The US military campaign against Iran has persisted for nearly two weeks. As the conflict continues, geopolitical advisory firm Signum has developed a mathematical model aimed at quantifying President Trump's decision-making threshold in the Iranian crisis.

According to CCTV News, on July 24, local time, President Trump discussed an "exit strategy" from the Iran conflict at the White House, stating that the US has two options: either continue current military operations, potentially escalating to gradually dismantle Iran's military capabilities, or pursue a negotiated agreement.

As previously noted by financial media, earlier that day, Reuters cited sources reporting that Pakistan is exploring ways to revive stalled US-Iran negotiations.

Following this news, markets briefly anticipated a diplomatic breakthrough in the Middle East conflict. Brent crude oil briefly dipped below $95.20, falling over 5% intraday, while US WTI crude dropped below $87.70, declining approximately 4.9% intraday.

Analysts at geopolitical advisory firm Signum have observed that historically, when the combined pressure from key market indicators reaches approximately 2.9 standard deviations, President Trump has taken de-escalation actions.

Based on a linear extrapolation of current trends, this "TACO moment" could occur as early as July 22, no later than July 30, with the most likely timing being July 26.

The model is called the "TACO Index," a name derived from the market adage "Trump Always Chickens Out."

Led by analyst Andrew Bishop, the research team used Brent crude oil prices, US 10-year Treasury yields, the number of vessels transiting the Strait of Hormuz, and the S&P 500 Index as variables to back-test Trump's behavioral patterns regarding Iran.

Back-testing results indicate that this index closely aligns with several of Trump's previous policy shifts. Analysts note that while the index has not yet triggered the threshold, it is steadily approaching it.

Model Construction: Four Variables Quantify Market Pressure

The analytical team at Signum Global Advisors set March 7 of this year as the baseline, approximately one week after the US and Israel first launched strikes on Iran.

The model combines Brent crude, 10-year Treasury yields, Strait of Hormuz transit volume, and the S&P 500 Index with weighted values, assigning different weights based on Trump's sensitivity to each indicator.

Analysts then validated the model against three subsequent key policy inflection points: the shift towards ceasefire negotiations on March 22, acceptance of a ceasefire agreement on April 7, and the pivot to memorandum of understanding talks on May 18.

Back-testing concluded that the range of composite market pressure needed to trigger Trump's action is between 2.3 and 3.4 standard deviations, with an average of approximately 2.9 standard deviations.

Time Window: July 26 Identified as Most Likely Date Based on Historical Projections

Based on a linear extrapolation of current market conditions, Signum analysts provide a relatively clear time frame.

The Andrew Bishop team states that, according to current trends, a "TACO" event could occur as early as July 22, with historical patterns pointing to July 26 as the highest probability point.

July 30 is identified as the latest upper limit, assuming market conditions do not materially improve—a scenario analysts deem "unlikely."

While the model shows some correlation in historical back-tests, the analysts themselves remain cautious about its limitations. The "TACO" concept has long circulated among investors as a market forecasting framework, but its reliability is inconsistent.

Trump currently leads a military operation in Iran that is widely perceived as difficult to win, with external variables far more complex than mere market pressure.

Signum's model essentially systematizes Trump's past sensitivity to financial market signals, but the non-linear nature of political decision-making means any extrapolation based on historical patterns carries significant uncertainty. Investors should maintain appropriate risk awareness when referencing this framework.