A complete guide to every 13Foresight feature — what it does, why it exists, and how to use it to make better investment decisions.
Every quarter, the most sophisticated institutional investors in the world — hedge funds, pension funds, endowments, and asset managers controlling hundreds of billions of dollars — are legally required to disclose their equity portfolios to the SEC. This data is public. But in its raw form it’s thousands of XML files full of CUSIPs, share counts, and regulatory codes that are nearly impossible to interpret.
13Foresight exists to close that gap. We parse every 13F filing from every manager with $100M+ in U.S. equity exposure, normalize the data, map holdings to live tickers, calculate performance metrics, and build the analytical layer that transforms raw disclosure data into actionable intelligence.
The result: a retail investor with an 13Foresight account has access to the same portfolio transparency that was once available only to Bloomberg terminal subscribers, prime brokerage analysts, and institutional research desks.
You don’t need to beat the market on your own. You can study the people whose full-time job is beating the market — see exactly what they own, how long they’ve held it, whether their strategy has historically worked, and how crowded a given trade is. That’s the informational advantage 13Foresight provides.
Form 13F is a mandatory quarterly disclosure for any institutional investment manager with $100 million or more in qualifying U.S. equity securities. Filed within 45 days of each quarter-end, it discloses the manager’s entire long equity portfolio — every stock, every ETF, every U.S.-listed option — as of the last trading day of that quarter.
13Foresight ingests 13F filings directly from the SEC EDGAR system in real-time as managers submit them throughout the 45-day filing window. Each filing is parsed, CUSIP-to-ticker mapped via our securities reference database, validated for completeness, and loaded into our normalized data warehouse. The entire process — from SEC submission to visible holdings on the platform — typically takes under 5 minutes.
To calculate performance, cost basis, and portfolio values, 13Foresight maintains a daily price history for every publicly-traded security. This price data is used to: calculate the Price Held at the quarter-end filing date, simulate portfolio returns in the backtester, compute the estimated weighted average cost basis for each holding, and derive all risk metrics (Sharpe, Beta, Volatility, etc.).
All risk-adjusted metrics (Sharpe Ratio, Alpha) use the 13-week U.S. Treasury Bill yield (^IRX) as the risk-free rate, updated monthly. This ensures that performance comparisons accurately reflect the prevailing “cost of doing nothing” at any given point in time — a critical distinction in high-rate environments where even sitting in cash carries a significant opportunity cost.
When a 13F marks a position as “New”, it means the manager first disclosed it in this quarter’s filing. But the actual purchase happened during that quarter — possibly 3 months earlier. The Price Held figure shown on every holding is the market price on the last trading day of the reporting quarter (e.g., December 31st for a Q4 filing).
This matters because it lets you instantly compare where a top institutional manager’s average cost basis approximately sits vs. where the stock trades today. A position where the fund’s Price Held is $40 and the stock now trades at $80 tells a very different story than one where Price Held is $200 and the stock is at $80.
For positions held across multiple quarters, 13Foresight’s Institutional Conviction Engine™ reconstructs the manager’s full purchase history and calculates a weighted average cost basis. This is done by tracking share count changes quarter over quarter and estimating entry prices based on intra-quarter price ranges. A fund that has held Apple for 12 consecutive quarters at varying position sizes will have a very different true cost basis than the current price implies.
Concentration measures the weight of a position in a manager’s total disclosed portfolio. A 25% concentration in a single stock is a very different signal than a 0.5% position — the former represents genuine high-conviction belief, the latter may be a small speculative bet or a legacy holding. 13Foresight surfaces concentration prominently because where a manager bets big is where you should pay the most attention.
This is one of the most misunderstood concepts in investing. Consider a fund with a Beta of 0.25 that returns 11% in a year where SPY returns 22%.
CAPM says: Expected Return = Risk-Free Rate + Beta × (Market Return − Risk-Free Rate). With a 5% risk-free rate: Expected = 5% + 0.25 × (22% − 5%) = 9.25%. The fund returned 11%, which is 1.75% above its risk-adjusted expectation — that’s positive Alpha.
This fund took one-quarter of the market’s risk and still beat expectations. It didn’t beat the raw index — but a rational investor comparing risk-adjusted performance should prefer this fund over a higher-beta fund with a slightly better raw return.
