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.
Empirical market behavior, volatility, and stylized facts.
Mathematical Financeq-fin.ST3d ago
Kenichiro Shiraya, Tomohisa Yamakami, Akira Yamazaki
This paper proposes a stochastic discount factor (SDF) scaled by time-varying volatility. By utilizing prices and market data implied solely from S\&P 500 options, the proposed framework recovers a stable, non-monotonic SDF that captures the pure forward-looking expectations of market participants while mitigating observation noise. Our e…
Statistical Finance4d ago
Andrés García-Medina
Detecting the number of global factors in high-dimensional correlation matrices is a central problem in multivariate statistics and random matrix theory, with important implications for asset pricing and econophysics. When the number of variables $p$ is comparable to the number of observations $n$, signal-to-noise separation becomes diffi…
stat.MEq-fin.ST5d ago
Sankalp Gilda
Finance, sensing, and demand streams violate the exchangeability that IID conformal prediction and the IID bootstrap assume, and existing libraries implement either a general resampling engine or conformal calibration without the other. tsbootstrap provides block, residual, sieve, and wild resampling, classical bootstrap confidence interv…
stat.MEq-fin.ST5d ago
Ahmad Koman
Rolling covariance estimates feed two objects that are routinely treated as market structure. The first is the dominant eigenspace, monitored through the projector movement $\widehat D_{K,t}=\|\widehat P_{K,t}-\widehat P_{K,t-1}\|_F$; the second comprises scalar spectral functionals such as the absorption ratio and the leading-eigenvalue …
Pricing of Securitiesq-fin.MFq-fin.ST5d ago
Mohammad Abedi
Standard models of stock price dynamics and option valuation usually begin by postulating stochastic processes. This paper develops an entropic inference framework that derives these processes from information constraints. The key symmetry is that markets reward returns rather than price levels, which selects log price as the dynamical va…
physics.soc-phq-fin.ST5d ago
Luis Enrique Correa Rocha
Collective emotion is often inferred from the tone of mass media, but such emotion is not directly observed. One approximation is to extract sentiment from text and use sentiment indexes as proxies to study the temporal organization of news sentiment. Using a daily index of U.S. economic news sentiment from 24 newspapers (1980-2025), we e…
Statistical Finance6d ago
Alessio Brini
We ask whether pretrained time series foundation models (TSFMs) improve on established econometric benchmarks for forecasting realized volatility. Using the VOLARE dataset, we conduct the first systematic comparison of nine zero-shot TSFMs against eight econometric specifications, including the Heterogeneous Autoregressive (HAR) family, a…
General Financeq-fin.CPq-fin.PR6d ago
Useong Shin
This paper extends the cap-axis integral diagnostic to general characteristic axes, measuring factor-model pricing errors as bridge-alpha curves. A predetermined characteristic order generates prefix portfolios; subtracting equal-exposure aggregate portfolios yields zero-investment bridges indexed by cutoff p. The null is a zero-curve res…
stat.MEq-fin.ST8d ago
Akash Deep, Gagan Deep
Local Gaussian correlation (LGC) measures dependence locally, making it a natural tool for tail dependence and financial contagion, but its estimates degrade in the joint tails, where they are most needed. Location-adaptive bandwidths have been tried for LGC and found inferior to a single global bandwidth; we explain why, and map the regi…
Statistical Financeq-fin.PM8d ago
Anders G Frøseth
We propose a multivariate generalisation of the Lo-MacKinlay (1988) variance ratio that decomposes long-horizon equity-return dynamics into separate return-channel and volatility-channel memory components across the cross-section of asset returns. The framework identifies a parsimonious five-factor model - capturing persistent, antipersis…
Portfolio Managementq-fin.RMq-fin.ST9d ago
William W. Lamptey, Nicholas Appiah, Abootaleb Shirvani, Priscilla Ati-Tay +2
This paper examines portfolio optimization and tail-risk analytics for a heterogeneous universe of actively managed investment funds. Using daily Bloomberg data for 30 funds from 4 December 2020 to 24 December 2025, the study evaluates buy-and-hold, mean--variance, CVaR-based, and tangency-type strategies under long-only and long--short c…
