THETA GROUP RESEARCH

Historical Performance

Historical Performance

The Adaptive Trade Portfolio (ATP) Framework is a rules-based SPX options portfolio built around four distinct trade structures designed for different market conditions. The current version has been tested across 10 years of historical data, from August 1, 2016 through July 31, 2026. The framework combines defined entry times, moving-average alignment, structure-specific pre-entry filters, and adaptive position sizing to create a highly systematic process with minimal trade management.

The Adaptive Trade Portfolio (ATP) Framework is a rules-based SPX options portfolio built around four distinct trade structures designed for different market conditions. The current version has been tested across 10 years of historical data, from August 1, 2016 through July 31, 2026. The framework combines defined entry times, moving-average alignment, structure-specific pre-entry filters, and adaptive position sizing to create a highly systematic process with minimal trade management.

Historical and backtested results are presented to illustrate the characteristics of the framework and should not be interpreted as guarantees of future performance.

10 Years

Historical Backtesting

2,325 Trades

Filtered Historical Sample

+$280,049

Total Backtested P/L

-$3,594

Maximum Historical Drawdown — One 10-Wide Lot

+$28,005

Average Annual P/L

Nearly 8:1

Average Annual P/L / Max DD Ratio

643 Trades

Filtered Out by Pre-Entry Rules

22%

Approximate Portion of Original Trades Removed

The original time-based, near-zero-management version contained 2,968 trades and produced a Max DD of approximately -$5,632. The current pre-entry filters reduced the historical sample to 2,325 trades and reduced Max DD to -$3,594.

Performance Dashboard

10 years of backtested portfolio performance

Combined backtested ATP portfolio performance, August 2016 through July 2026.

Drawdown Statistics

Drawdown Statistics

Performance is only meaningful when viewed alongside risk.

Performance is only meaningful when viewed alongside risk.

The current ATP portfolio produced a maximum historical drawdown of approximately $3,594 per 10-wide lot across the tested period. The same time-based, near-zero-management portfolio before the current pre-entry filters produced a Max DD of approximately $5,632. The filters removed 643 historical trades from the original 2,968-trade sample, leaving 2,325 trades in the current portfolio. The objective of these filters is not simply to increase win rate. They are designed to remove market conditions that historically produced weaker expectancy or contributed disproportionately to portfolio-level drawdown.

The current ATP portfolio produced a maximum historical drawdown of approximately $3,594 per 10-wide lot across the tested period. The same time-based, near-zero-management portfolio before the current pre-entry filters produced a Max DD of approximately $5,632. The filters removed 643 historical trades from the original 2,968-trade sample, leaving 2,325 trades in the current portfolio. The objective of these filters is not simply to increase win rate. They are designed to remove market conditions that historically produced weaker expectancy or contributed disproportionately to portfolio-level drawdown.

Before Current Filters

Max DD: -$5,632

Trades: 2,968

Current Framework

Max DD: -$3,594

Trades: 2,325

Annual Performance

Annual Performance

The ATP Framework is evaluated across individual calendar years as well as the full combined period. Year-by-year analysis helps identify whether performance is dependent on a single market regime or remains productive across different volatility, trend, and macro environments.

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Framework Characteristics

Framework Characteristics

Time-Based Execution

Trade times are defined in advance rather than dependent on discretionary breakout timing.

Four Complementary Structures

The framework contains bullish, bearish, neutral-consolidation, and neutral-expansion structures.

Moving-Average Alignment

Directional structures are only taken when SPX is positioned on the appropriate side of the 100 SMA.

Pre-Entry Filtering

Each structure uses predefined conditions designed to remove historically weaker environments.

Adaptive Position Sizing

Directional exposure can increase or decrease based on historically tested TICK conditions.

Minimal Management

The framework is designed to reduce screen time and active decision-making after entry.

Portfolio-Level Risk Analysis

Changes are evaluated based on their effect on the combined four-structure portfolio, not simply on the performance of one individual strategy.

AI-Assisted Research

AI is used to organize, compare, and test historical conditions across large datasets. Final rules are based on historical backtesting rather than discretionary interpretation.

A More Mechanical Trading Process

The newest version of ATP was built around a simple objective: maintain strong historical portfolio characteristics while reducing the amount of screen time, discretionary decision-making, and active trade management required.

Time-Based Directional Entries

PCS and PDS are no longer breakout-trigger entries. Both directional structures are evaluated and entered at 10:00 CST when their required conditions are met. Directional trades are only taken on the appropriate side of the 100 SMA on the 10-minute SPX chart.

Near-Zero Trade Management

The portfolio is designed to require as little active management as possible. The PCS and Short Iron Condor are closed at 2:45 CST, approximately 15 minutes before the market close. The PDS and Inverse Iron Condor do not require an intraday managed exit under the current framework.

