Residual Value Studio

Future value and risk scenarios

Residual Value Studio builds on Price Report and turns current market value into residual value scenarios, comparable market evidence, mileage assumptions and market timing. Audit-ready logic explains future value, risk and commercial decisions for pricing, buying, leasing and remarketing.

Explore decision workflows See calculation logic View auditability layer

Residual Value Studio

DEMO

BMW 320d Touring

6m12m24m36m

Current retail value€29,904Future value ratio93.4 %Future retail value€27,925

Evidence mix70 / 21 / 9 %

Confidence

Why future value is harder

Beyond depreciation

Residual value is not driven by depreciation alone. Mileage, market timing, supply, regulation and brand strength all shape how the value develops.

Thin evidence

For many segments, identical historical vehicles are rare. The model uses the closest comparable vehicles and shows what the estimate is based on.

Defensible logic

RV decisions must stand up to risk teams, leasing and CFO review. Every assumption needs traceable logic, not just expert judgement.

Risk scenarios

One number is not enough for risk management. P10/P50/P90 ranges show the base case, upside and possible downside of future value.

The future value ratio explains future value instead of just predicting it

Current retail value

€29,904

×Future value ratio

93.4 %

=Future retail value

€27,925

Evidence split for the demo BMW 320d Touring 2022

Future value ratio ingredients

01Same-model depreciation
02Comparable-model depreciation
03Segment fallback
04Market timing adjustment
05Optional scenario overlays

Decision workflows powered by Residual Value Studio

Price / reprice stock car

Combine current retail value with forward-looking RV to set a defensible asking price.

Max acquisition price

Work back from target gross margin and residual to a hard buy ceiling per vehicle.

Customer contract RV

Set the residual line in leasing offers using P50 with downside-aware P10/P90 ranges.

Guaranteed residual / buyback

Quantify the risk in guaranteed buyback programmes with scenario-aware reserves.

New model / cold-start

Blend segment fallback with brand maturity overlays where same-model history is thin.

Market timing

Decide whether to hold, list now or wait based on supply, sold-price and sell-through indexes.

Transparent evidence blend

Comparable	Why selected	Same fuel	Body match	Power distance	Layer weight	Effective contribution	12m ratio	Removal impact	Include / exclude
BMW 320d Touring · 2021	same gen + body	Yes	Match	0 kW	0.42	0.295	93.8 %	−0.3 %	Include
BMW 320d Sedan · 2020	same model, sedan	Yes	Close	0 kW	0.21	0.142	93.1 %	−0.1 %	Include
BMW 330d Touring · 2021	model-comparable	Yes	Match	25 kW	0.18	0.119	92.5 %	+0.05 %	Include
Audi A4 Avant 35 TDI · 2020	segment fallback	Yes	Match	5 kW	0.09	0.060	91.4 %	+0.2 %	Exclude

Methodology

Each comparable is weighted by recency, body/fuel match and power distance, then contributes to the future value ratio in proportion to its layer weight. Excluded rows do not affect the ratio.

Market timing indexes

Ask Price Index

102

Sold Price Index

−3

Listed Supply Index

113

+13

Sold Volume Index

−9

Sell-through Index

−11

Baseline 100. Next 6 months projected from the previous 12-month pattern.

RecommendationWatch / Price risk

Sold prices are below baseline while listed supply is increasing.

Macro & assumptions overlay

Six market-level layers nudge the base future value ratio up or down — compounded they turn one base curve into a scenario you can defend.

Macro layersDemo scenario · BMW 320d Touring 2022

Supply crowdingVolume of similar cars expected on the market at the horizon

×0.97

Macro-credit stressInterest rates and financing appetite shaping used-car demand

×0.99

Policy & fleet pipelineRegulation and fleet de-fleeting volumes in the pipeline

×1.01

Energy & trade shockFuel and energy prices shifting total cost of ownership

×0.98

Brand maturityPricing power of the brand as the model generation matures

×1.02

Battery transparencyBattery health disclosure for EVs — neutral for combustion cars

×1.00

RV Scenario = RV Base × Supply × Macro-Credit × Policy × Energy × Brand × Battery

Scenario resultBelow P50

RV base ratio

93.4 %

×Macro overlay

0.970

=RV scenario ratio

90.6 %

Compounded from six demo layers

Scenario future value€27,079−€846 vs base scenario

Methodology

Each macro layer is a multiplicative correction relative to a neutral 1.00. The layers compound into one overlay factor (×0.970 in the demo) that scales the base future value ratio, and the resulting scenario is read against the P10/P50/P90 band to keep decisions downside-aware.

Mileage scenario

Formula

Km at return = Current km + km/month × forecast horizon

Adjust the residual for above- or below-average usage. Low / Standard / High presets cover most leasing books; custom overrides are supported.

Demo scenarios

Low14 000 km/yr125 800 km

Standard20 000 km/yr145 300 km

High28 000 km/yr170 800 km

Auditability ledger

Net Residual Value at Return

Demo ledger

Future Retail Value€27,925

Post-return Costs−€3,527

Demo result€24,398

Demo ledger entry · audit-ready export

How Residual Value Studio is built

Raw market data / parquetListings and sale records normalized into columnar parquet storage
Precompute pipelineCurves, comparable weights and indices computed ahead of time
Vehicle artifactsOne self-contained valuation artifact per vehicle and horizon
Valuation ledgerEvery assumption and correction recorded as a traceable entry
Chart seriesReady-to-render series for residual curves, bands and indices
Frontend explorerThe studio reads precomputed artifacts — no live model calls

Roadmap

01Real-data prototype
02Decision scenarios
03Comparable blend lab
04Macro & assumptions overlay
05Production API

01Real-data prototype
02Decision scenarios
03Comparable blend lab
04Macro & assumptions overlay
05Production API

Bring residual value into your decisioning

Move from a single RV number to scenario-aware, audit-ready residual value decisions.

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