Hexaven

Results of consultation on structure and governance of the Credit Derivatives Determinations Committees. Following the launch by ISDA of an independent review of the Determinations Committees (DCs) last December, the publication of the review and recommendations by Linklaters in May, Boston Consulting Group (BCG) conducted a market-wide consultation on issues and solutions raised in the independent review. We were delighted to contribute to this market-wide consultation and give our technology infrastructure perspective. The results of the consultation indicate there is broad market support to implement many of the recommendations, among others: · Including establishing a separate governance body; · Implementing certain transparency proposals relating to the publication of DC decisions; · Appointing up to three independent members of the DCs. The report highlights that the representativity and transparency requirements could be supported by a "better use of technology", which would also be beneficial for the cost management of new rule implementations. What is the next step? Some of the proposals received a significant minority of objections, indicating that more industry input would be required to address the concerns raised. ISDA will work with its members to identify a package of practical changes that can be made to the DC rules and will present them to the DCs, which are solely responsible for agreeing and implementing any amendments. #cds #creditderivatives #digitalcds #cryptocounterpartyrisks #cryptodefaultrisks #defi #tradfi #cryptoriskmanagement #cryptohedgefunds #highyield

Crypto risk management: Top Picks from ETHCC [7] Following an exciting week in Brussels, it is time for Hexaven to reflect on the topic of #cryptoriskmanagement. Here are the top pick discussions we wanted to share from EthCC[7]. Pick#1: Automated and decentralized risk management frameworks 👉 Yaron Velner from B.Protocol 💡 Yaron defined DeFi economic risk management as the capacity to adjust risk parameters to keep a platform solvent and mentioned the benefits of having an automated on-chain risk formula calculating Loan to value (LTV) based on public data such as asset volatility and liquidity, until a decentralized veto mechanism for Lenders LPs. Pick#2: On-chain undercollateralized credit 👉 ⧫ Laurence E. D. and Andreas Fletcher  from The Wildcat Protocol 💡 While gauging counterparty credit risk in DeFi was regarded as extremely difficult, Laurence described the benefits of using zero-knowledge (ZK) proof to establish on-chain reputation so that borrowers could share financial credentials with privacy preserved. In a separate discussion, Andreas presented Wildcat’s framework for borrowers and lenders to agree upon the credit line parameters set by borrowers (APR, underlying assets, collateralization ratio, loan duration). Pick#3: Ethereum as a settlement layer in the financial system and Stablecoin 👉 Andrew O'Neill, CFA and Charles Jansen from S&P Global 💡 Andrew presented the key opportunities, but also the concentration risks and risk dependencies when considering Ethereum as a settlement layer for financial applications. Separately, Charles described the Stablecoin Stability Assessment (SSA) based on a 2-step analytical framework (1. asset assessment 2. other factor adjustments), where SSA could be used as a benchmark allowing other institutions to have an independent third-party view on the risks related to stablecoins. Pick#4: Depegs and market threats 👉 Angelo Canesso from Aleno 💡 In a workshop, Angelo presented Sentry, a DeFi alerting system which can be used for different use cases such as depegs, dumps and drains and market exploits. Alerts can be set via APIs based on time series metrics, both at the token level (total TVL, total supply, token USD price, token WETH price) and at the pool level (pool TVL and pool rates). Pick#5: Uncollateralized lending 👉 Samrat Lekhak from Liquity 💡 Sam presented Liquity v2’s approach driven by borrowers own choices for credit parameters rather than algo or governance. Liquity new stablecoin, BOLD, would allow borrowers to take out loans by depositing ETH and liquid staking ETH derivatives as collateral while setting their preferred interest rates with plans to pay most of the revenue from borrowing fees into the stability pool and secondary markets incentivized by the protocol. Looking forward now to follow up with market participants, partners and investors we met during this fruitful week. #cryptodefault #cryptorisks #cryptotrading #creditrisks #cryptohedgefunds #digitalcds

