The frontier of quantitative finance, in one feed. The newest peer-review-bound research from arXiv’s q-fin archive — trading and market microstructure, portfolio management, risk, pricing, and machine learning in markets — with titles, authors, and abstracts, linked straight to source. Updated continuously.
Execution, market making, order books, and market impact.
Trading & Market Microstructureq-fin.MFq-fin.RM3d ago
Ying Chen, Hoa Nguyen, Julian Sester, Hoang Hai Tran +1
We study sequential decision making under evolving uncertainty in high-frequency financial markets, where changing market dynamics continually challenge static decision policies. We show that robustness has two economically meaningful dimensions: uncertainty tolerance, which determines how much uncertainty the decision maker allows, and a…
Trading & Market Microstructure3d ago
Weiye Xi, Ciamac C. Moallemi, Mallesh Pai, Shouqiao Want
Forward-looking volatility forecasts are central inputs to derivatives pricing, market making, risk management, and volatility-linked trading strategies, with ARCH and GARCH models serving as the canonical workhorses. Such models are natural in standard asset markets, where prices are positive-valued stochastic processes and volatility is…
Trading & Market Microstructure5d ago
Ioanna-Yvonni Tsaknaki, Andrea Macrì, Fabrizio Lillo
In this paper, we investigate whether a model-free RL agent can identify and exploit price manipulation opportunities more effectively than a traditional model-based approach that assumes correct specification of the data-generating process but relies on noisy parameter estimates. We consider a single-asset market in which prices evolve a…
Computational Financeq-fin.TR6d ago
Yang Zhou, Jianwen Chen, Ruipeng Wei
We study a minimal agent-based market in which a single evolutionary-optimized institutional agent interacts with 20{,}000 herding retail traders. The agent spontaneously discovers a multi-cycle predatory strategy, producing 8--11 complete cycles over 2000 trading days with total portfolio return of $+51\%$ (best of 20 seeds; mean $+37.7\…
Pricing of Securitiesq-fin.MFq-fin.TR6d ago
Chris Angstmann, Tim Gebbie
We derive an operational-time variance kernel for a latent-order-book reaction boundary and use it to separate three objects usually collapsed in calendar-time volatility models: a structural boundary cumulant, a clock projection, and a pricing-measure choice. The reaction boundary is the zero of a bid--ask imbalance field. For a locally …
Computational Financeq-fin.MFq-fin.TR7d ago
Yang Zhou, Jianwen Chen, Ruipeng Wei
Three quantitative predictions have been advanced for the square-root law (SRL) of market impact, $I/σ_D = c\,(Q/V_D)^δ$ with $δ\approx 0.5$: GGPS ($δ=β-1$), FGLW ($δ=α-1$), and LOB walking ($δ=1/(1+γ)$). Using a minimal limit-order-book model populated by heterogeneous interacting agents and calibrated against the Tokyo Stock Exchange be…
Trading & Market Microstructureq-fin.MF7d ago
Umut Çetin, Mingwei Lin
We study a one period limit order market with informed traders, noise traders, and competitive liquidity suppliers, in which the number of informed traders is random. Liquidity suppliers know the distribution of the informed trader count, but not its realization, and therefore face uncertainty about both the presence and the intensity of …
Trading & Market Microstructure7d ago
Tim Gebbie
We propose a Gabor--Epps uncertainty principle for practical trading. The key idea is that high-frequency correlation is not observed in clock time alone, but is resolved through market activity, order-flow overlap, and finite coupling response. This suggests six simple rules of thumb that may be useful to traders and trading programs ope…
Trading & Market Microstructureq-fin.MF9d ago
Joseph Leclère, Youssef Ouazzani Chahdi, Mathieu Rosenbaum, Grégoire Szymanski
Market impact is defined as the difference between the observed price trajectory under a given execution strategy and the counterfactual trajectory that would have prevailed without it. Since this counterfactual is unobservable, estimating market impact requires simulating alternative paths under the same realized market randomness. We ad…
Trading & Market Microstructureq-fin.CPq-fin.ST9d ago
