“A portfolio is not paid for the size of the moves around it. It is paid for the share of them it was already holding, and the two can point in opposite directions for weeks at a time.”
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 compounding through trending years with sharp monthly declines and deep drawdowns when trends reverse. June’s -19.72% and August’s +12.27%, ten weeks apart, are characteristic of the strategy rather than departures from it, as is the -42.83 point peak-to-trough decline of 2024 to 2025.
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
August returned +12.27%, following July’s +10.72%, and the gains came from more places this time. The grain complex was the largest contributor at +3.75 percentage points on the trading basis, with Metals adding +2.71 and Energy +2.70. Six of the eight sectors contributed positively against four in July, and the two that did not, Currencies at -0.19% and Meat at -0.04%, cost little between them. Together July and August added 22.99 points on the fixed capital base, more than offsetting June’s -19.72% though not the combined May and June decline of 23.19 points. The portfolio finished August at a cumulative +202.4%, 0.2 points below its April high.
The month’s weekly path is worth setting out, because it does not say what the trend environment said. Decomposed from the daily per-system curves, the portfolio returned +3.16%, +3.98% and +5.46% through the first three weeks, then -0.26% in the fourth. Those weekly figures are stated on the engine trading basis, before the portfolio-level cost and interest adjustments, and sum to the +12.34% trading result rather than to the +12.27% fully-loaded headline. The third week was the strongest of the month and the fourth was the only losing one. The trend environment ran the other way. The TTU Barometer made its largest jump of the month in that third week and reached its highest reading in the fourth. The SG Trend Index, an external industry index and not a measure of this book, recorded August month-to-date figures of -0.75%, +0.83%, +1.13% and +1.66% at the weekly closes of 7, 14, 21 and 28 August, the last of these covering the month through 28 August rather than to the 31 August close. Its implied weekly changes were -0.75, +1.58, +0.30 and +0.53 points. Its smallest advance fell in the week this portfolio gained most, and it advanced +0.53 in the week this portfolio lost. Source: ATS This Week in Trend, 7, 14, 21 and 28 August 2026, each quoting the SG Trend Index month-to-date reading as of that Friday’s close. The divergence is the month’s most instructive feature and is examined below. The year-to-date figure now stands at +27.0%.
The Month, Week by Week
The TTU Trend Barometer ran 34%, 39%, 50% and 55% across the four weeks of August, a straight-line recovery that reclaimed all 22 points lost in the late July collapse and finished three points above the 52% that preceded the fall. It crossed from the cold band into Neutral in the third week and reached 55% in the fourth, the upper boundary of Neutral; a favourable reading requires a move above 55%.
Performance Snapshot
August net return of +12.27% against July’s +10.72%. The month is the third largest of 2026, behind April’s +15.34% and January’s +14.43%, and the twelfth largest of the 80 months since inception. The month-by-month comparison with 2025 shows 2026 running a far wider range in both directions, with a -19.72% month and five above +10% inside eight months.
Cumulative Performance and Drawdown
Since the January 2020 inception the portfolio has generated cumulative profit equivalent to +202.4% of the initial capital base, added month by month on the fixed denominator rather than reinvested. The April 2026 high of +202.6% has not been regained: the portfolio sits 0.201 points below it, against 12.5 points at the end of July and 23.2 at the end of June. The drawdown panel below places that in context. The -42.83 point decline between the March 2024 peak and the May 2025 trough remains the deepest the track has produced, and July and August together have returned the portfolio to within a fifth of a point of its high water mark without quite reaching it.
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 compound return carried alongside a deep maximum drawdown and elevated volatility, a win rate just above half, and a positive skew, the small-losses-and-occasional-large-gains shape the strategy is built to produce. August lifted the cumulative figure to +202.4% and the CAGR to 18.1% without moving the maximum drawdown, which remains anchored to the 2024 to 2025 decline. Both the cumulative return and the drawdown are stated on the additive basis, as percentage points of the initial capital base. Measured instead against the running model-equity level, the same monthly path gives a peak-relative maximum drawdown of 14.74%. The MAR ratio of 0.42 uses the additive drawdown denominator and should be read on that basis when set against other managers.
