📈 AlgoSoc-Sessions

Important note: The code here is not optimised to be used in market conditions, it is instead should be used as an educational tool to teach key prinicples.

Pedlar 2.0 Repo

Content

• data:
  • Contains all the csvs used for backtesting.
• intro_agents:
  • Contains 3 simple intro agents demonstrating key pedlar functionality.
• agents:
  • Contains the agents produced during the sessions. Frequently redesigned with improvements and optimisations.

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Next Steps:

For agents:

• Decision tree agent
• Linear agent
• NN agent
• RNN agent
• RL agent

For finding parameters:

• Explicit search
• Random search
• Grid search
• Gradient-based search
• Evolution-based search
• Sharpe Optimisation

Combining multiple signals & agents:

• Ensemble of agents
• K-Armed bandits

Risk Control:

• Time dependent behaviour (e.g. varying behaviour around market open/close)
• Real time statistics
• Add post-analysis of trades made.

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About us:

Algo soc website | Algo soc slack

Our trading platform Pedlar:

Imperial pedlar server → (requires access to Imperial Wifi Network)

You can contact us at: [email protected]