Research
On-device research index

arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,695 papers · 148 categories

Trend · papers per month

121241362482 · Jun 202019922001200920172026
48 results for option implied information

The paper extends option pricing theory for markets with informed traders.

problem Discontinuity in option pricing for markets with informed traders.
method New models for option pricing in complete markets considering informed traders' information on stock price direction and return mean.
result The discontinuity puzzle in option pricing is resolved using continuous diffusion price processes.

This paper provides a neural approach to represent option implied information.

problem Link between implied density and volatility for arbitrage-free modeling.
method Minimalist perspective on implied volatility, neural representation with arbitrage constraints.
result Shallow feedforward network with a single hidden layer effectively approximates implied density and volatility.

Enhanced hedging for S&P 500 options using volatility surface data.

problem Optimizing hedging strategies for S&P 500 options with transaction costs.
method Deep policy gradient reinforcement learning with volatility surface feedback.
result Outperforms conventional hedging methods in simulations and backtesting.

Proposes deep hedging for index options using implied volatility surface.

problem Managing risk in index option portfolios with complex dynamics.
method Integrates surface-informed decisions with multiple hedging instruments, accounting for transaction costs and variance risk premium.
result Consistently outperforms traditional hedging strategies across various market conditions.

Study finds adding more information to robust option pricing does not improve bounds.

problem Exploring robust pricing of financial claims using minimal assumptions.
method Empirical study of variance options, incorporating intermediate market data.
result Incorporating more information does not improve robust pricing bounds.

Study uses SABR model to create implied volatilities from sparse quotes.

problem Creating accurate implied volatility surfaces from limited market data.
method Multitask Gaussian process with SABR model embeddings and hierarchical regularization.
result Model produces more accurate volatilities than single-task methods.

Study finds option volume imbalance predicts equity market returns.

problem Predicting equity market returns using option volume imbalance.
method Nonlinear analysis of option volumes decomposed into five market participant classes.
result Strong signals of predictability of excess market returns from Market-Maker volumes.

iCOS method estimates risk-neutral densities and option prices without model assumptions.

problem Estimating risk-neutral densities and option prices without model assumptions.
method Leverages Fourier-cosine technique using option-implied cosine series coefficients, without model assumptions.
result Effective in extracting information from option prices under various market conditions.

Study uses sentiment analysis to predict implied volatility surface, improving prediction accuracy.

problem Improving prediction accuracy of implied volatility surface.
method Constructed daily high-frequency sentiment data, used VAR method, deep learning (BERT, LSTM), FFT, EMD for sentiment decomposition.
result High-frequency sentiment correlates with ATM options' implied volatility, low-frequency with DOTM options.

This study examines how earnings announcements affect option volatility and pricing.

problem The impact of earnings announcements on option volatility and pricing.
method Analysis of extremely short-term options data to study bimodality and concavity in IV curves.
result Investors pay a premium to hedge against extreme volatility during earnings announcements in the presence of concave IV smiles.

Improved price bounds for multi-asset derivatives using market option data.

problem Creating robust price bounds for multi-asset derivatives under market-implied dependence.
method Extracting inter-asset dependence information from market option prices and applying modified martingale optimal transport.
result Improved price bounds for multi-asset derivatives, demonstrating relevance and tractability.

Extracting the risk neutral density (RND) function from option prices is well defined in principle, but is very sensitive to errors in practice. For risk management, knowledge of the entire RND provides more information for Value-at-Risk (VaR) calculations than implied volatility alone [1]. Typically, RNDs are deduced …

2006-07-26abs ↗pdf ↗

FINN learns option pricing and hedging using financial theory.

problem Learning accurate option prices and sensitivities from financial theory.
method Self-supervised replication objective based on dynamic hedging.
result FINN accurately recovers classical Black--Scholes prices and performs robustly in stochastic volatility environments.

The paper develops Hawkes-based models for LOB and applies them to European, spread, and basket option pricing.

problem Developing accurate models for pricing options in the context of limit order books (LOB).
method Introduces multivariate Hawkes processes and their limit theorems, applies to European, spread, and basket options.
result Hawkes-based models provide more market forecast information than classical models.

A hybrid framework prices options using neural networks and VAE latent space.

problem Lack of explicit asset dynamics information in compressed volatility surfaces.
method Combining Weighted Monte Carlo with neural networks trained on VAE latent space.
result Effective pricing of vanilla and exotic options on idealized vol surface.

Study on implied volatility of Inverse options under stochastic volatility models.

problem Short-time behavior and skew of implied volatility for Inverse European options.
method Malliavin calculus, anticipating Itô's formula, asymptotic analysis.
result Asymptotic formula for skew of implied volatility, extending to Quanto-Inverse options.

