Quote from paulbechard:
1) It works on paper trading accounts and doesnât perform the same on live accounts.
3) It works on both paper and live, but the slippage on the live trades seems to lead to a loss in the long run. Ie. a bunch of good small trades. a few huge losses though.
Paul,
In regards to these two issues, your strategy is extremely susceptible to many perils associated with high-frequency trading. Some possibilities:
1. It is possible that you have a sampling error. When you detect a signal at time t+0 it has ceased to exist by the time your order reaches the market at time t+1.
2. It is possible that your strategy creates market impact. The act of attempting to take advantage of small inefficiencies could make the market more efficient.
3. It is possible that your strategy is detectable by other market participants. You are not the first person to develop an automated trading agent of this kind. Some of the adaptive agents can be very clever, and can detect anomalies in their environment very quickly.
4. It is possible that your strategy is trading random noise. It is quite easy to find a fit for some condition in a large amount of random data. Or, your system might be initiating trades based on some condition that is the result of some stochastic process. The condition may never have existed, but seemed to because of the stochastic arrival of information.
5. It is possible that your data is totally invalid. Quotes, trades, and other high-frequency market data are notoriously unreliable. Institutions that profit from this form of trading go to great expense in an attempt to sanitize their data in real-time.
I think that the field of high-frequency microstructure trading, in general, has reached the stage of diminishing returns for all but the most competitive institutions. My recommendation to you would be to explore other quantitative methods that are not dependent on such high-frequency data.
-segv