Paper: arXiv 2501.03171

Abstract

Lead-lag relationships, integral to market dynamics, offer valuable insights into the trading behavior of high-frequency traders (HFTs) and the flow of information at a granular level. This paper investigates the lead-lag relationships between stock index futures contracts of different maturities in the Chinese financial futures market (CFFEX). Using high-frequency (tick-by-tick) data, we analyze how price movements in near-month futures contracts influence those in longer-dated contracts, such as next-month, quarterly, and semi-annual contracts. Our findings reveal a consistent pattern of price discovery, with the near-month contract leading the others by one tick, driven primarily by liquidity. Additionally, we identify a negative feedback effect of the “lead-lag spread” on the leading asset, which can predict returns of leading asset. Backtesting results demonstrate the profitability of trading based on the lead-lag spread signal, even after accounting for transaction costs. Altogether, our analysis offers valuable insights to understand and capitalize on the evolving dynamics of futures markets.

Complexity vs Empirical Score

  • Math Complexity: 6.5/10
  • Empirical Rigor: 8.0/10
  • Quadrant: Holy Grail — high math complexity, high empirical rigor

Why this score: The paper uses advanced econometric methods like the Hayashi-Yoshida estimator and bootstrap testing, indicating high mathematical complexity. It also demonstrates high empirical rigor by using extensive tick-by-tick data, performing backtests with transaction costs, and presenting profitable out-of-sample results.

Research Flowchart

  flowchart TD
  A["Research Goal:<br>Investigate lead-lag relationships<br>in Chinese index futures market"] --> B["Data Source:<br>High-frequency tick-by-tick data<br>from CFFEX (Near, Next, Qtr, Semi-Annual)"]
  B --> C["Methodology:<br>Time-series regression &<br>Calendar spread analysis"]
  C --> D["Key Analysis:<br>Identify lead-lag spread &<br>Negative feedback effects"]
  D --> E["Validation:<br>Backtest trading strategy<br>using spread signals"]
  E --> F{"Key Outcomes"}
  F --> G["Near-month leads others<br>by one tick"]
  F --> H["Negative feedback on<br>leading asset"]
  F --> I["Profitable trading<br>after costs"]

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0 of 42 cited works are in the corpus; resolved via arXiv source bundles, Semantic Scholar and OpenAlex. Corpus-wide: 2518 linked papers.