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by adjkant 2934 days ago
Just buying and selling, all GDAX maker to avoid any fees which would more or less cancel out even the best model I have. Lack of fees is another unique feature of the space.

The training period I keep to 3 months and haven't really moved much since initially trying things. A month or less and the model is overfit and useless, too long and it's not working with current data.

The prediction/"hold time" changes absolutely make a difference. I was running on litecoin and found about an hour to be the sweet spot.

> days versus seconds

Seconds would be useless because you can't trade that fast - minutes is what I use.

Even if accuracy increases with a hold time over days, the average trade value doesn't go up nearly enough to make up for the trade frequency of the minutes/hours level. Why make 3 trades per week with an average value of .5% when you can make 4 trades a day for an average value of .15%? The compounding of that frequency works wonders, and that 4 trades a day for .15% is what I was actually hitting for a few months.

For the record, I do also compare to both naive buy/hold over the training period and the average trade value for the period for all times (different than the buy/hold time because I have a profit lock-in threshold for individual trades, also tuned with genetic algorithms), and the model outperforms both still.

The model is still predicting positively but the average trade value is shrinking + market thinning hence why it was breaking even recently until shut down.

1 comments

That's great. Do you use any other baselines, e.g. random daily positions? I'm guessing that your method soundly beat the 'buy and hold' baseline over the last 5 months.

Have you done any work on trying to predict breakouts or crashes? I often think how uncanny it is to compare market movements to simply the number of comments on Reddit threads, or numbers of tweets. I don't know if these are leading or lagging indicators though.

No other baselines (I'm only going for practical not theoretical or publishing so no need really).

Just market features but I'm sure other features are out there. At the minutes level, predicting crashes doesn't do much good as often crashes have ideal 1 hour buying windows so the macro crash/spikes don't really matter, and if they did, would be caputed by the model still.