“A trend book is long the persistence of the board, not the direction of it. When persistence goes, the losses arrive from every sector at once, and that is the cost of being paid when it returns."
About This Report
The ATS Classic Trend Benchmarking Portfolio is a systematic trend-following reference model. It runs a ten-strategy ensemble across sixty-eight futures markets spanning eight sectors, sized by a fixed-amount rule on prior-bar volatility, and serves as a clean benchmark for classic trend following. The figures in this report are produced by the ATS Classic Trend engine, a standalone Python implementation run on out-of-sample data using simple trend-following models. Results are computed as dollar profit and loss on a stated twenty-five million dollar capital base, with returns stated additively: the year-to-date figure is the sum of the monthly net returns, and drawdowns are measured on the same additive basis. The model carries no discretionary overlay; it is the rules, the markets, and the price data.
This is a high-volatility portfolio, and the figures should be read with that in mind. It is built to capture large, sustained trends rather than to smooth the path to them, so the return profile pairs strong accumulation through trending years with sharp monthly declines and deep drawdowns when trends reverse. August’s +12.70%, September’s +2.66% and October’s -6.95% are three consecutive expressions of the same architecture rather than departures from it, as is the -42.82 point peak-to-trough decline of 2024 to 2025. Drawdowns are stated in points of the fixed $25M base throughout, not as percentage declines in equity.
The report is published in the first trading days after each month-end as a fast, factual read on the prior month for classic trend followers. It documents the model’s performance, decomposes the result by sector and by market, and sets the numbers against the month’s market backdrop. The aim is a clear account of what the trend-following environment delivered, and of what the model is carrying into the month ahead.
Commentary
October returned -6.95%, after September’s +2.66% and August’s +12.70%, and the loss was about as broad as a loss can be. Six of the eight sectors detracted. Bonds cost -3.76 percentage points on the trading basis, Metals -2.81, Grains -2.65, Equities -2.34, Currencies -1.49 and Softs -0.35, against Energy at +5.62 and Meat at +0.83. Twenty-one of the 68 markets finished positive, 46 negative and one unchanged, which tied June for the second-lowest positive participation of 2026, behind March’s 18 advancing markets. The portfolio closed at a cumulative +197.9%, 6.95 points below the September peak, with the year to date at +23.1%.
All seven system families lost money, which has not happened in any month this year. September was carried by one family contributing +4.15 points while five lost; October had no such offset. The spread ran from -0.11 points to -2.47, so no single system explains the month and none escaped it. Decomposed from the daily per-system curves, the portfolio returned -0.47%, +3.85%, -4.63%, -1.33% and -4.36% across the five reporting weeks, one strong week inside four losing ones. Those figures are on the engine trading basis, before the portfolio-level cost and interest adjustments.
The Month, Week by Week
The TTU Trend Barometer ran 52%, 50%, 36%, 41% and 36% across the five weeks of October. It opened where September closed, eased, then fell 14 points in the week to 16 October, out of the Neutral band and below the 40% line that marks a cold environment. It recovered 5 points the following week and gave all of them back in the last. Two of the five readings sit in cold territory and none reached the favourable band.
Performance Snapshot
October net return of -6.95% against September’s +2.66%. The month is the third largest loss of 2026, behind June’s -19.77% and March’s -13.17%, and the fourth losing month of the ten.
How to Read the Track
The panel below steps through every month since the January 2020 inception, one at a time. It carries two lines. The solid line is the portfolio marked to market, the way the performance tables report it. The dimmer line is profit actually realised on closed trades. The gap between them is money still sitting in open positions, and watching it open and close is the clearest picture of what a long-horizon trend follower is doing between entry and exit. At the October 2026 close the marked line stands at +208.8% and the closed line at +138.9%, so 69.9 points of the result is in positions still running.
Both lines are on the engine trading basis, net of the embedded commission and before the portfolio level cost adjustments and the collateral interest credit. That is deliberate: it puts them on one basis so the distance between them is open profit and nothing else. The published fully-loaded track is about ten points lower over the period.
