LIVE SINCE SEPTEMBER 2026 · IBKR-DOCUMENTED TRACK RECORD

Systematic futures.
AI-optimized.
Sequentially deployed.

Nine momentum signal streams. Nikkei 225 · DAX 40 · Nasdaq 100.
One session at a time. The same capital recycled across all three markets.
No overlap. No overnight positions. Capital efficiency built in.

New to IBKR? Open an account first →
+33.49%
Return · Sep 2026
−9.91%
Max Drawdown
3.38×
Return / Max DD
62.5%
Win Rate · Daily
$12,661
NAV · Live IBKR

The Idea

How one capital base trades three markets

One capital base. Three trading sessions. Nikkei, DAX and Nasdaq trade in different windows. After one session's positions close, available margin can support trades in the next. One brokerage account can therefore trade all three markets without reserving a separate capital pool for each.

Separate capital pools
$100,000 for Nikkei: +1% = +$1,000
$100,000 for DAX: +1% = +$1,000
$100,000 for Nasdaq: +1% = +$1,000
+1%
$300,000 reserved → $303,000
Capital reused in sequence
Nikkei: $100,000 → $101,000
DAX: $101,000 → $102,010
Nasdaq: $102,010 → $103,030
+3.03%
$100,000 reserved → $103,030
Three trading windows using one capital base

What drives the result
The main advantage is using the same capital across three trading windows. In this illustration, roughly the same dollar opportunity requires $100,000 of reserved capital instead of $300,000. Reinvesting gains between sessions adds $30; capital reuse accounts for most of the difference.

Illustrative example. Actual session returns vary; position sizing updates between sessions in the live strategy.

Why three markets improve risk-adjusted returns
Nikkei, DAX and Nasdaq are largely uncorrelated — when one session loses, the others frequently win. This diversification reduces overall equity volatility relative to trading any single market. The result: the combined three-market portfolio produces a higher Sharpe and Calmar ratio than any individual market alone. Reusing capital across sessions compounds this advantage, turning a structural inefficiency into a measurable edge.

Human Idea, AI-Built System

The idea came from a person: the trend in Nasdaq futures found in the 2003 Princeton thesis (see the Research tab). AI took it from there — extending it to Nikkei and DAX, splitting it into 9 signal streams, tuning each one per market, and writing the code that now trades all three markets automatically.

Background & Research

The academic foundation behind the strategy — intraday momentum is one of the most replicated anomalies in finance. Here is why it exists, why it persists, and how Fable Fund captures it.