Statistical ratings: credit risk model optimized for the crypto markets. Agio Ratings - a risk assessment platform specializing in digital assets - has just released a new model version of statistical ratings. The new model extends the counterparty coverage by more than 50% and aims to improve both its predictive performance for known defaults and its correlation with observable market forecasts. Traditional credit risk models There are different types of #creditriskmodels, which differ on the types of inputs, on what is to be derived and on the assumptions: 👉 Structural or fundamental models: model default, derive measures of credit risk from fundamental data (e.g Merton model, which uses the black-Scholes formula to calculate the probability of default (PD) and loss given default (LGD) of a borrower based on its equity value, debt value, and volatility); 👉 Reduced-form models or intensity models: take estimates of PD or LGD as inputs (e.g. Jarrow-Turnbull model, which uses the cox-Ingersoll-Ross model to calculate the intensity or hazard rate of a borrower based on the term structure of interest rates and the credit spread); 👉 Factor models: leverage company, industry, economy-wide fundamentals, often in a highly schematized way, which lends itself to portfolio risk modelling; 👉 Statistical models: assess the likelihood of default or creditworthiness of borrowers based on statistical analysis of various factors, based on different techniques such as logistic regression or discriminant functions. Statistical Ratings: best pick for crypto? Due to lack of financial information on crypto counterparty references, the use of structural models is limited, while risk-neutral probability models also fail due to lack of “market price” given low supply of crypto reference obligations and credit products. Statistical modelling - Agio Ratings' approach - stands out as the "model of choice" as it could leverage public on-chain data series (e.g. on-chain reserves, self-report trading volumes and age), thus allowing to estimate PB based on a set of independent variables. Next developments However, crypto statistical predictions are based on constrained historical data series and small defaulted population sample compared to credit risk model standards in traditional finance. Statistical models seek for constant optimisation of the variables (e.g. calibration of observation period) and increase of number of variables to account for specific use cases of known defaulted companies, at the risk of potential model "overfitting". The degree of maturity of the crypto markets would warrant the use of a combined approach across statistical modelling and other techniques - benchmarking, digital CDS, jump-diffusing model. https://lnkd.in/eUn7qTPh #cryptorisks #cryptoriskmanagement #cryptodefaultrisks #digitalcds #cryptoriskrating #cryptoriskscoring #defi

Centralized exchange creditworthiness: going beyond trading volumes and market shares. Bybit has became the world’s second largest crypto exchange according to a report from crypto research firm Kaiko. Bybit’s market share has surged from 8% to 16% since last October (compared to a mere 1% increase over the same time period for Coinbase). CEX market share of volume Bybit surpassed Coinbase in March to become the second-largest exchange after Binance. Bybit managed to leverage more on the launch of spot Bitcoin ETFs in the US, seen as a strong catalyst for larger CEX volumes. A competitive, low fee strategy also supported the volume growth compared to CEXs on the high end of the fee range (e.g. Coinbase, Bitstamp, Kraken Digital Asset Exchange). CEX creditworthiness Trading volumes and market shares are important indicators of CEX creditworthiness. Some research papers (see "Crypto Exchanges and Credit Risk: Modeling and Forecasting the Probability of Closure" - Dean Fantazzini, and Raffaella Calabrese) highlight correlation patterns between crypto exchange trade volumes - financial soundness and, therefore, solvency state. However, this is only a sub-set of default risk indicators which are also used for creditworthiness assessment. For instance, Hexaven's risk assessment framework relies on other financial indicators (e.g. balances, net flows), and additional, non-financial categories (e.g. technology, governance, regulatory and reputation risks). Bybit use case  Let's illustrate some non-financial categories for the Bybit use case. 👉 Reputation risks: Bybit ranks particularly low on the Proof or Reserves (PoR) compared to his top tier peers. Back in May, Ben Zhou, the CEO of the Bybit, had to communicate on the PoR on the back of rumours of the platform being hacked and insolvent; 👉 Technological risks: Bybit ranks in the top tier overall, albeit relatively lower on its CryptoCurrency Security Standards (CCSS - a standard for securing crypto currency systems); 👉 Regulatory risks: Despite some derivatives trading ban in Brazil and penalties in Canada in 2022, and, more recently this year, some challenges by the markets regulators from Hong Kong and France, the opening of Bybit's global headquarters in Dubai last year had a positive contribution. Taking these other different categories into consideration, our risk assessment ranks Bybit's overall creditworthiness: 🏆 worse than Coinbase, Binance 🏆 closer to Kraken, OKX and Bitstamp 🏆 better than Huobi and Kukoin https://lnkd.in/ekzX4k9k #cryptodefault #cryptodefaultrisks #cryptorisks #cryptoriskmanagement #cryptohedgefunds #digitalcds #defi #tradfi #proofofreserves

