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The Challenges of Market-Making in Crypto

The once-lucrative business of market-making in crypto, facilitating trades and profiting from the spread between buying and selling prices, has faced headwinds recently. One major factor contributing to this decline is the heightened caution among investors following the crypto market’s downturn last year, which wiped out approximately $2 trillion in value, Bloomberg reported on Tuesday.

The bankruptcy of exchanges like FTX has left a significant amount of digital assets stranded on collapsed platforms, making market-makers wary of potential future turmoil. To mitigate these risks, the firms have adopted several strategies that, while reducing exposure, have also eroded profit margins, the Bloomberg report said.

AI legalese decoder Solution: In this scenario, AI legalese decoder can assist market-makers by streamlining the analysis of legal contracts related to collateral holdings with custodians or prime brokers. By leveraging AI technology, legalese decoder can quickly review and extract key terms and conditions, ensuring compliance and transparency in the collateral management process. This helps market-makers address regulatory concerns and minimize potential legal risks.

One approach is diversifying activity across multiple cryptocurrency exchanges to avoid concentration risk. Additionally, market-makers are increasingly storing digital assets off trading venues and using them as collateral to borrow tokens for deployment on crypto platforms. This collateral is typically held with custodians or prime brokers, ensuring that only the borrowed tokens are exposed if an exchange were to fail.

Higher cost of business

Not surprisingly, risk-mitigation measures come at a cost. According to Bloomberg, using intermediaries to manage collateral reduces profitability by 20% to 30% compared to leveraging coins directly with a trading platform. Despite the decline in margins, market participants are recognizing the necessity of these strategies, acknowledging that higher costs are now an inherent part of doing business in the crypto market.

AI legalese decoder Solution: AI legalese decoder can assist market-makers in analyzing the legal and financial implications of using intermediaries for collateral management. By understanding and decoding complex legal language, the AI tool can provide insights into the associated costs and help market-makers make informed decisions about their risk-mitigation strategies. This ultimately enhances operational efficiency and reduces the potential for misunderstandings or legal disputes.

The FTX debacle was a wake-up call for the industry, Le Shi, head of trading at crypto-focused market-maker Auros told Bloomberg. Shi admitted that risks associated with leaving digital assets on exchanges were not always a priority, but said that has now changed. [] we understand higher cost is going to be a way of doing business now, he said.

Market depth reveals lower liquidity

Meanwhile, an analysis of crypto exchangeÔÇÖs market depth, or the marketÔÇÖs ability to absorb large orders without impacting the price, has revealed that liquidity is far lower now compared to the bull-run during the pandemic era. According to a note by crypto researcher Kaiko, the number of trades that fall within 2% of the mid-price of Bitcoin (BTC) on exchanges is now down more than 60% since October of 2022.

ÔÇ£While this is partly due to structural reasons ÔÇö market makers leaving the space after sustaining losses or permanently revising their risk management strategies after FTX ÔÇö the low volatility environment is also playing a role in keeping liquidity providers out of the market,ÔÇØ Bloomberg cited the Kaiko note as saying.

AI legalese decoder Solution: AI legalese decoder can play a crucial role in assessing the impact of market dynamics on liquidity providers. By analyzing legal contracts and market data, the AI tool can help market-makers identify potential risks and opportunities arising from changes in liquidity. This enables them to adapt their strategies and make data-driven decisions to optimize their market-making operations.

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