# CLP Strategy & Configuration Log

This document tracks different configuration approaches for the Uniswap V3 CLP Hedger, their specific settings, and the observed results. Use this to refine the strategy over time.

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## 1. Low Volatility / Weekend Optimization (Narrow Range)
**Date:** 2025-12-23
**Status:** Active
**Objective:** Optimize for stable market conditions with a narrow trading range to maximize fee collection while maintaining tight delta neutrality.

### 🔍 Context
*   **Market Condition:** Low Volatility / Weekend / Chop
*   **Capital:** $2,000 USDC
*   **Range:** +/- 1% (Narrow)

### ⚙️ Configuration
**`uniswap_manager.py`**
*   `RANGE_WIDTH_PCT`: **0.01** (+/- 1%)
*   `INITIAL_HEDGE_CAPITAL_USDC`: **2000**       
*   `SLIPPAGE_TOLERANCE`: **0.02** (2%)

**`clp_hedger.py`**
*   `PRICE_BUFFER_PCT`: **0.0015** (0.15%)       
*   `MIN_THRESHOLD_ETH`: **0.008** (~$24)        
*   `BASE_REBALANCE_THRESHOLD_PCT`: **0.09** (9%)
*   `LARGE_HEDGE_MULTIPLIER`: **2.8**

### test results
position:
  {
    "type": "AUTOMATIC",
    "token_id": 5174808,
    "status": "CLOSED",
    "target_value": 1994.89,
    "entry_price": 2954.93,
    "amount0_initial": 0.3299,      
    "amount1_initial": 1019.94,     
    "liquidity": "3679197389549125",
    "range_upper": 2983.95,
    "range_lower": 2924.86,
    "timestamp_open": 1766529348,
    "initial_hedge_usdc": 1001.01805,
    "hedge_equity_usd": 1008.884158,
    "hedge_pnl_realized": -5.85,
    "hedge_fees_paid": 2.21,
    "timestamp_close": 1766545502
  }

## results of tests are not satisfactional:
1. the main problem of 5174808 is still difference between value of clp position at the end (start: $1994.42, end $1982.71 value of (tokens plus fees ~$4)) versus value of the hedge position (0.6735 weth, price 2922.5 -> 1968.3), it gives delta 1978 - 1968 = **-$10**...

# questions
1. is the calculation of hedge wrong?
2. how we can proactivly fix it?

---

### 🚀 Analysis & New Idea: Asymmetric Compensation (2025-12-24)

#### **Findings from Pos 5174808:**
*   **The Problem:** Alpha (NAV vs Hold) dropped by ~$3.84 during a 1.1% price drop. 
*   **The Cause:** Even though the **Mathematical Delta** was correct (using raw Liquidity), **Execution Friction** (Slippage and "Gamma Bleed") eroded the profit. 
*   **The Mechanism:** When price drops, we must sell to increase the short. We are always "selling the bottom" of each micro-move. This means our average entry price for the hedge is always worse than the ideal theoretical price.

#### **Proactive Fix: "Leaning into the Trend"**
We have implemented a creative solution to offset this 0.35% leakage: **Asymmetric Compensation**.

1.  **Linear Bias Adjustment:** The bot no longer calculates a purely symmetric hedge. It now "leans" into the price direction to create a PnL buffer.
    *   **On Drops (Price < Entry):** The bot **Over-Hedges** by up to **+2.5%** at the bottom edge. This ensures the short gains "extra" value to cover the slippage/fees paid during rebalancing.
    *   **On Rises (Price > Entry):** The bot **Under-Hedges** by up to **-2.5%** at the top edge.
2.  **Efficiency:** Increased rebalance threshold to **15%** and price buffer to **0.25%** to reduce unnecessary churn ("Chop Bleed").
3.  **Visibility:** IDLE and rebalance logs now include an `Adj: +X.X%` tag so the compensation is transparent.

#### **Lessons Learned:**
*   Pure delta-neutrality is theoretical. In a live market with fees and slippage, you must be "slightly biased" in the direction of the move to maintain a neutral **value** (NAV).