Hector DAO bankruptcy use case: from treasury losses, lawsuit, receivership to bankruptcy filing. The Hector decentralized autonomous organization (#DAO) - the Fantom fork of Olympus DAO - went into receivership in the British Virgin Islands (BVI) last February and is now filing for U.S. bankruptcy. History timeline 📅2021: early investors were allowed to buy the DAO’s token - HEC - at a discount through DAO bonds. The funds raised through this process went into the DAO’s treasury, where each HEC token represented ownership of a portion of the treasury, which could be reinvested to produce yield for DAO participants ("HEC Tokenholders")  📅Jul 2023: The Multichain bridge hack led to a $8mio loss for Hector DAO as some of its treasury assets de-pegged from their Ethereum collateral. The Hector community voted to liquidate its $16 million treasury and distribute the proceeds to HEC Tokenholders by Jan 2024 📅Jan 2024: A hack of $2.7mio further depleted the Hector DAO treasury as the protocol planned to dissolve itself and return assets to HEC Tokenholders 📅Feb 2024: A proceeding was filed against Hector DAO by some HEC Tokenholders. Hector DAO appointed insolvency consultancy firm Interpath to take full custody of the Hector DAO treasury to prepare for subsequent fund distribution Current status Since February, Hector DAO was in #receivership. Unlike #bankruptcy, a receivership isn't a legal action but rather an adjunct solution. The process aims to assist creditors in recovering funds in default and help troubled companies avoid bankruptcy. However, last Monday, Hector DAO filed for U.S. bankruptcy chapter 15 with a view to halting a lawsuit initiated by some HEC Tokenholders in February. The proceeding alleged, among other things, "that Hector DAO failed to fulfil its obligations to HEC Tokenholders and misapplied and/or wasted the Treasury Assets". Behind the scene Hector DAO was anything but decentralized. Beginning in early 2022, five individuals known as “Core 5” managed Hector DAO and the Hector Network. In May 2022, this group decided to form “Hector Enterprises Inc.” in the BVI for the purpose of serving Hector DAO as an intermediary for off-blockchain transactions, such as contracting with service providers, executing investment contracts, and onboarding with exchanges.  But the DAO participants never approved the creation of this corporation; on the contrary, token holders rejected centralization efforts. The corporation also pursued a wide array of services stretching far beyond the stablecoin vision of the protocol.  The use case outlines the concept of a Reference Entity given some degree of centralization within a #DeFi system and highlights key default drivers (hacks, lack of DAO governance and risk management).   https://lnkd.in/eaY4t6jR #cryptodefault #cryptoriskmanagement #digitalcds #cryptocounterpartyrisks #cryptohedgefunds

Default risks in DeFi: From the traditional finance concept of default risks… to the design principles of DeFi Default protection. Typical #DeFi risk models do not address #counterpartydefaultrisks as a standalone risk type, but rather via references to the Principal-Agent problem or systemic risks arising from interconnected networks of smart contracts and other applications. This Hexaven Insights article defines the concept of default risks for DeFi activities and derives design principles for DeFi default protection. 👉 Concept of default in traditional finance 👉 DeFi risk categorizations 👉 Defining default risks in DeFi 👉 Liquidations in DeFi 👉 Design principles of DeFi default protection 💡 The design principles of DeFi default protection leverage #liquidation events — either successful or failed liquidations — as default triggers, with some further characterizations required to determine the types of Reference Entities and impacted agents. https://lnkd.in/e3pbBwJ7 #creditrisks #counterpartydefault #insolvency #digitalcds #tradfi #cryptohedgefunds #defilending #defiderivatives #cryptocurrencies #rwalending #baddebt #failedliquidations