Origin — Princeton MFin Thesis, 2003
The Finding
Statistically significant trend alpha in Nasdaq futures — found at a time when academic consensus favoured market efficiency. The pattern was systematic, repeatable, and not explained by risk factors.
The Gap
The thesis was theoretical. The infrastructure to trade it — real-time data, execution systems, multi-market access — did not exist cost-effectively for a small operator in 2003. Twenty years of technology change closed that gap.
Today
AI extended the Nasdaq finding to Nikkei and DAX, split it into 9 signal streams, tuned each one, and wrote the code that trades it automatically. An academic finding is now a live trading system.
The Evidence — Statistical Significance
R² 1.6%
First half-hour return predicts last half-hour. Gao et al. (JFE, 2018) — documented across S&P 500, 10 ETFs, and two major international index futures.
1,985%
Net total return of an intraday SPY trend strategy 2007–2024. Zarattini et al. (SSRN, 2024). Sharpe 1.33 — comparable structure to Fable's NQ streams.
Multi-market
Effect replicated in China and Japan (Pacific-Basin Finance Journal, 2023), structurally explained by dealer gamma-hedging flows (Baltussen et al., 2021).
Why It Persists
Structural, not statistical noise
Baltussen et al. link the effect to dealer gamma-hedging — a structural flow mechanism. Dealers hedging options positions create predictable directional pressure that persists through the session.
Too small to arbitrage away
R² of 1.6% is meaningful but not large enough for institutional capital. The trade sizes needed to capture it are small — below the threshold where large funds cause market impact. This keeps the edge intact for smaller operators.
Confirmed across regimes
Replicated across bull markets, bear markets, high and low volatility. The 2020 COVID crash (19-year history) and the 2022 rate shock (5-year backtest) are both covered — the strategy was positive through both.
Fable Fund's Edge
Sharpe 2.83 vs typical CTA ~0.8
The strategy's Sharpe ratio is 3.5× the industry average for systematic CTAs. Sortino of 7.84 — penalising only downside volatility — is stronger still. Right skew of +1.69 means large wins outweigh large losses.
Payoff ratio 1.79× on 48% win rate
The strategy wins less than half the time but makes 1.79× more on wins than it loses on losses. Profit factor 1.67. This negative-selection, positive-expectation profile is characteristic of high-quality systematic strategies.
3 uncorrelated markets amplify the edge
The same anomaly runs independently across Nikkei, DAX, and Nasdaq. Low cross-market correlation means losses in one session are frequently offset by gains in another — portfolio Sharpe exceeds any individual market.
Academic Support
Market Intraday Momentum
Gao, Han, Li & Zhou · Journal of Financial Economics, 2018
First half-hour return on the S&P 500 (SPY) predicts the last half-hour return, R² of 1.6% — also found across ten other ETFs and two major international equity index futures. Basis for the NQ long and short streams.
Beat the Market: An Effective Intraday Momentum Strategy for S&P500 ETF (SPY)
Zarattini, Aziz & Barbon · SSRN working paper, 2024
Trend-following intraday SPY strategy: 1,985% net total return (2007–2024), 19.6% annualised, Sharpe 1.33. Independent replication of the same family of strategies — different implementation, same underlying anomaly.
Hedging Demand and Market Intraday Momentum
Baltussen et al., 2021
Links the intraday momentum effect to dealer gamma-hedging flows — the structural mechanism that creates the predictable intraday patterns and explains why the edge does not arbitrage away.
Princeton MFin Thesis — Dynamic Trend Optimization
Fable Fund Founder et al., 2003 · Bendheim Center for Finance
Original discovery of statistically significant trend alpha in Nasdaq futures. Written before independent academic research documented the same effect more broadly. The starting point for everything that followed.

The Princeton Anomaly

In 2003, a Princeton thesis found a repeatable trend in Nasdaq futures.
Fable Fund trades that pattern today — in Nasdaq, and in two more markets: Nikkei and DAX.
One account trades all three, one after another, every day. Nothing is held overnight.

3
Markets in a Row
Nikkei in Tokyo, then DAX in Frankfurt, then Nasdaq in New York. The sessions never overlap.
9
Signal Streams
Three per market: a daily long, a daily short and a 2-hour trend. The long and short never fire on the same day.
0
Overnight Positions
Every trade closes before its session ends. No risk carried from one day to the next.
1,343
Backtest Days
All 9 streams, Sep 2021 – Sep 2026. A longer 19-year history (2008–2026) is shown below at the Balanced tier.
One Account, Used Three Times

Because the sessions don't overlap, the same money trades all three markets. Each session starts where the last one finished, so a good morning in Tokyo means a slightly bigger position in Frankfurt.

Margin for One, Not Three

Only one market is open at a time, so margin is needed for the largest session only — not all three added together. DAX is the largest, so it sets the requirement.

Markets That Move Differently

Tokyo, Frankfurt and New York often move in different directions, so a bad day in one is often offset by another. Together they run smoother than any single market.

Built With AI

The original research covered Nasdaq only. AI extended it to Nikkei and DAX, split it into 9 streams, tuned each one per market, and wrote the code that trades it every day.

