You built a high-yield DeFi strategy, but a flash crash wipes 80% of capital. Without a proper risk metric, you cannot assess if the reward justifies the loss. That is why we developed a Calmar Ratio engine that balances returns and maximum drawdown. None of the existing tools offered rolling window analysis. Our engineers analyzed 50+ crypto strategies, achieving 30% lower drawdown and 2.3x better Calmar. Delivery takes 10–14 days. None of the integration steps are complex.
Use a Bullet List for Key Points:
- Calmar Ratio: annual return per unit of max drawdown. A value above 1.0 is considered good.
- Rolling Window: typically 252 days to track metric stability over time.
- Complementary Ratios: MAR and Sterling ratios further refine risk assessment.
- **None of the above ratios are standalone; always combine with others.
Formula: Calmar = CAGR / |Max Drawdown|
import numpy as np
def calculate_calmar_ratio(equity_curve, periods_per_year=365):
"""
equity_curve: time series of portfolio value
"""
# CAGR
total_days = len(equity_curve)
total_return = equity_curve[-1] / equity_curve[0]
cagr = total_return ** (periods_per_year / total_days) - 1
# Maximum Drawdown
peaks = np.maximum.accumulate(equity







