Sources: FIPE & FENABRAVE
Distributed by AltData Systems
01
Average MoM Change
Month-over-month FIPE price variation by model-year bucket,
highlighting new vehicles and recent used cohorts.
1.1
New Vehicles (0km)
1.2
Used Vehicles — Average 2026/2025/2024
Simple average of the month-over-month price variation across model years
2026, 2025, 2024. Each model year contributes equally to the aggregate figure shown below.
1.2.1
Model Year 2026
1.2.2
Model Year 2025
1.2.3
Model Year 2024
02
Rental Company Indicators
Price premium/discount monitoring for Localiza and Movida versus FIPE
and fleet depreciation dynamics.
2.1
Price Premium vs. FIPE — Localiza & Movida
2.2
Depreciation by Rental Company
03
Depreciation Curves by Model Year
Cumulative price index relative to initial value, with simple average
and FENABRAVE volume-weighted views.
3.1
Simple Average
3.2
Weighted Average (FENABRAVE)
04
Model-Year Impact Snapshot
Latest available month performance by model-year bucket.
The "Used" column reflects the average across 2026, 2025, 2024.
05
Chinese Brands
Monitoring Chinese brand and model share within new vehicles (retail)
based on FENABRAVE data.
The information contained in this report is generated automatically from public sources (FIPE and FENABRAVE)
and from proprietary processing by AltData Systems Ltd. This report is intended exclusively for authorized
subscribers and may not be reproduced, distributed, or shared without prior written consent from AltData.
The data and analyses presented herein are strictly informational in nature and do not constitute investment
advice, nor an offer or solicitation to buy or sell any financial asset or property. AltData assumes no
liability for decisions made based on the information contained in this report.
Historical series reflect prices published by the Fundação Instituto de Pesquisas Econômicas (FIPE) and
vehicle registration data from the Federação Nacional da Distribuição de Veículos Automotores (FENABRAVE).
Methodological changes in these sources may affect intertemporal comparisons. AltData does not guarantee the
completeness or accuracy of the underlying data.
