Asset Analyzer

Use Asset Analyzer to inspect one asset or compare a small set of tickers before using them in a portfolio. The tool focuses on return, risk, drawdown, correlation, and contribution-timing behavior.

1. Enter a ticker such as SPY and select it from the search results.
2. Start in Summary to review CAGR, volatility, Sharpe ratio, and max drawdown.
3. Open Correlations & Beta when the question is about overlap with other assets.
4. Open Rolling Metrics to inspect whether the asset behaved consistently across time.
5. Use Returns and Risk vs Return for distribution and cross-asset comparisons.
6. Use DCA vs Lump Sum, Best DCA Day, and ATH Proximity when the question is about entry path, contribution timing, or recovery behavior.
7. Open the PCA tab to run principal component analysis on the same tickers and date range. Choose a return frequency and matrix mode, then inspect explained variance and component loadings.

• Enter SPY with the default full-history date range.
• In Summary, review CAGR, volatility, Sharpe ratio, and max drawdown together rather than relying on one metric.
• In Correlations & Beta, add BND to inspect diversification behavior over the same sample.
• In Rolling Metrics, use a 5-year window to compare the full-period average against rolling outcomes.

Enter a ticker and choose a date range. The tool then loads the available views for that asset and sample window.

Use Save Analysis to store the current inputs and result snapshot. Saved analyses appear in Workspace and reopen in Asset Analyzer with the same configuration, and preserve the selected date range, price mode, and risk-free settings used in the run.

Summary shows current price, total return, CAGR, standard deviation, max drawdown, and other headline risk metrics.

Use Sharpe ratio, drawdown, and volatility together. No single metric is sufficient on its own.

This view compares how assets moved relative to each other over the selected sample. Add multiple tickers to inspect overlap and beta in the same window.

Correlation is sample-dependent. A relationship that looks stable in one window can change materially in another.

Rolling Metrics shows how return, volatility, and Sharpe ratio change across rolling windows.

Use it to compare the full-period average against the distribution of rolling outcomes.

Returns shows the distribution of daily, monthly, quarterly, and annual outcomes.

Use the distribution shape to inspect asymmetry and tail risk, not only the average return.

Risk vs Return plots realized annualized return against realized volatility for the selected assets and period.

This view compares one historical sample. It does not establish a stable forward-looking frontier by itself.

This view compares periodic contributions against a lump-sum entry for the same asset and sample period.

• Compare DCA and lump-sum outcomes.
• Inspect cost basis over time.
• Compare total invested capital against portfolio value.

The result is historical, not predictive. It changes with the start date, asset path, and contribution schedule.

Best DCA Day compares which day of the month produced the strongest historical DCA result for the selected sample.

Differences are usually small relative to the effect of contribution size, asset choice, and holding period.

ATH Proximity shows how close an asset was to its all-time high through time and how long drawdowns lasted before recovery.

Use it to compare recovery behavior across assets and market periods.

The PCA tab runs principal component analysis on the return matrix for the selected tickers and date range. It decomposes the correlation (or covariance) structure into principal components and shows how much variance each component explains.

Use it to diagnose concentration risk: if a single component explains most of the variance, the assets are driven by a common factor. See the PCA docs for detailed interpretation guidance.