Arati Uday Kamat
This paper reports a precision audit of a production filter stack against a 13-day window of post-rejection forward-market observations on Solana DEX trading (2026-04-10 to 2026-04-23, UTC). The audit yielded 99,510 follow-up samples across 2,402 unique rejection events spanning eight active filter rules. We classify each event under a fi…
Trading & Market Microstructureq-fin.CPq-fin.GN9d ago
Arati Uday Kamat
We present a Kaplan-Meier and Cox proportional-hazards survival analysis of 832,941 Solana pump.fun token launches with 24-hour graduation outcomes, observed continuously between 2026-05-08 and 2026-06-10. The pooled graduation rate is 0.198% (Wilson 95% CI [0.189%, 0.208%]), a 3.18x decline from the 0.63% rate reported by Marino et al. (…
Trading & Market Microstructureq-fin.CPq-fin.ST10d ago
Arati Uday Kamat
We study coordinated buyer behavior on the Solana pump.fun bonding-curve marketplace using 1,578,333 buyer observations from 166,098 token launches between June 12 and June 26, 2026. A two-stage detection pipeline - intra-launch first-buyer-window extraction followed by cross-launch persistent-cohort surfacing via union-find on co-occurre…
Trading & Market Microstructureq-fin.PM10d ago
Jutta G. Kurth, Zoltan Eisler, Adam Rej, Jean-Philippe Bouchaud
Systematic trend following has, on average, been profitable for at least two centuries; yet since approximately 2009, short-term trends have ceased to deliver reliable returns. Using a cross-section of roughly 100 liquid futures contracts spanning 1995-2025, together with an industry-representative CTA proxy, we document the break and cha…
econ.EMq-fin.PRq-fin.ST11d ago
Irene Aldridge
We estimate Kyle's (1985) price-impact coefficient $λ$ directly from daily equity order flow and test its ability to forecast the cross-section of subsequent stock returns. Using CRSP data from 2020 to 2025, we construct firm-month measures of signed order flow and two estimators of $\hatλ_{it}$: a within-month price-impact regression and…
Trading & Market Microstructureq-fin.MF11d ago
Umut Çetin, Mingwei Lin, Giulia Livieri
When is a large trade news, and when is it a liquidity shock? We study this question in a sequential competitive limit order book with asymmetric information. In our model, liquidity suppliers observe aggregate order flow but not its decomposition into informed demand and uninformed liquidity demand. We model uninformed order flow with St…
Statistical Financeq-fin.PMq-fin.TR11d ago
Austin Pollok, Kevin Robik
Timing-based tilts across asset classes can drive much of the risk and return of a diversified cross-asset portfolio. The standard approach forecasts returns and then optimizes weights. We instead study an end-to-end AI-based policy that maps market states directly to portfolio weights, and we then ask when this one-step modeling approach…
Trading & Market Microstructureq-fin.GN12d ago
David Dai, Ruizhe Jia, Shihao Yu
Prediction markets increasingly list contracts settling on an asset price that holders can move by trading the underlying. We build a model showing that such contracts transfer wealth from prediction-market liquidity traders to manipulators and harm price discovery in the underlying, even as it becomes more liquid. After the launch of Pol…
Trading & Market Microstructure12d ago
Gianmarco Morbelli, Sven Karbach, Mike Derksen
We develop a signature-based framework for optimal execution in statistical arbitrage strategies with path-dependent predictive signals. Both the alpha process and the trading speed are modelled as linear functionals of the truncated signature of a time-augmented market path, placing signal generation and execution on the same truncated s…
Trading & Market Microstructure14d ago
Victoria Portnaya
SPY's lag-1 return autocorrelation ($\hatρ(1)=-0.081$, $z=-7.4$) is among the most significant regularities in empirical equity finance, yet the standard variance-ratio (VR) test cannot determine whether it reflects directional reversal or magnitude shrinkage - phenomena with entirely different trading implications. We develop the Fourier…
cs.LGq-fin.STq-fin.TR18d ago
C. Evans Hedges