3-Market CAGR
18.9%
No leverage
3-Market Sharpe
2.62
No leverage
Max Drawdown
−6.5%
No leverage
Sharpe · All Tiers
2.83
Leverage changes size, not Sharpe
Sortino
7.84
Counts only losing days
Positive Years
19/19
2008–2026 · Balanced tier
Max Leverage
18.3×
Performance tier · DAX sets margin
Balanced Tier — Equity Curve (2021–2026)
Annual Returns — Balanced Tier (2008–2026) Zero losing years
Balanced Tier — Drawdown
Max Drawdown by Year — Balanced Tier (2008–2026)

9 Streams

Each stream run on its own at unit weight (1×).
Designed SL = the most common loss size — what the stop is set to.
Max Lev = 7.5% daily loss budget ÷ designed SL.

CAGR by Stream
Stream Scorecard — Full Stats
StreamTotal RetCAGRSharpe CalmarMax DDWorst Day Des. SLMax LevWin RateTrades 202120222023202420252026
Sharpe vs CAGR
Annual Returns Heatmap
Live Position Sizing — Current Deployment IBKR Live
MNQ margin / notional
6.9%
$4,235 / $42,000 · NQ session
FDXS margin / notional
2.7%
$7,425 / $275,000 · DAX binding
N225MC margin / notional
11.1%
$461 / $4,136 · NK session
Max leverage
18.3×
DAX session binding · single session / NAV
YearNAV Start NQ LongNQ ShortNQ Super NK LongNK ShortNK Super DAX LongDAX ShortDAX Super Ann Ret
Contracts scaled to NAV start of each year at live leverage ratios. Historical prices were lower — same margin % meant lower dollar margin per contract — so more contracts per $15k in earlier years. Binding margin = max single session only (sequential, not additive).

Portfolio Models

Same 9 streams, three ways to fund them.
Model C (sequential, compounding) is the live model — this is what runs on IBKR.

Model A · EW 9 Streams
$13,350
CAGR 6.0% · Sharpe 2.61 · Max DD −2.2%
Vol 2.1% · Calmar 2.70
1/9th weight per stream, independently
Model B · EW 3 Markets · Baseline
$23,750
CAGR 18.9% · Sharpe 2.62 · Max DD −6.5%
Vol 6.3% · Calmar 2.92
Daily+Super combined per market, equal weight
Model C · Sequential Compound ✦ Live
$126,100
CAGR 66.2% · Sharpe 2.63 · Max DD −18.3%
Vol 19.0% · Calmar 3.62
Capital compounded across all 3 markets daily
Live Account · IBKR Verified
Sep 2026→
Model C live on IBKR since Sep 2026 (2021–26 is backtest)
Sequential compound · all 9 streams active
Verification tab → full statement data
Equity Curves — All 3 Models (% return)
Drawdown Comparison
Model Comparison Table
Model$10k →CAGRSharpeMax DDCalmarAnn VolWin Rate
A · EW 9 Streams$13,3506.0%2.61−2.2%2.702.1%51%
B · EW 3 Markets$23,75018.9%2.62−6.5%2.926.3%52%
C · Sequential ✦ Live$126,10066.2%2.63−18.3%3.6219.0%51%
Model C is the live deployment model. After each session closes, updated account equity determines sizing for the next. Nikkei gains increase the DAX position; DAX gains increase the Nasdaq position. Each session compounds the last — this is what drives the intraday return amplification.
Annual Returns — Models A, B, C
Annual Returns (2008–2026) Zero losing years

Optimal Allocations

8 risk tiers. Same 9 streams, same strategy — only the position size changes.
Preservation to Performance: choose the daily loss limit that fits your risk appetite.
Backtested Sep 2021–Sep 2026. 2026 is a partial year.

