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Results for “rho” · papers 16 · wiki 1
Academic Papers · 16arXiv q-fin live 13 · desk corpus 5
arXiv · arXiv q-fin · 2019

The equivalent constant-elasticity-of-variance (CEV) volatility of the stochastic-alpha-beta-rho (SABR) model

This study presents new analytic approximations of the stochastic-alpha-beta-rho (SABR) model. Unlike existing studies that focus on the equivalent Black-Scholes (BS) volatility, we instead derive the equivalent constant-elasticity-of-variance (CEV) volatility. Our approach effectively reduces the approximation error in a way similar to the control variate method because the CEV model is the zero vol-of-vol limit of

Jaehyuk Choi, Lixin Wu
arXiv · arXiv · 2024

Efficient and accurate simulation of the stochastic-alpha-beta-rho model

We propose an efficient, accurate and reliable simulation scheme for the stochastic-alpha-beta-rho (SABR) model. The two challenges of the SABR simulation lie in sampling (i) integrated variance conditional on terminal volatility and (ii) terminal forward price conditional on terminal volatility and integrated variance. For the first sampling procedure, we sample the conditional integrated variance using the moment-m

Jaehyuk Choi, Lilian Hu, Yue Kuen Kwok
arXiv · arXiv q-fin · 2024

High-Frequency Options Trading | With Portfolio Optimization

This paper explores the effectiveness of high-frequency options trading strategies enhanced by advanced portfolio optimization techniques, investigating their ability to consistently generate positive returns compared to traditional long or short positions on options. Utilizing SPY options data recorded in five-minute intervals over a one-month period, we calculate key metrics such as Option Greeks and implied volati

Sid Bhatia
arXiv · arXiv q-fin · 2026

Implementation Risk in Portfolio Backtesting: A Previously Unquantified Source of Error

Portfolio backtesting is the primary tool for evaluating investment strategies before deployment, yet practitioners implicitly assume that different engines produce identical results for the same strategy. we formalise implementation risk, the systematic divergence in backtested portfolio metrics arising solely from differences in how engines implement the same logical strategy, and propose four metrics grounded in m

Dong Yin, Takeshi Miki, Vladislav Lesnichenko, Vasyl Gural
arXiv · arXiv q-fin · 2026

SABR Type Libor (Forward) Market Model (SABR/LMM) with time-dependent skew and smile

Volatility Skew and Smile of Interest Rate products (Swaption and Caplet) are represented by SABR (Stochastic Alpha Beta Rho model). So, the Interest Rate derivatives model for pricing the callable exotic swaps should be comparable to the SABR volatility surface. In the interest rate derivatives models, Libor Market Model (LMM) (in a post-Libor world, Forward Market Model (FMM)) is one of the most popular models used

Osamu Tsuchiya
arXiv · arXiv q-fin · 2026

A Geometry-Aware Residual Correction of Hagan's SABR Implied Volatility Formula

This paper proposes a hybrid methodology to improve the approximation of SABR (Stochastic Alpha Beta Rho) implied volatility by combining analytical structure with machine learning. The approach augments the neural-network input representation with geometric features derived from the stochastic differential equations of the SABR model. Unlike approaches that fully replace analytical formulas with black-box models, th

Adil Reghai, Lama Tarsissi, Gérard Biau, Alex Lipton
arXiv · arXiv q-fin · 2025

NMIXX: Domain-Adapted Neural Embeddings for Cross-Lingual eXploration of Finance

General-purpose sentence embedding models often struggle to capture specialized financial semantics, especially in low-resource languages like Korean, due to domain-specific jargon, temporal meaning shifts, and misaligned bilingual vocabularies. To address these gaps, we introduce NMIXX (Neural eMbeddings for Cross-lingual eXploration of Finance), a suite of cross-lingual embedding models fine-tuned with 18.8K high-c

Hanwool Lee, Sara Yu, Yewon Hwang, Jonghyun Choi, Heejae Ahn
arXiv · arXiv q-fin · 2025

Risk-Sensitive Option Market Making with Arbitrage-Free eSSVI Surfaces: A Constrained RL and Stochastic Control Bridge

We formulate option market making as a constrained, risk-sensitive control problem that unifies execution, hedging, and arbitrage-free implied-volatility surfaces inside a single learning loop. A fully differentiable eSSVI layer enforces static no-arbitrage conditions (butterfly and calendar) while the policy controls half-spreads, hedge intensity, and structured surface deformations (state-dependent rho-shift and ps

