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Mixed-data sampling (MIDAS) is an econometric regression developed by Eric Ghysels with several co-authors. There is now a substantial literature on MIDAS regressions and their applications, including Ghysels, Santa-Clara and Valkanov (2006), [ 1 ] Ghysels, Sinko and Valkanov, [ 2 ] Andreou, Ghysels and Kourtellos (2010) [ 3 ] and Andreou ...
Ghysels' most recent research focuses on Mixed data sampling (MIDAS) regression models and filtering methods with applications in finance and other fields. He has also worked on diverse topics such as seasonality in economic times series, machine learning and AI applications in finance, quantum computing applications in finance, among many ...
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]
Nowcasting methods based on social media content (such as Twitter) have been developed to estimate hidden sentiment such as the 'mood' of a population [16] or the presence of a flu epidemic. [17] A simple-to-implement, regression-based approach to nowcasting involves mixed-data sampling or MIDAS regressions. [18]
A variety of data re-sampling techniques are implemented in the imbalanced-learn package [1] compatible with the scikit-learn Python library. The re-sampling techniques are implemented in four different categories: undersampling the majority class, oversampling the minority class, combining over and under sampling, and ensembling sampling.
The best example of the plug-in principle, the bootstrapping method. Bootstrapping is a statistical method for estimating the sampling distribution of an estimator by sampling with replacement from the original sample, most often with the purpose of deriving robust estimates of standard errors and confidence intervals of a population parameter like a mean, median, proportion, odds ratio ...
The table shown on the right can be used in a two-sample t-test to estimate the sample sizes of an experimental group and a control group that are of equal size, that is, the total number of individuals in the trial is twice that of the number given, and the desired significance level is 0.05. [4]
MIDAS (Maximum Integration Data Acquisition System) has been developed as a general purpose data acquisition system for small and medium scale experiments originally by Stefan Ritt in 1993, followed by Pierre-André Amaudruz in 1996. It is written in C and published under the GPL.