Lighter FX Weekend Pricing Analysis

Overview

This project analyzes Lighter FX weekend pricing mechanisms to understand how they maintain price feeds during traditional FX market closures (Friday 22:00 GMT to Sunday 22:00 GMT).

Key Analysis Components

1. Data Collection

• Lighter FX Data: Weekend pricing data from Lighter protocol
• Spot FX Control: Traditional FX rates from Yahoo Finance
• Crypto Data: BTC rates for triangular arbitrage analysis

2. Core Research Questions

• How does Lighter maintain FX prices during weekends?
• Do they use crypto-implied FX rates (triangular arbitrage)?
• What triggers price updates (volume thresholds, trade sizes)?
• Is there time-dependent decay in pricing accuracy?
• How do they respond to significant events during market closures?

3. Analysis Methods

• Triangular Arbitrage: BTC/USD ÷ BTC/EUR = Implied EUR/USD
• Volume Correlation: Price changes vs trading volume analysis
• Time Decay Modeling: Exponential and linear decay fitting
• Event Response: Weekend event impact detection

Files

• lighter-fx.ipynb: Main analysis notebook (16 cells)
• lighter_assessment_data.csv: Lighter FX weekend data
• spot_fx_control_data.csv: Traditional spot FX data
• requirements.txt: Python dependencies

Key Findings

1. Triangular Arbitrage Confirmation: [Execute cells to populate]
2. Volume-Price Correlations: [Execute cells to populate]
3. Time-Dependent Decay: [Execute cells to populate]
4. Event-Driven Responses: [Execute cells to populate]

Usage

1. Install dependencies: pip install -r requirements.txt
2. Open lighter-fx.ipynb in Jupyter/VS Code
3. Execute all cells in sequence (1-16)
4. Review generated visualizations and analysis results

Dependencies

• pandas
• numpy
• matplotlib
• seaborn
• yfinance
• requests
• scipy
• scikit-learn

Output

• Comprehensive analysis charts (PNG format)
• Statistical correlations and model fits
• Professional quant research conclusions