Credit Derivatives Determinations Committees: independent review and market consultation. ISDA has published an independent review on the structure and governance of the Credit Derivatives Determinations Committees (DCs) and launched a market-wide consultation on its recommendations. The recommendations were made by Linklaters under the leadership of Partner Simon Firth following an independent review commissioned by ISDA at the end of last year. The report makes several recommendations on possible changes that could be made to improve the structure of the DCs. Recommendations Main recommendations of the independent review include appointing independent members of the DCs, permitting DC members to refer complex questions to an independent panel by a simple majority vote, establishing a separate governance body to overview the operation of the DCs and requiring the DCs to provide adequate reasons for all material decisions. Market-wide consultation These recommendations are now available on the ISDA website for public consultation, with Boston Consulting Group (BCG) being appointed to oversee the consultation process until July 26, 2024. The proposals for consultation include sections on: 👉 Conflicts of interests 👉 DC composition 👉 Governance 👉 Representation and transparency 👉 Funding Following the results of the consultation, ISDA will work with members to propose specific changes to implement any of the measures that receive broad public support. ISDA will then recommend these solutions to the DCs, which are solely responsible for agreeing and implementing any changes. We will be contributing to the market consultation by sharing insights based on the rules and mechanisms natively encoded in Hexaven’s decentralized default management system. Particularly, we welcome the consultation on the conflicts of interests, in a context where regulators’ concerns and potential breach of required standards could disrupt market confidence in the credit derivative markets. https://lnkd.in/e5AJYRj7 #creditderivatives #cds #digitalcds #cryptodefaults #cryptoriskmanagement #cryptotrading #cryptocurrencies #cryptorisks #cryptohedgefunds #defi #tradfi

FTX new reorganisation plan: happy creditors? FTX debtors' group, which is currently overseeing the bankruptcy process, proposed a new reorganisation plan for a “centralized distribution” for FTX customers and creditors affected by the company’s collapse in Nov 2022. New reorganisation plan Last October, FTX debtor’s group already announced that FTX would return up to 90% of customer funds. This was followed by a January announcement that customers could expect to be paid back in full. The new plan, still to be approved by a Delaware bankruptcy court, aims to give 98% of its creditors at least 118% of allowed claims. Other creditors will receive full repayment and compensation for the time value of their investments. The release stated that FTX monetized an “extraordinarily diverse collection” of assets, most of which were from investments held by Alameda and FTX Venture businesses, or litigation claims. Total value of cash available for distribution was estimated to be between $14.5 billion and $16.3 billion. Claims market dynamics The new reorganisation plan fuelled a claim price increase. Crypto bankruptcy site Xclaim shows that FTX claims are now going around 109%. More volumes on the secondary markets are also expected, as some creditors will try to dispose of their claims due to withholding tax for non-US customers or operational challenges to cash in USD cheques. But in the background, the reorganisation plan is subject to some tensions, mainly between 2 groups: 👉 Distressed asset investors: this group own a significant portion of the docket - a detailed and meticulous record of all the events and filings in a court case - and are supporters of the new plan; 👉 “Crypto activists”: this group favours a plan where creditors should be paid in cryptocurrencies rather than the dollar value of their losses, thus arguing that the debtors would owe FTX customers up to 10 times more than the petition prices. Synthetic default protection Claim strategy In another post, we already wrote about the challenges of solely betting on claims for asset recovery: potential long timeline for recovery; difficult recovery of lost assets (what choice of FX payout?); complex pricing dynamics (jurisdiction dependency, size, “cleaness” of the claim). Although the FTX use case looks rosy, enterprise asset recovery strategy should not solely rely on claim management, but can be completed (if not augmented) by synthetic default protection such as Hexaven contracts. The contracts are designed such that the protection buyer receives a payout upon default without any obligation to deliver the distressed assets/claims, thus not only keeping flexibility for claim management but also mitigating volatility of recovery process. https://lnkd.in/g9TYPw6J #cryptodefault #digitalcds #cryptorisks #cryptoriskmanagement