Sharpe Ratio = (Average Return − Risk-Free Rate) ÷ Volatility. When the risk-free rate (Treasury yields) is higher than market returns over the selected period — as happened during 2022 when SPY fell ~18% while T-bills yielded 4%+ — Sharpe turns negative. This is not an error. It accurately communicates that over that specific window, holding cash was objectively superior to holding the index on a risk-adjusted basis.
Calmar = Annualized Return ÷ |Max Drawdown|. A Calmar of 1.5 means the strategy earned 1.5% annually for every 1% of maximum peak-to-trough decline. It answers the question every serious investor must ask: ”Is the return I’m getting worth the pain I have to survive to get it?” Two funds with 15% annual returns but Calmars of 0.5 vs. 2.0 are fundamentally different risk propositions.
The Backtester is 13Foresight’s flagship feature. It answers the most important question you can ask about any institutional manager: ”If I had mirrored this fund’s disclosed portfolio at every quarterly filing date, what would my actual returns have been?”
Most fund performance databases show you a fund’s actual P&L — which includes short positions, leverage, intra-quarter trading, and derivatives that you as a copycat investor can never replicate. The 13Foresight Backtester shows you something more honest: the achievable performance of following only the publicly disclosed long book, using realistic entry timing.
At each quarter-end, the backtester identifies the manager’s disclosed holdings and rebalances the simulated portfolio on the filing date (not the quarter-end date). This is critical — it respects the 45-day lag. If a Q4 2023 filing was published on February 9, 2024, the simulation enters those positions on February 9, not December 31. This is what a real copycat investor could actually do.
Returns are calculated using daily closing prices from entry to the next rebalance date, capturing dividends and corporate actions. The result is a month-by-month equity curve you can directly compare against SPY, QQQ, IWM, and DIA.
Every holding gets the same allocation regardless of the manager’s actual position sizes. This removes concentration risk and produces a more diversified simulation — useful for evaluating a manager’s stock-picking ability independent of their sizing discipline.
Allocations mirror the manager’s actual reported position sizes, proportionally. If a fund had 40% in NVDA, your simulated portfolio does too. This is the closest replication of the manager’s actual strategy — but also means concentration risk is fully inherited.
Rather than mirroring all 80+ holdings of a diversified fund, you can limit the simulation to the manager’s top N positions by portfolio weight. This tests the hypothesis that a manager’s highest-conviction bets (their top 10 or top 20) outperform their full portfolio — a thesis supported by significant academic research on active management skill concentration.
The Market Heatmap answers one of the most valuable macro questions in investing: ”Where is institutional capital actually flowing right now?” Not where pundits say it’s flowing — where it’s actually going, according to the disclosed positions of thousands of institutional managers.
The heatmap aggregates every 13F filing for the latest quarter and visualizes the total institutional capital deployed in each sector and industry. The size of each tile represents total institutional AUM in that sector. The color represents the quarter-over-quarter change — green sectors are seeing net inflows (managers collectively adding), red sectors are seeing net outflows (managers collectively reducing or exiting).
Smart money flows often lead price. When institutions collectively rotate out of a sector — even before it shows up in price — it’s a meaningful signal that large allocators have updated their thesis. Conversely, sectors seeing accelerating institutional inflows despite flat prices can represent early-stage opportunities that haven’t yet been priced in by the broader market.
Use the Heatmap as a macro filter: before doing deep stock research in a sector, check whether institutions are adding or reducing exposure. Investing alongside smart money is not a guarantee — but investing against a coordinated institutional exit is a risk you should at minimum be aware of.
What happens when you combine the holdings of multiple institutional managers into a single portfolio? The Portfolio Builder lets you construct a custom multi-manager composite portfolio and backtest it — answering questions like: “Would a portfolio that blends Berkshire Hathaway’s top 10 with Tiger Global’s top 10 have outperformed either alone?” or “Does diversifying across three managers reduce drawdowns without sacrificing returns?”
Select up to 10 managers (Premium: unlimited), choose how many top holdings to take from each, set a weighting mode, and run. The builder deduplicates overlapping tickers across managers — if three funds all hold Microsoft, it won’t triple-weight it unless you explicitly choose to include duplicates. The result is a clean composite portfolio with a full backtest equity curve, risk metrics, and attribution breakdown.
