Arithmetic of Alpha. No Camouflage.

The Ordertune Performance Matrix combines two regimes. The historical equity curve from 2000 to 2021 is reconstructed from backtested signals on the exact strategy logic that runs in production today, including realistic slippage and commission assumptions on Nasdaq 100 constituents. From 2022 onward the curve transitions to live, time-stamped signals emitted nightly to subscribers and persisted in our public ledger. Every trade in the ledger from 2022-01-01 onward has an immutable signal timestamp that pre-dates the corresponding entry price — there is no “after-the-fact” optimisation. Trades and signals shown on the page are not paper-traded fills from Ordertune’s own brokerage account; they are the subscriber-facing instructions plus the resulting realised arithmetic.

Strictly the Nasdaq 100 (NDX) constituents. The Nasdaq 100 was chosen because it is the most liquid equity universe in the world by dollar volume, which collapses slippage and bid-ask spreads to near zero for retail order sizes. The NDX also has a clear, public reconstitution calendar, so every backtested signal can be re-verified by a third party using any standard data vendor. No futures, no FX, no crypto, no OTC pink sheets — by design.

The same signals are re-weighted at the new position size, the trade-level returns are re-aggregated into a daily portfolio return series, and the CAGR is recomputed as the geometric-mean annualised rate of the resulting equity curve. Changing the position-size scenario does not regenerate signals or re-run a backtest — it only changes the dollar exposure per trade. This is why the 7.5% Progressive scenario shows a higher CAGR and a deeper max drawdown than the 3.0% Conservative scenario: same underlying alpha, different leverage.

Yes. The historical equity curve embeds an explicit per-trade cost assumption of 0.05% per round trip covering both commissions and slippage. This is conservative for the Nasdaq 100 universe at retail size at modern discount brokerages, which typically pay zero commission and trade against tight spreads. For institutional-size accounts we recommend running your own slippage assumption — but the published numbers should not flatter retail subscribers.

This page is the aggregate view: equity curve, monthly matrix, Sharpe, drawdown, exposure, and the ensemble result. The separate Trading Ledger is the per-trade view: every closed position with ticker, dates, prices, return, holding period, and originating model. They reconcile by construction — the ledger is the input series from which the performance aggregates are computed.

The equity curve directly overlays QQQ on the same chart. The structural difference is exposure: the Ordertune long-only portfolio averages around 24% market exposure (it is fully invested less than a quarter of the trading days), versus 100% for buy-and-hold QQQ. The system is therefore not designed to beat QQQ in a sustained low-volatility melt-up — it is designed to compound at a competitive rate with most of the capital not in the market most of the time, which is what produces the favourable Sharpe and MAR ratios. Over the full measurement window the long-only portfolio outperforms QQQ on absolute return; over short windows it can and does underperform.

Approximately, yes — within the bounds of execution variance. Ordertune publishes signals after the U.S. equity market close; subscribers place orders at the open of the following trading day. Realised fills will deviate from the published entry prices by a small amount based on overnight gap risk and your broker’s order routing. The published equity curve uses the executed open price on the day after the signal. For the most conservative replication assumption, model an additional 5–10 basis points of slippage per trade on top of the in-curve assumption.

Because a single “headline return” is misleading. A retail trader with $25,000 of risk capital has a fundamentally different position-size economics than a $250,000 account, and a different drawdown tolerance again. Publishing three scenarios (3% conservative, 5% standard, 7.5% progressive) lets every reader pick the configuration that matches their own risk budget and behavioural ceiling, instead of taking our preferred sizing on faith. The 5% Standard scenario is the one referenced in the headline KPIs because it is the median configuration of our active subscriber base.

Two figures, because one number without its window is meaningless. At the 5% Standard position size, the deepest peak-to-trough decline over the trailing twelve months is -17.8%; across the full published window it is -22.4%. At 7.5% Progressive the same two figures are -23.6% and -31.5%. These numbers are not pleasant to live through in real time, and the Performance Matrix is explicit about which calendar month the drawdown occurred — most max-drawdown windows compressed into a single quarter rather than dragging across years.

Daily, after the U.S. equity market close. New closed trades are appended to the ledger as positions are exited, the monthly cell for the current month is re-aggregated, and the equity-curve datapoint for the current day is published. There is no manual review step between trade close and publication — the data pipeline runs end-to-end without an editorial layer.

No. Past performance — including this performance — is not a guarantee of future returns. Systematic trading strategies are derived from historical statistical regularities that can erode as markets evolve, as participant behaviour adapts, and as structural regime changes occur. Ordertune’s specific defence against this is the multi-strategy ensemble: orthogonal edges are less likely to all decay simultaneously than any single one. But probability is not certainty. Trade only with risk capital, validate independently, and size for the drawdown you can tolerate behaviourally — not the one you want intellectually.