How are the 147 compound indexes weighted and maintained?

Each index uses a weighting method appropriate to its asset class. Cryptocurrency indexes typically use market cap weighting that updates in real-time—when Bitcoin's dominance changes, the Top 10 Crypto index reweights automatically. Equity sector indexes use either market cap or revenue weighting depending on the basket (Cloud Infrastructure uses Azure/AWS/GCP revenue splits). Commodity baskets use production volume or futures open interest. Forex aggregates weight by trade volume or export ratios. OmniaChart maintains these indexes by monitoring constituent changes—if a coin drops out of the top 50, the Alt Season Index rebalances. You don't manually update anything; the index reflects current composition at all times.

Can I chart compound indexes against individual assets or only other indexes?

You can chart any index against any instrument in OmniaChart's 12,650+ pairs. Common workflows: DeFi Blue Chips index divided by ETH/USD (shows protocol outperformance vs. base layer), Global M2 index overlaid on gold price (monetary expansion vs. hard asset), Industrial Metals index ratio to S&P 500 (commodity demand vs. equity performance). You can also combine multiple indexes—Emerging Market FX against Commodity Currencies to see risk-on vs. risk-off currency flows. The ratio tools work identically whether you're comparing indexes to single assets or to other baskets, and you can add up to four instruments on one chart for multi-way comparisons.

What historical data depth do the compound indexes provide?

Data depth varies by asset class and constituent availability. Cryptocurrency indexes start in 2013 when sufficient market cap data exists for basket construction (earlier coins like Bitcoin have data from 2010, but multi-coin indexes need multiple constituents). Equity sector indexes extend to 1971 for traditional sectors where component stocks have decades of history; thematic baskets like Cloud Infrastructure start in 2006 when AWS launched. Commodity baskets reach back to 1968 using futures data from CME and LME archives. Real estate aggregates pull from national statistics—some European capital city indexes have annual data from 1950. This depth lets you compare current index readings to historical regimes like 1970s stagflation, the 1997 Asian crisis, or the 2000 dot-com crash for context on whether correlations are structural or temporary.

How do NFT and TCG card indexes calculate floor prices and market caps?

NFT collection indexes aggregate floor prices from OpenSea and Blur, weighted by collection size (10,000-item collection has more weight than 1,000-item). The Blue-Chip NFTs index currently includes CryptoPunks, Bored Ape Yacht Club, Azuki, and others—each weighted by total items × floor price to get market cap contribution. When you chart this index, you see the average floor price (simple mean) and total market cap (sum of all constituent caps). TCG card indexes like Vintage Pokémon PSA 10 use verified sale data from eBay, PWCC, and Goldin Auctions for graded cards—Base Set Charizard, Blastoise, Venusaur PSA 10 prices averaged together, weighted by population reports (fewer PSA 10 Charizards exist than Blastoise, so scarcity affects weighting). Both index types update daily as new floor prices or verified sales get recorded.

147 Compound Indexes: Pre-Built Cross-Asset Benchmarks

What Compound Indexes Actually Do

A compound index aggregates multiple assets into a single trackable metric. Instead of charting Bitcoin, Ethereum, and Solana separately, you chart "Top 3 Crypto by Market Cap" as one line. The value updates based on constituent performance, weighted by your chosen method (market cap, equal weight, or custom).

OmniaChart ships with 147 of these pre-configured. You don't build baskets manually—they're already constructed, tested, and ready to compare against individual assets or other indexes.

Why Pre-Built Indexes Matter for Cross-Asset Analysis

Most platforms force you to create custom watchlists, then manually calculate ratios. If you want to compare the S&P 500 Energy sector against crude oil, you're charting two separate instruments and eyeballing correlation.

Compound indexes solve this by packaging related assets into a single instrument. Now you can:

Chart "Global Central Bank M2" (aggregated money supply from Fed, ECB, BOJ, PBOC) against gold prices
Compare "DeFi Blue Chips" (Uniswap, Aave, Curve weighted by TVL) to Ethereum gas fees
Track "Luxury Goods Equities" (LVMH, Richemont, Hermès) versus Bitcoin as alternative stores of value
Overlay "Top 10 NFT Collections by Floor Price" on ETH/USD to see correlation during bear markets

Each index updates in real-time. When a constituent's market cap changes, the weighting adjusts automatically. You're analyzing baskets, not static snapshots.

The 147 Index Categories

The library breaks into seven groups:

Cryptocurrency Indexes (41 total)

Market cap tiers (Top 10, Top 50, Top 100), sector-specific baskets (Layer 1s, DeFi, GameFi, Meme Coins), and protocol categories (Proof-of-Stake chains, DEX tokens, Lending protocols). One useful example: "Alt Season Index"—the aggregate performance of coins ranked 11-50 by market cap, excluding Bitcoin and Ethereum. When this index outpaces BTC, you're seeing rotation into smaller caps.

Equity Sector Indexes (28 total)

Beyond standard S&P sectors, these include thematic baskets: "Cloud Infrastructure" (Amazon AWS, Microsoft Azure, Google Cloud revenue-weighted), "EV Supply Chain" (lithium miners, battery manufacturers, charging networks), "Defense Contractors" weighted by government contract value. Each basket uses a different weighting schema appropriate to the sector.