Six declines deeper than eight points are shaded in red, from peak to trough, and the three stretches in which the portfolio made new highs by fifteen points or more are shaded in green. The deepest ran from March 2024 to May 2025 and took the portfolio 43.08 points below its high, regaining that high in February 2026, 23 months from peak to recovery. The April 2022 episode was shallower at 29.39 points and took 22 months. Against them, the largest advance ran from February 2022 to April 2022 and added 45.52 points, and February 2024 to March 2024 added 29.06. Neither the declines nor the advances are departures from the model. They are the same behaviour seen from two sides: a strategy that holds positions until a trend ends rather than exiting when it becomes uncomfortable.
Months carrying an explanation are numbered on the chart, and the numbered chronology beneath the panel fills in as the walkthrough reaches each one. Any entry can be clicked to jump back to that month. Each explanation is sourced: the contemporaneous This Week in Trend record where one exists, published sources where the account depends on market history, and our own attribution where the claim is about this portfolio. Every month, annotated or not, shows its largest contributors and largest costs, computed from the portfolio’s own records rather than recalled.
The chronology is being written month by month and is not yet complete. Months without an explanation show their drivers alone, which is the honest position until the account behind them has been checked.
The track, month by month
Every month since the January 2020 inception, stepped one at a time. The solid line is the portfolio marked to market; the dimmer line is profit actually realised on closed trades. The gap between them is money still in open positions. Red bands are declines of more than eight points, green bands are stretches making new highs. Where a month carries an explanation it appears on the right and is added to the chronology below it.
Largest contributors
Largest costs
Chronology of major events
Click the panel, then space plays and pauses and the arrow keys step one month. Click any entry in the chronology to jump to that month. Figures are on the engine trading basis, net of the embedded commission and before the portfolio level cost adjustments and the collateral interest credit, so both lines sit on one basis and the gap between them is open profit alone. The published fully-loaded track is about ten points lower over the period. Some months are not yet annotated; those show their drivers only while the research is verified.
Cumulative Performance and Drawdown
Since the January 2020 inception the portfolio has generated cumulative profit equivalent to +197.9% of the initial capital base, across 82 months. The series peaked at +204.9% in September and sits 6.95 points below that. The maximum peak-to-trough decline of -42.82 points, reached in May 2025, remains the deepest regime transition the model has traversed.
Monthly Performance Since Inception
Key Statistics Since Inception
Computed from the monthly series since the January 2020 inception. CAGR annualises the cumulative return over the capital base; the MAR ratio is CAGR divided by the maximum drawdown; win rate, profit factor and skew are measured on monthly returns.
The profile is characteristic of classic trend following: a high annualised return carried alongside a deep maximum drawdown, with the monthly distribution positively skewed. Annualised volatility of 34.1% and a MAR of 0.40, the latter measured against a maximum drawdown of 42.8 points, describe a model built to stay with large moves rather than to limit the variance of the path. The best month in the record is +28.9% and the worst -19.8%, and both sit inside the last two years.
Trade Statistics Since Inception
This section reports the portfolio on a realised, closed-trade basis since inception, the lens by which classic trend followers assess a programme. It complements the equity-curve statistics above and is stated on the trading basis, net of commission. It does not reconcile to the additive equity curve, because open positions and mark-to-market timing differ; it is a distinct, realised view rather than a restatement.
Direction: long and short participation
Of 3,760 closed trades, 73.1% were long and 26.9% short. Long positions contributed 115.5% of net trade P&L and short positions -15.5%. Eighty trades closed in October, more than double September’s thirty-two, which is what a month of reversals looks like in the realised record. The month’s result still sits largely in positions open at the close, which is why this view does not reconcile to the equity curve.
R-multiple framework
Every trade is sized to a fixed initial risk, one R, so outcomes are directly comparable across all 68 markets. Average trade expectancy is +0.18R. The average winner returned +1.58R against an average loser of -0.64R, a win-to-loss ratio of 2.48. The largest winning trade reached +35.2R while the largest realised loss was -3.0R. That asymmetry, many small losses against occasional very large gains, is the historical shape of the approach. The stop discipline is intended to contain losses, and the realised distribution shows it doing so over this period, but no observed figure sets a limit on what a future loss can be.