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 3,648 closed trades, 72.7% were long and 27.3% short. Long positions contributed 115.2% of net trade P&L and short positions -15.2%. Twenty trades closed in August: the month’s result sits almost entirely in positions still open at month-end, which is precisely why this realised view does not reconcile to the equity curve. The grain trends that drove the month were still running at the close.
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 +0.19R. The average winner returned +1.60R against an average loser of -0.64R, a win-to-loss ratio of 2.51. 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 -0.33R, win rate 36.9%) funded by a small number of very large winners. The top 5% of trades account for 169% of total R; the remainder, in aggregate, net negative. This fat-tailed payoff is the shape the Fractals of Finance research examines, and it is why discipline through the many small losses is the price of capturing the few outsized, regime-defining trends. The figures here describe the portfolio distribution since inception; they are not a claim that every market or system reproduces it individually.
Holding period
The average trade is held 146 days and the median 86 days, consistent with a low-frequency, high-conviction programme. Holds range from same-day stop-outs to a single position carried for 1,376 days. Long trades are held slightly longer on average (151 days) than shorts (133 days), reflecting the longer duration of the dominant upward trends over the period.
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 +212.6% gross. This gross figure should not be confused with the headline net return. After the full cost stack, the portfolio returned +202.4% net, as reported in Key Statistics Since Inception. The difference of 10.2 points is a portfolio-level overlay and is not attributed to any single system, which is why the per-system curves reconcile to +212.6% gross and not to the +202.4% 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 0.68 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 12.3% 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 +212.6% 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 portfolio; the CAGR, MAR ratio, maximum drawdown and correlation are properties of each system’s own curve.
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 684.0R, and the Total column reproduces the portfolio’s realised figures on the frozen book of 3648 closed trades.
None of these per-system differences is visible in the blended portfolio line, and that is precisely why the blend compounds more steadily than its parts.
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
Six of the eight sectors contributed in August, against four in July. The grain complex led with +3.75% of the +12.34% trading total, with Metals at +2.71% and Energy at +2.70% behind it, and Softs, Equities and Bonds all positive. Currencies at -0.19% and Meat at -0.04% were the two detractors. The month and year-to-date contributions each sum to the portfolio trading result.
This is a different shape of month from July, and the contrast is instructive. July’s +10.67% came almost entirely from one complex; August’s +12.34% came from three, with two more adding meaningfully and the two detractors costing 0.23 points between them. The book did not become better diversified between the two months. What changed is that separate trends established themselves in separate places at the same time, which is the condition a trend follower waits through long stretches of concentration to meet.
Energy remains the year’s largest sector contributor at +24.93% year-to-date after August’s +2.70%, though the month’s contribution came from the products rather than crude, which surrendered in the final week most of what it had taken in the two before. The more significant change beneath the totals is the grain complex, which has moved from a detractor through the middle of the year to +1.87% year-to-date on the strength of August alone, and the Metals, which have turned positive at +1.19% for the first time since the February highs. Softs remain the year’s weakest sector at -2.57%.
Attribution Highlights
August’s contributors were spread across four complexes rather than clustered in one. Heating Oil led at +1.29%, with Soybeans at +1.13%, Zinc at +1.04%, Gold at +0.90% and RBOB Gasoline at +0.81%. The month’s detractors were few and small: the Brazilian Real at -0.68% was the only market to cost more than half a point, followed by Corn at -0.35% and Live Cattle at -0.30%. Corn is worth noting against the price table: the contract rose 15.89% over the month and still detracted, which is what happens when a market turns while the book is positioned the other way.
Across 2026 the petroleum complex still leads. Heating Oil is the year’s largest contributor at +12.11%, joined by RBOB Gasoline at +5.44% and Light Sweet Crude Oil at +4.81%, with Zinc at +2.85% the first non-energy market to reach the leading group this year. The year’s detractors remain the precious metals, Palladium at -2.07%, Gold at -1.86% and Platinum at -1.79%, all three of which spent August recovering ground inside declines that have run since February without clearing them.
