ALL THINGS BIG AND SMALL 2.0

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...

:-) Thank you to the University of Kansas, the Hexacoral project at http://www.kgs.ku.edu/Hexacoral/ for the use of the beautiful animated GIF which is a visualization of Principle Component Analysis . I copied it and I hope they don't mind. This animation shows how 12 clusters of data [the different colors] are reduced to 3 Principle Components. [the 3 orthogonal vectors (perpendicular to each other)] To see the animation, click on it to view it in a new window. In a world where so much information is available, we must learn to manage information overload. When we have several data feed on the same subject, chances are that much of the information overlaps i.e. is redundant. Overlap, meaning that mathematically speaking, if you could and did draw circles representing the true information content of the each data set, the circles would overlap. This is important when we are trying to use the data to model some aspect of the real world. For example, if we are trying to analyze a...