Portfolio analyzer: a stock portfolio analysis tool for weights, concentration and backtesting.
Read your holdings as one weighted index instead of a list of tickers. See where the risk actually sits, test the basket over real history, and measure it against a benchmark that fits.
Educational only · Never places a trade
In short
A portfolio analyzer is a tool that treats your holdings as one combined position and reports what that position is really made of: how much weight sits in the largest name, how much sits in the heaviest sector, whether the top holdings move together, where the return actually came from, and how the whole thing behaved against a matching benchmark. Portfolio analyzers come in three shapes. Aggregators such as Empower and Morningstar Investor link your accounts and describe what you already own. Modeling tools such as Portfolio Visualizer run statistics on an allocation you type in. Construction tools such as Indexes let you build the weighted basket, backtest the construction, and follow it as a named index. Pick by which of those three jobs you have, because no product is best at all three.
Last updated July 2026
What a portfolio analyzer measures
The five checks that actually tell you something
Most dashboards show far more numbers than these. These are the five that change decisions. Run them in order, because each one narrows what the next has to explain.
| Check | What it reads | Why it matters | Where to look |
|---|---|---|---|
| Position concentration | Weight of your single largest holding | A position above roughly 20% to 25% of the portfolio means one company now decides your year. Many practitioners flag anything past 10% to 15% as worth a plan. | Weight column, sorted |
| Sector concentration | Combined weight of your heaviest sector | Owning fifteen names that are all software is one bet, not fifteen. A sector past 35% to 40% is a concentrated position wearing a diversified costume. | Group the members and read the totals |
| Correlation | Whether the top holdings move together | Diversification is about co-movement, not count. If the largest positions rise and fall on the same news, the extra tickers bought very little protection. | Backtest the basket and read the drawdowns |
| Return attribution | Share of the gain coming from the top few names | When most of the return traces to two or three positions, the rest of the portfolio is decoration and the risk is far less spread than the holdings list suggests. | Compare the full index against a version without them |
| Risk versus benchmark | Volatility and drawdown against a fitting index | The number that matters is not the return, it is the return next to a benchmark that holds the same kind of thing. Everything else is a story. | Track the index against the S&P 500 or BTC |
The thresholds above are conventions rather than rules, and reasonable people argue about them. What is not arguable is the direction of the error. Almost every self-directed portfolio that gets analyzed for the first time turns out to be more concentrated than its owner believed, usually because the winners were never trimmed. A position bought at 5% that tripled while everything else stayed flat is now most of the portfolio, and nobody decided that. Reading the weight column once a quarter is the single highest value habit a portfolio analysis tool supports.
Correlation is the check people skip, and it is the one that makes a holdings count misleading. If your ten largest positions are all large US technology companies, you own one macro bet expressed ten ways. The way to see it without a statistics package is to build the basket, backtest it, and look at the drawdowns: a genuinely diversified basket has shallower drawdowns than its worst member, while a correlated one falls almost as hard as a single stock. Our how many stocks you need to diversify write-up goes through where the count stops helping.
Portfolio analyzer tool comparison
Three kinds of portfolio analyzer, and which job each one does
An honest comparison, including where each tool is stronger than ours. Pricing checked against each vendor's own page in July 2026 and it does change, so confirm before you buy.
| Tool | Type | Price | What it is genuinely good at | Best for |
|---|---|---|---|---|
| Empower Personal Dashboard | Aggregator | Free to use, monetized through its advisory service | Links live accounts, shows allocation and fee drag on what you already own | Seeing the truth about a portfolio you already hold |
| Morningstar Investor (X-Ray) | Aggregator plus research | Paid subscription, see Morningstar for current pricing | Looks inside your funds to find overlapping stock exposure across ETFs | Fund and ETF investors checking hidden overlap |
| Portfolio Visualizer | Modeling and statistics | Free tier up to 15 assets with limited history; Basic $30/month, Pro $55/month, both billed annually | Deep quantitative work: backtests, factor regressions, efficient frontiers, Monte Carlo | Quantitative research on allocations |
| PortfoliosLab | Modeling and comparison | Free tier with paid plans | Fast ticker and portfolio comparison with risk metrics side by side | Quick lookups and screening |
| Indexes | Construction | From $12/month | Build the weighted basket yourself, backtest the construction, and track it as a named index against a benchmark | Designing and testing a basket before and after you own it |
Aggregators
You link brokerage and retirement accounts and the tool pulls live holdings. The strength is completeness: it sees the old rollover IRA you forgot about and the fund overlap you never noticed. The cost is that you hand over account access, and the analysis is limited to what you already own. It cannot tell you what a different set of weights would have done.
Modeling tools
You type an allocation and get statistics on it: backtests, factor exposure, correlation matrices, efficient frontiers, Monte Carlo projections. This is the deepest quantitative layer available to an individual investor, and Portfolio Visualizer is genuinely better at it than we are. The trade is that the output is a research report rather than something you keep.
Construction tools
You define the basket itself: which names are members, how they are weighted, how often the weights reset. The analysis and the object are the same thing, so the index persists, gets tracked against a benchmark, and can be revised. This is where Indexes sits, and it is the right shape when the portfolio is something you are designing rather than only auditing.
Worth being direct about the boundaries of ours. Indexes does not link to a brokerage account, so it will not pull your holdings in automatically and it cannot find an account you forgot. It does not run Monte Carlo simulations. It never places a trade, never holds assets and is informational and educational software rather than advice. What it does instead is let you state a basket explicitly, weight it the way you want, test that construction over real market history, and keep it as a tracked index. If you want the account-linking view as well, most people end up using an aggregator alongside a construction tool rather than choosing between them.
