Historical pricing

Historical pricing evaluates a trade against a sequence of recorded markets. The Excel workflow uses the same native snapshot archive and selection rules as Python. Each snapshot records the observations and construction inputs for one market instant.

Load the XLL before opening the example workbook, then press Ctrl+Alt+F9 to reconstruct its objects. Regenerate both Excel examples with python tools/excel/examples/create_examples.py after installing bindings/excel/examples/requirements.txt. The historical workbook uses explicit zero rates; the same snapshot workflow accepts bootstrapped markets, volatility, FX, simulation, and model configurations.

Capture each market

Build a separate context for each market reference date with the usual QS.QUOTES.*, curve configurations, and QS.CONTEXT.CREATE. Give every constructor a workbook-unique name. Store the context handles in B12 and C12, and capture their observations:

B13 =QS.SNAPSHOT.FROM.CONTEXT("history_snapshot_20260115","2026-01-15T16:00:00Z",B12)
C13 =QS.SNAPSHOT.FROM.CONTEXT("history_snapshot_20260116","2026-01-16T16:00:00Z",C12)
B15 =QS.SNAPSHOTS.CREATE("history_archive",B13:C13)

The archive is reconstructed from the full range. Changes to market inputs advance snapshot and archive handles; deleting a row removes that observation. Blank range cells are skipped. Duplicate instants, including equivalent timezone offsets, are errors. A missing or blank scalar input creates an empty archive. Unchanged recalculation reuses current handles without reconstructing markets.

Each snapshot contains one complete set of native construction inputs. To use curves already supplied as zero rates in a sheet, place ISO date text or tenor text in A5:A7 and annual decimal rates in B5:B7:

B10 =QS.CURVE.CONFIGS.CREATE("history_curves_20260115")
B11 =QS.CURVE.CONFIGS.ADD.ZERO(B10,"SOFR","Actual365","Linear",FALSE,A5:A7,B5:B7,"Continuous","Annual")

Pass B11 as the curve configurations when creating the context. The pillar and rate ranges must have equal counts; rates must be finite numbers. Pillars must resolve in increasing date order. Composite construction is also available:

=QS.CURVE.CONFIGS.ADD.COMPOSITE(configurations,"TermSOFR6m","SOFR","TermSOFR3m")

The two component curves must be configured in the same market. Direct QS.CURVE.FLAT / constructed-element objects are runtime values and cannot be captured. An explicit zero curve with one 0D pillar and extrapolation enabled provides serializable flat-curve construction inputs.

Select and price

Keep the trade handle in B17. Create one selector/context pair for each requested timestamp and reuse the same trade:

B20 =QS.SNAPSHOT.SELECTOR("history_selector_20260115","2026-01-15T16:00:00Z","Exact","Mid")
B21 =QS.CONTEXT.FROM.SNAPSHOT("history_selected_20260115",$B$15,B20,)
B22 =QS.CONTEXT.SNAPSHOT.TIMESTAMP(B21)
B23 =QS.CONTEXT.EVALUATION.DATE(B21)
B31 =QS.DISCOUNT.POLICY.CSA("history_policy","USD","SOFR")
B32 =QS.PRICER.CREATE("history_pricer","DiscountedCashflowPricer",B31)
B33 =QS.EVALUATE("history_results",B32,$B$17,B21,"Value")
B24 =QS.RESULT.VALUE(B33)

The optional fourth context argument is a FixingStore handle. Fixings are supplied separately, without publication-vintage filtering. Use the correct historical fixing dataset when publication times or revisions affect a result.

The default quote side is Mid; Bid and Ask rebuild quoted construction and calibration inputs at that side. A consumed missing side raises an error. FX spots are side-independent; zero-rate quotes use the selected level.

Selection preserves the matched snapshot’s market reference date as the valuation date. Requesting Monday with Previous and matching Friday prices at Friday’s market date; it does not roll curves to Monday. The observation instant and market business date are distinct, including across UTC midnight. Inspect both context properties when displaying historical results.

QS.SNAPSHOTS.SELECT(name,store,selector) returns the matched snapshot handle without constructing a context. Inspect it with QS.SNAPSHOT.TIMESTAMP and QS.SNAPSHOT.REFERENCE.DATE. QS.SNAPSHOTS.TIMESTAMPS(store) lists available instants, while QS.CONTEXT.QUOTE.LEVEL(context) reports the construction side. QS.DATETIME.PARSE normalizes offset-aware timestamp text to UTC; QS.DATETIME.DATE returns its UTC calendar day. Neither accepts naive timestamps or Excel serial datetimes.

Python and Rust interoperability

QS.SNAPSHOTS.FROM.JSON(name,json_text) imports the same native snapshot-array schema saved by Python’s MarketSnapshotStore.to_json. QS.SNAPSHOTS.TO.JSON(store) returns JSON text, excluding fixing histories, constructed curves, and AD state. These functions exchange JSON as worksheet text. Export fails above Excel’s 32767 UTF-16-unit cell limit.

The archive captures base market configurations. Materialized scenario contexts with supplied runtime elements are rejected; capture the original base context. The workbook chapter relates these handles to ordinary valuation and recalculation. The worksheet reference provides exact argument lists.