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See it work for your role

Pick your role and run a real workflow on sample data. Sign up to run it on your own.

Try it · Appraisers

Build a valuation in three steps

Start here on a sample item. Sign up to run it on any piece and export a dated, defensible report.

1 Find comps
2 Review value
🔒 Export report
Find comparable sales for
$18,900fair market value · from 18 comparable salesHigh confidence
Comparable saleSold
5513, matching gilt dial, excellent, 2024$19,400
5513, service dial, very good, 2024$17,800
5513, honest wear, original, 2025$18,600
5513, meters-first dial, 2024$21,200
5513, maxi dial, refinished, 2023$16,900

That's 3 of 18 comparables. Sign up to see the full set and export a dated, defensible report.

Sign up to export your report → No commitment · cancel anytime
Try it · Brand Marketers

Benchmark your brand in three steps

Run a sample benchmark. Sign up to track your own brand and export a board-ready chart.

1 Pick a category
2 See the benchmark
🔒 Export chart
Benchmark resale strength in
86%value retention · you lead the categoryLeader
BrandValue retention
Your brand86%
Rival A71%
Rival B63%
Rival C58%
Category average67%

That's a sample. Sign up to benchmark your actual brand and export the board chart.

Sign up to export the chart → No commitment · cancel anytime
Try it · Luxury Sellers

Price your piece in three steps

Value a sample piece. Sign up to value your own and get the best saleroom and timing.

1 Enter a piece
2 See the value
🔒 Full plan
What's it worth?
$32,400median realised · range $28,200–$33,10024 recent sales
Where it soldMedian result
House A$33,100
House B$31,900
House C$30,600
House D$28,900
Online marketplace$27,400

That's a sample. Sign up to value your piece, pick the best saleroom, and time the sale.

Sign up for the full plan → No commitment · cancel anytime
Try it · Collectors

Value your collection in three steps

Value a sample collection. Sign up to track yours and set alerts.

1 Add pieces
2 See the value
🔒 Save & alert
Value this sample collection
$284,600total value · +9.2% YTDLive comps
CategoryValue
Watches (12)$148,000
Jewellery (8)$82,400
Handbags (15)$41,800
Fine art (3)$12,400

That's a sample. Sign up to build your collection, track value over time, and set alerts.

Sign up to save & set alerts → No commitment · cancel anytime
Try it · Wealth Managers

Value a client collection in three steps

Run a sample client valuation. Sign up to manage real clients and send updates.

1 Build collection
2 Value it
🔒 Send update
Value a client collection
$284,600current value · +9.2% YTDComparable sales
HoldingValue
Watches$148,000
Jewellery$82,400
Handbags$41,800
Fine art$12,400

That's a sample. Sign up to manage client collections, allocate, and send branded updates.

Sign up to send the update → No commitment · cancel anytime
Try it · Researchers

Query the dataset in three steps

Preview a sample query. Sign up to run any query and pull the full dataset.

1 Write a query
2 Preview results
🔒 Pull dataset
Sample query
4,105,363rows · 496 houses · 1989–2026USD-normalised
BrandAvg result
Patek Philippe$218,400
Audemars Piguet$96,300
Rolex$41,900
Cartier$28,700
Omega$9,400

That's a preview. Sign up to run any query and pull the full dataset over SQL or bulk export.

Sign up to pull the dataset → No commitment · cancel anytime
Try it · Developers

Call the API in three steps

Run a sample request. Sign up for a key to call it live.

1 Pick an endpoint
2 See the response
🔒 Get a key
Sample request
200 OK142 ms · application/jsonREST · MCP · SQL
FieldValue
lot"Daytona 116500LN"
sold_price32400
currency"USD"
sale_date"2025-03-14"
house"Christie's"

That's one record. Sign up for a key to query 19M+ results over REST, MCP, SQL and bulk export.

Sign up for an API key → No commitment · cancel anytime
Products

Explore ALT/FNDATA

View all →
Who it's for

One dataset, three ways to put it to work

Whether you value and sell, collect and advise, or build and research, the same realized-price data works for your corner of the market.

Market Insights

Value, benchmark and sell on evidence

Defend a valuation with comparable sales, benchmark a brand against its rivals, and time a sale to rising demand.

Passion Investing

Track a collection like a portfolio

Value your holdings, watch the brands and categories you care about, and advise on when to buy or sell.

Data Analytics

Build on the market

Tap 19M+ realized results over REST, MCP, SQL and bulk export for analysis, modelling and AI.

Works with your stack

Use the data where you already work

Query it from your AI assistant, pull it into a notebook or warehouse, drop it into a spreadsheet, or push it to your tools, over MCP, REST, SQL, exports and webhooks.

ClaudeClaude
GeminiGemini
PythonPython
PostgreSQLPostgreSQL
SnowflakeSnowflake
BigQueryBigQuery
Google SheetsSheets
ZapierZapier

Now, you can

Research Faster,
Backtest Smarter,
Strategize Confidently

137+ years of
historical data
95% coverage in secondary markets
8 asset
classes covered
Advanced datasets
and indices

The leading alternative data provider trusted by luxury brands, hedge funds, family offices, and alternative asset managers worldwide

Alternative asset data built for data analysts, quant researchers, and market strategists

The most comprehensive alternative data platform for alternative asset markets. Powerful alternative asset data to help you generate higher investment returns.

