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ADX Indicator. The average directional movement index (ADX) was developed in 1978 by J. Welles Wilder as an indicator of trend strength in a series of prices of a financial instrument. [1] ADX has become a widely used indicator for technical analysts, and is provided as a standard in collections of indicators offered by various trading platforms.
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 dynamic lot-size model in inventory theory, is a generalization of the economic order quantity model that takes into account that demand for the product varies over time. The model was introduced by Harvey M. Wagner and Thomson M. Whitin in 1958.
It is a leading indicator providing advanced signaling of potentially new market highs or lows within a given time frame. [ 5 ] The support and resistance levels calculated from the pivot point and the previous market width may be used as exit points of trades, but are rarely used as entry signals.
Ideal test indicator pushed. Prior to modern geared dial mechanisms, test indicators using a single lever or systems of levers were common. The range and precision of these devices were generally inferior to modern dial type units, with a range of 10/1000 inch to 30/1000 inch, and precision of 1/1000 inch being typical.
Ichimoku trading system example in the forex market for NZDCAD pair. Ichimoku Kinko Hyo (IKH) (Japanese: 一目均衡表, Hepburn: Ichimoku Kinkō Hyō), usually shortened to "Ichimoku", is a technical analysis method that builds on candlestick charting in an attempt to improve the accuracy of forecast price moves.
The Battenberg course indicator is a mechanical calculating device invented by Prince Louis of Battenberg in 1892 for taking station on other vessels whose range, bearing, course and speed are known. By extension, it has a range of other functions related to relative velocity calculations.
In statistics, the k-nearest neighbors algorithm (k-NN) is a non-parametric supervised learning method. It was first developed by Evelyn Fix and Joseph Hodges in 1951, [1] and later expanded by Thomas Cover. [2]