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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 ]
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.
MetaTrader 4 Administrator - is designed to remotely manage the server settings. MetaTrader 4 Manager - designed to handle trade inquiries and manage customer accounts. MetaTrader 4 Data Center - a specialized proxy server and can be an intermediary between the server and client terminals. It reduces the price quote sending load on the main server.
The Double Exponential Moving Average (DEMA) indicator was introduced in January 1994 by Patrick G. Mulloy, in an article in the "Technical Analysis of Stocks & Commodities" magazine: "Smoothing Data with Faster Moving Averages" [1] [2] It attempts to remove the inherent lag associated with Moving Averages by placing more weight on recent values.
Moving average crossover of a 15-day exponential close-price MA (red) crossing over a 50-day exponential close-price MA (yellow) In the statistics of time series, and in particular the stock market technical analysis, a moving-average crossover occurs when, on plotting two moving averages each based on different degrees of smoothing, the traces of these moving averages cross.
In particular, the use of oscillator-like Bollinger Bands will often be coupled with a non-oscillator indicator-like chart patterns or a trendline. If these indicators confirm the recommendation of the Bollinger Bands, the trader will have greater conviction that the bands are predicting correct price action in relation to market volatility.
In the field of mathematical optimization, stochastic programming is a framework for modeling optimization problems that involve uncertainty. A stochastic program is an optimization problem in which some or all problem parameters are uncertain, but follow known probability distributions .
In probability theory, a Markov model is a stochastic model used to model pseudo-randomly changing systems. It is assumed that future states depend only on the current state, not on the events that occurred before it (that is, it assumes the Markov property).