ALL THINGS BIG AND SMALL 2.0

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...

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 ...

Chart 1: Noise Reduction Algorithms Compared. Data as of 12 June 2025 As compared with established and mature stock exchanges such as the New York, Japanese and European stock exchanges, frontier and emerging stock exchanges have a higher level of ‘noise’. In financial markets, "noise" refers to the erratic and often unpredictable fluctuations in price and volume that can make it difficult to discern genuine market trends. This noise can stem from various sources, including news reports, market sentiment, and even algorithmic trading. It essentially obscures the underlying fundamental value of an asset, making it difficult for investors to make sound decision. In this post, I am applying four types of de-noising algorithms on the Bombay Stock Exchange Sensex Index (“BSE” or “Sensex”). My hypothesis is that the Sensex  has  a high level of noise. This is because a large proportion of the investors on the approximately 5000 stocks listed on the BSE are retail investors stee...

1. A Self-Organizing Map of 2800 US stocks' Beta. Any area can be selected with mouse to Open up and identify the stocks in it. 2. A Daubechies 4 Wavelet; 5 Level decomposition of the Hang Seng Index. 3. Using a Wavelet to De-Noise the Hang Seng Index:more efficient than a Moving Average, with no lag. (click on image to see how the Wavelet 'hugs' the time series closely, yet gets rid of daily noise) 4. A 1-D complex continuous wavelet of the Straits Times Index in Jet Color Mode. Self-similar patterns are indications of fractals i.e. the Index is not totally random but has its own 'memory'. 5. A 1-D Continuous Wavelet of the Straits Times Index in Prism Color Mode. Again we see patterns of sorts. But it takes a skilled Wavelets practioner to interpret, Unfortunately, I'm just beginning to understand Wavelets. Financial markets historical data are essentially the same as digital signals. And therefore they can be processed and analyzed with the tools used in...