Disclaimer & risk notice

Not financial advice

Nothing on this site — no verdict, backtest, copilot answer, research page, or accompanying communication — constitutes investment advice, financial advice, tax advice, legal advice, or a recommendation, solicitation, or offer to buy or sell any security or other financial instrument. The operator of Schmatz is not a registered investment adviser, broker-dealer, or financial professional. No content published here should be construed as personalized advice.

You are solely responsible for evaluating the merits, risks, and tax implications of any investment decisions you make. Consult your own qualified financial, legal, and tax advisors before acting on anything you read on Schmatz.

Paper trading only

The portfolio you see described as the "V7 portfolio," "shadow portfolio," or any variant thereof is a simulated paper portfolio. It does not hold, buy, or sell any real security. No real money is at risk in any holding shown on Schmatz. In recommendation-only mode the system records signals without placing an order; paper modes may simulate orders and fills. Neither mode executes a real-money trade.

Users are observers of this simulated research. You are not authorizing Schmatz to access or control a brokerage account, and Schmatz does not execute real-money trades for users. If you choose to mirror any position you see published here in your own brokerage account, you do so entirely at your own discretion and risk.

Backtested and simulated performance

The headline strategy ("V7") is supported by a five-year walk-forward backtest covering 2021 through 2026 on a curated 81-stock universe. The results are pinned to a fixed, reproducible reference run so the numbers we cite don't drift. The current canonical numbers are:

• Sharpe ratio: approximately 1.06 (walk-forward out-of-sample, 15bp round-trip costs)
• Pooled out-of-sample mean return per trade: approximately +1.29% (t-statistic 3.45, p ≈ 0.0006)
• Annualized return: approximately +9.5%
• Maximum drawdown: approximately −8.5%
• Portfolio beta vs. SPY: approximately 0.00

Honest caveats on these numbers

Backtested performance is not a forecast of live performance. Actual execution can be materially worse than a backtest due to slippage, market impact, liquidity, borrow availability, taxes, outages, and other unmodeled frictions. Past performance does not predict future performance. The backtest window (2021-2026) covers only one major macroeconomic regime; the strategy's behavior in regimes outside that window is unknown.

A Fama-French 3-factor regression of the strategy's daily returns shows statistically significant exposure to the size (SMB) and value (HML) factors. After adjustment for these factor exposures, the strategy's residual idiosyncratic alpha is positive (approximately +5.5% annualized) but not statistically significant at the 5% level (t-statistic 1.39, p ≈ 0.16). A meaningful portion of observed returns is therefore attributable to documented factor risk premia rather than to a unique strategy edge.

Independent statistical-rigor checks include López de Prado & Bailey's deflated Sharpe ratio, which falls below the conventional 0.95 significance threshold given the number of strategy variants tested during development. Selection bias from iterative strategy development is a real and acknowledged risk.

Look-ahead bias and methodological caveats

The Schmatz backtest engine is point-in-time on price data and macro indicators. Trades enter at the next session's open after a signal fires, exit at end-of-session per the strategy's exit rule, and feature inputs are pulled from data available before the entry date. However, fundamentals sourced from third-party vendors (earnings, analyst grades, financial-health scores) are timestamped to filing date, not the as-of-knowledge date. Backtests that rely on fundamentals may capture small amounts of look-ahead bias on this dimension; this is a known limitation, not a hidden one.

Universe selection is also subject to survivorship and coverage bias. Some research universes are built from securities currently present in the database and historical coverage of delisted securities remains incomplete. Results may therefore overstate what a point-in-time, fully investable universe would have achieved. The size and direction of that bias vary by question and should not be assumed to match a single fixed percentage.

User-driven backtests in the Lab inherit the same caveats. The numbers shown for any user-run backtest are illustrative of what the strategy would have done on the chosen tickers and dates in our corpus — not what a live account would realize today.

