How does liquidity shape the yield curve?

ArXiv ID: 2409.12282 “View on arXiv”

Authors: Unknown

Abstract

The phenomenology of the forward rate curve (FRC) can be accurately understood by the fluctuations of a stiff elastic string (Le Coz and Bouchaud, 2024). By relating the exogenous shocks driving such fluctuations to the surprises in the order flows, we elevate the model from purely describing price variations to a microstructural model that incorporates the joint dynamics of prices and order flows, accounting for both impact and cross-impact effects. Remarkably, this framework allows for at least the same explanatory power as existing cross-impact models, while using significantly fewer parameters. In addition, our model generates liquidity-dependent correlations between the forward rate of one tenor and the order flow of another, consistent with recent empirical findings. We show that the model also account for the non-martingale behavior of prices at short timescales.

Keywords: Microstructure, Order Flow, Forward Rate Curve, Cross-impact, Liquidity, Fixed Income

Complexity vs Empirical Score

  • Math Complexity: 7.5/10
  • Empirical Rigor: 4.0/10
  • Quadrant: Lab Rats
  • Why: The paper employs advanced statistical mechanics and field theory (e.g., stiff elastic string, Langevin noise, matrix operators) with dense mathematical derivations, qualifying as high complexity. However, the empirical evidence is primarily conceptual and theoretical, focusing on model consistency with past findings (e.g., Epps effect, non-martingale behavior) rather than providing backtests, datasets, or performance metrics for trading strategies.
  flowchart TD
    A["Research Goal<br>How does liquidity shape<br>the yield curve?"] --> B["Data & Inputs<br>Order Flow & Price Shocks"]
    B --> C{"Computational Process<br>Stiff Elastic String Model"}
    C --> D["Relate Exogenous Shocks<br>to Order Flow Surprises"]
    D --> E["Model Joint Dynamics<br>Prices + Order Flow"]
    E --> F["Account for Impact<br>& Cross-Impact Effects"]
    F --> G["Key Findings / Outcomes"]
    
    subgraph G ["Outcomes"]
        G1["Liquidity-dependent correlations<br>between forward rates & order flows"]
        G2["Explanatory power >= existing models<br>with significantly fewer parameters"]
        G3["Accounts for non-martingale<br>price behavior at short timescales"]
    end