Predicting financial data (choosing a model)
Well, evaluating your model just by comparing matrixes can be pretty hard.
In your case, your matrixes are not done with the same number of row classified 1 or 0, so comparing them is really hard. Let's take an example : your logistic regression classifies around 64000 as 1, while your RandomForest only classifies around 4500, so comparing these data by this matrix is pretty hard.
I'd suggest you to use the ROC AUC metric, that is really useful to compare models. You might find many info on this subject in the Internet. The closer your AUC is than 1, the better your model is. If it's 0.5 or less, your model is less efficient than a random classifier.