Random Forest is easier to train because it is less prone to noise. On Forex it is impossible to separate the noise from real data.
Unfortunately that statement is not quite true.
While RF do reduce variance in your forecast, they are not “less prone to noise”. Your forecasts are likely to be more stable but it is still affected by noise (AKA bias).
Another property of RF that makes it not quite desirable for time series data such as FX is the method of sampling. As time series have a natural temporal ordering, random sampling may distort or erode some key information or pattern, or worse, create fictatious ones! Although the workaround this is rather simple.
I look for value wherever it can be found