Distribution and skew
The distribution of outcomes in R has a skew of +6.8: a majority of small losses (median trade -0.32R, win rate 37.0%) against a small number of very large gains, with 8.1% of trades closing beyond -1R and the right tail reaching +35.2R. The shape is the mechanism rather than a by-product of it. A model that cuts quickly and holds without a profit target produces this distribution by construction, and the same asymmetry is visible in the monthly series and in the per-system breakdown, at three different time scales.
Holding period
The average trade is held 146 days and the median 87 days, consistent with a low-frequency, long-horizon profile. Long positions are held 151 days on average against 132 for shorts. The gap between the mean and the median is itself informative: a minority of positions run far longer than the typical trade, and those are the positions the record is built on.
System Analytics
The portfolio is built from seven distinct trend systems, described here as System 1 through System 7. It does not trade one of each. On every market it runs a 10-model ensemble drawn from the seven systems, with each model’s parameters tuned to that market, so a system can appear more than once on a market, with different parameters, and need not appear on all of them. Across the 68 markets that is 680 models in total. This section groups those models by the system they come from and reports the seven resulting streams: how each contributes to the return, how each behaves in isolation, and how each moves in relation to the whole. The construction and parameters of the individual systems are proprietary and are not disclosed; what follows is the performance anatomy of the ensemble, not its recipe.
A note on basis: gross versus net
The cumulative figures in this section are stated on the engine trading basis. That basis is already net of the embedded USD 5 round-turn commission and is described here as gross only in relation to the portfolio-level overlays that follow it: the per-side commission charge that replaces the embedded one, slippage, roll execution and the collateral interest credit. It is not gross of every cost. On this basis the seven systems sum to +208.8% gross. This gross figure should not be confused with the headline net return. After the full cost stack, the portfolio returned +197.9% net, as reported in Key Statistics Since Inception. The difference of 10.9 points is a portfolio-level overlay and is not attributed to any single system, which is why the per-system curves reconcile to +208.8% gross and not to the +197.9% net headline.
How the ensemble works
Each of the seven systems expresses a different rule for defining and following a trend, and each is deployed several times over, with market-specific parameters, inside the per-market ensemble. Because their dollar results are additive on the fixed $25M base, the models, and the seven systems they roll up into, sum day by day to the portfolio equity curve: nothing is left unexplained, and no system is weighted by discretion. The benefit of combining them is not that any one is exceptional, but that they are imperfectly aligned. Across the period the average pairwise co-movement between systems was 0.58, and each system’s correlation to the whole ranged from 0.67 to 0.89. These are positive throughout, so the systems are distinct rather than independent. No single system is the portfolio.
That imperfect alignment is where the diversification benefit sits. The sum of the seven systems’ standalone monthly volatilities is 12.2% a month. The portfolio’s own monthly volatility was 9.9%, roughly four fifths of that sum. The comparison measures dispersion between the systems, not total portfolio risk, and no inference about risk-adjusted performance is drawn from it here. Each system also captures a slightly different slice of every trend: some enter earlier, some hold longer, some carry more of the short side, so the ensemble stays exposed across more of each move, and through more kinds of regime, than any single rule could.
The convex, positively skewed payoff that defines classic trend following is visible at more than one level of the book. The portfolio distribution and the seven per-system distributions reported below all show the same broad shape: many small losses funding a few large winners. The per-market distributions are not shown here and no claim is made about them. Diversifying across seven expressions of that signature does not dilute it; it stabilises the path by which the result accumulates, and it keeps the programme in contact with trends that any single system would miss.
Per-system cumulative contribution since January 2020, additive on the $25M base, stated on the engine trading basis, which is net of embedded commission and before the portfolio-level overlays. The seven curves sum to the portfolio’s +208.8% trading-basis result.
Per-system return characteristics
The table below reads each system on the equity-curve basis. Contribution is additive and sums to the engine trading-basis result; the portfolio-level overlay then reconciles that result to the fully-loaded headline. The CAGR, MAR ratio, maximum drawdown and correlation are properties of each system’s own curve. Drawdowns are stated in points of the fixed $25M base, not as percentage declines in equity.
