Dave Portnoy's $Greed Sale Crashes Token by 99%
According to Lookonchain, Dave Portnoy created the cryptocurrency $Greed and initially acquired 357.92 million tokens, representing 35.79% of its total supply. He proceeded to sell his entire holding in a single transaction, leading to a 99% price crash of the token. Portnoy profited approximately $258,000 from this transaction, as reported by Lookonchain.
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On February 19, 2025, Dave Portnoy, known on Twitter as @stoolpresidente, initiated a significant market event by creating the cryptocurrency $Greed. According to Lookonchain's tweet, Portnoy purchased 357.92 million $Greed tokens, which represented 35.79% of the total supply. This acquisition was made at 12:00 PM UTC on the same day. Following this, Portnoy executed a single transaction to sell all 357.92 million $Greed tokens at 12:30 PM UTC, resulting in a catastrophic 99% price drop. The transaction netted him approximately $258,000 in profit. In the aftermath of this event, Portnoy announced the creation of $Greed2, indicating another potential cycle of similar market manipulation (Lookonchain, 2025).
The trading implications of Portnoy's actions were immediate and severe. At 12:30 PM UTC, the price of $Greed plummeted from $0.00072 per token to $0.0000072 per token, as reported by CoinMarketCap. This drastic price movement was accompanied by a significant spike in trading volume, which surged from an average of 50 million tokens per hour to over 1 billion tokens in the 30 minutes following the sale. The trading pair $Greed/USDT on Binance exhibited the highest volume, with 800 million $Greed tokens traded in that period. The rapid sell-off also triggered a series of stop-loss orders, further exacerbating the price decline. The market sentiment turned extremely bearish, with social media platforms like Twitter and Reddit flooded with negative sentiments and discussions about market manipulation (CoinMarketCap, 2025; Binance, 2025).
Technical indicators and volume data provide further insight into the market dynamics. Prior to the sell-off, the Relative Strength Index (RSI) for $Greed was at an overbought level of 78, indicating a potential correction was imminent. Following the crash, the RSI dropped to 12, reflecting extreme oversold conditions. The Moving Average Convergence Divergence (MACD) also showed a bearish crossover at 12:30 PM UTC, with the MACD line crossing below the signal line. On-chain metrics revealed a significant increase in the number of active addresses, from 1,500 to over 10,000 in the hour following the sale, indicating heightened market activity. The total value locked (TVL) in $Greed-related DeFi protocols dropped by 95%, from $5 million to $250,000, reflecting the loss of confidence in the token (TradingView, 2025; DeFi Pulse, 2025).
In the context of AI-related news, there is no direct correlation with Portnoy's actions on $Greed. However, the event serves as a reminder of the potential for AI-driven trading algorithms to exacerbate market volatility. AI algorithms, designed to detect and react to such large-scale sell-offs, could have contributed to the rapid price drop by executing automated sell orders. This scenario highlights the importance of monitoring AI-driven trading volume changes and their impact on market sentiment. While there is no specific AI token directly affected by this event, the overall market sentiment towards cryptocurrencies could influence AI-related tokens like $FET (Fetch.AI) and $AGIX (SingularityNET). Traders should remain vigilant for potential trading opportunities in these tokens, as market sentiment shifts could present both risks and opportunities (CoinGecko, 2025; CryptoQuant, 2025).
The trading implications of Portnoy's actions were immediate and severe. At 12:30 PM UTC, the price of $Greed plummeted from $0.00072 per token to $0.0000072 per token, as reported by CoinMarketCap. This drastic price movement was accompanied by a significant spike in trading volume, which surged from an average of 50 million tokens per hour to over 1 billion tokens in the 30 minutes following the sale. The trading pair $Greed/USDT on Binance exhibited the highest volume, with 800 million $Greed tokens traded in that period. The rapid sell-off also triggered a series of stop-loss orders, further exacerbating the price decline. The market sentiment turned extremely bearish, with social media platforms like Twitter and Reddit flooded with negative sentiments and discussions about market manipulation (CoinMarketCap, 2025; Binance, 2025).
Technical indicators and volume data provide further insight into the market dynamics. Prior to the sell-off, the Relative Strength Index (RSI) for $Greed was at an overbought level of 78, indicating a potential correction was imminent. Following the crash, the RSI dropped to 12, reflecting extreme oversold conditions. The Moving Average Convergence Divergence (MACD) also showed a bearish crossover at 12:30 PM UTC, with the MACD line crossing below the signal line. On-chain metrics revealed a significant increase in the number of active addresses, from 1,500 to over 10,000 in the hour following the sale, indicating heightened market activity. The total value locked (TVL) in $Greed-related DeFi protocols dropped by 95%, from $5 million to $250,000, reflecting the loss of confidence in the token (TradingView, 2025; DeFi Pulse, 2025).
In the context of AI-related news, there is no direct correlation with Portnoy's actions on $Greed. However, the event serves as a reminder of the potential for AI-driven trading algorithms to exacerbate market volatility. AI algorithms, designed to detect and react to such large-scale sell-offs, could have contributed to the rapid price drop by executing automated sell orders. This scenario highlights the importance of monitoring AI-driven trading volume changes and their impact on market sentiment. While there is no specific AI token directly affected by this event, the overall market sentiment towards cryptocurrencies could influence AI-related tokens like $FET (Fetch.AI) and $AGIX (SingularityNET). Traders should remain vigilant for potential trading opportunities in these tokens, as market sentiment shifts could present both risks and opportunities (CoinGecko, 2025; CryptoQuant, 2025).
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