Mathematical Models and Loops Used by GliderGPT AI Agents

1. Liquidity Pool Price Impact (Constant Product AMM):

   Plain text: P_new = P_old * (1 - Q_trade / Q_pool)

   Explanation:

   • Q_trade: Trade quantity

   • Q_pool: Total liquidity in the pool

2. Slippage Calculation:

   Plain text: S = ΔP / P_original

   Explanation:

   • ΔP: Change in price

   • P_original: Initial price before the trade

3. Transaction Fee Estimation:

   Plain text: F = V * r

   Explanation:

   • V: Trade volume

   • r: Fee rate (e.g., 0.3% for most DEXs)

4. Net Proceeds from Liquidation:

   Plain text: N = P_sell * Q_sell - F - G

   Explanation:

   • P_sell: Selling price

   • Q_sell: Quantity sold

   • F: Fees

   • G: Gas costs

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Loops for Computation

1. Optimization Loop for Best DEX:

   pythonCopyEditfor dex in available_dexes:
       simulate_trade(dex, asset, trade_amount)
   select_dex_with_highest_proceeds()

2. Trade Size Adjustment to Minimize Slippage:

   pythonCopyEditwhile slippage > threshold:
       reduce_trade_size()
   execute_trade_if_conditions_met()

3. Dynamic ROI Calculations:

   pythonCopyEditfor price_data in real_time_market_data:
       calculate_roi(price_data, fees, gas_costs)