Qwen Councils

Quantitative Finance

arXiv preprints from January 1, 2026 through September 18, 2026 — 18:36:36 EST

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Posted in q-fin.MF · 2026-09-16 · Jun Maeda

Optimal entry and exit for variance swaps: closed-form rules for the perpetual contract

Variance swaps are a convenient instrument for trading vega and convexity, and a listed contract now trades on Cboe. We ask when a trader should put such a position on and when she should take it off, and for a perpetual, continuously settled contract we answer both in closed form: each threshold is the unique root of a smooth-pasting...

💬 0 commentsarXiv:2609.19102v1PDF
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Posted in q-fin.MF · 2026-09-16 · Jaehyun Kim, Hyungbin Park

Quadratic G-BSDEs for bond pricing with endogenous short-rate feedback

We study robust bond valuation with endogenous short-rate feedback under volatility uncertainty. Within the $G$-expectation framework, the dependence of the short rate on the bond price yields a nonlinear fixed-point problem, represented by a quadratic $G$-BSDE for the logarithmic price. Under suitable assumptions, we establish...

💬 0 commentsarXiv:2609.19094v1PDF
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Posted in q-fin.TR · 2026-09-16 · Vincent Maciejewski

Model-Free Passive Execution via Order-Level Shadowing

Automated execution algorithms are organized into schedule-based and liquidity-seeking families. This paper concerns the first, whose members -- Time-Weighted Average Price (TWAP), Volume-Weighted Average Price (VWAP), Percentage of Volume (POV) and Implementation Shortfall -- are all model-based: each derives its decisions from an...

💬 0 commentsarXiv:2609.18019v1PDF
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Posted in q-fin.MF · 2026-09-15 · Florian Bourgey, Jim Gatheral

Demystifying the Bergomi-Guyon expansion

Alòs, Gatheral and Radoičić derived the Bergomi-Guyon expansion of the implied variance smile from the forest expansion of the cumulant generating function. Its coefficients are sums of products of diamond trees, with prefactors that are polynomials in the log-strike $k$. Matching moments order by order produces, at order $ε^\ell$,...

💬 0 commentsarXiv:2609.17869v1PDF
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Posted in q-fin.TR · 2026-09-15 · Georgios Chionas, Charalampos Kleitsikas, Stefanos Leonardos, Leandro Sánchez-Betancourt, Carmine Ventre

SAiFE-gym: Model-based Environments for Automated Market Making with Concentrated Liquidity

We present SAiFE_gym, a Python module that provides a collection of simulation environments for studying trading problems in Constant Product Markets (CPMs) with Concentrated Liquidity (CL). These markets give Liquidity Providers (LPs) granular control over how their capital is allocated and enable them to adjust their range of...

💬 0 commentsarXiv:2609.17788v1PDF
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Posted in q-fin.PM · 2026-09-14 · Marc da Costa Nunes

Separated Signal Libraries: Packing, Saturation, and Joint Spectral Limits

We study libraries of cross-sectional signals: at each date, a forecast vector over $d$ assets intended to predict the next period's cross-sectional return. Demeaned and unit-normalized, a signal is a point on a sphere and its $T$-date history a point on a product of $T$ spheres. A pairwise correlation cap on histories is a minimum...

💬 0 commentsarXiv:2609.17609v1PDF
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Posted in q-fin.TR · 2026-09-15 · Maksym Nechepurenko

From Public Evidence to Contractual Outcome: First and Stable Decidability on Kalshi

Public evidence can become sufficient to settle a prediction-market contract before the venue records its first determination, but the relevant boundary depends on the applicable rule version, exact release object, source hierarchy, correction history, and unfinished contract conditions. This paper defines two Kalshi clocks: first...

💬 0 commentsarXiv:2609.16642v1PDF
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Posted in q-fin.PM · 2026-09-12 · David Reinhardt

Special Markowitz: Thermodynamic Formalism for the Joint Regularisation of Returns and Covariance

Special Markowitz (SM) regularises returns and covariance jointly, relative to a reference state (mu_ref, Sigma_ref). Each eigendirection of the whitened relative operator carries a spectral reliability potential Phi_k, derived from its estimation quality. Its exponential reliability weight exp(-Phi_k) governs both the fraction of the...