Adding multiple funds doesn’t automatically improve diversification — if two “different” managers both have heavy Magnificent 7 exposure, combining them barely reduces correlation. The Portfolio Builder includes a Pearson correlation matrix showing how returns from each component fund’s top holdings co-move with each other, plus an ENB (Effective Number of Bets) score that measures true portfolio diversification. A portfolio of 50 stocks with ENB = 3 is actually a concentrated bet on 3 themes — the matrix makes this visible.
Institutional multi-manager portfolios are constructed by teams of quantitative analysts with access to sophisticated risk systems. The Portfolio Builder puts a simplified version of that infrastructure in your hands: you can test portfolio construction hypotheses, stress-test diversification assumptions, and build a watchlist of institutional positions that collectively satisfy your risk preferences — all without a single line of code or a Bloomberg terminal.
There are over 5,000 institutional managers filing 13Fs. Most of them are mediocre. A small minority consistently generate risk-adjusted outperformance over multiple market cycles. Manager Rankings exist to find that minority.
The Rankings leaderboard is not sorted by raw returns — any levered fund in a bull market looks good on raw returns. It’s sorted by a composite score that simultaneously evaluates five dimensions of manager quality:
Raw compounded return of the disclosed long portfolio over the trailing 3 years, net of the 45-day filing lag. Measures absolute performance.
Return per unit of volatility, adjusted for the risk-free rate. Rewards managers who deliver consistent, low-noise performance over those who simply rode market beta.
CAPM-derived excess return above what the manager’s beta exposure would predict. The purest measure of skill — separating market tailwind from genuine stock selection.
The deepest peak-to-trough decline over the period. Managers who protect capital during downturns score better — because avoiding large losses is mathematically more powerful than chasing large gains.
Return per unit of maximum drawdown. The composite risk-reward metric that rewards the most efficient generators of return relative to the worst-case loss investors had to endure.
Each metric is percentile-ranked across all funds in the database, then combined into a single 0–100 composite score. This peer-relative approach ensures the Rankings are meaningful regardless of market conditions — the #1 fund excels relative to all peers, not just relative to an absolute threshold that becomes meaningless in different market regimes.
Use Rankings as a discovery and screening tool: find managers whose style, AUM bracket, and concentration level match your investment thesis, then examine their fund page to understand why they rank well — is it concentrated bets in a hot sector, or genuine multi-cycle consistency?
The 13Foresight Score (13F Score™) is a per-fund quality rating displayed prominently on every fund profile. It condenses a manager’s full multi-dimensional performance record into a single 0–100 number, making it easy to compare managers at a glance without needing to manually interpret five separate metrics.
It is calculated as a weighted composite of the same pillars used in Rankings, but normalized to the fund’s own history rather than purely peer-relative. This means a fund’s 13F Score reflects both its absolute quality and its performance consistency over time. A fund with an 13F Score of 85 is genuinely high-quality by any reasonable standard — not just high-quality relative to a poor peer group.
How much return does the manager generate per unit of volatility and drawdown? This pillar rewards capital efficiency — extracting maximum performance while consuming minimum risk budget.
The fraction of returns that cannot be explained by market Beta exposure. High Alpha isolation means the manager is genuinely making superior stock-selection decisions — not just riding the S&P 500 with leverage.
Performance during identified market stress periods (2020 COVID crash, 2022 rate shock, etc.) and the speed and completeness of subsequent recovery. Managers who hold up during downturns and recover quickly earn top scores here.
How frequently does the manager outperform SPY in any given quarter? What percentage of rolling 12-month windows show positive Alpha? Consistency separates structural skill from lucky streaks.
13F Scores are calculated across 3-year and 7-year horizons independently. A manager can score high on 3Y (recent tactical performance) but lower on 7Y (hasn’t proven consistency across a full market cycle). The gap between the two scores is itself informative — a large 3Y–7Y spread suggests recency bias risk, while convergence signals durable, structural skill.
When every major hedge fund simultaneously holds the same stock, an invisible risk accumulates that standard portfolio analysis doesn’t capture. Crowding risk — the danger that a heavily institutionally-owned stock will experience a violent, self-reinforcing selloff when one large holder decides to exit — is one of the most underappreciated sources of tail risk in modern markets.
