A quick refresher for the previous article in the News Trading Made Easy series. In part 1, we went through the concept of DST(Daylight Savings Time) and the various versions for different countries that essentially change their time zones by an hour ahead and behind during a financial year. This will change trading schedules for the related brokers using DST. The reasons for creating a database and the benefits were addressed. A database was created to store the news events from the MQL5 Economic Calendar ...
Smart Money Concepts (SMC) and Order Blocks are critical areas on the chart where institutional traders typically execute large buying or selling orders. These zones often mark the origins of significant price movements, making them vital for traders seeking to align their strategies with institutional market activity. Understanding how these key levels influence price action can provide retail traders with more profound insight into the underlying market dynamics, allowing them to anticipate ...
This article continues the series on how the MQL5 wizard is ideal for rapid testing and prototyping ideas for traders. For a lot of people developing expert advisers and trade systems, the need to keep learning and be abreast with trends in not just machine learning but trade & risk management in general is important. We therefore consider within these series how the MQL5 IDE is useful in this regard by not only saving time but also minimizing coding errors. more...
More to follow about good free channels (which we can subscribe to) for some information about trading and coding), and for now - the channels about the articles and about new free tools in CodeBase (it is recommended to subscribe): RU - https://www.mql5.com/ru/channels/algo-trading-ru EN - https://www.mql5.com/ru/channels/algo-trading-en ES - https://www.mql5.com/ru/channels/algo-trading-es FR - https://www.mql5.com/ru/channels/algo-trading-fr PT - https://www.mql5.com/pt/channels/algo-trading-pt ...
Principal Component Analysis (PCA) is the focusing on only the ‘principal components’ among the many dimensions of a data set, such that one is reducing the dimensions of that data set by ignoring the ‘non-principal’ parts. PCA though, with eigen values & vectors, take on a slightly deeper approach. Typically, data sets that are handled under PCA are in a matrix format and the principal components, that are sought from a matrix would be a single vector column (or row) that is ...
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