Market-Contribution Review
The since-inception contribution paths show a familiar structure at the portfolio scale: a handful of durable trends carry the result, and the leaders rotate by regime. The petroleum complex separated from the field through the first half of 2026 and has flattened since, while the grain complex has turned up sharply from a base that had been drifting for most of the year.
Trend Spotlights
Heating Oil is the month’s largest single contributor for the second month running, at +1.29%. The contract rose 6.65% over August and, as in July, held what crude gave back: WTI and Brent both surrendered in the final week the ground that had carried them beyond the origin of the July decline, while Heating Oil finished the month higher.
Soybeans show the shape the month was built on. The contract added 6.10% and contributed +1.13%, and the pattern matters more than the size: three consecutive weekly advances into the highest levels on the chart, in a complex that took all eight of its contracts higher in the final week and seven of them to chart highs. This is a trend establishing itself and then extending, which is the kind the model can hold for long.
The Brazilian Real was August’s largest single cost at -0.68%, and it cost through indecision rather than through a break. The contract finished the month 0.47% lower, having been moved twice by a dollar that fell as a single common factor across the whole basket in the third week and rose as one in the fourth. Two coordinated weeks pointing in opposite directions leave a book positioned in either direction paying for both.
Sector Rundown
The Trend Environment
The barometer ran 34%, 39%, 50% and 55% over the four weeks of August, opening six points below the Neutral floor and closing at 55%, the upper boundary of Neutral. The path matters more than the destination, and this month the path and the portfolio disagreed. The largest jump in the reading, 11 points in the third week, coincided with the portfolio’s strongest week at +5.46%, even though much of the movement the barometer registered was counter-trend: the precious metals recovering inside declines that have run since February, and the petroleum complex retracing its July fall. The final week, with the reading at its highest and breadth collapsed from 31 contracts to 21, cost the portfolio -0.26%, because the interruptions stopped and metals and crude resumed the declines those rallies had interrupted. Trend strength measures the persistence available on the board. The return records what a particular book was holding while that persistence played out, and the two are different measurements. That the same signature appears at the weekly, monthly and multi-year scales is the point the Fractals of Finance research keeps returning to: what separates a cost from a gain is where in the sequence the exposure was established, not how far price travelled.
The Lesson of the Month
August is a reminder that the environment reading and the portfolio result answer different questions, and that a strong reading is not a claim on any particular book. The month’s highest barometer reading fell in the week this portfolio lost money, and the portfolio’s largest weekly gain fell in the week the SG Trend Index advanced least on its month-to-date readings of 7, 14, 21 and 28 August. Neither figure is wrong. They describe the persistence available on the board and the persistence a particular book was holding, and only the second one is what the model is paid on.
Monthly Wrap
August returned +12.27%, the third largest month of 2026 and the twelfth of the 80 months since inception, and completed the offset of June’s decline. The grain complex was the largest contributor at +3.75%, taking all eight of its contracts higher in the final week and seven to chart highs, with Metals at +2.71% and Energy at +2.70% behind it. Six of eight sectors contributed, with Currencies at -0.19% and Meat at -0.04% the only detractors. The barometer recovered every point it lost in the late July collapse to finish at 55%, the upper boundary of Neutral. The year-to-date figure stands at +27.0% and the since-inception track at +202.4%, with the portfolio 0.2 points below its April high.
Looking Ahead
The barometer at 55%, the upper boundary of Neutral, and still rising describes a board on which several separate structures have established themselves at once. Three questions carry into September. Whether the grain complex extends a fourth and fifth week or stalls at the chart highs seven of its contracts have just reached. Whether the metals, which turned lower again in the final week without ever clearing their February highs, resume the decline or make a second attempt. And whether the dollar, having moved the entire currency basket in opposite directions two weeks running, settles on one. The model will not answer any of them in advance. It will hold what persists and release what does not.
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 portfolio result at the sector and market level. 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.
Available now on Amazon in paperback, hardcover, and Kindle.
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.