ALL THINGS BIG AND SMALL 2.0

End-Of-Day Prices as of 27 Sep 2025. We thank EODHD.com for making the Indices data available to us.  With EODHD.com You can be assured that the data is clean, reliable and of the highest quality.  Sure beats trying to fetch data from Yahoo Finance.   For methodology of this post please refer to our original blog post at  https://ngtiankhean.blogspot.com/2025/09/markov-regime-switching-model-for.html Below are the  Markov Regime Switching Risk-On/Risk-Off readings for SP500, DJI, Nasdaq100, STOXX 600, Nikkei225, CSI300 and HSI.  Major global equity markets have a significant positive correlation with the US equity market, as well as the US economy. The US economy is currently showing signs of being in a stagflation- while economic indicators such as payroll data, manufacturing output indicate a recessionary outlook, gold prices,  the CPI and bond yields indicate an inflationary outlook.  But one thing for sure is that the Fed's lowering of th...

Knowing the market’s current risk state is foundational for portfolio decisions. Basic Markov chain models are a good starting point, but they fall short on three realities of financial data. Using as case study China's CSI300 Index, here’s how our model resolves each one and delivers a robust, reproducible Risk‑On/Risk‑Off signal. 1) Beyond “memoryless”: markets have persistence and aging Problem: Standard Markov chains assume memorylessness—the next state depends only on the current state, not on how long we’ve been there. Markets don’t behave that way; regimes “age” and persistence changes with time. Our solution: We use a hidden semi‑Markov model (HSMM) with explicit duration modeling. Each regime has a duration distribution (e.g., Negative Binomial), and transitions are allowed to depend on time spent in the state. This breaks the memoryless assumption, curbs flicker, and captures realistic regime persistence. 2) Heavy‑tailed, skewed returns are the norm—not Gaussian Problem: ...

Some of the 17 Rare Earth Elements ("REE") are indispensable for the production of military equipment and platforms. But as of 2024, China mines nearly 70% of the world's rare earths and refines about 90% of the global supply. Without REE, the US Defence industries become lame ducks. If these industries  are crippled, Trump has shot himself in the foot in trying to contain China's economic and miltary power.  And that is the reason why Trump walked back on his Tariff tough talk and threats to China.   Defense Applications of Rare Earth Elements Rare earth elements (REEs) run through nearly every advanced military system. They enable compact, reliable power; precise sensing and guidance; hardened communications; and survivable performance at high temperatures. Where REEs show up in defense systems High-performance magnets (Nd, Pr, Dy, Tb; Sm) What they do: Create compact, powerful, and heat‑tolerant permanent magnets. Where used: Missi...

Introduction Uncertainty is an inherent property of financial markets due to its highly dynamic and ever-evolving nature. Therefore, forecast models of financial markets should not focus on pin-point accuracy, for it will be spurious accuracy.  Rather the output should be within a statistical confidence levels band. Bands can be based on quantiles of the Probability Distribution Function of the data.  Case study: Singapore’s 6-month T-Bill and SORA (Singapore Overnight Rate Average). The chart above shows the time series (daily yields) of Monetary Authority of Singapore (MAS) 6-month T-Bill (6MT), overlaid on the SORA.  SORA has a broad positive correlation with 6MT but has daily swings of significant volatility. This is natural because SORA’s daily volatility is a feature of an unsecured overnight funding benchmark: sensitive to immediate liquidity, calendar, and cross ‑ currency conditions of banks and other users while 6MT yield is a forward-looking, term ‑ averaged pr...

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  Singapore's Re-Exports Singapore's Re-Exports are goods that are imported and re-exported without physical transformation. The definition excludes as re-exports, even goods with minor physical transformations such as sorting, grading and repackaging.  So what enables Singapore companies to function as a middle-man to re-export goods? Their value-add arises from their role as agents, and appointments by MNCs as distributors for the region. Their value add may also come from granting credit facilties, providing logistical services, and in general connecting producers from other countries to the rest of the world. Re-exports exemplifies Simgapore's role as a major trading hub for the region. The graphic above shows Singapore's rexports are still growing despite the countries in the region becoming more developed in their economies.   Singapore's exports to China and USA compared The chart above shows the value of Singapore's exports to US and China in USD. Even b...

  What is Logistic Regression (LR)? What it does: It predicts the probability of an outcome (like yes/no, default/no default) from input features (like income, age, credit score). Instead of drawing a straight line through the data, it fits an S‑shaped curve that maps any input to a probability between 0 and 1. Interpreting the image above Feature space: Think of each axis as one standardized input (e.g., core CPI z-score vs. unemployment z-score). Real models use more than 2 features; this is a 2D illustration. Multinomial logistic regression: For each scenario k, it learns a linear score Score_k = w_k · x + b_k. Applying softmax to all four scores yields a probability surface per class. Boundaries: The class decision boundaries are linear (straight lines in 2D), but probabilities change smoothly across them, which is the S-curve behavior generalizing to multiple classes. Why 4 classes but only 2 features in the chart The model has four scenarios (classes): Inflation-first, Soft-l...