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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.

169,341 papers · 148 categories

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20405979 · May 202619922001200920182026
48 results for forward smile

We prove here a general closed-form expansion formula for forward-start options and the forward implied volatility smile in a large class of models, including the Heston stochastic volatility and time-changed exponential Lévy models. This expansion applies to both small and large maturities and is based solely on the p…

2012-12-04abs ↗pdf ↗

In this paper we investigate the asymptotics of forward-start options and the forward implied volatility smile in the Heston model as the maturity approaches zero. We prove that the forward smile for out-of-the-money options explodes and compute a closed-form high-order expansion detailing the rate of the explosion. Fu…

2013-03-18abs ↗pdf ↗

We provide a full characterisation of the large-maturity forward implied volatility smile in the Heston model. Although the leading decay is provided by a fairly classical large deviations behaviour, the algebraic expansion providing the higher-order terms highly depends on the parameters, and different powers of the m…

2014-10-27abs ↗pdf ↗

We simplify no-arbitrage bounds calculation for financial derivatives.

problem Calculating robust replication of forward-start straddles from market data.
method Proposed a discretisation scheme and a new linear programming approach to the dual problem.
result Reconciled two approaches: semi-infinite linear programming and optimal martingale measures.

We provide approximations for VIX futures and options in forward variance models.

problem Modeling VIX futures and options in forward variance models.
method Weak approximations and explicit formula derivation for VIX futures and options.
result Explicit combinations of Black-Scholes prices and greeks for option price approximations.

Model for commodity forward prices with stochastic volatility and decorrelation.

problem Capturing dynamics of commodity forward prices and volatility.
method Two-factor model with stochastic volatility and decorrelation, numerical and Monte Carlo methods.
result Efficient pricing of various derivative payoffs.

We provide a general and flexible approach to LIBOR modeling based on the class of affine factor processes. Our approach respects the basic economic requirement that LIBOR rates are non-negative, and the basic requirement from mathematical finance that LIBOR rates are analytically tractable martingales with respect to …

2009-04-03abs ↗pdf ↗

Proposes a new framework for invariant quadratic P&L predictions in option books.

problem Inconsistent second-order P&L predictions across different factor parameterizations.
method Local, model-agnostic framework using covariant Hessian defined by an affine connection.
result Coordinate-invariant quadratic P&L predictions that match desk targets.

Characterizes smiles in delta satisfying specific conditions.

problem Characterizing no butterfly arbitrage smiles in delta.
method Using parametrization of the smile in delta, we characterize the set of smiles.
result Obtained a parametrization of the set via one real number and three positive functions.

All SMILES VAE learns molecule latent representations from SMILES strings.

problem Non-unique SMILES strings and high computational cost of graph convolutions hinder VAEs for molecular property optimization.
method Stacked recurrent neural networks encode multiple SMILES strings, pooling hidden representations, and attentional pooling builds a final latent representation.
result All SMILES VAE significantly surpasses state-of-the-art in molecular property optimization tasks.

GEN generates millions of valid SMILES with high novelty and property conservation.

problem Generating high-quality, de novo molecules in a known chemical space.
method GEN uses bidirectional RNNs with concatenated sub-models to learn and generate SMILES, with online examination to ensure quality.
result GEN can generate SMILES with 95-98% validity, 85-90% novelty, and 95-99% property conservation.

We study a Markov-Functional (MF) interest-rate model with Uncertain Volatility Displaced Diffusion (UVDD) digital mapping, which is consistent with the volatility-smile phenomenon observed in the option market. We first check the impact of pricing Bermudan swaptions by the model. Next, we also investigate the future s…

2014-04-24abs ↗pdf ↗

Text classification on drug SMILES strings yields competitive drug type classification results.

problem Classifying drug types using conventional text classification methods.
method Treated drug SMILES as sentences and applied basic NLP methods for classification.
result Competitive drug type classification results achieved.

Study examines implied volatility smiles around jumps in high-frequency S&P500 index data.

problem Understanding implied volatility smiles around market jumps.
method High-frequency analysis of SPX S&P500 index option data using principal components.
result Volatility smiles exhibit abnormal properties around jumps, independent of maturity and option type.

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.

