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MetaTrader EAs: The "Set & Forget" Myth [EAS-II]
This is the second post in the MetaTrader Expert Advisor [EAS] series we've begun recently. In case you missed it, here's a link to the first post: Commercial Expert Advisors: everything that glitters is not gold. If you're wondering what "set & forget" means, it's a common catch phrase used widely by many commercial MetaTrader EA vendors. It implies…
P5.A6-MachineLearning-Darwin-Datasets-scaled
Machine Learning on DARWIN Datasets (MLD-I)
Machine learning in essence, is the research and application of algorithms that help us better understand data. By leveraging statistical learning techniques from the realm of machine learning, practitioners are able to draw meaningful inferences from and turn data into actionable intelligence. Furthermore, the availability of several open source machine learning tools, platforms and libraries today enables…
Mean Reversion Tests on DARWIN $DWC
Mean Reversion Tests on DARWIN $DWC
In a previous post - Quantitative Modeling for Algorithmic Traders - we discussed the importance of Expectation, Variance, Standard Deviation, Covariance and Correlation. In this post we'll discuss how those concepts can be applied to DARWIN assets. As a practical example, we will employ a series of statistical tests to assess if DARWIN $DWC is a Mean…
Hidden Markov Models & Regime Change_ S&P500
Hidden Markov Models & Regime Change: S&P500
In this post, we will employ a statistical time series approach using Hidden Markov Models (HMM), to firstly obtain visual evidence of regime change in the S&P500. Detecting significant, unforeseen changes in underlying market conditions (termed "market regimes") is one of the greatest challenges faced by algorithmic traders today. It is therefore critical that…
Serious Algorithmic Trading Series – Part 1
Serious Algorithmic Trading Series – Part 1
Can individual traders really compete with large institutions? This post is the first of a four-part “Serious Algorithmic Trading” series, introduced here. A trader will at one point or another, question how practical it is to compete with large institutions in the same markets. After all, it is “big money” at the end of the day that…
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