cs.AI · cs.CL · cs.LG · cs.CV · cs.CR · cs.SE · stat.ML · q-fin.TR · q-fin.ST · econ.GN · q-bio.QM · physics.soc-ph · math.OC · cs.RO · cs.HC
Joseph Cary, Thomas Morstyn · 2026-10-20
The electricity system in Great Britain (GB) allows participants to deliberately produce or consume a different volume to their traded position and has incentivised this practice with a single imbalance price since 2015. In particular, non-physical traders (NPTs) often take an op…
George Nigmatulin, Valentin Mohl, Sascha Frey, Kang Li, Aramis Marti-Shahandeh and others · 2026-10-19
Realistic market impact is essential for generative limit order book (LOB) models to serve as world models for trading agents. If a simulator misprices this mechanism, agents learn policies that are optimal in the simulator but wrong in the real market. Existing metrics assess ge…
Skander Lejmi · 2026-10-19
A market maker provides liquidity by quoting prices to buy and sell an asset, earning the spread while managing inventory risk. We study market makers trained with multi-agent reinforcement learning on prediction markets, specifically Polymarket, whose thin order books pose disti…
Saad Naja, Nasser Odtallah, Jake Van-Praag, Sarah May · 2026-10-19
Trading discipline often fails people. Our study tested whether four AI trading agents followed their strategies and risk rules. Offering traders the evidence and an agent evaluation toolkit to separate luck from following the rules, before giving agents meaningful autonomy or ca…
Aadit Jerfy · 2026-10-19
Topological Data Analysis (TDA) and Persistent Homology (PH) have been utilized in numerous fields$-$from protein modeling to financial analysis$-$to understand the underlying structure of data. In this paper, we incorporate TDA and PH into forecasting models over a prediction ma…
Junyu Chen, Franklin Liu, Moshu Xu, Lijian Yang · 2026-10-18
Modeling limit order book (LOB) dynamics is central to market forecasting and execution-strategy evaluation. While diffusion models achieve strong empirical performance, existing LOB snapshot models typically lack a learned recurrent encoder and formal statistical guarantees. We …
Dnyanesh Kulkarni, Revant Nayar · 2026-10-16
Classical execution models assume linear impact, diffusive prices, and an exogenous horizon. We study execution under concave power-law impact and Hurst-scaled price fluctuations, and make two contributions. First, we choose the execution horizon by maximizing the Sharpe ratio of…
Ayoub Jhabli, Tarek Alskaif, Kwabena E. Bennin, Bedir Tekinerdogan, Joost M. E. Pennings · 2026-10-16
As renewable energy integration accelerates, intraday continuous (IDC) electricity markets have become essential for short-term balancing. However, the simultaneous trading of overlapping contracts with varying granularities creates complex, hidden liquidity dependencies that are…
Hongjian Shi, Daojing Zhai · 2026-10-16
We develop a framework to identify and quantify arbitrage across logically related prediction-market contracts. We prove that prices outside the convex hull of admissible payoff vectors admit arbitrage and identify optimal arbitrage portfolios through integer programming. Using v…
Donghwa Seo, Doohwi Cha, Seunghan Son, Juyeong Lee, Minsuk Sung and others · 2026-10-16
Crypto venues increasingly list perpetual futures on equities and other real-world assets (RWAs), which trade continuously yet reference dividend-paying stocks: a long equity perpetual marked to the ex-dividend cash price bears the ex-dividend drop without receiving the dividend.…
Jung Hun Phee, Tucker Balch · 2026-10-15
We study the conditional distribution of limit-order volume submitted over the next five minutes, given the current order book and recent order flow. The task requires capturing price placement, total volume, and predictive uncertainty jointly. Coordinate-wise diffusion losses do…
Irene Aldridge, Lourenco Belleau-Bhowmik, James Chan, Josh Chang, Kelly Deng and others · 2026-10-15
Automated markets increasingly host autonomous, learning trading agents and are powered by formulaic automated market makers (AMMs). We study how heterogeneous agent behavior shapes stress, risk-adjusted performance, liquidity, and volatility in these types of markets. Three beha…