DeFi lending liquidations: highest volumes since June 2022. Over $136 million has been liquidated on Ethereum lending markets in April, which made the highest volume of on-chain liquidations since June 2022. The bulk of the volumes happened on Aave and Compound, the two major lending markets on Ethereum. However, it is still very far from the liquidations in the futures markets (over $281 million liquidated in bitcoin long positions on Apr13th alone). Liquidation mechanisms Lending markets and margin trading liquidations are two types of liquidations used in the crypto markets. Although operating under slightly different mechanisms, they are based on the similar concept: the collateral posted to initiate a transaction - either to borrow a digital asset or to trade a margin product - is seized and disposed of according to liquidation mechanisms - liquidity collector programs/auctions or liquidity support program. A useful indicator Liquidations generally reflect asset volatilities and downturn in asset prices. The April liquidation spike is in line with what we saw in the digital asset market during that month, with pressures from inflation and geopolitical tensions. Interesting analytics are available to compare the currency breakdown of deposits Vs. borrowed assets on lending protocols, which can give a composite risk outlook based on market price fluctuations. Extreme market scenarios, sometimes marked by de-pegging events and network congestion, combined with potential hacks, could lead to so called “failed liquidations”. Such liquidations are not properly handled by liquidation mechanisms and could lead to “bad debt”. DeFi default assessment Because failed liquidations could result in bad debt creation, liquidation events are considered as good proxy to assess the solvency of a DeFi protocol. Recognising that: i) all failed liquidations do not necessarily lead to bad debt because of the offsetting effects of some protocol-specific safeguard measures (with first and second lines of defence) ii) not all the bad debts are necessarily an indicator of insolvency (e.g. "dust bad debt"), such extreme events can result in asset losses for different agents of the protocol, across borrowers themselves, LPs/lenders, utility token holders. Such losses can be associated with default events, well defined in concept in traditional finance: failure to pay, restructuring, credit deterioration. We will share more on this topic with our next 🚀 Hexaven Insights : "Default Risks in DeFi"🚀. #defi #tradfi #cryptodefaults #cryptoriskmanagement #cryptotrading #cryptocurrencies #cryptorisks #cryptohedgefunds #defirisks #cryptolending

Preview of the credit Determinations committees independent assessment: improving transparency and representativity. A preview of the main findings of the Credit Determinations Committees (DCs) assessment was revealed last week at the ISDA AGM in Tokyo, and was addressed in this Risk.net article. Last December, ISDA launched a review of the structure and governance of the DCs and commissioned Linklaters under the leadership of partner Simon Firth. The big elephant in the room The largest problems which were reported by the industry relate to transparency and representativity of the credit derivatives markets. But the big “elephant in the room” is the long-held conflict-of-interest perception which holds smaller market players and hedge funds back from being more active in the CDS markets. Potential changes ahead Recommendations for potential changes to credit DCs include: 👉 The use of independent members: either used for the toughest decisions only or for all decisions 👉 The creation of a new governance framework: in charge of supervising DC activities, reporting to the market and make rule changes 👉 Improved transparency and representativity around the decision-marking process: supported by a wider market participant participation and a shared-funding mechanism Aiming for efficiency Such recommendations will be assessed based on their efficiency in terms of cost of implementation and rapidity of decision-making process. Should DC operations be funded by all market participants and not only by current DCs representatives, the operational costs need to be cheap for each market participant. Moreover, a wider representativity may come at the cost of a long decision-making process due to lengthy review of arguments and, potentially, counter-arguments. How can digitalization (and blockchain) bring efficiency Digitalization could play an important role to deliver efficiency to support these potential changes: 💡 Digitalization of the project management of the case under review, from representation to DC, reviews, decisions 💡 Rule-based qualification to capture the bulk of “straight-forward” decision (e.g. bankruptcy related events) 💡 Digitalization of the voting mechanism, with incentives and penalties to achieve representativity at low cost and organise delegation to independent committee or expert panels for the toughest decisions Such principles are "encoded" in the decentralized default management system which supports Hexaven's counterparty default marketplace. #creditderivatives #cds #digitalcds #cryptodefaults #cryptoriskmanagement #cryptotrading #cryptocurrencies #cryptorisks #cryptohedgefunds #defi #tradfi