We study whether a scaling-law-style inference-compute frontier appears in limit order book prediction. Using FI-2010 and a suite of models ranging from small decision trees to neural LOB architectures, we find that the realized empirical frontier of predictive loss versus structural forward work is well summarized by a power law. In part…
Trading & Market Microstructureq-fin.PMq-fin.PR18d ago
Yoonsik Hong, Diego Klabjan
Commodity futures can be represented hierarchically, with underlying assets at the upper level and individual futures contracts at the lower level. Entities at each level can be connected by edges reflecting inherent correlations, with cross-level edges capturing contract-to-underlying asset connections. Building on our observations of th…
Trading & Market Microstructureq-fin.GN18d ago
Shubhangam Shukla, Mahesh Peyyala, Abhijit Chakraborty
We investigate the evolving structure of interactions in cryptocurrency markets using a network-based framework constructed from high-frequency price data spanning 2020-2025. Directed and weighted networks are constructed from statistically significant Granger causal relationships between cryptocurrency log-returns, enabling us to quantif…
Trading & Market Microstructureq-fin.ST19d ago
Aniket Vasaikar
We test the square-root law (SRL) of market impact on a single U.S. large-capitalisation equity, Apple Inc. (AAPL), using the full Nasdaq TotalView-ITCH market-by-order feed over 178 trading days (2 December 2024 -- 19 August 2025; ~0.5 billion events). Without broker-tagged parent orders, we reconstruct metaorders from the anonymous tape…
Trading & Market Microstructure20d ago
Daniele Maria Di Nosse, Fabrizio Lillo
Automated Market Makers based on concentrated liquidity, such as Uniswap v3, significantly improve capital efficiency but expose Liquidity Providers (LPs) to adverse selection costs, formalized as Loss-Versus-Rebalancing (LVR). While theoretical literature quantifies these costs, the interplay between realistic blockchain microstructure a…
Trading & Market Microstructure20d ago
Jian Sun
We propose a deterministic adversarial market model in which apparent randomness emerges endogenously from the interaction between a market mechanism and a population of predictive traders. Unlike a classical generative adversarial network, the model does not attempt to imitate an external empirical data distribution and does not inject r…
Trading & Market Microstructure22d ago
Meghan Ambrosia, Bruce Mizrach
We study the evolution of transaction speed and fees from January 2024 through March 2026, comparing Ethereum Mainnet and its Layer 2 (L2) networks, as well as Solana and Polygon. Ethereum has undergone upgrades that have increased block size and blob count. These upgrades have doubled transactions per second (TPS) on both the Mainnet and…
cs.DCq-fin.TR23d ago
Shakya Jayakody, Prarthinie Jayakody
Simulating financial markets at scale with multi-agent (Agent-Based) models is critical for market design, regulatory stress-testing, and reinforcement learning, but traditional CPU simulators are bottlenecked by sequential processing while vectorized GPU frameworks suffer from kernel-launch overhead and redundant global-memory round-trip…
Mathematical Financeq-fin.TR23d ago
Farbod Ghasemlu
We study the fee policy of a liquidity provider (LP) in a constant-product automated market maker (AMM) whose fee can be adjusted continuously, as enabled by programmable hooks. Building on the loss-versus-rebalancing (LVR) framework of Milionis et al. (2022) and its extension to nonzero fees by Milionis et al. (2024), we model the LP's w…
Trading & Market Microstructure25d ago
Victoria Portnaya
The digitization of financial markets has produced two classes of platforms that price, in principle, the same state - contingent payoffs: centralized crypto-option exchanges and blockchain-based prediction markets. This paper provides the first option-implied benchmark test of prediction-market pricing for cryptocurrency threshold contra…
Trading & Market Microstructure27d ago
Chris Angstmann, Tim Gebbie
Starting with a coupled discrete reaction--diffusion formulation for the lit and latent order books with non-uniformly sampled event times and meta-order source terms we show how two familiar market-microstructure regularities can emerge from this framework: the long-memory of trade signs associated with the Lillo--Mike--Farmer (LMF) theo…
