Impact of arbitrage between leveraged ETF and futures on market liquidity during market crash

Paper: arXiv 2603.05862

Authors: Ryuki Hayase, Takanobu Mizuta, Isao Yagi

Abstract

Leveraged ETFs (L-ETFs) are exchange-traded funds that achieve price movements several times greater than an index by holding index-linked futures such as Nikkei Stock Average Index futures. It is known that when the price of an L-ETF falls, the L-ETF uses the liquidity of futures to limit the decline through arbitrage trading. Conversely, when the price of a futures contract falls, the futures contract uses the liquidity of the L-ETF to limit its decline. However, the impact of arbitrage trading on the liquidity of these markets has been little studied. Therefore, the present study used artificial market simulations to investigate how the liquidity (Volume, SellDepth, BuyDepth, Tightness) of both markets changes when prices plummet in either (i.e., the L-ETF or futures market), depending on the presence or absence of arbitrage trading. As a result, it was found that when erroneous orders occur in the L-ETF market, the existence of arbitrage trading causes liquidity to be supplied from the futures market to the L-ETF market in terms of SellDepth and Tightness. When erroneous orders occur in the futures market, the existence of arbitrage trading causes liquidity to be supplied from the L-ETF market to the futures market in terms of SellDepth and Tightness, and liquidity to be supplied from the futures market to the L-ETF market in terms of Volume. We also analyzed the internal market mechanisms that led to these results.

Complexity vs Empirical Score

• Math Complexity: 3.5/10
• Empirical Rigor: 4.0/10
• Quadrant: Philosophers — conceptual discussion, limited math and data

Why this score: The paper uses an agent-based simulation (artificial market) to study liquidity dynamics during market crashes between leveraged ETFs and futures markets. While the mechanics of the market model are clearly explained, the math is relatively simple and the work relies entirely on simulation rather than empirical financial data.

Research Flowchart

  flowchart TD
    A[Research Goal: Impact of L-ETF & Futures Arbitrage on Market Liquidity During Price Plummets] --> B[Methodology: Agent-Based Artificial Market Simulation]
    B --> C[Inputs: Order Books & Erroneous Orders in L-ETF or Futures Market]
    C --> D[Simulate Scenarios: Presence vs. Absence of Arbitrage Trading]
    D --> E[Measure Liquidity Metrics: Volume, SellDepth, BuyDepth, Tightness]
    E --> F[Outcomes & Findings]
    
    F --> G[L-ETF Crash: Arbitrage supplies liquidity from Futures to L-ETF SellDepth & Tightness]
    F --> H[Futures Crash: Arbitrage supplies liquidity from L-ETF to Futures SellDepth & Tightness, and Futures to L-ETF Volume]

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2 of 266 cited works are in the corpus; resolved via arXiv source bundles, Semantic Scholar and OpenAlex. Corpus-wide: 2518 linked papers.