Price Slippage Model
Problem Statement
When simulating miner performance, our current PTN system does not account for potential slippage that may occur during market order execution. As a result, the PTN system tends to overestimate the performance of miners with higher trading turnover. When a miner’s market order size is large, and the traded asset has low liquidity, it can lead to “walking the order book” which refers to the process where a large market order consumes liquidity across multiple price levels in the order book. This happens because the size of the order exceeds the available quantity or liquidity at the best bid or ask price, causing the trade to execute at progressively less favorable prices as it moves through successive levels of the order book. This often results in significant slippage and lower expected return of trading strategies, especially in markets with low liquidity or shallow order books.
What is a Price Slippage Model
A price slippage model estimates the difference between a trade’s expected price (typically the last traded price or mid-price between the best bid and ask) and its actual execution price, often due to market factors like liquidity, volatility, and order size. It helps assess trading costs in simulation, optimize execution strategies, and improve the accuracy of miner performance in PTN, making it more aligned with real-world trading dynamics.
Model Specification
Where:
- S: Slippage percentage,
- Q: Order size
- V1: The 10-day average daily trading volume prior to miners’ market order
- vol: The asset’s annualized volatility or intra-day volatility
- spread: lowest ask - highest bid
- mid-price:
- fn: Linear functions
- a: Constant term
These proposed model specs are general and tentative. Models may vary across asset classes and even specific assets.
Reference: Equity Market Impact Models
Proposed Changes
Implementation of the price slippage model will happen concurrently with the transition to real position sizing in our Dec roadmap found here. In order to determine order size from the leverage value, we will implement a translation layer where every 1x position leverage translates to $100K in value. For example, a 0.5x leverage long order will be translated to $50K for purposes of order sizing and slippage calculation.
This change will impact the positional returns and miner performance, particularly for assets with high slippage. The parameters of the model will be determined using order book data and distributed quarterly.
Timeline
Proposal Delivery: January 13, 2025
PR: January 20, 2025
Implementation: January 2025