Adaptive Order Slicing from Forecast Volume and Price Ranges

Summary

The document describes an adaptive execution strategy for large orders, motivated by the market impact and slippage that can arise when substantial volume is traded. It proposes estimating future trading volume and price ranges, then using those estimates to adjust the sizes of order slices as market conditions change.

The forecasting approach combines an Exponential Weighted Moving Average with Markov Chain Monte Carlo simulations. The paper reports that the method improves execution efficiency and reduces market impact, and presents it as useful in volatile conditions. The excerpt does not specify the data, comparison benchmarks, evaluation design, or size of the reported improvements, so it is not possible to assess how robust or transferable those results are from this description alone.

Key ideas

• Large orders can create market impact and slippage during execution.
• The strategy forecasts trading volume and price ranges to adjust slice sizes.
• It combines an Exponential Weighted Moving Average with Markov Chain Monte Carlo simulations.
• The document reports improved execution efficiency and lower market impact, but gives no evaluation details in the excerpt.

Tags

# Volatility-Volume Order Slicing via Statistical Analysis


# Volatility-Volume Order Slicing via Statistical Analysis









This paper addresses the challenges faced in large-volume trading, where executing substantial orders can result in significant market impact and slippage. To mitigate these effects, this study proposes a volatility-volume-based order slicing strategy that leverages Exponential Weighted Moving Average and Markov Chain Monte Carlo simulations. These methods are used to dynamically estimate future trading volumes and price ranges, enabling traders to adapt their strategies by segmenting order execution sizes based on these predictions. Results show that the proposed approach improves trade execution efficiency, reduces market impact, and offers a more adaptive solution for volatile market conditions. The findings have practical implications for large-volume trading, providing a foundation for further research into adaptive execution strategies.

Shown in full with attribution under the source's licence. Licence: abstract CC0

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.