Advanced systems and methods for allocating capital to trading strategies for big data trading in financial markets
Exemplary systems and methods for allocating capital to trading strategies may include a means for generating a virtual machine for a trading strategy in a historical server, a means for obtaining historical performance data for the trading strategy from the historical server, a means for transforming the historical performance data into metrical data, a means for transforming the historical performance data and metrical data into a neural network usable data set, a means for creating a neural network base, and a means for forming a neural network.
1. A method for allocating capital to trading strategies comprising:
generating a virtual machine for a trading strategy;
obtaining historical performance data for the trading strategy;
transforming by the virtual machine the historical performance data into metrical data;
transforming by the virtual machine the historical performance data and metrical data into a neural network usable data set;
creating by the virtual machine a neural network base;
forming by the virtual machine a neural network;
training by the virtual machine the neural network for one or more data points; and
calculating by the virtual machine an error rate for the one or more data points until the error rate stops converging or cannot converge.
2. The method of claim 1 , further comprising saving by the virtual machine the neural network.
3. The method of claim 2 , further comprising testing by the virtual machine the saved neural network against updated metrical and historical data.
4. The method of claim 2 , further comprising training by the virtual machine the saved neural network.
5. The method of claim 1 , further comprising saving by the virtual machine the neural network as a binary object.
6. The method of claim 5 , further comprising transmitting by the virtual machine the binary object to a historical server.
7. The method of claim 1 , further comprising activating by a fusion server the neural network.
8. The method of claim 7 , further comprising obtaining by the fusion server the historical metrical and the historical performance data.
9. The method of claim 8 , further comprising calculating by the fusion server a confidence value.
10. The method of claim 8 , further comprising determining by the fusion server whether to execute a trade.
11. The method of claim 10 , further comprising performing by the fusion server a survey.
12. The method of claim 11 , further comprising determining by the fusion server an order to send to an exchange.
13. The method of claim 12 , further comprising sending by the fusion server the order to the exchange.
14. The method of claim 13 , further comprising updating by the fusion server to reflect an executed order.
15. A system for allocating capital to trading strategies comprising:
a means for generating a virtual machine for a trading strategy;
a means for obtaining historical performance data for the trading strategy;
a means for transforming the historical performance data into metrical data;
a means for transforming the historical performance data and metrical data into a neural network usable data set;
a means for creating a neural network base;
a means for forming a neural network;
a means for training the neural network for one or more data points; and
a means for testing a saved neural network against updated metrical and historical data.
16. The system of claim 15 , further comprising a means for training the saved neural network.
17. The system of claim 15 , further comprising a means for saving the neural network as a binary object.
18. The system of claim 17 , further comprising a means for transmitting the binary object to a historical server.
19. The system of claim 15 , further comprising a means for activating the neural network.
20. The system of claim 15 , further comprising a means for obtaining the historical metrical and the historical performance data.