================================================================================================ DRAFT — HYPOTHETICAL MODEL PORTFOLIO — NOT A REGISTERED FUND, NOT AN OFFER TO SELL SECURITIES, NOT INVESTMENT ADVICE. ================================================================================================ Momentum, volatility-managed (FMVM) Prospectus · November 2026 · Dated 2026-11-14 Issuer: ETF Foundry Research (hypothetical) | Listing: Not listed (hypothetical) | CUSIP: Not applicable (hypothetical model portfolio) Before you invest, you may want to review the Fund's full (draft) Statement of Additional Information, which contain more information about the Fund. This is a hypothetical model portfolio, not a registered fund: no shares are offered or sold, and the figures below are illustrative. Not listed (hypothetical). ## Investment Objective The Fund seeks long-term capital appreciation by tracking a rules-based model built on one stock-ranking signal (12-month momentum), before the placeholder expense ratio and trading costs. ## Fees and Expenses of the Fund This table describes the placeholder fees and expenses you would pay if you bought, held, and sold shares of the Fund, if it were a real fund. Investors do not actually pay these fees because the Fund is hypothetical. ## Annual Fund Operating Expenses (% of the value of your investment, per year) Item | Amount -----------------------------------------+------- Management Fee | 0.35% Distribution and/or Service (12b-1) Fees | 0.00% Other Expenses | 0.00% Total Annual Fund Operating Expenses | 0.35% ## Example This example is intended to help you compare the cost of investing in the Fund. It assumes you invest $10,000, earn a 5% return each year, and that the Fund's placeholder operating expenses remain the same. Although your actual costs may be higher or lower, your costs would be: Period | Cost ---------+----- 1 Year | $37 3 Years | $115 5 Years | $202 10 Years | $454 ## Portfolio Turnover The Fund's model is rebuilt monthly, which in a real fund would cause it to buy and sell securities frequently. During the sample, on average 28.05% of the stocks on the long side were new each month (about 337% a year). Higher turnover would generate transaction costs and taxable gains that are not reflected in the hypothetical performance shown. ## Principal Investment Strategies The hypothetical Fund seeks to track a rules-based model that ranks stocks on one signal, 12-month momentum, and rebuilds its portfolio monthly. The stocks are U.S. common stocks listed on the NYSE, NASDAQ or NYSE American, with a share price of at least $5 and a market value of at least $50 million. Each month every signal is signed so that higher values are the ones the model buys, and turned into a percentile among the eligible stocks that have a value for it. Stocks are ranked on that percentile. The model buys the top decile (10%) and sells short the bottom decile (10%). A month is used only when at least 50 stocks are ranked. Within each side, stocks are weighted by market value. The model is long-short: it holds the long side and sells the short side short in equal dollar amounts, so its return is the long side's return minus the short side's. The portfolio is rebuilt at the end of every month from data known at that date and held through the following month. An overlay scales the model's exposure: each month exposure is set to the 12% annualized volatility target divided by the model's realized volatility over the previous 6 months, capped at 1.5×. Exposure below 1× leaves the rest in cash at the 1-month Treasury bill rate, and exposure above 1× is financed at that rate plus 0.5% a year. Over the backtest the average exposure was 0.62× and the model was in cash in 0% of months. The overlay changes the return stream, not the holdings: holdings shown are the underlying portfolio's. The model uses point-in-time Sharadar fundamentals and split- and dividend-adjusted total- return prices. It is a research backtest, not a live trading record. Because this is a hypothetical model portfolio and not a registered investment company, the Fund does not actually hold securities, accept investments, or transact; all figures are illustrative. ## Signals Signal | Share | What it buys on its own ------------------+-------+------------------------------------------- 12-month momentum | 100% | Buys the biggest winners of the past year. ## Additional Information About the Fund's Strategies Each signal is computed from Sharadar point-in-time fundamentals and total-return prices and signed so that higher values map to the long side. Each month it is turned into a percentile among the eligible stocks that have a value for it, with tied values sharing their average rank. The book is formed at the end of a month and earns the following month's return. The full sample is split into Train (2000-2012), Validation (2013-2018), and Test (2019-2026) windows. Because the rules fit no parameters, these windows show whether the record holds across eras; they are not out-of-sample tests. Alpha is estimated by regressing the model's monthly returns on the Fama-French five