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…
General Financeq-fin.CPq-fin.MF10d ago
Useong Shin
I propose a cap-axis integral diagnostic for factor-model evaluation. Low-dimensional factor models can improve the maximum-Sharpe frontier while leaving zero-alpha violations on economically fixed subspaces. The diagnostic studies one such subspace by lifting pricing errors into a bridge-alpha curve along the market-capitalization rank a…
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…
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…
Statistical Finance12d ago
Rosie Hayward, Orla Lennon, Fabio Biancalana
Extreme events in financial systems, often captured by indicators such as volatility, remain difficult to identify close to their onset. Volatility shares many statistical properties with other natural, complex systems which experience extreme events, which we explore in this manuscript. We extend the analogy between rogue waves in optica…
Statistical Finance12d ago
Krzysztof Ozimek
Conventional comparisons of algorithmic trading strategies reduce each performance metric to a single number over the full backtest horizon, thereby discarding information about how performance varies with market conditions. This paper proposes a distributional framework that addresses this shortcoming. A walk-forward backtest of 146 out-…
cs.LGq-fin.RMq-fin.ST13d ago
Sichao He, Yansong Zhang
In a deep forecasting pipeline for fat-tailed financial returns at short horizons, which matters more - the backbone architecture or the output head? We compare four modern backbones (TimesNet, DLinear, N-BEATS, iTransformer) under three output heads: a point head, a single-Gaussian density head, and a Gaussian mixture density head with K…
Statistical Financeq-fin.MF16d ago
Daniele Angelini
Testing self-similarity in fractional processes from a single observed trajectory is difficult under long-range dependence, because the associated Kolmogorov--Smirnov (KS) statistic undergoes a phase transition when $H>1/2$. In this regime, the classical limit collapses to a non-functional absolute Gaussian law and finite-sample convergen…
cs.CEq-fin.ST16d ago
Yu Peng, Matloob Khushi, Josiah Poon
Cryptocurrency price prediction is a significant challenge in quantitative investment. In recent years, time series models have made significant progress in financial forecasting tasks, especially in the stock market. Despite the growing performance over the past few years, we question the validity of this line of research in cryptocurren…
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…
cs.LGq-fin.ST19d ago
Mohammadamin Dashti Moghaddam, Nick Sciarrilli
Financial fraud detection in digital banking requires reasoning over multiple heterogeneous event streams -- transactions, login sessions, risk signals -- that individually appear benign but collectively reveal fraudulent patterns. We propose the Multi-Stream Fraud Transformer (MSFT), a unified architecture that encodes each event stream …
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…
Statistical Financeq-fin.CPq-fin.RM20d ago
Abdulrahman Alswaidan, Cade Jin, Jeffrey D. Varner
Synthetic generators of daily equity returns let practitioners stress test, backtest, and design scenarios that a single realized market history cannot supply, but only if the generator reproduces the stylized facts of real returns: heavy tails, negligible linear autocorrelation, and slow decay of the absolute-return autocorrelation. Hidd…
cs.DCq-fin.CPq-fin.ST20d ago
Mohammed Benseddik, Benjamin Kraner, Claudio J. Tessone
Ethereum's beacon chain hosts over 920,000 active validators, a number inflated by the legacy 32 ETH stake cap. The Pectra upgrade (May 2025) addresses this by introducing 0x02 compounding validators, raising the maximum stake per validator from 32 to 2,048 ETH and enabling automatic reward reinvestment. This paper examines how compoundin…
Statistical Finance20d ago
Mao Guan, Qian Chen
Forecasting benchmarks for retrieval-augmented LLMs routinely confound model capability with information leakage: features labeled with a target's timestamp are often not observable at the system's decision time. We study leakage-controlled equity factor ranking with a retrieval-augmented 7B open-source LLM forecaster. At each month-end f…
stat.MEq-fin.RMq-fin.ST23d ago
Yuan Christopher Qiang, Fabio Sigrist