Structure-Specific Pre-Entry Filters

Each of the four trade structures has its own unique pre-entry conditions. Most filters are based on the previous trading session’s SPX price action. The Short Iron Condor additionally evaluates SPX price action during the hour immediately preceding its entry. If a structure does not meet its required conditions, no trade is taken.

Adaptive Position Sizing

PCS and PDS incorporate the NYSE TICK Index as an adaptive sizing input. Ten years of historical TICK data were cross-referenced with ten years of Option Omega trade results. The weakest quartile is filtered out, the middle two use standard position size, and the strongest directional quartile uses increased position size.

The Four Trade Structures

ATP is designed as a portfolio of complementary structures rather than a single directional strategy.

Inverse Iron Condor

Market Environment: Neutral expansion / volatility expansion. Entry: 8:30 CST at the market open. Current Construction: Slight upside skew. Role: Designed to participate when the market is positioned for larger movement rather than consolidation.

Put Credit Spread (PCS)

Market Environment: Bullish directional. Entry: 10:00 CST. Condition: SPX must be on the appropriate bullish side of the 100 SMA. Current Construction: At least one version is positioned slightly farther out of the money. Exit: 2:45 CST. Additional Layer: TICK-based filtering and adaptive sizing.

Put Debit Spread (PDS)

Market Environment: Bearish directional. Entry: 10:00 CST. Condition: SPX must be on the appropriate bearish side of the 100 SMA. Management: Designed as a minimal-management trade. Additional Layer: TICK-based filtering and adaptive sizing.

Short Iron Condor

Market Environment: Neutral consolidation. Entry: 12:00 CST. Current Construction: Upside-skewed. Exit: 2:45 CST. Pre-Entry Filter: Includes SPX price action during the hour before entry.

Directional Alignment

One of the most important findings in the historical research is that a significant portion of the directional edge comes from keeping the directional structures on the correct side of the moving average. PCS trades are only considered when SPX is positioned on the bullish side of the 100 SMA. PDS trades are only considered when SPX is positioned on the bearish side of the 100 SMA. Rather than waiting for an intraday breakout trigger, the current framework combines that directional alignment with fixed 10:00 CST entry times and pre-entry filtering.

Using Market Breadth to Adjust Exposure

The NYSE TICK Index measures real-time market breadth by comparing the number of NYSE stocks ticking higher with the number ticking lower. For the current ATP research, 10 years of historical TICK data were cross-referenced with 10 years of Option Omega backtesting results for the directional structures. AI-assisted analysis was used to separate the TICK readings into quartiles and compare the historical performance of each group.

WEAKEST QUARTILE

No Trade

MIDDLE TWO QUARTILES

Standard Size

STRONGEST QUARTILE

Increased Position Size

For PCS, the strongest bullish TICK quartile receives increased size while the weakest bullish condition is filtered out. For PDS, the logic is reversed: the strongest bearish TICK quartile receives increased size while the weakest bearish condition is filtered out. The purpose is to move position sizing away from discretion and toward predefined historical conditions.

Defined Entry Times

8:30 CST

Inverse Iron Condor

10:00 CST

PCS · PDS

12:00 CST

Short Iron Condor

2:45 CST

Close PCS · Close Short Iron Condor

When the required conditions are met, entry times are known in advance. Members do not need to wait for breakout triggers or continuously monitor the market for entries.

Position Sizing and Spread Width

The performance figures shown on this page are based on one 10-wide lot. The historical Max DD for the current 10-wide portfolio is approximately $3,594. Position sizing should be based on the amount of portfolio drawdown an individual trader is prepared to tolerate. Examples of possible drawdown targets include 10%, 20%, or 25% of allocated trading capital.

Five-wide spreads are expected to produce broadly similar performance characteristics at approximately half the dollar P/L and approximately half the dollar drawdown of the 10-wide version. Detailed position-sizing guidelines will be published separately.

The objective of the Adaptive Trade Portfolio is not to predict every SPX move. The objective is to maintain a repeatable process across multiple market environments using four complementary structures, defined entry times, historical filters, adaptive exposure, and minimal trade management.

The objective of the Adaptive Trade Portfolio is not to predict every SPX move. The objective is to maintain a repeatable process across multiple market environments using four complementary structures, defined entry times, historical filters, adaptive exposure, and minimal trade management.

Backtested and historical performance is presented for informational and educational purposes only. Past performance does not guarantee future results. Backtests involve assumptions and may not reflect actual execution, slippage, commissions, liquidity constraints, or future market conditions. Options trading involves substantial risk and is not suitable for every investor.