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Market Making With Alpha Signals

Author

Listed:
  • ÁLVARO CARTEA

    (Mathematical Institute, University of Oxford, Oxford, UK2Oxford-Man Institute of Quantitative Finance, Oxford, UK)

  • YIXUAN WANG

    (Mathematical Institute, University of Oxford, Oxford, UK)

Abstract

We show how a market maker employs information about the momentum in the price of the asset (i.e. alpha signal) to make decisions in their liquidity provision strategy in an order-driven electronic market. The momentum in the midprice of the asset depends on the execution of liquidity taking orders and the arrival of news. Buy market orders (MOs) exert a short-lived upward pressure on the midprice, whereas sell MOs exert a short-lived downward pressure on the midprice. We employ Nasdaq high-frequency data to estimate model parameters and to illustrate the performance of the market making strategy. The market maker employs the alpha signal to minimise adverse selection costs, execute directional trades in anticipation of price changes, and to manage inventory risk. As the market maker increases their tolerance to inventory risk, the expected profits that stem from the alpha signal increase because the strategy employs more speculative MOs and performs more roundtrip trades with limit orders.

Suggested Citation

  • Álvaro Cartea & Yixuan Wang, 2020. "Market Making With Alpha Signals," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 23(03), pages 1-26, May.
    • Handle: RePEc:wsi:ijtafx:v:23:y:2020:i:03:n:s0219024920500168
    DOI: 10.1142/S0219024920500168
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    Citations

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    Cited by:

    1. 'Alvaro Cartea & Fayc{c}al Drissi & Marcello Monga, 2023. "Decentralised Finance and Automated Market Making: Predictable Loss and Optimal Liquidity Provision," Papers 2309.08431, arXiv.org, revised Jun 2024.
    2. Peter Bank & 'Alvaro Cartea & Laura Korber, 2023. "Optimal execution and speculation with trade signals," Papers 2306.00621, arXiv.org, revised Dec 2024.
    3. Zhou Fang & Haiqing Xu, 2023. "Over-the-Counter Market Making via Reinforcement Learning," Papers 2307.01816, arXiv.org.
    4. Xuchen Wu & Sebastian Jaimungal, 2024. "Broker-Trader Partial Information Nash Equilibria," Papers 2412.17712, arXiv.org.
    5. Emilio Barucci & Adrien Mathieu & Leandro S'anchez-Betancourt, 2025. "Market Making with Fads, Informed, and Uninformed Traders," Papers 2501.03658, arXiv.org, revised Feb 2025.
    6. Carè, Rosella & Cumming, Douglas, 2024. "Technology and automation in financial trading: A bibliometric review," Research in International Business and Finance, Elsevier, vol. 71(C).
    7. Robert Boyce & Martin Herdegen & Leandro S'anchez-Betancourt, 2024. "Market Making with Exogenous Competition," Papers 2407.17393, arXiv.org.
    8. Marcello Monga, 2024. "Automated Market Making and Decentralized Finance," Papers 2407.16885, arXiv.org.
    9. Joseph Jerome & Leandro Sanchez-Betancourt & Rahul Savani & Martin Herdegen, 2022. "Model-based gym environments for limit order book trading," Papers 2209.07823, arXiv.org.

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