Forward-looking statements

Any forward-looking statements made on Schmatz — predicted shock attributions, projected mean-reversion outcomes, probability estimates, or strategy expectations — are inherently uncertain. They are produced by statistical models and large-language-model analysis applied to historical data and current filings, and they are subject to error. They should not be relied upon as predictions of future events or returns.

No fiduciary relationship

Your use of Schmatz does not create a fiduciary, advisory, or agency relationship between you and Schmatz, the operator, or any contributor. We owe you no duty of care with respect to your investment decisions. You are not our client.

No personalized recommendations

Schmatz publishes research impersonally — the same backtest engine, the same shock dossiers, the same Ask responses are available to every reader. Nothing on Schmatz takes into account your age, income, existing portfolio, tax situation, risk tolerance, or investment objectives. Schmatz never tells "you" personally to buy or sell any security. Any wording you encounter that could read like such a recommendation is editorial framing, not advice.

Allowed (and what Schmatz does): "Here is a backtested mean-reversion model that historically beat SPY in the breadth-gated regime. The model's most recent simulated trades are X, Y, Z."

Not allowed (and what Schmatz does not do): "Based on your portfolio and risk profile, you should buy Stock X tomorrow."

General research design

Schmatz is designed as a general research publication, not as an individualized advisory relationship. Its research tools use the same product rules and available datasets for users rather than collecting a user’s financial circumstances to create a personal recommendation.

• No brokerage connection — Schmatz does not ask for brokerage credentials, accept assets, or place trades.
• General inputs — stock, index, corpus, and backtest views are generated from the question and available market data, not from a suitability profile.
• No suitability assessment — Schmatz does not evaluate your income, holdings, tax position, risk tolerance, or investment objectives. That is one reason its output cannot be treated as individualized advice.

This describes current product behavior, not a legal classification or exemption. Schmatz has not had this analysis reviewed by counsel. The operator should obtain securities counsel before enabling paid access, materially personalizing output, or changing how securities are selected and presented.

Data sources and licensing

Schmatz combines public government records with historical market-data services. Availability to the public does not mean every market-data record is public domain or freely redistributable.

• SEC EDGAR — publicly accessible corporate filings: 8-K, 10-K, 10-Q, Form 4 insider transactions, 13D activist filings, and XBRL-tagged financial statements used to compute fundamentals.
• Federal Reserve FRED — selected macroeconomic and market series, subject to each series’ source notes.
• Historical market-data services — end-of-day US equity records used for charts, backtests, event detection, and pattern matching, subject to upstream terms and coverage.

Separately licensed datasets may be used for ingestion, enrichment, or quality assurance. Provider restrictions apply, and restricted records are not intentionally exposed through customer APIs.

What Schmatz displays: derived research output, selected chart points needed to render a requested view, filing links, classified events, AI-assisted narratives, and editorial commentary. A result is reproducible only when the same code, configuration, corpus snapshot, and provider data are available.

What Schmatz does NOT publish or sell: downloadable bulk exports of any underlying historical price archive, bulk export of the fundamentals corpus, or any general-purpose “query the database” endpoint. Subscribers consume derived analytics; we are an analytics publisher, not a data reseller.

Jurisdictional considerations

Schmatz is operated from the United States and the content is directed primarily to adult U.S.-based users. Nothing on Schmatz should be construed as soliciting business in jurisdictions where the operator is not qualified to do so, and the content may not be appropriate for, or available in, all jurisdictions.

Limitation of liability

To the maximum extent permitted by applicable law, the operator of Schmatz disclaims all liability for losses or damages — direct, indirect, incidental, consequential, or punitive — arising from your use of, or reliance on, any content published here. You assume all risk associated with any decisions you make in connection with Schmatz output.

Early-access notice

Schmatz is currently in an early-access release with free self-signup. Features, content, methodology, and data presentation may change without notice. This disclaimer is itself subject to revision; you will find the date of last revision near the top of this page.

Contact

Questions about this disclaimer or a specific item of content can be sent through the Legal contact form or to [email protected].