Cboe stated that market demand for downside hedges ahead of mega-cap earnings releases has lifted the VIX index. This view comes from a related report by Traders Union.
Read originalPluang released an analysis stating that Bitcoin volatility may increase ahead of the US midterm elections. Historical data shows that Bitcoin market reactions triggered by this event are mixed and difficult to predict.
Read originalThe VIX closed 9.6% lower as AI stocks rebounded.
Read originalThe paper proposes a branching signature model that generalizes the classical geometric rough path based on the branching rough path framework, proving its universal approximation theorem, which can approximate high-level signatures through iterative combinations of low-level signature mappings. The model can explicitly extend the original path to a high-dimensional space via the mapping Ψ, implementing it as the classical geometric signature of the extended path, and its effectiveness is verified in two applications: rough volatility calibration and optimal execution.
Read originalThe study proposes a conditional latent diffusion framework that jointly generates 30-step trajectories of the implied volatility surface and underlying returns. It learns surface representations through an arbitrage-aware autoencoder, with the diffusion process capturing the evolution dynamics. The framework is evaluated on the SPX surface dataset and can generate realistic probabilistic multi-step scenarios, with its forecast mean outperforming the persistence benchmark for horizons beyond the shortest maturity.
Read originalThis paper proposes an arbitrage-aware latent flow matching framework for unconditional generation of implied volatility surfaces. The framework first compresses high-dimensional surfaces into a low-dimensional latent space using a variational autoencoder with differentiable penalty regularization for calendar spreads, call spreads, and butterfly arbitrage. A flow matching model then learns to map a Gaussian prior to the empirical latent distribution, which is finally decoded back to a volatility surface. This method can generate 90.8% of surfaces that satisfy all tested static no-arbitrage conditions, performs best in the extreme Q99 range, and balances distributional similarity, tail preservation, and financial consistency without post-sampling reweighting.
Read originalThis study formulates and solves a stochastic control problem for Ethena protocol's core yield strategy, which generates returns through a delta-neutral combination of long stETH positions and short ETH perpetual contracts of equal size. The model takes the rate of simultaneously buying stETH and shorting perpetual contracts as the control variable, incorporating both permanent price impact and temporary execution slippage. The study solves both the infinite-horizon discounted problem and the finite-horizon problem with terminal liquidation costs, obtaining explicit optimal control solutions in both cases.
Read originalThis paper proposes AddMart, a few-shot implied volatility surface reconstruction framework that embeds no-arbitrage structure into the architecture to achieve global static no-arbitrage, enabling continuous and valid surface generation from a small number of option quotes. Experiments on 10 real-world option datasets show that the framework delivers competitive reconstruction accuracy with no significant static arbitrage violations, and can be directly applied to VaR, CVaR and crash probability estimation.
Read originalThis 9-page paper accepted by ICAIF '26 proposes a diagnostic protocol to examine the true source of incremental information from LLM embeddings of r/WallStreetBets posts for volatility prediction. The study covers panel data of 202,145 mentioned stock-days from 2015 to 2022, using a retrospective rolling out-of-sample test.
Read originalThis study extends the classical Black-Scholes market framework to infinite-dimensional scenarios, modeling asset prices with stochastic evolution equations in separable Hilbert spaces, deriving an infinite-dimensional Black-Scholes equation, and establishing exact replication results for strong solutions and asymptotic replication results for weak solutions. The study also introduces Hilbert lattice structures to characterize no-arbitrage conditions, provides sufficient conditions for the existence and uniqueness of equivalent risk-neutral measures, and explicit pricing formulas for some tractable cases; the model can be interpreted as a segmented market composed of a series of one-dimensional geometric Brownian motions.
Read originalPublished at ICAIF 2026, this study finds that accurate option prices do not necessarily mean accurate recovery of the underlying risk-neutral density. By comparing synthetic simulation benchmarks with out-of-sample NIFTY option benchmarks, the research reveals that the two-component lognormal mixture model demonstrates overall pricing performance on synthetic benchmarks.
Read originalThis paper focuses on the impact of hybrid dynamics (rough volatility and infinite variation Lévy processes) on the implied volatility skew and curvature of at-the-money options. By analyzing the leading terms of their short-time expansions, the origin mechanism of the power-law behavior of skew and curvature can be determined from the hybrid dynamics model. The paper confirms that hybrid models also produce power-law relationships, and the relevant conclusions are crucial for model design and calibration. Numerical evidence for the rough Heston model with CGMY Lévy jumps is also provided.
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