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Stochastic oscillator is a momentum indicator within technical analysis that uses support and resistance levels as an oscillator. George Lane developed this indicator in the late 1950s. [ 1 ] The term stochastic refers to the point of a current price in relation to its price range over a period of time. [ 2 ]
In the theory of stochastic processes, filtering describes the problem of determining the state of a system from an incomplete and potentially noisy set of observations. While originally motivated by problems in engineering, filtering found applications in many fields from signal processing to finance.
Stochastic music was pioneered by Iannis Xenakis, who coined the term stochastic music. Specific examples of mathematics, statistics, and physics applied to music composition are the use of the statistical mechanics of gases in Pithoprakta, statistical distribution of points on a plane in Diamorphoses, minimal constraints in Achorripsis, the ...
An oscillator in technical analysis of financial markets is an indicator that informs if the price of a financial instrument is very high or very low, indicating whether it is overbought or oversold. This helps traders make decisions about when to trade (buy or sell) that instrument.
George Lane (1921 – July 7, 2004) was a securities trader, author, educator, speaker and technical analyst.He was part of a group of futures traders in Chicago who developed the stochastic oscillator (also known as "Lane's stochastics"), which is one of the core indicators used today among technical analysts.
The Stochastic oscillator study, for example was programmed from the work of George Lane and Ralph Dystant. The indicator's lines were named "%K" and %D" but Slater needed a single name which was more accessible and the word "stochastic" was written on the paper, so he gave the study that name, and it has persisted. [ 3 ]
The oscillator is on a negative scale, from −100 (lowest) up to 0 (highest), obverse of the more common 0 to 100 scale found in many technical analysis oscillators. A value of −100 means the close today was the lowest low of the past N days, and 0 means today's close was the highest high of the past N days. (Although sometimes the %R is ...
Indeed, this randomization principle is known to be a simple and effective way to obtain algorithms with almost certain good performance uniformly across many data sets, for many sorts of problems. Stochastic optimization methods of this kind include: simulated annealing by S. Kirkpatrick, C. D. Gelatt and M. P. Vecchi (1983) [10] quantum annealing