How to analyze a stock portfolio
Analyze your portfolio in four passes
Enter the holdings as weights
List every position as a percentage of the total, not in dollars. Dollars hide the shape. The moment the portfolio is expressed as weights, the concentration problem is usually visible without any further analysis.
Read concentration by name and sector
Sort by weight and look at the top of the list, then group the members by sector and read those totals. This pass takes two minutes and finds more real risk than any other step here.
Backtest the combined basket
Run the weighted combination over historical prices and read the drawdowns alongside the returns. A basket that fell 55% in a bad stretch is a different object from one that fell 25%, whatever their average returns look like.
Compare against a fitting benchmark
Chart the basket against an index that holds the same kind of asset, then keep tracking the gap. A return without a benchmark next to it has not told you anything about your decisions yet.
The order matters more than it looks. Weights first, because a concentration problem makes every downstream statistic misleading: a Sharpe ratio computed on a basket that is 40% one stock is really a fact about that stock. Backtest before benchmark, because the drawdown number tells you which benchmark is even fair. The mechanics of the third step are covered in backtest a portfolio, and choosing the yardstick for the fourth in portfolio benchmark.
One caveat that applies to every analyzer on the market, ours included. Every backtest is hypothetical historical performance. It shows what a set of weights would have done over a period that has already happened, which is useful for understanding how a construction behaves and useless as a prediction. Past performance is no guarantee of future results.
Who this fits
Who gets the most out of a construction-style analyzer
Investors who let winners run
If you have never trimmed, your allocation was set by price moves rather than by you. Seeing the weights once is usually enough to prompt a decision, and portfolio rebalancing covers what to do about it.
Anyone testing a basket before buying
Aggregators can only describe what you already hold. If the question is whether a set of names is worth owning at all, you need to be able to model the basket first and read its history.
People holding stocks and crypto together
Most analyzers treat crypto as an awkward add-on or ignore it. Weighting equities and tokens inside one index and backtesting the combination is a specific gap, and the crypto index page covers that side.
Theme and thesis investors
A theme basket needs its weights decided deliberately and its benchmark chosen before the test rather than after. See thematic investing for how those usually go wrong.
Anyone comparing weighting methods
Cap weighting and equal weighting produce very different portfolios from identical holdings. Running both is the clearest way to see it, and equal weight index works through the trade.
People who want the index to persist
A one-off report gets closed and forgotten. A named index with a rebalancing schedule stays live, which is what turns analysis into something you actually keep checking. See index construction.
Questions
Portfolio analyzers, answered
What is a portfolio analyzer?
A portfolio analyzer is a tool that evaluates your holdings as a single combined position rather than as a list of tickers. It reports how much weight sits in each name and sector, how the holdings move relative to each other, and how the whole thing performed against a benchmark index. The point is to see the portfolio as one object with one risk profile.
How do I analyze my stock portfolio?
Start with weights. Write each holding as a percentage of the total, then read the largest position and the heaviest sector. Next check whether the top names move together, because five correlated stocks are close to one position. Then compare the whole basket against an index that holds the same kind of asset. Those four passes catch most of what is actually wrong with a portfolio.
What is the best portfolio analyzer?
It depends on which job you have. If you want to see what you already own across linked accounts, an aggregator like Empower or Morningstar Investor fits. If you want deep statistics on an allocation, Portfolio Visualizer is the specialist. If you want to design a weighted basket and test the construction before committing to it, a construction tool like Indexes is the closer match. No single product is best at all three.
Is there a free portfolio analyzer?
Yes, several. Empower is free to use, Portfolio Visualizer has a free tier capped at 15 assets with limited history, and PortfoliosLab has a free level. The paid tiers generally buy history depth, asset count, saved models and export. Whether that is worth paying for depends on how often you rerun the analysis and how far back you need the data to go.
What does a portfolio analyzer actually measure?
The useful ones measure five things: position concentration, sector concentration, correlation between holdings, where the return actually came from, and risk against a matched benchmark. Everything else on a dashboard tends to be presentation. If a tool shows you a return number without a benchmark beside it, it has not analyzed anything yet.
How often should I analyze my portfolio?
Quarterly is enough for most people, with a fuller review once a year. Weights drift as prices move, so a portfolio set at 5% per position can be at 12% in one name within a couple of strong quarters without you buying a single share. Checking more often mostly generates activity, since meaningful conclusions about a strategy need several years of evidence.
Can a portfolio analyzer backtest my holdings?
Some can. Backtesting means running your current weights over historical prices to see what that combination would have returned and how deep its drawdowns were. Portfolio Visualizer and Indexes both do it. Aggregator style analyzers usually do not, because they are built to report on live linked accounts rather than to model a hypothetical. Any backtest is hypothetical historical performance and does not predict future returns.
Does a portfolio analyzer connect to my brokerage account?
Aggregators do, and that is their whole design: you link accounts and they pull live balances and holdings. Modeling and construction tools generally do not. Indexes does not connect to a brokerage, does not hold assets and never places a trade. You enter the members and weights yourself, which means there is no account to link and nothing to fund.
What is a good level of diversification in a portfolio?
There is no single number, but the shape matters more than the count. A portfolio where no position runs past roughly 10% to 15% and no sector past about 40% is diversified in a way most people would recognize. Owning forty stocks that are all large-cap US technology is less diversified than owning twelve names spread across sectors that behave differently.
See what your portfolio is actually made of
Build the basket as a weighted index, read the concentration, backtest the construction and track it against a benchmark. No account to link, no minimum, no trades. Educational and informational only.