Inconsistent Handling of Time Zones in Market Simulation #7
Description
Description: The current documentation and examples for MarS do not explicitly address the handling of time zones in market simulations. This lack of clarity can lead to inconsistencies and incorrect results, especially when dealing with data from different exchanges or when simulating events across multiple time zones.
To Reproduce:
Run a simulation that involves data from exchanges located in different time zones (e.g., New York and Tokyo).
Observe the timestamps of events, orders, and transactions.
Compare the simulated market behavior with the expected behavior, considering the time zone differences.
Expected behavior:
MarS should provide clear guidance on how to specify and handle time zones for market data and simulation events.
The simulation engine should correctly account for time zone differences when processing events and updating the market state.
Ideally, MarS should support time zone-aware data structures and functions to prevent ambiguity and errors.
Possible Solutions/Improvements:
Add a dedicated section to the documentation explaining how to work with time zones in MarS.
Introduce parameters or configuration options to specify the time zone for market data and simulations.
Consider using a time zone-aware library (e.g., pytz in Python) to handle time zone conversions and calculations.
Provide examples demonstrating how to simulate markets with data from different time zones.
Additional context:
This issue is crucial for ensuring the accuracy and reliability of market simulations, especially when dealing with global markets. Inconsistent time zone handling can lead to incorrect order matching, incorrect calculation of market metrics, and ultimately, flawed simulation results. This issue also impacts reproducibility and comparability of results across different simulations.