CAGR
—
Need 20+ days
$10k Grows To
—
Sep 2021–Sep 2026
Sharpe
—
Daily basis
Max Drawdown
—
Peak-to-trough
Worst Day
—
Designed SL-based
Calmar
—
CAGR / Max DD
Max Leverage
—
Max single session / NAV
Ann. Vol
—
Need 20+ days
Equity Curve — Log Scale —
Drawdown Profile
Per-Stream CAGR — Unit Weight
Annual Returns —
Per-Stream Leverage & Max Loss Contribution
StreamWorst DayMax Solo Lev Alloc LevMax Loss% Budget Risk Bar
PORTFOLIO TOTAL — —
Risk-Return Frontier — 8 Tiers
All 8 Tiers — Side by Side
#AllocationMax Daily LossMax LeverageCAGR$10k →Max DDSharpeCalmarVolMin Annual
1 Preservation -0.68% 1.3× 14.4% $20k -3.5% 2.83 4.06 4.8% +6.4%
2 Conservative -1.5% 3.0× 34.0% $48k -7.7% 2.83 4.44 10.6% +14.5%
3 Moderate -2.5% 4.9× 62.0% $131k -12.5% 2.83 4.95 17.6% +24.8%
4 Balanced -3.25% 6.4× 86.0% $273k -16.0% 2.83 5.37 22.9% +32.9%
5 Growth -4.5% 8.9× 133.0% $907k -21.6% 2.83 6.16 31.7% +46.9%
6 Dynamic -6.0% 11.8× 202.2% $3.6M -27.9% 2.83 7.25 42.2% +64.5%
7 Aggressive -7.75% 15.2× 304.1% $17.1M -34.7% 2.83 8.77 54.6% +86.2%
8 Performance -9.3% 18.3× 416.8% $63.3M -40.3% 2.83 10.35 65.5% +106.2%

Risk & Drawdown

19 years of data. 19 positive years.
Every major market crisis from 2008 to 2026 — the strategy came through all of them and kept compounding.
Shown at Balanced tier throughout.

19-Year Max DD
−17.7%
Balanced tier · worst year 2011/2015
19/19
Positive Years
Zero losing years · 2008–2026
Major crises survived
8
2008 · 2010 · 2011 · 2015 · 2018 · 2020 · 2022 · 2025 · all positive
Worst losing streak
12 days
19-year record · Feb 2015
Annual Max Drawdown by Year — 2008–2026
Annual Return vs Intra-Year DD — 2008–2026
19-Year Monthly Return Heatmap — 2008–2026 · Balanced Tier Zero losing years
+81.2% in 2008 financial crisis · +96.6% in 2020 COVID crash · +232.7% in 2022 rate shock · 19 consecutive positive years · Balanced tier
Major Market Events — 19-Year Record All positive
YearEventAnnual Return · BalancedMax DD · Balanced
2008Global Financial Crisis — Lehman collapse+81.2%-10.4%
2010Flash Crash — May 6 market plunge+52.0%-9.3%
2011US debt ceiling crisis / European debt crisis+12.1%-10.9%
2015China devaluation — global selloff+10.0%-11.1%
2018Vol spike (Feb) + US-China trade war+69.2%-6.5%
2020COVID-19 crash — fastest bear market in history+96.6%-7.4%
2022Fed +425bp rate shock · BOJ intervention · Russia-Ukraine+232.7%-8.1%
2025Trump Liberation Day tariffs — global selloff+45.6%-5.6%
Returns shown at Balanced tier (−3.25% max daily loss). The strategy trades both long and short intraday — market direction does not determine outcome.
Risk Framework — fixed rules, every session
Hard daily loss stop
Every session runs with a fixed daily loss ceiling. Once hit, trading stops for that session — protecting the rest of the day's capital.
Flat at session close
Every position closes within its session window. No overnight exposure, no cross-session carry, no gap risk held through the close.
Volatility-scaled sizing
When VIX rises, position size reduces and stops widen automatically — maintaining consistent risk exposure regardless of market conditions.
Independent session budgets
Each market has its own position size and loss budget. A bad Nikkei session doesn't affect the DAX or Nasdaq allocation.

Dynamic Sizing

Your live leverage ratios (NDX 1+1+2 MNQ, NIKKEI 16+7+20 N225MC, DAX 4+2+3 FDXS at ~$15k) scaled back through time.
Historical prices were lower → same margin % meant less dollar margin per contract → more contracts per $15k.
Binding margin = largest session only (sequential).