Alex Vidovich, Zivana Zerjal · 2026-10-15
Backtests of intraday strategies can drift away from what the live system actually does; in our case, the drift never showed in summary statistics. We report six defects found while running one intraday US equity system live and comparing its live days with their backtest replay.…
Doohwi Cha, Hanhee Kim, Hyeonjun Yeo, Minsuk Sung, Minjae Lee and others · 2026-10-15
Privacy-preserving protocols can repair a vulnerability without establishing whether it was exploited beforehand, even when no theft is reported and aggregate supply is protected. We call the potential value reduction from this gap the verifiability discount. A turnstile model sh…
Aleksei Adadurov, Eduard Airapetian, Anton Chtepine, Antero Eloranta, Boris Pletenev and others · 2026-10-15
We study the spread a liquidity provider needs to break even against counterparties that can exploit a stale quote, and we place two defenses on a single scale: repricing sooner and screening informed flow. A break-even condition pins down the exact screening rate at which a slow…
Doohwi Cha, Minsuk Sung, Minjae Lee, Hyeonjun Yeo, Hanhee Kim and others · 2026-10-15
Tokenized equities trade while listed markets are closed, so their marks could improve off-hours measurement along layered exposures that link Bitcoin, crypto-treasury stocks, and leveraged ETFs. A token return and the next opening gap, however, share the price move from the prev…
Arshia Abolghasemi, Seyed Reza Tavakoli, Parsa Naderi, Nazanin Mirzaei, Behrad Jahani and others · 2026-10-15
Score-based diffusion methods usually perturb data with Brownian Gaussian noise, corresponding to a light-tailed forward stochastic differential equation (SDE). For market time series this SDE can be a poor abstraction: limit order book (LOB) order flow is heavy-tailed, bursty, a…
Farbod Ghasemlu · 2026-10-12
Ethereum sells data-availability capacity to rollups through "blobs" priced by a controller: the blob fee rises and falls exponentially with cumulative usage above or below a target, and no auction sets it. We measure what this mechanical price costs. The Pectra upgrade of 7 May …
Hyeonjun Yeo, Doohwi Cha, Yoontae Hwang · 2026-10-12
A path indistinguishable from its own reverse carries no arrow of time, so time irreversibility is a necessary condition for a directed mechanism to be readable from trajectories alone. In finance it has been measured only on scalar series such as returns and volatility. We defin…
Alessio Brini · 2026-10-11
EIP-4844 gave Ethereum rollups a separate fee dimension for data, governed by a multiplicative update rule that targets three ``blobs'' per block. Whether this target is reached depends on how many independent, self-interested rollups choose to post data, a question that closed-f…
Sayak Dutta · 2026-10-10
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 event. We show that one algebraic object, the phase-type (Erlang-chain) state spac…
Jianning Wang, Robert Ślepaczuk, Paweł Sakowski · 2026-10-09
This paper studies exit timing for SPX short-straddle portfolios using a two-stage supervised and reinforcement-learning framework. Historical episodes first generate ex-post optimal hold/exit labels for training a multilayer perceptron (MLP) using only contemporaneously availabl…
Shivesh Prakash, Frank Ferstler, Nicholas Pezolano · 2026-10-09
FLEX options are customized exchange-traded contracts allowing participants to choose nonstandard strikes, expirations, exercise styles, and settlement terms while retaining central clearing. We investigate whether single-name FLEX activity leaves measurable footprints in regular…
Dennis Thumm, Ying Chen · 2026-10-08
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, yet classical models (Almgren--Chriss, propagators) regress price on flow, which …
Julius F. Bonart · 2026-10-08
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 \citep{bonart2026diffusive}. One of its central predictions is that an information-neutral trading strat…
Yingli Wang, Wei Xu, Lingjiong Zhu · 2026-10-07
We provide an event-level Hawkes microfoundation for a multitype inverse-Gaussian stochastic clock. We show that the event counts and integrated intensities of nearly critical multivariate linear Hawkes processes converge jointly to a multivariate pure-jump subordinator when repr…
