antitrust collusion.  Even if the benchmark calculation methodology is public and has been in existence for a long time (as is true of many benchmarks), it can be difficult to discover and investigate manipulation.  In LIBOR for example, the calculation methodology, which included features to deter manipulation, was known for decades (since its launch in 1986) before the manipulation was ever discovered.

Econ One has experts in finance and economics with academic, industry, consulting, and expert testimony experience in assisting clients in benchmark manipulation issues.

Industries: Financial Markets

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