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I'm working on high frequency trading in the Chinese Futures market and I've been having a bit of trouble with getting orders to go through due to the lack of liquidity and large fluctuations. To tackle this problem, I was thinking about working out a model to somewhat predict the next price tick so that I can send my orders accordingly and achieve a higher percentage of successful trades.

The problem is that Chinese futures markets are different from other markets because data is only released every half a second. Rather than a continuous stream of information, quotes and other information is updated every half second so the time in between is a sort of black box which makes some models hard to apply. I was wondering if anyone has some suggestions for either how to predict the next tick (which models or variables to try) or a better way to place my orders to increase the number of successful trades.

Things I've tried so far are logistic regression (decomposed to guess 1. if there will be a price change 2. given there is, is it up or down 3. if its up or down, how much will it move using geometric distribution), arithmetic brownian motion, geometric brownian and mean reversion with another future option for a later date (most hopeful).

Thanks in advance

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