💬 0 commentsarXiv:2609.14029v2PDF
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Posted in q-fin.CP · 2026-09-11 · Yinbin Han, Jack Yuxiang Zhang, Manuel Torres, Fernando Acero, Renyuan Xu

Diffusion models for dynamic volatility surface generation and data-driven hedging

We develop a diffusion-model framework for dynamic implied-volatility surface generation and evaluate its economic usefulness through data-driven hedging. The framework consists of two models. AD-Seq-Vol jointly learns the conditional evolution of the underlying asset return and the high-dimensional implied-volatility surface,...

💬 0 commentsarXiv:2609.13402v2PDF
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Posted in q-fin.RM · 2026-09-14 · Said Khalil, Fatima Zahrae Chaayra

Quantifying the 2027 Solvency II Risk Margin Reform

The 2027 Solvency II reform recalibrates the Risk Margin by reducing the prescribed cost-of-capital rate from 6% to 4.75% and introducing a time-dependent attenuation of future Solvency Capital Requirements. This paper develops an analytical and numerical framework for characterizing the effect of the final regulatory calibration. By...

💬 0 commentsarXiv:2609.15741v1PDF
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Posted in q-fin.TR · 2026-09-14 · Maksym Nechepurenko

Resolution Is Not Settlement, Part II: Protocol Finality and Observed Redemption on Polymarket

An Oracle result is not yet a protocol payout, a redeemable position is not yet collateral in a holder's account, and a redemption event is not a complete measure of economic entitlement. This companion paper develops an event-sourced framework for Polymarket conditions from preparation through protocol finality and observed holder...

💬 0 commentsarXiv:2609.15373v1PDF
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Posted in q-fin.TR · 2026-09-14 · Maksym Nechepurenko

Resolution Is Not Settlement, Part I: Oracle Adjudication and Semantic Governance on Polymarket

Prediction-market resolution is often reduced to a terminal outcome and one timestamp. That representation is inadequate for leveraged event claims because rule versioning, request creation, proposal, dispute, reset, Oracle finality, and adapter terminality are distinct states with different observation precision and balance-sheet...

💬 0 commentsarXiv:2609.15368v1PDF
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Posted in q-fin.MF · 2026-09-14 · Lorenzo Torricelli, Michele Bufalo

The skew Brownian motion should not be used as a risk-neutral returns process: a well-posed skew-normal alternative

Return models for risk-neutral financial valuation based on skew Brownian motions (SBMs) have been introduced about twenty years ago, and have recently enjoying growing popularity. Unfortunately, the story behind their development is one of mistakes and erroneous interpretations, beginning from the foundational misrepresentations that...

💬 0 commentsarXiv:2609.15306v1PDF
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Posted in q-fin.TR · 2026-09-14 · Nicholas Hall

Gate Design and Stage-Dependent Incentives in Retail Proprietary-Trading Evaluations: Why Passing Is Not Standalone Evidence of Skill, and Why the Product Fails to Pay Under Measured Trading Constraints

Retail proprietary-trading firms sell a two-stage product: a paid evaluation that must reach a profit target before breaching a trailing drawdown, then a funded account that must survive a minimum window and a consistency rule before a payout. We show the geometry of this contract creates incentives that differ by stage and make...

💬 0 commentsarXiv:2609.14859v1PDF
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Posted in q-fin.RM · 2026-09-13 · Christopher Blier-Wong

Towards foundation models for insurance risk modelling

Claim narratives, images and sensor data contain information about insured risks that is difficult to use through existing actuarial models. Foundation models learn patterns from large datasets before being adapted to particular tasks. By turning these high-dimensional sources into variables or numerical representations, they could...

💬 0 commentsarXiv:2609.14576v1PDF
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Posted in q-fin.PM · 2026-09-12 · David Reinhardt

Special Markowitz: Thermodynamic Formalism for the Joint Regularisation of Returns and Covariance

Special Markowitz (SM) regularises returns and covariance jointly, relative to a reference state (mu_ref, Sigma_ref). Each eigendirection of the whitened relative operator carries a spectral reliability potential Phi_k, derived from its estimation quality. Its Gibbs weight exp(-Phi_k) governs both the fraction of the return signal and...

