Safeguarding Bitcoin benchmarks: Lessons learned

Safeguarding Bitcoin benchmarks: Lessons learned

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By Sui Chung, chief executive of CF Benchmarks

In financial markets, price benchmarks are used extensively for a variety of purposes, from settling derivatives transactions, to determining Net Asset Value (NAV) for investment funds amongst a host of use cases in institutional finance. One could almost go as far as saying that the preponderance of the use of a benchmark is a hallmark of the degree to which any market is institutional in nature. The market for Bitcoin trading has, since its inception in 2010, been largely driven by individual investors but there has been increasing institutional participation through derivatives contracts from CME Group and Eurex as well as a variety of exchange traded products and funds in Canada, Brazil, Hong Kong and Europe.

Whilst Bitcoin is a novel asset, the requirements of a benchmark price for Bitcoin are no different from those required of a benchmark price for any asset. Whether it be Brent/WTI for crude oil, Term SOFR for money markets, or EuroStoxx 50 for the European equity markets – all benchmarks need to be; representative of the underlying market, resistant to manipulation and replicable by market participants to be able to foster further institutional participation in the underlying market that is being measured.

CF Benchmarks has provided the CME CF Bitcoin Reference Rate (BRR), the index that settles the CME BTC-USD futures contract, since 2017 and was the first crypto index provider to be regulated under the Benchmark Regulation (BMR) - CF Benchmarks has been an FCA regulated Benchmark Administrator since 2019, as such we have unique experience of what market participants and investors require of benchmarks for crypto assets to give them the confidence to trade products that settle to them. First and foremost, in their minds is whether the benchmark is resistant to manipulation.

Manipulation Resistance by Design

As the BRR is used for a wide range of activities such as asset valuation, derivatives settlement, Net Asset Value calculation, investment fund unit creation and redemption it has been heavily scrutinised by many financial institutions and has been shown to be free of manipulation and furthermore been administered and calculated in a manner that deters and impedes manipulation. The first and most valuable tool for protecting a benchmark from manipulation is in the selection of input data as the old adage goes; garbage in, garbage out. This is doubly true of trying to benchmark Bitcoin given that it is traded on a multitude of venues (200 and counting by our estimates) that are not subject to capital markets regulations, and in some cases have no actual domicile so observance of AML/KYC requirements can sometimes be difficult to ascertain.

Input Data selection

CF Benchmarks first line of defence against manipulation is to exclusively source input data from cryptocurency exchanges that meet published criteria as set out in its Constituent Exchanges Criteria. The criteria are available here.

CF Benchmarks ascertains the presence of fair and transparent market conditions and processes to identify and impede illegal, unfair or manipulative practices (criterion 2) by conducting a thorough review of any exchange under consideration for inclusion as a Constituent Exchange. The arrangements of all Constituent Exchanges are reviewed annually to ensure that they continue to meet all criteria specified within “Constituent Exchange Criteria”. This due diligence is documented, and the information is distributed to CF Benchmarks’ oversight organs to consider. The deliberations of oversight organs are conducted during regular meetings, minutes of such meetings are publicly available, being published on our website. To date the six cryptocurrency exchanges that meet these requirements are Coinbase, Gemini, Bitstamp, Kraken, itBit and LMAX Digital.

Manipulation resistance through the calculation methodology

Resistance to manipulation is a priority aim of the methodology design underlying the BRR. The methodology takes an observation period and divides it into equal partitions of time. The volume-weighted median of all transactions within each partition is then calculated. The benchmark index value is determined from the arithmetic mean of the volume-weighted medians, equally weighted. The benefits of this process with respect to achieving manipulation resistance are outlined below.

●        Use of partitions

Individual trades of large size have limited effect on the Index level as they only influence the level of the volume-weighted median for that specific partition. A cluster of trades in a short period of time will also only influence the volume-weighted median of the partition or partitions they were conducted in.

●        Use of volume-weighted medians

Use of volume-weighted medians as opposed to volume-weighted means ensures that transactions conducted at outlying prices do not have an undue effect on the value of a specific partition.

●        Equal weighting of partitions

By not volume weighting partitions, trades of large size or clusters of trades over a short period of time will not have an undue influence on the index level.

●        Equal weighting of constituent exchanges

CF Benchmarks applies equal weight to transactions observed from CME CF Constituent Exchanges. With no pre-set weights, potential manipulators cannot target one platform for the conduct of manipulative trades.

●        Use of arithmetic mean of partitions

Using the arithmetic mean of partitions of equal weight further denudes the effect of trades of large size at prices that deviate from the prevailing price having undue influence on the benchmark level.

Benchmark Surveillance

Whilst we have every confidence in our framework for resisting manipulation, we also remain vigilant against attempted benchmark manipulation and monitor input data continuously. Any and all instances of suspected benchmark manipulation are escalated through appropriate regulatory channels in accordance with CF Benchmarks’ obligations under the UK Benchmarks Regulation (UK BMR). CF Benchmarks’ Control Procedures with respect to compliance with the UK BMR have been audited by ‘Big Four’ accountancy firm Deloitte. The Independent Assurance Report on Control Procedures Noted by CF Benchmarks Regarding Compliance with the UK Benchmarks Regulation as of September 12 2022 is available here.

This further verification of CF Benchmarks’ compliance with the UK BMR places the BRR on the same level of scrutiny applied to widely used traditional financial benchmarks like ICE SWAP, SONIA and RONIA.

Assessing BRR input data for signs of manipulation

Whilst the CME CF BRR was designed and is administered to the highest standards, including efforts to uphold provisions of the UK BMR, the proof of the pudding is in the eating and further analysis of the data is required. Were there to be a lack of integrity in the input data that could in turn affect the integrity of the benchmark, one would expect to see one of a number of phenomena reflected in the input data provided by Constituent Exchanges, a potential example would be significant price dislocations between Constituent Exchanges.

How well correlated are Constituent Exchange prices?

An analysis was undertaken of the pair-wise correlation of prices from Constituent Exchanges on a per-minute basis (the price difference between transactions for each minute at each exchange) during the observation period. The results of this analysis are shown in graphical form in the chart below. The clustering towards correlation coefficients of 1.00 and the fact that on less than 1% of days any exchange had a correlation with another exchange below 0.5 demonstrate strong price correlation between the Constituent Exchanges, and point towards fair and orderly markets. The pattern is understandably broken around the time of the FTX bankruptcy (Nov-Dec 2022) given the extreme volatility this event precipitated.

 It is quite clear that the BRR has Resistance to Manipulation built into every facet of its construction and the quantitative analysis shows that integrity of the benchmark is upheld. The CME CF Constituent Exchange Criteria ensures that it takes input data only from cryptocurrency exchanges that exhibit fair and orderly behaviour, where trading shows strong price correlations amongst each other. On top of this, the methodology the BRR employs nullifies effects of any manipulation, and the Administrator’s policies and processes regarding surveillance ensure that any manipulation is detected and regulatory authorities notified so that appropriate action can be taken.

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