This sprint was productive and gave us so much fun because we made progress.
Orbit v2 was the main objective of this sprint. Orbit v1 proved its performance, but it has a drawback, too small trade frequency. To overcome this problem, we have started orbit v2 since last Aug.
We have conducted thousands of tests with many ideas to pave the way. We have to admit that it was not a pleasant journey; most of the experiments did not pass the verification process. Few ideas could survive and are eligible to go to the next stage. The stringent evaluation process picked one idea, and we have planted the idea into Orbit v2.
We are planning to test Orbit v2 in the coming sprint.
Athena
Distributed Machine Learning Library
- To test many ideas for Orbit v2, we had to try the views more than 1,000,000 times. Testing 1 idea takes around 5-10 minutes, so the time required to complete the whole idea is 1,000,000*10 minutes = 6,944 days.
- The above library comes into the picture to accelerate the process; then, we can shorten the testing time.
- It was not easy to create the library even though we did not build it from scratch.
Obit v2
- We have implemented Orbit v2 using the selected idea; it seems to be working because backtest results show good performance, MDD(maximum drawdown) is acceptable, and log_loss value is low.
- We have started an intensive test on the Orbit v2 model using the library. By the end of the coming sprint, we may see the result.
Mercury
Infrastructure
- We have revised the current infrastructure for Mercury to accommodate Orbit v2. We have several updates on Athena.
- The deployment yaml is updated. We are going to deploy a new service environment for Mercury in the coming sprint.
Preparation for Orbit v2 testing
- We will test Orbit v2 in the Korean stock market at the beginning. To do that, we need to update Mercury configuration using prepared accounts, balances, etc.
- In the coming sprint, we update the infrastructure and Mercury.
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