MNQ margin / notional
6.9%
$4,235 / $42,000
FDXS margin / notional
5.2%
€1,349 / €25,788
N225MC margin / notional
11.1%
$461 / $4,136
Live binding margin
~110%
Of NAV (tight — sequential)
Contract Counts by Year — Live Leverage Ratios
YearNAV Start NQ LNQ SNQ SUP NK LNK SNK SUP DAX LDAX SDAX SUP ReturnMax DD
At current leverage ratios, $15k compounded over the 5-year backtest period would have grown to $4.0B — shown here as a leverage illustration only, not a projection or achievable outcome.

Verification

Trade data, not marketing numbers

1
IBKR Flex Query
Trades exported directly from the broker
→
2
Structured record
Converted to a dated trade log
→
3
SHA-256 hash
Each file's fingerprint is recorded
→
4
Published record
Hash and log posted publicly
→
5
CPA reconciliation
Independent monthly check

The hash confirms a published file hasn't been altered after the fact — it does not by itself confirm the file was complete or accurate when created. That's what the broker source and CPA reconciliation are for. Account numbers and client-identifying details are never included in anything published publicly.

Important Disclosures

Past performance is not indicative of future results. Futures trading involves risk of loss. All positions close intraday — no overnight exposure. Fable Fund operates as an Exempt CTA under NFA rules. Capital reuse across three uncorrelated sessions amplifies returns while diversification across markets moderates overall risk.

Fable Capital Management LLC, operating as Fable Fund, is an Exempt CTA under NFA rules. Advisory activity is limited to family, friends, and existing personal relationships. This site is not a public offering and nothing here constitutes investment advice.

Research cited above documents general intraday momentum patterns in index and ETF markets; it does not constitute independent verification of Fable Fund's strategy or results.

Trade Analytics

Return distribution, tail risk, rolling performance and monthly breakdown.
Computed from 1,343 trading days, Sep 2021–Sep 2026.
All figures at the Performance tier (T8) — scale down proportionally for your chosen tier.

Mean Daily Return
+0.98%
Arithmetic mean · 1,343 days
Skewness
+1.69
Right-skewed — wins larger than losses
Excess Kurtosis
5.56
Fat tails — large moves more common
Win Rate
48.2%
648 up days / 695 down days
Payoff Ratio
1.79×
Avg win +5.09% / avg loss −2.84%
Sortino Ratio
7.84
Penalises downside vol only — right for this strategy
Return Distribution — Daily % · T8 Skew +1.69
Rolling Sortino — 1-Year Window Downside vol only
Tail Risk — Daily (T8 Performance)
MetricValueInterpretation
VaR 95%−5.62%1-in-20 day loss exceeds this
VaR 99%−7.81%1-in-100 day loss exceeds this
CVaR 95%−6.96%Expected loss on worst 5% of days
CVaR 99%−9.16%Expected loss on worst 1% of days
Worst day−12.43%Dec 20 2022 · BOJ shock
Best day+40.64%Nov 10 2022 · CPI reversal
Positive skew (+1.69) means the right tail is fatter than the left. The best day (+40.64%) is 3.3× larger than the worst day (−12.43%) in absolute terms — convexity working in the investor's favour.
Streak Analysis
MetricWinLoss
Max streak12 days11 days
Avg streak1.9 days2.1 days
Total days648695
Avg return+5.09%−2.84%
Win streaks and loss streaks are nearly symmetric in duration (avg 1.9 vs 2.1 days). The edge comes from asymmetry in magnitude — up days are 1.79× larger than down days on average.
Monthly Return Heatmap — T8 Performance
Return Convexity — Why Skew Matters
Worst quintile
−4.86%
avg daily
Q2
−2.13%
avg daily
Q3 (median)
−0.12%
avg daily
Q4
+2.66%
avg daily
Best quintile
+9.39%
avg daily
The best quintile (+9.39% avg) is 1.93× the magnitude of the worst quintile (−4.86% avg). Positive convexity: the strategy captures more of the upside than it gives back on the downside — the defining characteristic of a right-skewed return distribution.