Per-system R-multiple analysis
Every trade is sized to a fixed initial risk of one R, so outcomes are comparable across all systems and markets. The table applies the R-multiple framework of Trade Statistics Since Inception to each system as a separate column, with a total that reconciles to the portfolio. The Sum of R row is the reconciling line: the seven systems’ R contributions add to 691.1R, and the Total column reproduces the portfolio’s realised figures on the frozen book of 3760 closed trades.
None of these per-system differences is visible in the blended portfolio line, and that is precisely why the blend accumulates more steadily than its parts.
System concentration this month
The since-inception figures above describe the ensemble over six and three quarter years. Within a single month the seven streams can diverge sharply, and October 2026 did. Every one of the seven lost money, which is the rarer case and the more informative one. The spread ran from -0.11 points on System 7 to -2.47 on System 2, so no single family explains the -6.95% trading result and none escaped it. Diversification across the ensemble works by holding streams that fail at different times. In a month where they all fail together, it has nothing to offset, and the loss is the cost of staying positioned for the months when they do not.
This section is regenerated each month from the same frozen book of record and the append-only monthly loader. The per-system curves are decomposed from the engine’s daily mark-to-market and continue to sum to the portfolio, so the mark-to-market variance measured against the locked baseline each month applies to the systems and to the whole on one consistent basis. The System 1 to System 7 mapping is fixed and carried forward unchanged from month to month.
Sector Attribution
Two of the eight sectors contributed in October and six detracted. Energy led with +5.62% of the $25M base on the trading basis and Meat added +0.83%. Against them, Bonds cost -3.76%, Metals -2.81%, Grains -2.65%, Equities -2.34%, Currencies -1.49% and Softs -0.35%. The spread from best to worst sector is 9.38 points against a portfolio result of -6.95%.
September and October were built from the same two blocks in opposite proportions. In September Energy and Bonds together produced more than three times the month’s result and five detractors gave back most of it. In October Energy produced +5.62 on its own and the other seven sectors removed 12.57 between them. Bonds swung from the second largest contributor to the largest detractor, a move of 6.97 points in a single month, and that swing is most of the difference between the two results.
Energy remains the year’s dominant sector contributor at +38.03% year-to-date after October’s +5.62%, and it is now the only sector positive for the year by any margin. Meat sits second at +0.20%. Every other sector is negative year to date: Currencies -0.63%, Equities and Bonds both -2.08%, Grains -2.30%, Softs -3.48% and Metals -3.97%. One sector is carrying the year.
Attribution Highlights
October’s contributors were concentrated in petroleum and its costs were spread almost everywhere else. Light Sweet Crude led at +2.14%, followed by ICE Brent Crude at +2.04%, Lean Hogs at +0.84%, Heating Oil at +0.81% and Henry Hub Natural Gas at +0.68%. On the other side Tin was the month’s largest single cost at -1.61%, ahead of the Brazilian Real at -1.44%, the Nasdaq 100 at -1.30%, Soybeans at -0.93% and Soybean Meal at -0.82%. The US Treasury curve cost across all four maturities. Twenty-one of the 68 markets finished positive, 46 negative and one unchanged, tying June for the second-lowest positive participation of 2026, behind March’s 18.
Across 2026 the petroleum complex still leads and has extended its lead again. Heating Oil is the year’s largest contributor at +16.05%, joined by Light Sweet Crude at +8.09%, RBOB Gasoline at +6.91% and ICE Brent Crude at +6.40%. Those four markets account for more than the portfolio’s entire year-to-date result, and the rest of the board nets against them. Gold is the year’s largest single detractor at -3.05%, with Platinum at -2.36% and Palladium at -1.91% behind it.
Market-Contribution Review
The since-inception contribution paths show the structure the portfolio is built to exploit: a small number of markets carrying the record over long horizons, a long tail contributing little in either direction, and the identity of the leaders changing slowly. October is the same shape read from the other end. Four energy contracts produced +5.67 points between them and the remaining 64 markets removed 12.62. A month in which the leaders keep working and everything else gives ground is not a different structure from a winning month; it is the same structure with the tail moving against it.
