ALL THINGS BIG AND SMALL 2.0

 EXECUTIVE SUMMARY This week delivered a compelling but contradictory picture. Gold rose 1.8% to $4,055.70 and silver surged 4.6% to $58.49 — silver's outperformance compressing the Gold/Silver Ratio from 71.3 to 69.3, a notably bullish signal for silver relative to gold. The GBDT forecasting model responded with sharply higher median forecasts across all horizons, and gold's 60-day probability of gain jumped to 79.7%. Yet under the surface, the macro environment deteriorated on every front. The DXY-Metals Nexus Monitor composite scores deepened materially — Gold to −0.87 and Silver to −0.86, from −0.73/−0.72 last week — as all five signal modules held at Strong Reduce. Real TIPS yields continued to rise: the 10-year reached 2.43% (+8bp) and the 5-year climbed to 2.17% (+13bp), both firmly in Strong Headwind territory. The week's most significant signal shift: Gold's 60-day Skew Score flipped from Bullish Lean (+0.09) to Bearish Lean (−0.12), revealing that even as the ...

Weekly update is the output of the Gold/Silver trinity of models: 1. GS-GBDT which is a price momentum and autoregression model, 2. GS-DXY Monitor which is a model of the DXY Index and its correlation with Gold and Silver prices, 3. GS-Real Yields Monitor which tracks real yield of Treasuries (Nominal interest rate minus Rate of inflation) and its impact on Gold and silver prices. The tables and charts here are mostly self-explanatory but one thing to note: Since I am a long-term holder of Gold and silver I treat extreme bearish signals ("Strong Reduce" in model signals) as a deeply oversold reading and an invitation to buy; due to the fundamentals underpinning Gold and Silver.  For technical details and methodology of models see: https://ngtiankhean.blogspot.com/2026/07/the-finalized-trinity-of-models-for.html https://ngtiankhean.blogspot.com/2026/07/the-finalized-trinity-of-models-for_01846758995.html https://ngtiankhean.blogspot.com/2026/07/the-finalized-trinity-of-models-...

  Data used: Boeing Co. Data as of 17 April 2025 It is true that short-term modeling and predictions of stock prices using just price data is valid and useful. We do not need fundamental data as input variables for short-term predictions. But there are inherent flaws in traditional Technical Analysis (TA). The inherent flaws of traditional technical analysis indicators, such as RSI, MACD, Bollinger Bands, all assume that the relationship between market variables is linear and that data distributions are Gaussian (Normal). But it is well-known that financial markets exhibit non-linear dynamic characteristics with distributions that are not Normal i.e. have more than 1 peak, are highly skewed and have long fat tails (kurtosis). And that the relationship between market variables is highly non-linear.  However, these short-term linear relationships can be modeled with Linear Regression . The Table below shows that Linear Regression, particularly its Boosted version produces the sm...