SMILES Transformer learns molecular fingerprints for drug discovery.

problem Poor performance of rule-based molecular fingerprints in shallow prediction models or small datasets.
method Unsupervised pre-training of a sequence-to-sequence language model on a corpus of SMILES.
result SMILES Transformer outperformed existing methods in small-data settings.

Calibrates historical and implied correlations in energy markets.

problem Challenges in aligning historical correlations of futures contracts with implied volatility smiles.
method Multiplicative multi-factor Heath-Jarrow-Morton model combined with stochastic volatility from lifted Heston model, using Kemna-Vorst approximation and Fourier-based techniques.
result Remarkable joint historical and implied calibration fits on the German power market.

We derive a new, exact and transparent expansion for option smiles, which lends itself both to analytical approximation and, perhaps more importantly, to congenial numerical treatments. We show that the skew and the curvature of the smile can be computed as exotic options, for which the Hedged Monte Carlo method is par…

2012-03-26abs ↗pdf ↗

In the Black-Scholes context we consider the probability distribution function (PDF) of financial returns implied by volatility smile and we study the relation between the decay of its tails and the fitting parameters of the smile. We show that, considering a scaling law derived from data, it is possible to get a new f…

2010-10-11abs ↗pdf ↗

Deep learning for smile detection on embedded systems.

problem Real-time smile detection in low-resource environments.
method Comparison of neural network architectures on NVidia Jetson platform with asynchronous multithreading.
result Low complexity architectures can achieve similar performance to larger networks with less computation.

DCNN improves volatility smile and skewness calibration without arbitrage constraints.

problem Calibrating volatility smile and skewness surfaces with no arbitrage constraints.
method Derivative-Constrained Neural Network (DCNN) incorporating derivatives in the loss function.
result DCNN generates a smooth surface that satisfies no-arbitrage conditions.

Improved Heston model produces steeper smile for short maturities.

problem Implied volatility surface does not produce a steep enough smile for short maturities.
method Introduced Stationary Heston model with invariant measure and used Product Recursive Quantization for numerical solution.
result Stationary Heston model produces a steeper smile for short maturities.

We develop a new method to price SOFR futures contracts considering convexity, skew, and smile.

problem Analyzing and pricing SOFR futures contracts with convexity, skew, and smile adjustments.
method A perturbative formalism based on a time-ordered exponential series to solve the backward-Kolmogorov diffusion PDE.
result An analytic pricing formula for SOFR futures contracts that incorporates convexity, skew, and smile adjustments.

The rBergomi model is improved with a regime switching change of measure to match market VIX smiles.

problem The rBergomi model produces flat VIX smiles, not matching market observations.
method A regime switching stochastic change of measure is applied to the rBergomi model, using an inhomogeneous fractional Ornstein-Uhlenbeck equation and an efficient Monte Carlo method.
result The model produces upward sloping VIX smiles, aligning with market observations.

Derives an option-pricing formula for fractional markets with skew and smile.

problem Developing a pricing formula for financial options with skew and smile.
method Employed the Lévy-Khintchine theorem and fractional Gaussian noise to generalize the Black-Scholes-Merton formula.
result An exponentially convergent option-pricing formula for fractional markets.

Smile-GANs clusters brain MRI scans to reveal disease subtypes and progression.

problem Understanding disease heterogeneity in brain MRI scans.
method Generative Adversarial Networks (GANs) for semi-supervised clustering.
result Discovered four subtypes of Alzheimer's and prodromal phases, with two progressive pathways.

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.

Study examines implied volatility behavior in Bachelier model.

problem Characterizing implied volatility in Bachelier model for large strikes.
method Exploiting regular variation theory, derived explicit expressions for Bachelier implied volatility.
result Established a rigorous connection between characteristic function analyticity and volatility smile asymptotic slope.

We review and illustrate how the volatility smile translates into a probability distribution, the market-implied probability distribution representing believes priced in. The effects of changes in the smile are examined. Special attention is given to the effects of slope, which might appear at first counter-intuitive. …

2009-11-04abs ↗pdf ↗

SMILES2Vec learns chemical properties from SMILES strings without feature engineering.

problem Predicting chemical properties from SMILES strings without manual feature engineering.
method Deep RNN (SMILES2Vec) learns features from SMILES strings, optimized using Bayesian optimization.
result Optimized SMILES2Vec outperforms MLP neural networks and achieves 88% accuracy in predicting solubility.