SELECT 
    asset_id,
    asset_name,
    asset_type,
    trade_date,
    price,
    volume,
    market_value,
    return_percentage
FROM alternative_assets_market_data
WHERE asset_type = 'private-equity'
    AND trade_date BETWEEN '2024-01-01' AND '2024-12-31'
ORDER BY trade_date DESC;

from datetime import datetime
from typing import Dict, List, Optional
class AlternativeAssetsAPI:
    def __init__(self, api_key: str):
        self.api_key = api_key
        self.base_url = "https://api.altfndata.com/v1"
        self.headers = {
            "Authorization": f"Bearer {api_key}",
            "Content-Type": "application/json"
        }
    def get_market_data(
        self, 
        asset_type: str, 
        start_date: str, 
        end_date: str,
        fields: Optional[List[str]] = None
    ) -> Dict:

// Example: Fetching alternative asset data from ALT/FNDATA API
const API_KEY = 'your_api_key_here';
const BASE_URL = 'https://api.altfndata.com/v1';
async function getAlternativeAssetData(assetType, startDate, endDate) {
  const endpoint = `${BASE_URL}/market-data/${assetType}`;
  const params = new URLSearchParams({
    start_date: startDate,
    end_date: endDate,
    format: 'json'
  });

func (c *AlternativeAssetsClient) GetMarketDataWithFields(assetType, startDate, endDate string, fields []string) (*MarketDataResponse, error) {
	endpoint := fmt.Sprintf("%s/market-data/%s", c.BaseURL, assetType)
	params := url.Values{}
	params.Add("start_date", startDate)
	params.Add("end_date", endDate)
	params.Add("format", "json")
	if len(fields) > 0 {
		for _, field := range fields {
			params.Add("fields", field)
		}
	}
	fullURL := fmt.Sprintf("%s?%s", endpoint, params.Encode())
	req, err := http.NewRequest("GET", fullURL, nil)
	if err != nil {
		return nil, fmt.Errorf("error creating request: %w", err)
	}

/**
 * Client for accessing alternative asset market data API
 */
public class AlternativeAssetsClient {
    private final String apiKey;
    private final String baseUrl;
    private final HttpClient httpClient;
    private final ObjectMapper objectMapper;
    public AlternativeAssetsClient(String apiKey) {
        this.apiKey = apiKey;
        this.baseUrl = "https://api.yourcompany.com/v1";
        this.httpClient = HttpClient.newBuilder()
                .connectTimeout(Duration.ofSeconds(30))
                .build();
        this.objectMapper = new ObjectMapper();
        this.objectMapper.registerModule(new JavaTimeModule());
    }
Made to power your advanced workflows.
SOLUTIONS

Advanced analytics with data access

Connect your favorite data analytics tools directly to our datasets for a streamed workflow.
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Integration iconIntegration iconIntegration iconIntegration iconIntegration iconIntegration icon

Why Leading Firms Choose ALT/FNDATA for Alternative Asset Data

8 asset classes
in one platform

Aircraft
Fine Art
Classic Cars
Jewelry & Gems
Luxury Handbags
Motorcycles
Luxury Watches
Fine Wine
‍

Institutional
Quality

Verified auction, marketplace and direct sale data from over 1,000 sources.

Up to 37 years of historical pricing and sale data

Over 19 million verified transactions from 1988.

Seamless
Integration

Access data with multiple cloud platform integrations through:

FactSet
AWS,
Google Cloud,
APIs,
Excel,
Tableau
‍
...and more.

‍

Alternative Data Built for Investment Professionals

Portfolio Managers

- Backtest allocation strategies
- Risk-adjusted return analysis
- Diversification optimization
- Vintage/brand selection

Quantitative Researchers

- Build factor models
- Correlation analysis
- Systematic strategy development
- Historical performance testing

Brand Strategy Executives

- Competitive market positioning
- Pricing strategy optimisation
- Collector segment analysis
- Product line portfolio analysis

Market Intelligence Teams

- Market share and geographic trend analysis
- Competitor pricing benchmarks
- Secondary market tracking
- Consumer demand forecasting

What Investment Professionals Say

Why professionals choose ALT/FNDATA for alternative data
"The depth of historical pricing data has been essential for our alternative asset allocation models. We can finally backtest luxury collectible strategies with confidence."
— Portfolio Manager, $4.2B Asset Management Firm
"ALT/FNDATA is the only platform with institutional-grade data across watches, cars, art, and wine. It's essential for our multi-asset alternative strategies."
— Chief Investment Officer, Multi-Strategy Hedge Fund
"We use the API to integrate pricing data directly into our portfolio management system. The data quality and coverage is unmatched in the alternative assets space."
— Head of Quantitative Research, Family Office
No items found.

Market Trends

Highlights on recent market activity in the last quarter.
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