Trading & Market Microstructure28d ago
Davide Barone, Fabrizio Lillo
Sunshine trading theory predicts that publicly disclosing trading intentions can reduce adverse selection and attract liquidity provision, lowering execution costs. Evidence is scarce, because explicit preannouncement of large orders is rare in traditional markets. We study Hyperliquid, a fully on-chain limit order book for cryptocurrency…
Trading & Market Microstructureq-fin.ST1mo ago
Chris Angstmann, Tim Gebbie
We give a unified analytic account of correlation emergence and the Epps effect in two coupled limit order books. The model starts from a discrete random-walk description of order flow with creation, cancellation and diffusion. A pair-trader coupling between the books is introduced at the level of order creation. We clarify how the discre…
Trading & Market Microstructure1mo ago
Ilija I Zovko
An important question for an algo trader working an order is to understand if their actions are moving the market against them -- i.e., causing market impact. The conventional answer usually is one of two: (i) monitor price slippage in real-time, potentially reducing adverse activity with increased slippage, or (ii) do away with dynamic t…
Pricing of Securitiesq-fin.MFq-fin.TR1mo ago
Chris Angstmann, Tim Gebbie
We consider the role of a continuum operational time u and its mapping to calendar time t and how these relate to event time for option pricing problems. We derive option-pricing equations from an operational-time Markov lattice rather than from a calendar-time diffusion. The primitive model is a nearest-neighbour log-price lattice with s…
Trading & Market Microstructureq-fin.CPq-fin.MF1mo ago
Xinyue Fang, Robert Ślepaczuk
This study investigates whether regime-dependent volatility forecasting and machine-learning-based return prediction can be jointly integrated to improve both statistical forecasting performance and economic strategy outcomes in equity markets. Using high-frequency CSI 300 Index data from 2005 to 2023, a sequential twostage framework is d…
Mathematical Financeq-fin.TR1mo ago
Frank M. V. Feys
This paper axiomatizes the bid-ask market maker's quoting rule. A quoting rule maps the maker's state, namely inventory, belief, variance, trade intensity, and informed-trader fraction, to a bid-ask pair. Eight natural axioms, together with six environmental assumptions on the maker's inventory cost, force a unique three-parameter family:…
Mathematical Financeq-fin.TR1mo ago
Wenpin Tang
We consider the interaction between centralized trading and decentralized Proof of Stake (PoS) blockchain ecosystems. Motivated by the increasing dominance of centralized exchanges and the institutionalization of crypto markets, we study how trading activities on centralized exchanges affect staking behavior, token allocation, and decentr…
cs.AIq-fin.CPq-fin.TR1mo ago
Ilia Zaznov, Atta Badii, Julian Kunkel, Alfonso Dufour
This study addresses the optimal execution of large stock sell programs by introducing TT-DAC-PS (Twin-Target Deterministic Actor-Critic with Policy Smoothing), a deterministic actor-critic architecture that combines twin exponential-moving-average critic targets with pessimistic min backup, TD3-style target policy smoothing noise, delaye…
cs.AIq-fin.CPq-fin.TR1mo ago
Junyi Yao, Zihao Zheng
Large language models (LLMs) and agentic systems are increasingly proposed for financial trading, yet their reported performance remains difficult to compare because studies vary in data provenance, temporal split discipline, execution timing, turnover treatment, and transaction-cost modeling. This article presents a targeted topical revi…
Portfolio Managementq-fin.TR1mo ago
Yiqing Wang, Dehao Dai, Ding Ma, Kerui Geng
We test whether large language models (LLMs) add value in commodity portfolio construction when the information set and implementation rules are held fixed across strategies. A Hawkish Agent (inflation-tightening prior), a Dovish Agent (growth-easing prior), a Debate Agent, and a deterministic z-score Rule Agent each receive identical FRE…
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