CVA, DVA and FVA

Aggregators (src/xva/aggregator.rs) consume the netted NpvCube of a netting set and produce a single number plus AD adjoints. Each implements name() -> &'static str ("CVA", "DVA", "FVA").

Definitions

Let \(V_k^p\) be the netted NPV on path \(p\) at grid date \(t_k\), \(n\) the number of paths, \(P(0,t_k)\) the system discount factor, and

\[ \text{EPE}_k=\frac1n\sum_p \max(V_k^p,0),\qquad \text{ENE}_k=\frac1n\sum_p \min(V_k^p,0). \]

Aggregator	Formula	Inputs
`CvaAggregator { lgd, ... }`	\(\text{CVA}=\text{LGD}\sumk P(0,t_k)\,\text{EPE}_k\,[S(t{k-1})-S(t_k)]\)	counterparty survival \(S\); LGD \(=1-\text{recovery}\)
`DvaAggregator`	\(\text{DVA}=\text{LGD}{own}\sum_k P(0,t_k)\,(-\text{ENE}_k)\,[S{own}(t{k-1})-S{own}(t_k)]\)	own survival curve
`FvaAggregator`	\(\text{FVA}=\sum_k P(0,t_k)\,\text{EPE}_k\,s_f(t_k)\,\Delta t_k\)	funding spread \(s_f\) (flat, term structure or from a funding curve)

Survival with a flat spread is \(S(t)=e^{-\lambda t}\) with \(\lambda=\)credit_spread; with credit_index it is interpolated from the bootstrapped credit curve pillars (CreditCurveCvaFactory). Positive exposure is taken after netting, so the collateral policy and FX conversion applied in the exposure evaluator directly affect these values.

Factories

PfeAggregatorFactory implementations create one aggregator per netting set:

Factory	Fields
`CvaFactory`	`credit_spread`, `recovery`, `n_paths`, `system_dfs`
`CreditCurveCvaFactory`	`pillar_dates`, `pillar_survivals`, `pillar_labels`, `recovery`, `n_paths`, `day_counter`, `system_dfs`
`FvaFactory`	flat `funding_spread`
`FundingCurveFvaFactory`	dated spreads (from `funding_spread_curve` or `funding_index` minus the system curve)
`DvaFactory`	own-credit inputs; not wired by `XvaEngine::run`, use it directly with `AggregatorBundle`

Reading results

let result = engine.run(&mut netting_sets)?;
for v in result.xva_values.iter().flatten() {
    println!("{:<10} {:<4} {:>14.2}", v.netting_set, v.measure, v.value);
}

cargo run -p cva output shape:

netting_set  measure  value
CLIENT_A     CVA      12345.67
CLIENT_A     FVA       4567.89

Credit curves for CVA

Bootstrapped from CDS quotes with a CurveConfiguration whose market_index is {"Credit": "CLIENT_A"} and quotes like Cds_USD_CLIENT_A_1Y; the bootstrapper solves piecewise-constant hazard rates by bisection (see Curve Bootstrapping). Set credit_index in CsaTerms to use it, and the CVA sensitivities then include one entry per credit pillar.

Exposure metrics

NpvCube::epe(), ene(), ee() return per-date vectors; PfeAggregator gives the quantile profile used for limit monitoring (examples/pfe). These are available in result.cubes regardless of CSA fields.