Market-making research answers one question three ways: how should a liquidity provider set quotes given inventory risk and adverse selection? The stochastic-control lineage (Avellaneda–Stoikov and descendants) answers with closed forms; the RL lineage answers with learned policies; the DeFi lineage redesigns the mechanism itself. The branches below follow those lines — with the venue-specificity caveat that applies doubly to anything empirical here.

  flowchart TD
  ROOT["Market-Making Research<br>630 papers"]
  ROOT --> S0["Inventory & optimal quoting<br>85 papers"]
  ROOT --> S1["Adverse selection & information<br>44 papers"]
  ROOT --> S2["RL market making<br>79 papers"]
  ROOT --> S3["AMMs & DeFi liquidity<br>105 papers"]
  ROOT --> S4["Empirical market making<br>121 papers"]

630 papers mapped · ranked by rigor-weighted score · regenerated automatically as the daily pipeline scores new papers.

Inventory & optimal quoting

The stochastic-control core: quotes as a function of inventory and time.

Adverse selection & information

Who picks you off, and what spreads must charge for it.

RL market making

Learned quoting policies and their evaluation problems.

AMMs & DeFi liquidity

Constant-function markets, LP returns, and impermanent loss.

Empirical market making

Measured spreads, dealer behavior, and liquidity supply in real books.

Evaluation lens for this field: see the guides index · Full hub: /topics/market-microstructure/