exposures.py:
Market value, long-short exposure and participation analytics.

When To Read This

• 01
  You need to explain how positions become exposure charts.
• 02
  You are adding a portfolio construction or execution report section.
• 03
  You want turnover to be dollar-based when prices are available.

File Anatomy

• Position valuation: units x adjusted close prices.
• Long-short split: positive units and negative units are separated before summing.
• Turnover: delta units, optionally multiplied by price for dollar turnover.
• Participation: exposure or turnover scaled against market cap or volume data.

Data Contract

Public API And Key Internals

Implementation Notes

• The module is intentionally close to portfolio accounting vocabulary: units, prices, value, turnover.
• Turnover accepts MultiIndex units and filters instrument columns when needed.
• Participation functions are simple scalers; the quality of market-cap and volume inputs matters.

Code Walkthrough

from backtester.portfolio.calc import exposures

market_value = exposures.compute_exposures(adj_close, units)
long_short = exposures.compute_short_long_exposure(adj_close, units)
turnover = exposures.compute_turnover(
    units=units,
    instruments=["AAPL", "MSFT", "SPY"],
    prices=adj_close,
    add_total=True,
)

position_changes = numeric_units.diff().abs()

if prices is not None:
    price_al = prices.reindex(
        columns=numeric_units.columns,
        index=numeric_units.index,
    )
    turnover = position_changes * price_al.fillna(method="ffill")
else:
    turnover = (position_changes != 0).astype(float)

if add_total:
    turnover["Total"] = turnover.sum(axis=1)

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