This paper presents a novel approach to quantifying execution risk in fragmented liquidity venues. We utilize a proprietary stochastic model to estimate slippage probability under varying volatility regimes.
### 1. Data Processing in R
The initial data cleaning was performed using R. We filtered for anomalous trade prints that deviated more than 3 sigma from the VWAP.
### 2. Results
The model demonstrates a 14% reduction in execution costs compared to standard TWAP algorithms.