Economics & Finance · Interdisciplinary & Society
Trading & Market Microstructure
The newest papers in Trading & Market Microstructure that ReadSearch has read, newest first. Each links to its own page, with its authors, date, where it was published and the original.
97 papers, from 5 September 2026 to 4 November 2026: 97 arXiv preprints.
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Newest papers, page 3
Do Rollups Self-Organize? Multi-Agent Reinforcement Learning in the EIP-4844 Blob Fee Market
EIP-4844 gave Ethereum rollups a separate fee dimension for data, governed by a multiplicative update rule that targets three ``blobs'' per block.Exact Phase-Type Point Processes for Certified Measurement and Prediction of Event Streams
Temporal point processes are used both to measure market mechanisms, for example how fast prices absorb news and how much of the reaction is the market responding to itself, and to predict the next…FOMO: FLEX Options and Market Outcomes
FLEX options are customized exchange-traded contracts allowing participants to choose nonstandard strikes, expirations, exercise styles, and settlement terms while retaining central clearing.MLP-Initialized Reinforcement Learning for Exit Timing in SPX Short-Straddle Portfolios
This paper studies exit timing for SPX short-straddle portfolios using a two-stage supervised and reinforcement-learning framework.Diffusive Market Impact: A Consistent Microfoundation
Structural price diffusivity explains many empirical regularities of market impact including the ``square-root law'' and its crossover to a linear regime for low trading rates…Market Impact Estimation via Causal Foundation Models
When a trader executes a large order, the relevant question is not \emph{what will the price be?} but \emph{what would the price have been had I not traded?} Market impact is thus a causal quantity…On Bonart's interpretation of the Square-Root Impact Law
The square-root impact law (SRIL), $I = Yσ\sqrt{Q/V}$, bundles two facts that a single mechanism must explain at once: a shape (impact proportional to square-root of traded volume $Q$) and an…SOTA: Stock Options Trading Agents Guided by Option-Implied Return Distributions
As option markets grow and AI advances, agentic systems for option trading are gaining increasing attention.A Hawkes Microfoundation for Multitype Inverse Gaussian Subordinators
We provide an event-level Hawkes microfoundation for a multitype inverse-Gaussian stochastic clock.A Finite Bid--Ask Spread from Replenishment Displaced from the Quote
We give a unified analytic account of a finite bid--ask spread in a two-field reaction--diffusion order book.Modelling Regime Shifts in Continuous Intraday Electricity Markets with State-dependent Hawkes Processes
The growing importance of intraday trading in Europe, driven by the increasing penetration of renewable energy sources, has led to higher volatility and periods of market stress.Latent Continuum of Regimes in Limit Order Book Dynamics
Market-regime models typically assume a finite set of discrete latent states.Measuring Trade Direction in a Prediction Market: Settlement Ground Truth and Trading-Cost Measurement on Polymarket
Trade-sign errors can change measured trading costs even when classification accuracy is high.Buying at Support: The Entry Problem under Multi-Skew Brownian Motion
We study when to buy a share that will later be sold optimally, when the price follows a geometric multi-skew Brownian motion whose skew levels model support and resistance.Axient: Canonical Protocol-Graph Composition for Leveraged Event Markets: Single State Authority, Atomic Composition, Durable Sagas, and Exactly-Once Recovery
A modular leveraged event-market protocol can contain individually correct contracts for risk approval, positions, debt, settlement evidence, credit pools, junior backstops, reserves, liquidation…Axient: Manifest-Bound Evidence for On-Chain Financial Protocols: Seven-Layer Derivation, Correlation, Tamper Rejection, and Reproducible Claim Promotion
Hybrid on-chain financial protocols are frequently evaluated with evidence that is individually useful but collectively insufficient: a unit test, transaction receipt, screenshot, service response…MintEval: Do LLMs Implement the Trading Strategy You Asked For? A Behavioural-Equivalence Benchmark for Natural-Language-to-Strategy Code
Large language models are moving from producing trading signals to writing the code that executes them.Mixture-of-Experts for Cryptocurrency Order Execution: Training Stability, Tail Risk, and Failure Modes
Deep reinforcement-learning policies for order execution can vary substantially across training seeds, so apparent architectural gains may reflect favourable training realisations rather than…When a Correct Reward Is Not Enough: Diagnosing and Guiding PPO in an Analytically Solved Broker-Trader Game
Reinforcement learning (RL) is increasingly used for financial optimal-control problems when complex dynamics make analytical strategies difficult to obtain.Priority Gas Auction Cadence and Searcher Competition: Evidence from Flashblocks on Base
Flashblocks divide a block's priority gas auction into shorter sequential auctions that commit transaction order before the block is complete.