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Tom Kadala posted on LinkedIn

#artificialintelligence

Take a LOOK at what 100% Win/Loss Ratio means with RagingFX.com It's as real as it comes. I traded two #FX signals yesterday (delivered to my iPhone by our algo) while on several #Zoom Conference Calls. Here's what I did... Fortunately I was on listen mode when the first one came in for an #Aussie BUY. The Rule# assigned to the signals was 63-Y, which meant I could trade up to 6 lots at the MARKET and 3 lots at the LIMIT.


Tom Kadala posted on LinkedIn

#artificialintelligence

Summer is over and I'm fully rested and ready for some fun FX trading this Fall. This morning was a classic example of what RagingFX.com is all about, 'Trade and Forget'. Here's what I did... Since the signal came in while I was asleep, I had to run it through our litmus test, ...which is simply to check that the price action had not hit one of the exit levels. It passed, so I decided to go ahead with the trade. Next, I checked the Rule#.


Step-by-Step Signal Processing with Machine Learning: PCA, ICA, NMF

#artificialintelligence

Signal processing is crucial in many data science tasks. As soon as we start handling audio files, images or even biological measurements, it is useful to know techniques to process such data. In this article, I will introduce three algorithms you can use for two use cases: Principal Components Analysis (PCA) for dimensionality reduction and feature extraction, Independent Components Analysis (ICA) and Nonnegative Matrix Factorization (NMF) for source separation. All three methods have ready-to-use implementations on scikit-learn which are useful for your projects, but for the purpose of this article I will show how you can implement these methods from scratch, using only OpenCV to open and save images, and NumPy to handle matrices. I will provide code snippets throughout the article, and you can find the full code as well as the example datasets on Github.


Artificial Intelligence Powers Trading for GO Market Investors

#artificialintelligence

GO Market has made the decision to include a-Quant's trading signals to selected clients. This means clients can use artificial intelligence (AI) to forecast the movement of their asset portfolios. AI has been utilized in the financial trading world for a while but has only recently seen more traction in the retail industry due to the demands of traders wanting tools to maximize their gains. GO Market has promoted this recent change to the public and state that they are happy that their clients can quickly deploy the signals a-Quant services provide, by using this cutting-edge technology. GO Market made the headlines earlier this year by adding stocks from the Australian Stock Exchange to be traded on MT5.


Tom Kadala on LinkedIn: Trade Forex differently… using a learning algorithm designed by expert

#artificialintelligence

Trade Forex differently… using a learning algorithm designed by expert traders. Just over four years ago, we embarked on an ambitious task on the banks of the Thames in London. We decided to rewrite the rules on FOREX trading. Granted there's a lot to choose from, but for the individual who just wants to trade FOREX profitably without having to be glued to their screen all day, we feel we have developed a viable alternative. Our intuitive approach pushes all the technical analysis onto an AI and ML solution called RagingFX.