Curious what your thoughts on this are: <a href="http://globalslant.com/2015/06/black-box-trading-why-they-all-blow-up/" rel="nofollow">http://globalslant.com/2015/06/black-box-trading-why-they-al...</a><p>TLDR: Essentially black box trading inevitably fails because they're all trying to do the same thing. At a certain point everyone tries to liquidate, or buy, or perform same trades at the same time which can lead to a blow up.<p>I wonder if getting around this assumes some sort of diversity in algorithms/ML approach, and if that diversity is a realistic assumption
Can someone put in layman's terms the passage below? please. Assuming the reader has some machine learning experience but no financial knowledge. Thanks<p>#### numerai_training_data.csv
Use this dataset to train your machine learning algorithm. The first fourteen
columns (`f1` - `f14`) are integer features. Column `c1` is a categorical
feature, column validation indicates a dataset that you can use to validate
your model, and target is the binary class you’re trying to predict.