Yizhen Xie, Mengyang Liu · 2026-10-07
As option markets grow and AI advances, agentic systems for option trading are gaining increasing attention. Language-model-based agents can reason over contextual information such as news, but option trading presents a particularly challenging decision problem: a single stock ca…
J. -P. Bouchaud, I. Mastromatteo, B. Toth · 2026-10-07
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 amplitude ($Y=O(1)$, independent of the participation rate $\varphi$). Bonart has recent…
Ayoub Jhabli, Tarek AlSkaif, Kwabena E. Bennin, Bedir Tekinerdogan, Axel Naumann and others · 2026-10-06
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. Understanding how order flow behaves under varying liquidity conditions requires models that adapt to…
Christopher Angstmann, Derick Diana, Tim Gebbie · 2026-10-06
We give a unified analytic account of a finite bid--ask spread in a two-field reaction--diffusion order book. The model retains separate bid and ask densities in operational time, with diffusion, cancellation, reaction and external order creation. On the symmetric equal-coefficie…
Philipp D. Dubach · 2026-10-05
Trade-sign errors can change measured trading costs even when classification accuracy is high. We validate the side of Polymarket's public trade prints against the taker leg of each print's on-chain settlement. On twelve selected days between April and August 2026, spanning both …
Anjali Thawait · 2026-10-05
Market-regime models typically assume a finite set of discrete latent states. We examine whether high frequency limit-order-book dynamics exhibit distinct regime separation or apparent regimes result from discretising an underlying continuum, analysing deep limit-order book data …
Jun Maeda · 2026-10-04
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. The reward for buying is the exit premium of the liquidation problem solved in a companion paper. This pre…
Mingyang, Chen, Yida, Xu, Huiwen and others · 2026-10-02
Financial LLM agents are often evaluated by comparing their end-to-end returns with those of a baseline and testing the paired difference against zero. This measures whether deploying the agent changes realized performance, but it does not isolate event-selection skill. An agent …
Pranay Anchuri, Edward W. Felten, Akaki Mamageishvili · 2026-10-02
Flashblocks divide a block's priority gas auction into shorter sequential auctions that commit transaction order before the block is complete. We ask how this auction cadence affects bidding and competition among automated arbitrageurs, or searchers. In July 2025 Base replaced a …
Siu Tung Wong, Carlo Campajola · 2026-10-02
Reinforcement learning (RL) is increasingly used for financial optimal-control problems when complex dynamics make analytical strategies difficult to obtain. There are financial mathematics literactures which provides many solved models whose equations and controls could evaluate…
Alexander Ardaiz, Varun Budati, Ali Habibnia · 2026-10-02
Deep reinforcement-learning policies for order execution can vary substantially across training seeds, so apparent architectural gains may reflect favourable training realisations rather than reproducible properties of the architecture. We evaluate vanilla Double Deep Q-Learning …
Siyu Wang, Yifan Wang, Yuecheng He · 2026-10-02
Large language models are moving from producing trading signals to writing the code that executes them. The failure mode of the second role is silent: generated code runs, a backtest plots, yet the risk logic that the trader described is not the logic being executed. Existing cod…
Maksym Nechepurenko · 2026-10-02
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, or several matching hashes may be presented as proof of a complete workflow even w…
Maksym Nechepurenko · 2026-10-02
A modular leveraged event-market protocol can contain individually correct contracts for risk approval, positions, debt, settlement evidence, credit pools, junior backstops, reserves, liquidation, and governance while still lacking one authoritative financial execution path. This…
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