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In finance, MIDAS (an acronym for Market Interpretation/Data Analysis System) is an approach to technical analysis initiated in 1995 by the physicist and technical analyst Paul Levine, PhD, [1] and subsequently developed by Andrew Coles, PhD, and David Hawkins in a series of articles [2] and the book MIDAS Technical Analysis: A VWAP Approach to Trading and Investing in Today's Markets. [3]
Technical indicators are a fundamental part of technical analysis and are typically plotted as a chart pattern to try to predict the market trend. [2] Indicators generally overlay on price chart data to indicate where the price is going, or whether the price is in an "overbought" condition or an "oversold" condition.
In 1969 Russell devised the Primary Trend Index, composed of eight market indicators that he never publicly divulged as his own secret recipe. When his index outperformed an 89-day moving average, it was time to buy. When it underperformed the 89-day moving average, a bear market was at hand.
The indicator is a highly-effective technical tool used to evaluate the strength of the current trend and to determine if an established trend will continue or reverse.
The momentum and ROC indicators show trend by remaining positive while an uptrend is sustained, or negative while a downtrend is sustained. A crossing up through zero may be used as a signal to buy, or a crossing down through zero as a signal to sell. How high (or how low when negative) the indicators get shows how strong the trend is.
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.
Chemometrics is the science of extracting information from chemical systems by data-driven means. Chemometrics is inherently interdisciplinary, using methods frequently employed in core data-analytic disciplines such as multivariate statistics, applied mathematics, and computer science, in order to address problems in chemistry, biochemistry, medicine, biology and chemical engineering.
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