Paper: arXiv 2610.31141

Authors: Xinlei Hao, Jiajun Guo, Jussi Keppo, Xianhua Peng

Abstract

This study uses a high-frequency dataset from a stock exchange to examine how forecasting ability and liquidity provision relate to institutional traders’ proprietary intraday profitability. We discover persistent forecasting abilities among traders. Specifically, we demonstrate that hypothetical flow-following strategies based on the execution flows of these skillful traders yield annualized Sharpe ratios ranging from 16 to 63 across various trading frequencies. We match buy and sell executions into positions, linking realized profit and loss (P&L) to horizon-matched forecasting proxies and the liquidity roles of both executions. Our findings indicate a direct correlation between improved forecasting ability and profitability, where a one-standard-deviation increase in the forecasting ability proxy is associated with 1.02 – 1.19 currency units higher P&L per matched position. Additionally, we measure liquidity-provision intensity within a matched position by its number of passive executions: zero, one, or two. In these regressions, P&L is 1.28 – 1.31 currency units higher for one passive execution than for none, and a further 3.79 – 3.82 higher for two than for one, underscoring the significant financial benefits of liquidity provision.

Complexity vs Empirical Score

  • Math Complexity: 6.0/10
  • Empirical Rigor: 6.0/10 (capped from 8.0: transaction costs only partially modelled; see penalty flags)
  • Quadrant: Holy Grail — high math complexity, high empirical rigor

Why this score: The paper demonstrates strong empirical rigor through its use of high-frequency data, detailed statistical methodology, and backtesting of strategies. While the mathematical complexity is moderate, the novelty of linking specific intraday P&L to horizon-matched forecasting proxies and liquidity roles is significant. The overall clarity and completeness are good, though reproducibility could be enhanced with explicit code/data availability.

Research Flowchart

  flowchart TD
    A[Research Goal: Examine Forecasting Ability & Liquidity Provision Impact on Institutional Traders' Intraday Profitability] --> B{Key Methodology Steps};
    B --> C[Data/Inputs: High-frequency Stock Exchange Dataset];
    C --> D[Computational Processes: Match Buy/Sell Executions into Positions, Calculate P&L, Forecasting Proxies, Liquidity Provision Intensity];
    D --> E[Key Finding 1: Persistent Forecasting Abilities & High Sharpe Ratios (16-63) for Skillful Traders' Strategies];
    D --> F[Key Finding 2: Direct Correlation - 1-SD Increase in Forecasting Ability Linked to 1.02-1.19 Currency Units Higher P&L/Position];
    D --> G[Key Finding 3: Significant Financial Benefits of Liquidity Provision - P&L 1.28-1.31 Higher for 1 Passive Execution, and 3.79-3.82 Higher for 2 vs. 1];