Every stock tracked by 13Foresight receives a Crowding Score (0–100) calculated from two dimensions:
High-crowding stocks often outperform when sentiment is positive — everyone buying the same thing drives the price up. But they carry asymmetric downside: when sentiment turns, there are too many sellers and not enough buyers. The 2022 Nasdaq selloff and the August 2024 yen carry unwind are textbook examples of crowding risk materializing across popular institutional positions simultaneously.
The Smart Money Pulse aggregates the net conviction changes across all institutional managers for any given stock: how many are adding, how many are reducing, and what is the net change in total institutional shares held quarter-over-quarter. A stock seeing consistent, broad-based institutional accumulation — not just one large buyer — is a qualitatively stronger setup than one where a single manager explains all the inflow.
Tracking what institutions hold is only half the picture. The other half is tracking how their conviction is changing over time. Conviction Dynamics surfaces the behavioral signals hidden inside quarter-over-quarter position changes.
At each fund profile, 13Foresight classifies holdings into six behavioral categories based on how the position changed from the prior quarter:
Managers rarely explain their trades publicly. These behavioral signals are the closest proxy to understanding conviction in real time. A fund that consistently increases a position over 4 consecutive quarters while the stock drops is displaying maximum conviction — they believe their thesis and are dollar-cost averaging against the market. That’s a very different signal than a one-quarter addition followed by immediate reduction.
For each holding on a fund profile, 13Foresight displays the full weight history — how large this position has been as a percentage of the fund’s total portfolio in every quarter it was held. A position that grew from 2% to 18% over two years tells a story of building conviction. One that has shrunk from 15% to 3% over the same period signals an exit in progress, even if the fund hasn’t fully sold out yet.
Not sure if 13Foresight is right for you? The Live Demo gives you full, unrestricted access to our backtester and analytics on three real funds — no account, no credit card, no time limit. It’s not a mock interface or a stripped-down preview. Every premium feature is fully functional.
A focused long-only manager — good example of concentrated conviction bets in large-cap equities.
Open Demo →A mid-size manager with a track record spanning multiple full market cycles, including both bull and bear periods.
Open Demo →A growth-oriented, broadly diversified portfolio — contrasts well with the more concentrated funds above.
Open Demo →The demo is read-only and limited to these three funds. To run backtests on any of the 5,000+ funds in our database, create a free account.
13Foresight uses Google OAuth for authentication — there are no passwords to create or remember. Click “Sign in with Google”, authorize once, and you’re in. Your account is tied to your Google email, so it’s as secure as your Google account.
A free account gives you immediate access to all 5,000+ fund profiles with 8 quarters (2 years) of holdings history, the backtester with a 2-year simulation window, the Portfolio Builder (3 funds, equal weight), and up to 10 saved favorites. No credit card required.
Premium removes all data depth limits, unlocks Manager Weight backtesting, full Manager Rankings, the complete advanced analytics suite (Crowding, Conviction Dynamics, Scenario Lab, Correlation Matrix), unlimited Portfolio Builder, and CSV data export. It’s designed for serious investors who treat research as a professional activity, not a casual hobby.
We store only your email address and session data. No financial information, no brokerage connections, no personal portfolio data. 13Foresight is a read-only research platform — we don’t touch your money.
13Foresight is an informational research platform, not a registered investment adviser, broker-dealer, or financial planning service. Nothing on this platform — including backtest results, rankings, crowding scores, cost basis estimates, conviction signals, 13F Scores, or any other data — constitutes investment advice or a recommendation to buy, sell, or hold any security.
Backtested performance is not actual performance. All backtest results are hypothetical simulations based on publicly disclosed holdings with a 45-day lag, equal or proportional weighting, and zero transaction costs beyond the commission setting. Real-world results would differ materially due to execution slippage, liquidity constraints, tax considerations, and the inability to perfectly replicate institutional position sizing.
13F filings represent only the long equity book of institutional managers. They do not capture short positions, leverage, derivatives strategies, private investments, or intra-quarter trading activity. The “performance” shown on 13Foresight reflects what a copycat long-only strategy would have achieved — not the fund’s actual P&L. Always conduct independent due diligence and consult a qualified financial professional before making investment decisions.