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23 Mar 20223 dakikada okunur

Return (▲Price), Likelihood & Probabilities: Top10 Traded ETFs in USA from 21/12/2021 to 29/03/2022.

In conclusion, as in a prior post it was demonstrated that there is not significant difference between the return and risk of the Top10 trad

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2 Mar 20224 dakikada okunur

Markov Chain Proj.: Return (▲Price) with Highest & Above Zero Probabilities, SQQQ, 21/12/2021

The graph at the beginning of this post corresponds to the univariate spline that will alow the user to find out what is the return (▲Price)

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6 Şub 20225 dakikada okunur

Simulation & Bootstrap: Adv. Stats & Markov Chains for the 10 Most Traded ETFs in USA, 12/21/2021

The Top10 traded ETFs in USA are compounded by SQQQ, SPY, XLF, QQQ, UVXY, TQQQ, VXX, EEM, IWM, and XLE.

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2 Şub 20224 dakikada okunur

LP: Adv. Statistics & Markov Chain Projection for the 10 Most Traded ETFs in USA, FREE (12/21/2021)

The Top10 traded ETFs in USA are compounded by SQQQ, SPY, XLF, QQQ, UVXY, TQQQ, VXX, EEM, IWM, and XLE.

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3 Oca 20224 dakikada okunur

LP: Advanced Statistics for the 100 Most Traded ETFs in USA, Date: 12/21/2021

On this first paid-post it is being released the key statistics for the most traded ETFs in the USA. As the securities with the most...

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3 Oca 20226 dakikada okunur

LP: Adv. Statistics & Markov Chain Projection for the 100 Most Traded ETFs in USA, Date: 12/21/2021

On this first paid-post it is being released advanced statistics for the most traded ETFs in the USA. As the securities with the most...

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18 Ara 20214 dakikada okunur

Stock Market Quotes Estimator (Part II)

In part I of the stock market quotes estimator it was explained that even though stock prices are random, the variable ▲Price is not and...

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30 Kas 20213 dakikada okunur

Stock Market Quotes Estimator (Part I)

As its name says it, the stock market quotes estimator is a machine learning program developed to estimate, with a probability, within...

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17 Kas 20211 dakikada okunur

Welcome to ML Perspective Blog

ML Perspective or Machine Learning Perspective is a new way to analyze (leverage) data without the classical constrain to 2D and 3D graphs.

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