We introduce the zero-one censored transformed normal (ZOC-TN) model for proportional responses with potential probability mass at the boundaries 0 and 1. The model combines a censored Gaussian variable with a two-parameter affine-logit transformation on the interior (0,1). We characterize the transformation parameters, establish large-sa…
Statistical Financeq-fin.MFq-fin.RM24d ago
Sara A. Safari, Christoph Schmidhuber
We forecast future volatilities and correlations of financial markets based on the current trends in these markets. This complements previous work that models future expected returns by a cubic polynomial of the current trend strength. Empirically, we observe that volatilities and correlations tend to increase day after day in times of st…
Statistical Financeq-fin.MF25d ago
Siqi Shao, R. A. Serota
We analyze distributions of historic S&P500 multi-day returns, for the number of days of accumulation from 20 to 120. With the increase of the number of days of accumulation, we observe clear tempering of power-law tails toward a seemingly finite value. To explain this phenomenon, we employ a model that produces a "capped Inverse Gamma" s…
Statistical Finance27d ago
Rama Siva Sarwari Mallela, Manuele Leonelli
Cryptocurrency markets are prone to violent, synchronised drawdowns, challenging the claim that a basket of crypto-assets offers genuine internal diversification. Because standard covariance-based metrics fail to capture asymptotic tail dependence, they systematically understate systemic risk and overstate diversification benefits precise…
Risk Managementq-fin.ST28d ago
Mante Zelvyte, Jim E. Griffin
We introduce the Multiplex Network Hawkes model, which extends the network Hawkes framework of Linderman & Adams (2014) by allowing multiple excitation layers whose weights depend on observed edge and node covariates. We use the model to investigate how contagion in financial networks is affected by different transmission channels. The mu…
cs.LGq-fin.ST28d ago
Tien Thanh Thach
Transformers have shown remarkable success in sequence modeling, yet their direct application to financial time series remains challenging due to noisy signals, short-memory dynamics, and distributional shifts. This paper proposes a modified Transformer architecture for one-step stock index forecasting, combined with advanced learning-rat…
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…
stat.MEq-fin.ST1mo ago
Mathis Fourreau, Matthieu Garcin
The composite likelihood method reduces the computational cost of parameter estimation in time series by considering several subsets of observations instead of all observations at once. The asymptotic properties of this method are related to the Godambe information, an extension of the Fisher information that accounts for the dependence b…
Statistical Financeq-fin.RM1mo ago
Nicola Baldoni, Michele Sparviero, Lorenzo Viola
Generating stochastic trajectories for asset classes is an increasingly relevant task in quantitative finance. Traditional approaches, such as the stationary bootstrap, preserve by construction the empirical distribution of asset-class returns, but do not ensure that each individual simulated path is economically realistic: scenarios may …
Risk Managementq-fin.ST1mo ago
Michele Sparviero, Lorenzo Viola
This paper develops a methodological framework for reverse stress testing (RST) in which a multivariate stress scenario, coherent with the empirical dependence structure of a market, is reconstructed from a single exogenous shock prescribed on one asset class. The problem is formulated as the maximisation of the conditional density given …
econ.EMq-fin.PMq-fin.RM1mo ago
Irene Aldridge
We study the problem of auditing a black-box algorithmic decision-maker from observable inputs and outputs alone. Our main result is an exact decomposition: under precisely characterized conditions, the cumulative \emph{regret} of a dynamic policy equals the sum of per-period covariances between the cost vector and the policy's decision. …
Statistical Finance1mo ago
Krzysztof Ozimek
Anomaly detection methods in financial time series score statistically unusual observations in observable data, not topologically misexpected persistent deviations in the latent structure of co-movement. This study constructs a stock-level topological anomaly score jointly conditioned on market-level topological structure and cross-sectio…
Thank you to arXiv for use of its open-access interoperability. Paper metadata is sourced from the arXiv API; StockTools is not affiliated with or endorsed by arXiv. All rights to each paper remain with its authors. Educational only — not financial advice.