To determine the optimal stop loss (SL) and take profit (TP) levels for your leveraged crypto trades, follow this structured approach:

### Key Variables:
- **Current Setup**: TP = SL = 20% price movement.
- **Leverage Impact**: Profit/Loss = Leverage × Price Movement (%).
- **Historical Data**: 90 wins, 51 losses (63.83% win rate).

### Formula for Expected Value (EV):
\[
\text{EV} = (\text{Win Rate} \times \text{TP}) - (\text{Loss Rate} \times \text{SL})
\]
Goal: Maximize EV by optimizing TP and SL.

### Steps to Optimize:
1. **Model Win Rate Dependency**:
   - If historical price data is available, calculate how often price movements would hit different TP/SL thresholds.
   - Assume a stochastic model (e.g., Brownian motion with drift) to estimate win probabilities for varying TP/SL.

2. **Kelly Criterion for Risk-Reward Ratio**:
   - Optimal risk-reward ratio \( b = \frac{\text{TP}}{\text{SL}} \) balances growth:
   \[
   b > \frac{1 - \text{Win Rate}}{\text{Win Rate}} \approx 0.566 \quad (\text{for your 63.83% win rate}).
   \]
   - Example: If \( \text{SL} = 15\% \), set \( \text{TP} > 8.5\% \) (but backtest to validate win rate changes).

3. **Backtesting**:
   - Adjust TP/SL levels in historical data to see how many trades would have hit new thresholds.
   - Compute EV for each combination to find the maximum.

### Practical Recommendation:
- **Experiment with Ratios**: Start with a risk-reward ratio > 0.566 (e.g., TP:SL = 1.5:1) and adjust based on observed performance.
- **Conservative Adjustment**: Gradually widen TP and tighten SL while monitoring the win rate to ensure it stays profitable.

### Example Calculation:
If you set \( \text{TP} = 30\% \) and \( \text{SL} = 15\% \), and assume the win rate drops to 50%:
\[
\text{EV} = (0.5 \times 0.3) - (0.5 \times 0.15) = 0.075 \ (\text{7.5% per trade}),
\]
which is higher than your current 5.53%.

### Final Answer:
The **optimal stop loss and take profit** depend on how adjusting these levels affects your win rate. Based on your current 63.83% win rate at a 1:1 ratio, consider testing a **risk-reward ratio of 2:1** (e.g., TP = 24%, SL = 12%) to maximize expected value. Use backtesting or incremental adjustments to refine further. 

**Formula for Optimization**:
\[
\boxed{\text{Optimal TP/SL} = \arg\max_{TP, SL} \left[ (\text{Win Rate} \times TP) - ((1 - \text{Win Rate}) \times SL) \right]}
\]

**Action Steps**:
1. Backtest historical trades with varying TP/SL.
2. Use the Kelly Criterion to guide risk-reward ratios.
3. Gradually adjust levels while monitoring performance.