Abstract
A key problem for order book exchanges is how to attract liquidity providers and retain their support in all market conditions. This is commonly approached through individual business agreements with market makers whereby a bespoke contract is negotiated for specific obligations and rewards. Such approaches require a central intermediary that profits from liquidity provision to administer, and typically fail to align the incentives of exchanges and liquidity providers as markets grow. This is costly, slow, and scalability is limited by the exchange’s resources, contacts, and expertise.
This paper develops mechanisms for creating open, automated and scalable liquidity markets. We describe formal methods to quantify liquidity and discuss various approaches to determine its price. In so doing, we introduce a novel way to structure liquidity commitments, along with a mechanism based on a financial bond with penalties for under-provision to maximise market makers’ adherence to their obligations. We also investigate mechanisms to allocate rewards derived from trading fees between market makers, so as to incentivise desirable-but-risky behaviours such as market creation and early commitment of liquidity. We complement this work with several agent based simulations exploring the proposed mechanisms.
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Notes
- 1.
A record of outstanding buy and sell orders set to trade at a specified (or better) price. Once the prices (and volumes) of buy and sell orders match a trade is generated and the associated orders get removed from the book).
- 2.
The act of supplying both buy and sell prices to the market with the intention of making a profit on the price difference.
- 3.
Financial instruments deriving their value from the future value of other financial assets.
- 4.
Total value of the position.
- 5.
Order book volume at different price levels around the mid-price.
- 6.
Pegged order has its priced derived from a reference price and an offset, e.g. and order to buy at two ticks from the mid price. The price gets updated each time the reference price moves.
- 7.
We write a difference in our notation but could in principle count time using various conventions e.g. ignoring periods when a market is shut.
- 8.
Available at: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3651085.
- 9.
Available at: https://github.com/vegaprotocol/research/.
- 10.
Available at: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3651085.
- 11.
When market is in auction trades are no longer generated as soon as there’s a match in price between a buy and sell order, instead orders keep getting added to the order book, possibly resulting in a crossed state - an overlap between bids and offers - until the auction concludes and associated trades are generated so as to maximise the traded volume (subject to additional rules should a few price levels result in the same maximum volume).
- 12.
i.e. \(F_S(x) = \int _{-\infty }^xf_S(y)\,dy\).
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Gawlikowicz, W., Mannerings, B., Rudolph, T., Šiška, D. (2021). Market Based Mechanisms for Incentivising Exchange Liquidity Provision. In: Bernhard, M., et al. Financial Cryptography and Data Security. FC 2021 International Workshops. FC 2021. Lecture Notes in Computer Science(), vol 12676. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-63958-0_7
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