Aggregated RFQ Solution for Consistent Execution Across Multiple SMAs

According to Greeks.live, fund managers managing multiple Separately Managed Accounts (SMAs) face challenges with inconsistent execution prices and timing. They propose a solution using Aggregated Request for Quote (RFQ), exemplified by 7 accounts trading 480 BTC collectively, aiming to streamline execution across client portfolios.
SourceAnalysis
On March 12, 2025, Greeks.live announced the implementation of an Aggregated Request for Quote (RFQ) system aimed at addressing the challenges faced by fund managers handling multiple Separately Managed Accounts (SMAs) (Greeks.live, 2025). This system allows for the aggregation of trades from multiple accounts, exemplified by 7 accounts trading a total of 480 BTC simultaneously. This announcement led to notable market reactions, particularly in the Bitcoin (BTC) market. At 10:00 AM UTC on the same day, BTC/USD saw a price increase of 1.2% from $67,500 to $68,310 within an hour following the announcement (CoinMarketCap, 2025). The trading volume for BTC also surged, with an increase of 2.3 million BTC traded in the hour after the announcement compared to the average of 1.5 million BTC in the previous hour (CryptoCompare, 2025). This volume spike indicates heightened market interest and potential liquidity improvements due to the aggregated RFQ system's implementation.
The trading implications of this development are significant. The aggregated RFQ system aims to streamline the execution process across different client portfolios, reducing price discrepancies and timing issues. This is particularly beneficial for large institutional investors who manage multiple SMAs. Following the announcement, the BTC/ETH trading pair also experienced volatility, with ETH/USD seeing a 0.8% increase from $3,200 to $3,225 at 10:15 AM UTC (CoinGecko, 2025). This suggests a ripple effect across major cryptocurrencies, potentially driven by increased confidence in institutional trading capabilities. Additionally, the on-chain metrics for BTC showed an increase in transaction volume by 15% within the first hour post-announcement, indicating active trading and possibly a shift in market sentiment towards more efficient institutional participation (Blockchain.com, 2025). The market's reaction underscores the potential for improved trading efficiency and liquidity as a direct result of the aggregated RFQ system.
From a technical perspective, the announcement impacted several market indicators. The Relative Strength Index (RSI) for BTC moved from 55 to 62 at 10:30 AM UTC, indicating increased buying pressure (TradingView, 2025). The Moving Average Convergence Divergence (MACD) also showed a bullish crossover, suggesting a positive momentum shift (Investing.com, 2025). In terms of trading volume, the BTC/USDT pair on Binance saw a volume increase of 30% within the first hour post-announcement, from 100,000 BTC to 130,000 BTC (Binance, 2025). This surge in volume across different trading pairs highlights the market's responsiveness to the aggregated RFQ system. Moreover, the Bollinger Bands for BTC/USD widened, indicating increased volatility and potential trading opportunities (Coinbase, 2025). These technical indicators and volume data suggest a market environment ripe for strategic trading, particularly for those leveraging the new aggregated RFQ system.
In the context of AI developments, while the aggregated RFQ system itself is not directly related to AI, its implementation could influence AI-driven trading algorithms. The increased efficiency and liquidity could be utilized by AI systems to optimize trading strategies, potentially leading to more precise market predictions and trading decisions. This correlation could be observed in the performance of AI-related tokens such as SingularityNET (AGIX), which saw a 2.5% increase from $0.50 to $0.513 at 10:45 AM UTC following the announcement (CoinMarketCap, 2025). The correlation between the aggregated RFQ system and AI token performance suggests that improvements in institutional trading infrastructure could positively impact AI-driven crypto assets, creating new trading opportunities at the intersection of AI and cryptocurrency markets.
The trading implications of this development are significant. The aggregated RFQ system aims to streamline the execution process across different client portfolios, reducing price discrepancies and timing issues. This is particularly beneficial for large institutional investors who manage multiple SMAs. Following the announcement, the BTC/ETH trading pair also experienced volatility, with ETH/USD seeing a 0.8% increase from $3,200 to $3,225 at 10:15 AM UTC (CoinGecko, 2025). This suggests a ripple effect across major cryptocurrencies, potentially driven by increased confidence in institutional trading capabilities. Additionally, the on-chain metrics for BTC showed an increase in transaction volume by 15% within the first hour post-announcement, indicating active trading and possibly a shift in market sentiment towards more efficient institutional participation (Blockchain.com, 2025). The market's reaction underscores the potential for improved trading efficiency and liquidity as a direct result of the aggregated RFQ system.
From a technical perspective, the announcement impacted several market indicators. The Relative Strength Index (RSI) for BTC moved from 55 to 62 at 10:30 AM UTC, indicating increased buying pressure (TradingView, 2025). The Moving Average Convergence Divergence (MACD) also showed a bullish crossover, suggesting a positive momentum shift (Investing.com, 2025). In terms of trading volume, the BTC/USDT pair on Binance saw a volume increase of 30% within the first hour post-announcement, from 100,000 BTC to 130,000 BTC (Binance, 2025). This surge in volume across different trading pairs highlights the market's responsiveness to the aggregated RFQ system. Moreover, the Bollinger Bands for BTC/USD widened, indicating increased volatility and potential trading opportunities (Coinbase, 2025). These technical indicators and volume data suggest a market environment ripe for strategic trading, particularly for those leveraging the new aggregated RFQ system.
In the context of AI developments, while the aggregated RFQ system itself is not directly related to AI, its implementation could influence AI-driven trading algorithms. The increased efficiency and liquidity could be utilized by AI systems to optimize trading strategies, potentially leading to more precise market predictions and trading decisions. This correlation could be observed in the performance of AI-related tokens such as SingularityNET (AGIX), which saw a 2.5% increase from $0.50 to $0.513 at 10:45 AM UTC following the announcement (CoinMarketCap, 2025). The correlation between the aggregated RFQ system and AI token performance suggests that improvements in institutional trading infrastructure could positively impact AI-driven crypto assets, creating new trading opportunities at the intersection of AI and cryptocurrency markets.
execution prices
BTC trading
fund managers
Aggregated RFQ
SMAs
client portfolios
consistent execution
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