🤠 Is the market sending a clear signal, or are we hearing more noise than news?

In this episode of Trail Boss Bull Weekly, we put FG through four ARDL statistical model runs, examining inflation (CPI), the Federal Funds Rate, the 10-Year Treasury Yield, and WTI crude oil.

With FG closing at $19.57 for the week ending October 16, 2026, the four models produced different forecasts:

• CPI inflation: $19.61 — projected price gain of 0.20%, with a reported total-return estimate of 0.30%.

• Federal Funds Rate: $20.05 — projected price gain of 2.43%, with a reported total-return estimate of 2.53%.

• 10-Year Treasury Yield: $19.52 — projected price decline of 0.25%, with a reported total-return estimate of -0.15%.

• WTI crude oil: $19.72 — projected price gain of 0.75%, with a reported total-return estimate of 0.85%.

So, what do these four readings tell us?

The Federal Funds Rate model produced the strongest bullish forecast, while the 10-Year Treasury Yield model was the only one projecting a negative total return after the estimated dividend contribution. The crude oil model showed little measurable short-run influence from oil prices, making its forecast primarily a reflection of the model’s price-trend component.

But there’s an important warning in the numbers: all four models reported high persistence readings, ranging from 0.902 to 0.971. The reports flag these readings as a reason not to rely on long-run estimates. In this episode, we focus on the short-run forecasts and explore why the same stock can produce very different results depending on the factor being tested.

We also examine FG’s reported dividend information: approximately $1.00 per share over the previous 12 months, with a reported annual yield of about 5.11%. The model adds an estimated weekly dividend contribution of approximately 0.098% to its total-return calculations. Actual dividend payments and timing can differ, and dividend income does not guarantee a positive overall return.

This is a practical lesson in AI-assisted investing research. We’re not treating model outputs as promises or assuming that a statistical relationship proves cause and effect. We’re comparing signals, questioning assumptions, and learning to separate a useful research tool from market noise.

Study the data. Question the assumptions. Walk your own trail.

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Disclaimer: This podcast is for educational and entertainment purposes only. It is not financial, investment, tax, or legal advice. Statistical models use historical data and assumptions and may produce inaccurate forecasts. Model estimates are not guarantees of future performance, and observed relationships do not establish causation. Investing involves risk, including the possible loss of principal. Dividend payments and yields can change. Always conduct your own research and consult a qualified professional when appropriate.