factors. All results are hypothetical and gross of expenses and costs. ## How the Model Is Constructed Setting | Value --------------------+-------------------------------------------------------- Signals | 12-month momentum (100%) Combined | One ranking Stocks | U.S. common stocks on the NYSE, NASDAQ or NYSE American Screens | Price $5+; market value $50M+ Sectors | All Industry adjustment | None Long side | The top decile (10%) Short side | The bottom decile (10%) Weighting | Company size Largest position | No cap Rebalance | Monthly Overlay | Vol target 12% ## Principal Risks The principal risks of the strategy are: - Not a Registered Fund Risk. This is a hypothetical model portfolio, not a registered fund or an investment company. No shares exist, nothing is offered or sold, and no one can buy or redeem. Nothing here is investment advice. - Model and Signal Risk. The strategy depends entirely on one quantitative signal and fixed rules. The signals may not persist, may be arbitraged away, or may underperform the broad market for long periods. - Hypothetical Performance Risk. All performance is a backtest computed with hindsight, gross of the placeholder expense ratio and of trading costs, taxes, and slippage. It is not what any investor earned. The signals and settings were chosen by the person who built this fund, possibly after seeing backtests, which tends to overstate future results. - Market Risk. Equity prices can fall due to company, industry, market, or economic conditions. - Long/Short Risk. Short positions can lose more than their initial value if prices rise, and the long-short spread can move against the model. - Small- and Mid-Capitalization Risk. The model can hold smaller companies whose shares are more volatile and less liquid than large-cap stocks. - Portfolio Turnover Risk. Monthly rebuilding implies high turnover that, in a real fund, would create transaction costs and taxable distributions not reflected in the backtest. - Overlay Risk. The exposure changes are modeled on the model's monthly returns; a real fund would need to trade and borrow to do this, with costs and risks the model does not capture. ## Additional Risks - Data and Methodology Risk. Errors in source data, look-ahead bias, or model specification could materially change results. - Rebalancing and Timing Risk. Forming portfolios at month-end and holding for one month exposes the model to timing luck and gaps between formation and execution. - Concentration Risk. Holding only part of the ranked stocks can concentrate exposure in relatively few names, increasing volatility relative to a diversified portfolio. ## Performance The following performance is HYPOTHETICAL and BACKTESTED — it was calculated by applying the model to historical data with the benefit of hindsight, is gross of the placeholder expense ratio and trading costs, and does not represent the results of any actual account. Past (hypothetical) performance does not guarantee or predict future results. Returns are those of the long-short spread: the long side's return minus the short side's. They include the overlay. ## Hypothetical Calendar-Year Returns (long-short spread, with overlay) Year | Hypothetical Return -----+-------------------- 2017 | 16.17% 2018 | 17.47% 2019 | 4.03% 2020 | 9.12% 2021 | -3.78% 2022 | 27.86% 2023 | -5.93% 2024 | 13.93% 2025 | -5.14% 2026 | 20.87% ## Average Annual Returns (hypothetical, as of the most recent sample month) Period | Hypothetical Avg. Annual Return ------------------------------------+-------------------------------- 1 Year | 18.46% 3 Years | 5.99% 5 Years | 8.29% 10 Years | 8.73% Since Model Inception (full sample) | 7.66% ## Management of the Fund Investment Adviser (hypothetical): ETF Foundry Research (hypothetical). Portfolio Managers: Quantitative Model (rules-based) — the portfolio is constructed entirely by automated rules with no discretionary manager. The Fund would pay the Adviser a unitary management fee of 0.35% of average net assets, out of which the Adviser would pay substantially all operating expenses. Because the Fund is hypothetical, no fee is charged or paid. ## Buying and Selling Shares Illustrative only. A real ETF issues and redeems shares in large blocks (Creation Units) with Authorized Participants, and individual investors buy and sell shares on a secondary market exchange at market prices that may differ from net asset value. The Fund is hypothetical and issues no shares. ## Distributions and Taxes Illustrative only. A real fund would distribute net investment income and capital gains and those distributions would generally be taxable. The Fund makes no distributions. ## Financial Highlights Not applicable — hypothetical. The Fund has no audited financial statements, net asset value, or shares outstanding because it is a model portfolio, not a registered fund. ================================================================================================ DRAFT — HYPOTHETICAL MODEL PORTFOLIO — NOT A REGISTERED FUND, NOT AN OFFER TO SELL SECURITIES, NOT INVESTMENT ADVICE. ================================================================================================