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Welcome to Quant-Stackexchange Sleepy Panda, this is an interesting question and it also seems to be an interesting book. Regarding your Question: It depends on your goal and your definition of success. If you intend to learn a lot about an interesting topic and deepen your understanding of financial market dynamics, study companions and individuals who work ...


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This r/answers post can assist with your second question. The short answer is no. An individual will probably not succeed at making models with predictive powers. Even if you are a successful quant (extremely hard and rare), to be so you need expensive resources not available to individuals. Knowledge and learning are always super helpful in building ones ...


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The soul-crushing self-doubt is half the fun! I would say the most important things to understand are pot odds, comparative advantage, adverse selection and market structure (microstructure and macro players). As an individual, it is my personal belief that it is necessary to find a niche in which you have a comparative advantage, where the major players ...


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surrounding yourself with like minded people is a proven route to success. now doing research on your own is ok, but make sure you cross check your research and findings with others on forums, quantopian for instance has a community, tests datasets and competitions, things are always different when seen throughout another person's paradigm, and backtesting ...


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Just based on my understanding of the ML models themselves, I have a hard time believing KNN or RF are useful in anyway. They wouldn't be the first models I try and tend to just be ML models taught in class for who knows what reason honestly - maybe because they are easy to understand? From what I have read about ML in general (not in relation to time ...


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In time series prediction for trading there are two parts: -prediction model -trading strategy based on it. As for construction of prediction model, there are also two parts: - feature selection (which can be very time-consuming) - actual prediction. For feature selection the model should be simple and thus just predicting direction is more desirable.You ...


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