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Showing posts with the label Monte Carlo Simulation

GOLD SILVER WEEKLY UPDATE 01 AUG 2026

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  Next week’s 2,10,30-year Treasury yields may determine whether we will see the straw that will break the camel’s back, the snowflake that will trigger the avalanche, the spark that will set off the powder keg. Refer to image above for my 8 July post for a checklist of what will happen.   This week's models were run against a backdrop of extraordinary macro turbulence compressed into the final two trading sessions of July. On July 29, the Federal Reserve held its benchmark rate at 3.5–3.75% in a divided 9-3 vote — three members dissented in favour of an immediate hike — sending a hawkish signal that drove the 30-year nominal Treasury yield to 5.28%, its highest level in 19 years. The following day, the Japanese Ministry of Finance conducted stealth yen-buying intervention (estimated at $74bn YTD), sending USD/JPY down almost 3% to 158 before a partial recovery. The combined effect: the DXY briefly fell below 100 — its lowest since mid-June — while nominal Treasury yields...

Weekly Gold and Silver Update 25 July 2006

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 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 ...

The Finalized Trinity of Models for Gold/Silver Bullion Portfolio (Part 1)

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 Model No. 1 of 3: GOLD & SILVER 20-DAY AND 60-DAY QUANTILE FORECASTS General introduction to the 3 models: These three consecutive posts (after a long absence) is the culmination of many months of hard work resulting in a suite of 3 models for the monitoring, forecasting and risk/reward calculation of my Gold and Silver bullion portfolio. Why do we need three models?  Because Gold and Silver are monetary metals that carry no yield (interest-earning capacity) but are also hedges against inflation, currency debasement and geopolitical uncertainty. Additionally, Silver is an industrial metal that is required for nearly all products of the modern economy- from EV batteries to, semiconductors, solar panels, smart weapons, and indeed anything that requires electrical conductivity. Thus, we need to monitor not only the USD which is the currency that Gold and Silver are quoted in, but also bond yields, inflation and major currencies such as USD/EUR and USD/JPY. Also, Model No.1 u...

An ETF Portfolio for [Very] Uncertain Times

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  Folk music icon Bob Dylan’s song “The times they are a-changin” has never been more true. We are living in a period of unprecedented geopolitical and economic upheaval-the final consequences of which we are not yet able to discern. Uncertainty is the silent killer of financial markets. But while Uncertainty by itself is bad for the financial markets, the events that unfold during the period of uncertainty can be either good or bad. More US tariffs? Bad. Fed rate cuts? Good. Powell’s term ends in May 2026 and new Trump-appointed Fed Chair leads to even more rate cuts in 2026? Good in the short-term. This leads to heightened inflation and asset bubbles in the long-term? Ultimately bad.   So, today we design a portfolio in which the main objective is to be low risk and yet yield a return that is above the rate of inflation. And we will do an analysis and 1-year ahead forecast for the Portfolio, and use the SPY ETF as a reference benchmark.   We   are not att...

USD/JPY Support/Resistance with Wavelets and Monte Carlo Simulation

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USD/JPY data as of 20 Aug 25 from FRED. USD/JPY is one of the most interesting currency pairs to trade these days, with some opportunities  for short term gains. If we review the MAGA Man's Trade War and Tariff antics, we can see that of all the countries this school yard bully has bullied/cajoled/ran away from, Japan is most at his mercy. (In 2nd place is Europe). China doesn't give a hoot about Trump, India will keep buying Russian oil, the BRICS countries are making good progress in de-Dollarization, Russia will keep pummeling Ukraine. Japan, being the most dependent on the US market for its exports (steel, autos, semiconductors) has a high probability of tipping into a recession. (at least the South Korean economy is more diversified in its export markets)And with a debt/GDP ratio of 260, and rising inflation, there is not much room for fiscal or monetary stimulus. All this will be reflected in a new secular trend for USD/JPY. In this post we will attempt to determine the r...

USD/JPY: Musings on the Rise and Fall of Economies.

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The chart above shows USD/JPY from 1971 at 6-monthly intervals. It's rather frightening to see that USD/JPY used to be as cheap as 350 Yen to USD1.00. Compared to this the current range of USD/JPY 140 to 150 is fantastic. What has happened to USD/JPY  has also happened to the GBP/SGD and the USD/SGD and now AUD/SGD.  If I remember correctly, in the early 70's GBP/SGD was around 7.00 (today it's 1.73) and USD/SGD was around 3.60. (today it's 1.28). So if you take a long term view and the big picture I would dare to say that exchange rates are a valid and good indicator of the rise and fall of economies. When I  take a look at SGD/AUD, I wonder if the good old days of the Lucky Country  are over. SGD/AUD is now around 1.22 It used to be that SGD/AUD was <1. This brings me to what I quoted from the Bible on this blog in 2008-15 years ago. I was reflecting on the unpredictability of financial markets. The image below is a n-dimensional continuous wavelet transform of ...

Long term Dow Jones Industrial Average Support and Resistance Levels using ARIMA, Monte Carlo Simulation and Gaussian Mixture Model

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Data as of 14 August 2025 If you believe that the US economy still has potential (which I do not) and if you also believe that MAGA Man's antics will not destroy it (which I do not) then you may want to sit on the Dow Jones Index (through an ETF) for a long time. If the $37 Trillion debt, the rout in the Bond Market, de-dollarization, and Stagflation does not deter you, see above for the Support (cut loss if price breaks from above) and Resistance price levels (take profit  if price crosses from below) for the DJI.  How the S/R levels were determined It's rather technical but I shall try to explain in simple language.  We first smoothed and fitted the raw 270 data points time series of the DJI Close price with ARIMA (1,1,1,) We then ran the fitted ARIMA data through 5000 trials of Monte Carlo Simulation to see how it behaved. The post-Simulation data was then put though a Gaussian Mixture Model (GMM) with K=3 components. The highest density interval (HDI) at 60% probabili...

Technical Analysis of Stock Prices: Inherent Flaws and Proposed Model

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  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...