Learning Center

How We Match Your Holdings Against Our Risk Model

Before we compute your Risk Index or any charts, we split your portfolio into two buckets:

Matching holdings — Positions whose tickers are in our ERM3 model universe (largest 3000 U.S. listed stocks). These contribute to the Risk Index, factor decomposition, and all graphs.
Everything else — Cash, currencies, or positions not in the universe. These are excluded from the analysis so we can accurately measure factor exposure.

Your dashboard shows "X/Y holdings analyzed" — that's the count of matching holdings (X) out of your total queryable positions (Y). Only the matching portion drives your Risk Index and the risk/return charts.

From here, the ERM3 model deconstructs risk into market, sector, and sub-sector—and you can use it to reveal hidden exposures and build smarter hedges.

This teach-in walks you through core concepts, a simplified visual walkthrough, practical use cases, and answers to common questions. For the full mathematical foundations, see our Technical Wiki.

Core Concepts: L1, L2, L3

Our model uses three levels of factor decomposition. Each level adds another hedge layer, progressively isolating what SPY, XLK, and subsector ETFs explain—and what they don't.

L1: Market Factor

What SPY explains. The broad market moves that affect your stock. Hedge with SPY to neutralize.

L2: Sector Factor

What XLK adds on top of SPY. Sector-specific risk (e.g., tech). Hedge SPY + XLK for finer control.

L3: Sub-sector

What SOXX adds on top of market and sector. The L3 residual (what's left after hedging SPY, XLK, and SOXX) is a proxy for your pure alpha—your unique stock-picking edge.

Visual Walkthrough

Step through the 4-stage decomposition: gross returns → market-hedged → sector-hedged → sub-sector residual. The final sub-sector residual is a proxy for your pure alpha. Charts show cumulative returns and risk breakdown at each step.

Calculating Factors for NVDA...

Configure in Visual Library.

Use Cases

Hedging a concentrated tech position

You hold a large position in a tech stock. Use L2/Sector to see how much XLK explains. Short the right amount of SPY + XLK to neutralize market and sector risk while keeping your stock-specific view.

Analyzing portfolio overlap

Cross-product indexing reveals factor overlaps across stocks and ETFs. Identify hidden concentration when your S&P 500 ETF overlaps heavily with your individual tech picks.

Tax-efficient risk scaling

Scale down sector exposure without selling winners. Use inverse ETF hedges (e.g., short XLK) to reduce tech tilt and avoid triggering capital gains.

Frequently Asked Questions

What is my "Risk Index" and why does it matter?

Your Risk Index is a total risk metric—it measures your portfolio's overall volatility. A score of 100 means your portfolio has the same total risk as the S&P 500 (SPY); above 100 means higher volatility, below 100 means lower. By deconstructing your stocks and ETFs, we reveal your true "Active Exposure"—the parts driven by your unique investing edge. See How the Risk Index is computed for the full methodology.

Is my financial data private?

Absolutely. Your specific portfolio holdings and financial data never reach our servers. We use a "Local-First" architecture where your data from Plaid is combined with our ERM3 risk model directly in your browser. We only see that you have linked an account at a specific institution (e.g., Fidelity or Schwab); we never see or store the actual assets you own.

What does it mean to "Tax-Efficiently Scale" my risk?

Scaling allows you to adjust your market exposure without selling your winners and triggering a capital gains tax event. If your Risk Audit shows you are over-indexed to a specific sector, you can "scale down" that risk by using an inverse ETF hedge. This keeps your capital invested and growing while protecting you from targeted volatility.

Can I access ERM3 via API?

Yes! The ERM3 factor data that powers this site is available via API for developers and institutional clients. Access daily updated factor metrics, decomposition endpoints, and ticker returns data. Visit our API Docs to learn more about authentication, endpoints, and getting started.

How ERM3 Compares to Traditional Risk Models

Traditional models rely on Beta, VaR, or Sharpe. ERM3 adds hierarchical factor decomposition so you see exactly what SPY, XLK, and subsector ETFs explain—and what they don't.

Approach	Metrics	ERM3
Traditional	Beta	Only captures your market risk—misses your additional sector or subsector risks
ERM3	Hedge Ratios, Explained Risk	ERM3 enables measurement of your Risk Index (total risk) with actionable trades (short X% SPY, Y% XLK) to adjust it

For mathematical foundations, see our Technical Wiki.

Glossary

Quick reference. For deeper technical definitions, see the Glossary in our Wiki.

Risk Index

A total risk metric—portfolio volatility. Index 100 = same risk as SPY; above/below = higher/lower volatility. Computed only from holdings in our ERM3 universe. See How the Risk Index is computed for the full methodology.

L1 (Market)

The broadest level: exposure to the overall market (SPY). See L1/L2/L3 in the Wiki.

L2 (Sector)

The sector level: incremental exposure to industry sectors (e.g., XLK for Tech) beyond market. See L1/L2/L3 in the Wiki.

L3 (Subsector)

The subsector level: incremental exposure to narrower industries (e.g., SOXX for semiconductors) beyond market and sector. See L1/L2/L3 in the Wiki.

Hedge Ratio (HR)

Dollars of an ETF to trade per $1 of stock to neutralize a factor. Qualified by level (L1/L2/L3). E.g., L1 HR 0.78 means short 78% of position size in SPY. See Hedge Ratios in the Wiki.

Explained Risk (ER)

Percentage of variance in returns explained by a factor at that level. Qualified by level (L1/L2/L3). Higher ER means the factor drives more volatility. See Explained Risk in the Wiki.

Residual Risk (RR)

The portion of variance not explained by factors at that level—the idiosyncratic remainder. L3 RR is whatever risk remains after market, sector, and subsector. See Variance Decomposition in the Wiki.