Expected Shortfall (ES)

The Expected Shortfall (ES) module provides functionality to calculate the Expected Shortfall, also known as Conditional Value at Risk (CVaR), for financial risk management.

Functions

Usage Example

Here’s an example of how to use the calculate_es function:

import torch
from torchquantlib.core.risk.market_risk.expected_shortfall import calculate_es

# Generate sample returns data
returns = torch.randn(1000)  # 1000 random returns

# Calculate Expected Shortfall at 95% confidence level
es_95 = calculate_es(returns, confidence_level=0.95)

print(f"Expected Shortfall (95% confidence): {es_95.item():.4f}")

# Calculate Expected Shortfall at 99% confidence level
es_99 = calculate_es(returns, confidence_level=0.99)

print(f"Expected Shortfall (99% confidence): {es_99.item():.4f}")

Notes

  • Expected Shortfall is always greater than or equal to Value at Risk (VaR) for the same confidence level.

  • ES provides a more comprehensive view of tail risk compared to VaR.

  • Higher confidence levels result in more conservative (higher) ES estimates.

  • The calculate_es function internally uses the calculate_var function from the VaR module.

See Also

  • var for information on Value at Risk calculation.