Commodity Baskets (19 total)

Precious metals (gold, silver, platinum, palladium as one index), base metals, agricultural staples, energy (crude, natural gas, coal, uranium combined). The "Industrial Metals" index—copper, aluminum, zinc, nickel—often leads equity markets by 3-6 months during expansion cycles. Charting it against the S&P 500 reveals leading/lagging periods.

Forex Aggregates (15 total)

Currency baskets like "Emerging Market FX" (BRL, INR, ZAR, TRY equally weighted) or "Commodity Currencies" (AUD, CAD, NOK weighted by export ratios). The "Dollar Smile Index" measures USD strength against both safe-haven and risk-on currencies—useful for identifying regime shifts.

Fixed Income Composites (12 total)

"Global Sovereign Yields" aggregates 10-year rates from US, Germany, Japan, UK. "Corporate Credit Spreads" combines investment-grade and high-yield spreads across regions. These indexes let you compare bond market stress to equity volatility (VIX) on the same chart.

Real Estate Aggregates (18 total)

28-country real estate data organized into indexes: "Global Tier-1 Cities" (NYC, London, Tokyo, Hong Kong residential prices), "US Sunbelt" (Phoenix, Austin, Nashville, Tampa), "European Capitals" weighted by transaction volume. Track these against mortgage rates or construction material costs.

Alternative Asset Baskets (14 total)

This is where OmniaChart's 15+ asset class coverage shows up. "Blue-Chip NFTs" (CryptoPunks, BAYC, Azuki floor prices), "Vintage Pokémon PSA 10" (Base Set Charizard, Blastoise, Venusaur), "Fine Wine Investment Grade" (Bordeaux First Growths). Each basket uses price data from verified marketplaces—NFT floors from OpenSea/Blur, TCG cards from eBay/PWCC, wine from Liv-ex.

How to Use Indexes for Ratio Analysis

The real power comes from charting indexes against each other or individual assets. Go to app.omniachart.com, select any index from the instrument picker, then add a ratio overlay.

Example workflow: Chart "DeFi Blue Chips" as the base instrument. Add a ratio overlay for ETH/USD. When the ratio trends up, DeFi tokens are outperforming Ethereum—protocol revenue or TVL growth is driving value beyond the base layer. When the ratio falls, Ethereum is capturing more value than its dApps.

Another: "Global M2 Money Supply" (the aggregate index) divided by gold price. This ratio shows how many ounces of gold the world's money supply can buy. Rising ratio = monetary inflation outpacing gold's price appreciation. Falling ratio = gold gaining relative to fiat expansion. Add Bitcoin to the chart for a three-way comparison across 2020-2026.

Custom Weighting vs. Pre-Built: When to Use Each

Pre-built indexes use tested weighting methods—market cap for crypto, revenue for equities, export volume for commodity currencies. They're maintained by OmniaChart as constituent assets change (a coin drops out of Top 10, a stock exits the S&P 500).

You'll want custom baskets when:

Your thesis requires specific weightings (equal-weight the Magnificent 7 instead of market-cap weight)
You're testing a strategy that needs rebalancing control (monthly vs. quarterly)
You're combining assets from different classes into a portfolio simulation

But for 90% of analysis—sector rotation, correlation studies, macro trend tracking—the 147 pre-built indexes cover the use case. You're not guessing at weightings or updating baskets when constituents change.

Data Depth: Indexes Backed by Historical Records

Most index providers start their baskets at recent dates—2015 for crypto indexes, 2000 for thematic equity baskets. OmniaChart's commodity and equity indexes extend back to 1971 (Nixon Shock) where data allows, and some real estate baskets pull from national statistics going to 1950.

This lets you compare current readings to historical regimes. The "Precious Metals" index during the 1970s stagflation period versus 2020-2026. The "Emerging Market FX" basket during the 1997 Asian Financial Crisis versus the 2022 dollar rally. The "Cloud Infrastructure" basket's correlation to Nasdaq during the 2000 dot-com crash versus 2021-2023.

Long-term index data reveals which correlations are structural and which are regime-dependent. A five-year chart shows relationships. A fifty-year chart shows breakdowns.

Sector Market Caps: Index Values You Can Act On

Each index displays current aggregate market cap, 24-hour change, and constituent breakdown. For crypto indexes, this means seeing total DeFi market cap ($127B as of March 2026) versus DeFi Blue Chips index ($89B)—the concentration tells you how much value is in top protocols.

For equity sector indexes, you see total capitalization for "EV Supply Chain" ($890B) versus "Traditional Automakers" ($1.2T). Track the ratio over time. When EV supply chain cap exceeds traditional auto, you've identified a structural shift, not just price momentum.

NFT indexes show aggregate floor price plus total market cap. The "Blue-Chip NFTs" index floor = $47K (average of constituent floors weighted by collection size), market cap = $2.1B. Compare to ETH market cap ($340B) for NFT-to-L1 ratio analysis.

Try Compound Indexes on OmniaChart

Open any of the 147 indexes from the instrument picker. Add a ratio overlay (another index, an individual asset, or a macro indicator like M2). Toggle supply data on crypto indexes to see circulating vs. max supply impact. Export the chart with annotations for your research notes.

Try it on OmniaChart—the indexes are live and ready to chart against any of the 12,650+ curated pairs.