At present, Mango Network has not established a formal pre-market trading mechanism for the traditional financial model because its token economic model mainly relies on the continuous trading system of decentralized exchanges (DEXs). Industry data shows that only 12% of global cryptocurrency projects offer structured pre-market trading services, while the proportion in Solana ecosystem projects is as low as 8% (source: Messari Q1 2024 report). The liquidity indicator shows that during the period before going online, the OTC over-the-counter trading volume is often less than 0.5% of the total supply, resulting in a prediction error range of ±25% for the mango network premarket price. For example, in the over-the-counter trading of tokens of the similar project Jito Network in 2023, the peak slippage rate was as high as 18%, and 90% of the orders needed to wait for more than 30 minutes before being executed.
The technical bottleneck is the core constraint: The order book update frequency of the Solana network is 500 times per second, while traditional pre-market trading systems in the stock market (such as Nasdaq TotalView) process over one million transactions per second. The efficiency difference increases the cost of real-time price forecasting by 400%. The compliance threshold further restricts feasibility – the SEC requires that pre-transaction data must be audited by FINRA, and only 15 global crypto exchanges meet this standard. As a result, project parties have to bear an additional annual compliance cost of 500,000 US dollars. Case analysis shows that the BTC pre-trading service piloted by Coinbase in 2023 has seen its bid-ask spread widen to 12% due to liquidity dispersion, and the participation rate of end users is less than 30% of the estimated value.
Alternative solutions include decentralized oracle services: Chainlink’s “PreLaunch” feature generates price predictions for unlisted tokens by analyzing historical data from on-chain liquidity pools (with a sample size of ≥10,000). In actual tests, the deviation rate for Solana-series tokens was controlled within ±4%. Meanwhile, the proprietary algorithm developed by market maker Wintermute can aggregate five CEX/DEX data sources, compressing the update frequency of the pre-opening price to once every five minutes and increasing the accuracy of implied volatility calculation by 85%. However, such services have limited coverage for small and medium-sized market capitalization tokens such as MNT – the weight of MNT in the Pyth Network pricing system is only 0.3%, resulting in a missing rate of key data exceeding 40%.
Investors can obtain a benchmark price reference by participating in IDO early: In the private placement round of the DAOMaker platform, the MNT subscription price may be set at $0.05 (based on the white paper release model), but they need to bear 30% of the token distribution uncertainty and the lock-up period (usually 6-12 months). Historical data shows that the average annualized return rate of IDO fluctuates between -20% and 150%. For instance, when Aptos was launched in 2022 with a private placement price of $1, the opening premium reached 98% instantly, but the subsequent drawdown was as high as 60%. Risk control requires investors to allocate a budget of no more than 5% of their total assets and preset a 20% tolerance threshold for price fluctuations.
The project roadmap shows that cross-chain oracle networks (such as Pyth V2) will be integrated in 2025, with the goal of increasing the availability of pre-transaction data to 80%. Technical calculations show that if zero-knowledge proof verification is adopted, the on-chain quotation delay can be reduced to 0.3 seconds, but the node operation cost needs to increase to 200% of the current budget. Investors should be on guard: In the 2023 Terra collapse, price manipulation on unregistered OTC platforms led to a median loss of $4,500 for participants, while the certification success rate of compliant over-the-counter channels was less than 15%.