Trend Spotlights
Light Sweet Crude was the month’s largest single contributor at +2.14%, and Energy was the only substantial positive sector, Meat having added +0.83%. The advance that began in early September extended through October, easing in the first week without giving way, then resuming. In the week to 23 October the complex split sharply, with Brent up 6.24% and Natural Gas down 13.50%, the largest moves on the board in either direction that week. Both ran with the structures beneath them, so the book earned on both sides of the split.
ICE Brent Crude contributed +2.04% and tracked its US counterpart closely, which is the unremarkable case and worth noting for that reason. The year-to-date figures for the two have converged, Light Sweet Crude at +8.09% and Brent at +6.40%, after a September in which Brent led. Holding both through a ten-model ensemble rather than expressing one view on crude is what lets the book stay with an advance when leadership rotates inside it.
Tin was October’s largest single cost at -1.61%, and the metals complex was the month’s second largest detractor at -2.81%. The declines that have run since February deepened again, and in the final week Gold broke below its July low near 4,000 while Silver and Platinum recorded two of the three largest declines on the board. Those are trends extending, not reversing, which is the uncomfortable part: the sector cost the book while behaving exactly as a trend follower would want it to. The positions were on the wrong side of moves that persisted, and persistence is what the model is built to hold. A ten-model ensemble does not turn as one: a transition that is complete on a short lookback is still in progress on a long one, so individual models can sit on opposite sides of the same market while the sector as a whole is trending. That is how metals trends could extend through October while the sector cost the book 2.81 points.
How to Read the Trade Playback
The panel below plays October’s five largest contributing markets bar by bar: Light Sweet Crude Oil at +2.14%, ICE Brent Crude at +2.04%, Lean Hogs at +0.84%, Heating Oil at +0.81% and Henry Hub Natural Gas at +0.68%. Select a market to watch its positions develop through time. Each chart begins shortly before the earliest position still open at the October close, so the window opens on the move rather than at the start of the month. The earliest begins on 5 May 2025.
Every market is traded by a ten-model ensemble. When a model enters, a straight line traces the path from its entry to the position’s current value. A sustained trend therefore appears as a fan of trajectories opening from the different points at which the models joined the move. Green represents long positions and red represents short positions. Entries are marked by triangles and exits by crosses.
Each model’s stop is shown as a dashed red line. The stepped path records where the stop has been, while the horizontal rule shows where it stands at the selected point in time. The stop’s trailing component can only ratchet in the position’s favour, but the active level is the wider of that trailing stop and an ATR-based distance from entry. It can therefore widen when volatility expands. That occurred on 11% of open bars across these five markets.
There are 68 entries and 40 exits across the five playback windows, most originating before October. At month-end, 42 of the 50 model positions remained open. That persistence is central to the portfolio’s design. Different models enter at different stages of a trend, then remain with it until their own exit conditions are met.
Models are labelled Strategy 1 to Strategy 10 according to their position within each market. The numbering does not carry from one market to another, and the construction and parameters of the individual systems are not disclosed.
The contribution figures use the engine trading basis, before portfolio-level cost adjustments and collateral interest. They therefore do not necessarily reconcile to the fully-loaded headline return. Playback ends on 30 October, with every open position marked to the final valid close of the reporting month.
Trade playback
The five largest contributors in October 2026, played bar by bar from the start of the move. Each market runs a ten-model ensemble, and each model carries its own stop. Each trade draws a straight line from its entry to where it stands now, so a long trend shows as a fan of trajectories opening from the points the ensemble stepped in. Stops are the dashed red lines. The trailing component only ratchets, but the stop sits at the wider of that and an ATR distance from entry, so it can widen when volatility expands. That happened on 11% of open bars here.
Click the panel, then space plays and pauses and the arrow keys step one bar. Click a strategy to isolate it, click again to show all ten. Green marks longs and red marks shorts; entries are triangles and trajectories are solid lines. Exits are red crosses, whichever way the trade was facing. Stops are dashed red throughout: the stepped path is where a stop has been, the rule across the chart is where it sits now. Playback ends 30 October, with each open position marked to the final valid close for the reporting month.
