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Personally, I'm not fully, though I'm sure there are methods. Realistically, right now the naive solution is working just fine, which is just identifying market
by adjkant 9y ago
Personally, I'm not fully, though I'm sure there are methods. Realistically, right now the naive solution is working just fine, which is just identifying market trends. Because so much is bots, it inherently learns the trends of bots, allowing me to write an algorithm that reacts to said trends. The human trading more or less accounts to be the noise level over the bot patterns, though I'm sure some bots also react to the noise, increasing the noise in practice for my purposes. All I know is I can get a good enough accuracy right now to make pretty accurate guesses.
- multibit 9y agoWhat is your naive method? Like what is the algorithm?
- adjkant 9y agoThe learning method is really quite naive, I'll put it that way. The algorithm I chose is designed to be risk averse and crash resistant. The learning method and algorithm are orthogonal/separate, and what learning you pair with what trading algorithm can make a big difference in risk and returns obviously. I'd prefer not to say more than that simply because if the algorithm was run at any large scale I worry about its effect on the market as a whole. Imagine a bunch of bots all following the patterns of a few other bots and what happens if one of those big player bots errors or even if there's a change in the bot and people don't retrain their model. That's just one way it could all go south quick. I'm frankly worried that this risk doesn't already exist.