Lucre: Early Crypto Trading Algo

 

• Creation: Lucre (LCR) was developed by a team with eight years of algorithmic trading experience. The project was built on the philosophy of “Don’t HODL; Trade!” aiming to generate revenues in all market conditions by actively trading cryptocurrencies rather than just holding them.
• Objective: The primary goal of Lucre was to outperform the strategy of merely holding cryptocurrencies by allowing trading both long and short positions. This was intended to capitalize on market volatility, buying and selling at perceived opportunities.

 

• Trading Algorithm: The Lucre trading algorithm (Algo) was designed to run on the MetaTrader trading platform, which is known for its capabilities in Forex and CFD trading but was adapted here for cryptocurrency markets.
• LCR Token: Participants in the Lucre token sale received the LCR token, which tracked the performance of the trading algorithm. The price of LCR was meant to be updated regularly to reflect accurately the underlying value of the digital assets being traded by the algorithm.
• Market Operations: Initially, the Lucre Trading Algo was in an Alpha stage, trading only the BTCUSD derivative, with plans to include other cryptocurrencies later.

 

• Availability: Lucre (LCR) was not widely traded on known exchange markets, and current data suggests that its trading volume and market cap are minimal or non-existent.
• Current Status: As per the most recent data, Lucre Way (LCR) has a very low price, with significant decreases over recent periods, indicating it has not gained significant traction or sustained value in the cryptocurrency market.

 

• Lack of Adoption: The project did not seem to achieve widespread adoption or recognition within the broader crypto community, which might be due to various reasons including market saturation with similar trading algo projects, lack of trust, or failure to innovate beyond initial concepts.
• Market Fluctuations: The crypto market’s inherent volatility could have impacted Lucre’s strategy, especially if the algorithm did not adapt well to rapid market changes or if it was not robust enough against market manipulations or downturns.