Jian'an Zhang
arXiv · arXiv q-fin · 2025

Sentiment Feedback in Equity Markets: Asymmetries, Retail Heterogeneity, and Structural Calibration

We study how sentiment shocks propagate through equity returns and investor clientele using four independent proxies with sign-aligned kappa-rho parameters. A structural calibration links a one standard deviation innovation in sentiment to a pricing impact of 1.06 basis points with persistence parameter rho = 0.940, yielding a half-life of 11.2 months. The impulse response peaks around the 12-month horizon, indicatin

Lucas Marques Sneller
arXiv · arXiv q-fin · 2023

Computation of Greeks under rough Volterra stochastic volatility models using the Malliavin calculus approach

Using Malliavin calculus techniques, we obtain formulas for computing Greeks under different rough Volterra stochastic volatility models. Due to the fact that underlying prices are not always square integrable, we extend the classical integration by parts formula to integrable but not necessarily square integrable functionals. First of all, we obtain formulas for general stochastic volatility (SV) models, concretely

Mishari Al-Foraih, Òscar Burés, Jan Pospíšil, Josep Vives
arXiv · arXiv q-fin · 2020

A note on the option price and 'Mass at zero in the uncorrelated SABR model and implied volatility asymptotics'

Gulisashvili et al. [Quant. Finance, 2018, 18(10), 1753-1765] provide a small-time asymptotics for the mass at zero under the uncorrelated stochastic-alpha-beta-rho (SABR) model by approximating the integrated variance with a moment-matched lognormal distribution. We improve the accuracy of the numerical integration by using the Gauss--Hermite quadrature. We further obtain the option price by integrating the constant

Jaehyuk Choi, Lixin Wu
arXiv · arXiv q-fin · 2018

Computation of option greeks under hybrid stochastic volatility models via Malliavin calculus

This study introduces computation of option sensitivities (Greeks) using the Malliavin calculus under the assumption that the underlying asset and interest rate both evolve from a stochastic volatility model and a stochastic interest rate model, respectively. Therefore, it integrates the recent developments in the Malliavin calculus for the computation of Greeks: Delta, Vega, and Rho and it extends the method slightl

Bilgi Yilmaz
arXiv · arXiv q-fin · 2018

Hyperbolic normal stochastic volatility model

For option pricing models and heavy-tailed distributions, this study proposes a continuous-time stochastic volatility model based on an arithmetic Brownian motion: a one-parameter extension of the normal stochastic alpha-beta-rho (SABR) model. Using two generalized Bougerol's identities in the literature, the study shows that our model has a closed-form Monte-Carlo simulation scheme and that the transition probabilit

Jaehyuk Choi, Chenru Liu, Byoung Ki Seo
arXiv · arXiv q-fin · 2012

Performance Analysis of Hybrid Forecasting Model In Stock Market Forecasting

This paper presents performance analysis of hybrid model comprise of concordance and Genetic Programming (GP) to forecast financial market with some existing models. This scheme can be used for in depth analysis of stock market. Different measures of concordances such as Kendalls Tau, Ginis Mean Difference, Spearmans Rho, and weak interpretation of concordance are used to search for the pattern in past that look simi

Mahesh S. Khadka, K. M. George, N. Park, J. B. Kim
arXiv · arXiv · 2026

The Loop-Gain Matrix: Coupled Rebalancing Feedback and the Blind Spots of Scalar Stability Monitoring

The stability of markets hosting leveraged exchange-traded products is governed not by any single product's loop gain but by the spectral radius of a loop-gain matrix, and scalar per-product monitoring underestimates system feedback by construction. Recent work measures the self-reinforcement of a leveraged fund's daily close rebalancing through a scalar loop gain and treats cross-asset spillovers as bias. We model c

Jihwan Woo
arXiv · arXiv · 2026

A Certified Higher Order Quantum Framework for CSA and Margin-Aware Collateral Optimization

Collateral allocation for uncleared derivatives is a legally constrained and operationally discrete optimization problem. Institutions must satisfy margin requirements while respecting CSA eligibility rules, valuation percentages, rounding, transfer thresholds, concentration limits, custody conditions, inventory, and VM, IM, or IA side constraints. This manuscript develops CR-HO-QAOA, a certified higher-order quantum

Tao Jin, Stuart Florescu
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