We derive the implied volatility estimation formula in European power call options pricing, where the payoff functions are in the form of V=(STαK)+V=(S^α_T-K)^{+} and V=(STαKα)+V=(S^α_T-K^α)^{+} (α>0α>0)respectively. Using quadratic Taylor approximations, We develop the computing formula of implied volatility in European power call op…

2012-03-03abs ↗pdf ↗

Option written on several foreign exchange rates (FXRs) depends on correlation between the rates. To evaluate the option, historical estimates for correlations can be used but usually they are not stable. More significantly, pricing of the option using these estimates is usually inconsistent to the traded vanilla contr…

2009-04-30abs ↗pdf ↗

Improved bounds for multi-asset options using deep learning and market prices.

problem Computing model-free bounds for multi-asset options with uncertainty in dependence structure.
method Fundamental theorem of asset pricing, superhedging duality, penalization approach, deep learning.
result Deep learning approximations improve computational efficiency and accuracy.

Study examines short-term IVS dynamics using a model-independent approach.

problem Understanding the short-term behavior of implied volatility surface (IVS).
method Model-independent, distribution-based approach imposing cumulant conditions on asset log return distribution.
result Derives a quadratic expansion for implied volatility and asymptotic expressions for ATM skew and curvature.

New framework improves option pricing models by addressing volatility dynamics.

problem Challenges in standard option pricing models, especially in deriving implied volatility.
method Developed a new framework called Implied Remaining Variance (IRV), identifying minimal conditions for absence of arbitrage.
result Reformulated results of Schweizer and Wissel (2008b) and independently derived El Amrani, Jacquier and Martini (2021) results within IRV framework.

Enhanced options trading strategies using advanced portfolio optimization.

problem Generating consistent positive returns in high-frequency options trading.
method Advanced portfolio optimization techniques applied to SPY options data.
result Sophisticated strategies incorporating advanced Greeks show potential in high-frequency trading.

Study on implied volatility of Asian options with stochastic volatility.

problem Understanding the implied volatility of Asian options under stochastic volatility models.
method Using Malliavin calculus and anticipating Ito's formula, the paper computes and finds asymptotic formulas for the implied volatility and skew.
result Developed short-maturity asymptotic formulas for the skew of the implied volatility, which depends on the roughness of the volatility model.

The paper analyzes implied volatility for European and Asian options under stochastic volatility Bachelier model.

problem Analyzing implied volatility for European and Asian options under stochastic volatility.
method Using Malliavin calculus and anticipating Ito's formula, the paper computes and finds asymptotic formulas for implied volatility and skew.
result The paper provides a short maturity asymptotic formula for the skew of implied volatility that depends on the roughness of the volatility model.

The paper models Gasoil options using Brent benchmarks, improving volatility estimation.

problem Inability to directly model illiquid Gasoil options market.
method Jointly models Brent and Gasoil futures prices with a correlated Bachelier model, estimating volatility spread.
result The proposed framework accurately maps Brent implied volatilities to Gasoil implied volatilities.

This paper examines Bachelier implied volatility at extreme strikes.

problem Investigates appropriate implied volatility extrapolation at extreme strikes.
method Compares Bachelier and Black-Scholes models, focusing on normal distribution and vanilla options.
result Bachelier implied variance grows at most linearly in log-moneyness, similar to Black-Scholes.

The study models credit risk using Merton's framework and binomial trees.

problem Credit risk pricing and implied volatility estimation.
method Calibrated using Merton's structural model, with asset volatility derived from Black-Scholes-Merton. Implied mean return and probability surfaces constructed using a recombining binomial tree.
result Established a practical method for constructing implied credit surfaces.

QLBS and RLOP methods improve option pricing and hedging performance.

problem Improving option pricing and hedging performance under market frictions.
method Incorporates risk aversion and trading costs into QLBS, proposes RLOP approach.
result RLOP outperforms in dynamic hedging by reducing shortfall probability.

This study compares SPX and VIX options and quantifies their relationship.

problem Understanding the relationship between SPX and VIX options markets.
method Uses moment formulas in a model-free approach to compare implied volatilities.
result SPX options reflect the extreme-strike asymptotics of VIX options and vice versa.

In an incomplete market, including liquidly-traded European options in an investment portfolio could potentially improve the expected terminal utility for a risk-averse investor. However, unlike the Sharpe ratio, which provides a concise measure of the relative investment attractiveness of different underlying risky as…

2019-08-13abs ↗pdf ↗

In this paper, we address one of the main puzzles in finance observed in the stock market by proponents of behavioral finance: the stock predictability puzzle. We offer a statistical model within the context of rational finance which can be used without relying on behavioral finance assumptions to model the predictabil…

2019-11-06abs ↗pdf ↗

A new model for pricing ultra-short-term options with complex volatility patterns.

problem Complex pricing of ultra-short-term options due to oscillations in implied volatility.
method Edgeworth++ model with nonparametric stochastic volatility and deterministic shift extension.
result Fast and accurate closed-form option pricing for ultra-short-term options.

The paper develops bounds for multi-asset derivatives using option prices.

problem Computing model-free upper and lower bounds for multi-asset derivatives.
method Develops a fundamental theorem of asset pricing and superhedging duality, recasting the problem into a linear semi-infinite optimization problem and providing algorithms for exact computation.
result Provides ε\varepsilon-optimal upper and lower bounds for multi-asset derivatives, characterizing optimal pricing measures.