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In our previous article (Part 30), we developed an AB=CD Pattern system in MetaQuotes Language 5 (MQL5) that detected bullish and bearish AB=CD harmonic patterns using Fibonacci ratios, automating trades with calculated entry, stop loss, and take-profit levels, visualized through chart objects like triangles and trendlines. In Part 31, we create a 3 Drives pattern system that identifies bullish and bearish 3 Drives harmonic patterns through pivot points and specific Fibonacci retracements

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Eager to establish dominance in artificial intelligence, Meta has signed up to use cloud-computing services from Google Cloud in a deal worth at least $10 billion over six years, according to a report from Bloomberg.

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Japan's exports grew at a slower pace in April largely due to the higher tariffs imposed by the US administration, official data revealed Wednesday. Exports climbed 2.0 percent on a yearly basis in April, slower than the 4.0 percent increase in March, the Ministry of Finance reported. Exports have been rising since last September and the latest growth matched economists' expectations.

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We continue these series that explore various trade setups and ideas thanks to MetaTrade-5’s rapid development and prototyping environment with the MQL5 wizard. These articles, in principle, seek to explore how else traders can set themselves apart from the pack by exploring ideas that may not be so common and could deliver an edge to the interested trader, depending on how he chooses to exploit them. So, we are into exploring here, not necessarily exploiting and the reason why an edge matters

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Gaussian Process Kernels are covariance functions used in Gaussian processes to measure the relationships among data points, such as in a time series. These kernels generate matrices that capture the intra-data relationship, allowing the Gaussian Process to make projections or forecasts by assuming the data follows a normal distribution. As these series look to explore new ideas while also examining how these ideas can be exploited, Gaussian Process (GP) Kernels are serving as our subject

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