Add Value at Risk and Expected Shortfall to financial

[shuxue6662-a11y]

What changed

Adds two historical-simulation risk metrics to the financial directory:

• value_at_risk.py -- Value at Risk (VaR) using the linearly interpolated quantile of observed returns (NumPy default, type 7). The result is the negative of the return quantile, so it is a positive loss magnitude when the tail contains losses.
• expected_shortfall.py -- Expected Shortfall (ES / CVaR), the average loss beyond the VaR threshold. It captures the severity of tail losses that VaR alone misses and is a coherent risk measure.

Why

The financial directory already covers basic time-series and interest calculations, but it contains no risk measures. VaR and ES are the two most widely used risk metrics in portfolio management and regulatory risk control (for example Basel market-risk rules), and both fit the repository's pure-standard-library style.

Impact

Each module exposes a single, well-documented function that accepts a sequence of portfolio returns and a confidence level:

>>> value_at_risk([-10, -5, -2, 1, 4], 0.95)
9.0
>>> expected_shortfall([-10, -5, -2, 1, 4], 0.75)
7.5

Both functions validate erroneous inputs (empty sequences, non-finite values, and confidence levels outside (0, 1)) and include doctests for valid and invalid cases.

Checks

• python -m doctest financial/value_at_risk.py financial/expected_shortfall.py -- all doctests pass
• ruff check and ruff format --check -- pass
• mypy --ignore-missing-imports financial/value_at_risk.py financial/expected_shortfall.py -- pass
• pre-commit run --files financial/value_at_risk.py financial/expected_shortfall.py -- all hooks pass