💬 0 commentsarXiv:2609.14029v1PDF
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Posted in q-fin.PR · 2026-09-12 · Masaaki Fukasawa

Yet another asymptotic formula for implied volatility

We derive a first-order representation of Black-Scholes implied variance in a continuous local martingale model. Total implied variance is the conditional expectation of the quadratic variation of the log price given its terminal value, up to a smaller-order term, for bounded standardized log-strikes. The framework incorporates small...

💬 0 commentsarXiv:2609.13961v1PDF
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Posted in q-fin.TR · 2026-09-12 · Christopher Angstmann, Tim Gebbie

Event-Time Order-Flow Memory, Operational-Time Impact, and Subordinated Market Observables

We consider two canonical market-microstructure regularities: the long-memory of trade signs and the square-root law of meta-order impact. The point is not to propose new empirical laws, but to separate the clocks on which existing laws are defined. The sign-memory law is an event-time statement about the ordering and fragmentation of...

💬 0 commentsarXiv:2609.13715v1PDF
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Posted in q-fin.CP · 2026-09-11 · Riya Danait, Yuliana Zamora, Ioana Boier

Same Book, Different Fills: Partial Identification of FIFO Execution from Aggregate Order Books

Price-level limit order book (L2) data reveal aggregate liquidity but not the ordered queue required by price--time priority. Passive-execution backtests can therefore depend on an unobserved cancellation-allocation rule even when observed prices, quantities, and trades are held fixed. We frame recovery of market-by-order histories...

💬 0 commentsarXiv:2609.13597v1PDF
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Posted in q-fin.CP · 2026-09-11 · Yinbin Han, Jack Yuxiang Zhang, Manuel Torres, Fernando Acero, Renyuan Xu

Diffusion models for dynamic volatility surface generation and data-driven hedging

We develop a diffusion-model framework for dynamic implied-volatility surface generation and evaluate its economic usefulness through data-driven hedging. The framework consists of two models. AD-Seq-Vol jointly learns the conditional evolution of the underlying asset return and the high-dimensional implied-volatility surface,...

💬 0 commentsarXiv:2609.13402v1PDF
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Posted in q-fin.MF · 2026-09-11 · Frédéric Vrins, Damiano Brigo

Exact calibration of structural models via time-change

In this note, we propose a general structural approach to model a default time $τ$ as the first-passage time (FPT) of a (``firm-value'') process $S$ below a (``debt'') barrier $K$ that comply with a pre-specified survival probability curve $G(t)=\Pr(τ>t)$. Following an idea of Mbaye and Vrins (Mathematical Finance, 2022) applied to...

💬 0 commentsarXiv:2609.12666v1PDF
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Posted in q-fin.MF · 2026-09-11 · Johannes Brutsche, Julian Sester, Thorsten Schmidt

Arbitrage in Estimate Nothing: an example

We give a two-period counterexample to the absence of arbitrage for the posterior-weighted pricing rule in Estimate nothing by Duembgen and Rogers. Both physical models have strictly positive transition densities, and each model is equipped with an equivalent martingale measure. Nevertheless, the mixed price of a single derivative...

💬 0 commentsarXiv:2609.12515v1PDF
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Posted in q-fin.PM · 2026-09-11 · Marc da Costa Nunes

Large Signal Libraries: Equal-Weight Limits and the Divergent Spectra of Signals and PnL

An ensemble of roughly 3,000 signals over 20 assets was reported to have approximately 90% correlation with the leading component of the asset-space return structure. Does having about 158 signals per available linear dimension explain that alignment? The population answer depends on the research process's design distribution and its...

💬 0 commentsarXiv:2609.12477v1PDF
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Posted in q-fin.PM · 2026-09-10 · Ralph Kosch, Robin Forsberg

Seasonal Trading in Commodity Futures: Evidence from Regression and Singular Spectrum Signals

Commodity futures are shaped by harvest cycles, weather shocks, storage conditions, and seasonal demand, but it remains unclear whether recurring patterns yield robust out-of-sample trading profits. Existing research documents return seasonality in commodity futures as well as more complex seasonal structure, while leaving less...

💬 0 commentsarXiv:2609.12227v1PDF