Sector Rundown
The Trend Environment
The barometer ran 52%, 50%, 36%, 41% and 36% over the five weeks of October. Two readings sit below the 40% line that marks a cold environment and none reached the 55% favourable threshold. The SG Trend Index, an external industry index and not a measure of this book, read -0.08%, +0.28%, -0.73%, -1.29% and -0.77% month-to-date at the Friday closes of 2, 9, 16, 23 and 30 October, finishing the month at +14.92% year to date against +15.72% at the start. Source: ATS This Week in Trend, 2, 9, 16, 23 and 30 October 2026. The final week is the one worth sitting with. Breadth thinned to 14 of 49 contracts higher and the barometer fell 5 points, yet the external index rose and this book lost 4.36%. Three measures of the same week pointing three different ways is a reminder of how little any one of them says about a particular portfolio.
The Lesson of the Month
The lesson for October is that a broad loss is not evidence of a broken environment. Of the ten largest moves on the board in the final week, all ten were declines and eight ran with the structures already beneath them. The metals extended trends that have run since February. Lean Hogs and Lumber moved to new lows. What cost the book was not an absence of trends but a change in which markets had them, and the speed of that rotation. Bonds moved to new lows early in the month and then rose inside those declines from mid-month, which is the shape that costs a trend book most: enough movement to stay positioned, enough reversal to pay for it. The portfolio gave back 6.95 points and remains +23.1% for the year on the back of one sector.
Monthly Wrap
October returned -6.95%, the third largest loss of 2026 and the fourth losing month of the ten, and it took the cumulative track from its September peak to +197.9%. The result came from Energy at +5.62% and Meat at +0.83% on the trading basis against six detracting sectors, with Bonds the largest at -3.76%. All seven system families lost money. The year to date stands at +23.1%. Commission, slippage and roll execution deducted 0.20 points, including 0.11 points of roll execution. Replacing the engine’s embedded commission added back 0.02 points, while collateral interest at 4.05% added 0.18 points. The complete overlay changed the month by less than 0.01 point, so both the trading and fully-loaded returns round to -6.95%.
Looking Ahead
The barometer at 36%, four points below the line that separates a cold environment from the Neutral band and with breadth narrowing for a third consecutive week, describes a board on which fewer markets are trending than at any point since late July. The petroleum advances remain in place and were the month’s largest source of positive contribution. The precious metals declines deepened again and Gold broke its July low. The grain contracts that sat at the top of their charts in September have given that ground back. The book carries all three into November. Whether a cold reading persists or the board reorganises is the question November answers, and it is not one this report forecasts.
About these figures
All figures are generated by the ATS Classic Trend engine from back-adjusted continuous futures data across the sixty-eight-market universe. Returns are stated on a fully-loaded, pre-fee basis: net of estimated commission, a conservative slippage allowance and roll-execution costs on every trade and contract roll, and inclusive of collateral interest earned on the un-margined capital at the US 90-day Treasury bill rate. They are dollar profit and loss on a twenty-five million dollar capital base, additively. Results do not include performance or management fees, which would reduce the returns shown. Contribution figures are additive and sum to the engine trading-basis result at the sector and market level. The portfolio-level overlay then reconciles that result to the fully-loaded headline. This report is a benchmark study and is not investment advice or an offer of any product.
Richard Brennan writes on systematic trading, complex adaptive markets, and the philosophical foundations of trend following at atstradingsolutions.com. His books include The Fractals of Finance, Complex Adaptive Markets, Carved by Impossibility and The Aussie Turtles Trend Following Guide.
Want to explore why structure exists at all?
Carved by Impossibility: What Remains When Everything Else Is Eliminated
The book explores the architecture of constraint, emergence, and reality itself, and what it means for how we understand markets, life, and the universe.
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Want the theoretical foundation for why trend following works?
The Fractals of Finance: Determinism, Adaptation and the Geometry of Markets bridges complexity science with practical trading implementation. With a foreword by Jerry Parker, original Turtle Trader.
Available now on Amazon in paperback, hardcover, and Kindle.
Want a practical field manual for trading trends and capturing outliers?
The Aussie Turtles Trend Following Guide: A Field Manual for Hunting Outliers adapts the timeless principles of the original Turtle traders into a systematic, rules-based approach for modern markets. Co-authored with Adam Havryliv.
Available now on Amazon in paperback, hardcover, and Kindle.