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Showing posts with the label Noise

Silver: Measuring Noise vs Fundamentals as Guide for Investing

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Table 1 Chart 1 If we are able to measure and differentiate Noise from Fundamentals, it can be useful for investing . Using the spot price of Silver as a case study, we use Wavelets to measure what portion of the price movements (whether up or down ) is due to Noise (N ) and what portion is due to Fundamentals( F). We define Noise as Speculative Activity and its Residual (remainder) as Fundamentals.    About Wavelets  Wavelets are a powerful mathematical tool for cleaning noisy time-series data, such as stock prices or medical heart rates, because they can simultaneously identify when an event happened and what its frequency was. Unlike traditional statistical measures like the Fourier Transform—which views data as an endless series of smooth waves—wavelets use "mini waves" that start and stop quickly. This unique "multi-resolution" capability allows them to surgically remove high-frequency random noise while preserving sharp, abrupt changes in the data, such as a s...

DATA-DRIVEN (QUANTITATIVE) DECISION SUPPORT SYSTEMS

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Thoughts on definition of Noise and Thresholds 1.     I am obsessed by the thought of being able to make my everyday decisions in a more objective way, unclouded by emotions and biases so common with us humans. There must be academic papers on the topic of quantitative-based decision-making. But I have never read any.  So these are the ramblings of a novice in this field. 2.     Any data-driven (quantitative) decision support system must have (a) some kind of noise removal method for initial ‘cleaning’ to remove data that is considered not relevant to the model  (b) Methods for setting thresholds of some kind i.e. a numerical value that is the boundary for, and triggers a Yes/No decision. 3.      Thus, the two key aspects of any quantitative decision-making process are the removal of noise, and the establishment of thresholds that trigger decisions. For this reason, I am fascinated by the definition of Noise and...

Filtering Out Noise In Life

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Noise can mean much more than 'unwanted' audio signals. Noise can be defined as information that is not useful for your purpose at a certain point in time. It can be audio information, visual information or even olfactory [smell] or gustatory [taste] information. In this sense a frequent encounter with Noise is a part of daily Life. Here are some instances of Noise and how it is filtered: 1. When looking for a location or directions on a map, you have to choose the map with the appropriate scale. If you are traveling from Florida to New Jersey on a non-stop journey, a regional map showing the main highways is the one that is most useful. Detailed maps of each State are not necessary. The small county roads, the streets in each town are all Noise. 2. When getting familiar with a city, it pays to visualize the basic layout of it' s major streets first, and to ignore the rest temporarily. For example, anyone who wants to get to know Manhattan in New York City would first note ...