The paper analyzes futures trading under mean-reverting spot prices, incorporating timing and chooser options.
problem Trading futures with transaction costs under mean-reverting spot prices.
method Modeling spot dynamics with OU, CIR, or XOU models; deriving futures term structure; solving optimal double stopping problems.
result The option to choose between long or short positions delays market entry compared to pre-committing.
New method discovers context effects in choice data.
problem Identifying context effects from choice data is challenging.
method Automatic discovery of context effects from observed choices.
result Automatic discovery of context effects from observed choices.
Study optimal trading strategies for mean-reverting spreads using integral equations.
problem Optimal timing for trading mean-reverting price spreads.
method Utilized local time-space calculus and nonlinear integral equations of Volterra-type.
result Derived optimal boundaries for trading strategies.
Study optimal trading times for mean-reverting prices with deadlines.
problem Optimal timing strategies for mean-reverting price processes with deadlines.
method Solve optimal double stopping problems with sequential deadlines using local time-space calculus.
result Derive optimal trading boundaries for long-short, short-long, and chooser strategies.
Optimal model diagnoses funduscopic images for ocular diseases.
problem Binary classification of funduscopic images for ocular diseases.
method Transfer learning using Xception base architecture, Adam optimizer, mean squared error loss function, and custom heuristic equation.
result 90% accuracy, 94% sensitivity, and 86% specificity achieved.
This paper provides fast estimates for complex option types.
problem Estimating prices for constrained multiple exercise American options.
method Lookahead search for lower estimates and nearest-neighbor martingale for upper estimates.
result Probabilistic convergence guarantees for the algorithms.
Study bounds for prices of European and American options with optional termination.
problem Bounding prices of options with potential termination.
method Duality results linking upper prices of vulnerable options to American options with constrained exercise times.
result Linking upper prices of vulnerable options to American options and game options.
New option pricing formulas for American and Bermudan options.
problem Traditional option pricing models assume constant volatility and interest rate.
method Relaxing assumptions, using square root of Brownian motion, providing closed-form formulas.
result Simple, closed-form pricing formulas for American and Bermudan options.
Path integral method calculates barrier option prices.
problem Barrier option pricing in finance.
method Path integral method applied to trapezoid and square potential barriers.
result Analytical expressions for option pricing derived.
New framework identifies hidden risks and optionality in American options.
problem Underestimation of flexibility and convexity in early-exercise features.
method Introducing stochasticity into underlying determinants to quantify hidden risks and optionality.
result Remedies conventional pricing systems that underestimate optionality.
American options can be equivalent to European options under certain conditions.
problem Determining when American options can be simplified to European options.
method Using methods from Jourdain and Martini, Chrsitensen, and convex duality.
result A first step towards verifying representability of American options.
There exist several methods how more general options can be priced with call prices. In this article, we extend these results to cover a wider class of options and market models. In particular, we introduce a new pricing formula which can be used to price more general options if prices for call options and digital opti…
Path integral method calculates PDBS option prices with time-dependent parameters.
problem Pricing proportional double-barrier step options with time-dependent interest rates and volatilities.
method Path integral method applied to a quantum mechanical analogy of barrier options.
result Derivation of pricing kernel for PDBS options with time-dependent parameters.
The paper offers methods to price complex options using upper and lower bounds.
problem Pricing complex options like Asian and basket options.
method Develops a general framework using lower and upper bounds.
result Lower bounds simplify the problem and provide reasonable approximations.
Financial option insurance protects investors from option premiums losses.
problem Risk associated with financial option investments.
method Integrating insurance concepts with financial options, creating a three-entity framework and a mathematical model.
result Protection of option investors and minimization of insurer's risk.
Polynomial expansions improve option pricing accuracy.
problem Efficiently pricing and Greeks in stochastic volatility models.
method Analytic series representations for European and exotic options.
result Polynomial expansions match Fourier transform accuracy.
New method for pricing SOFR futures options, solving both American and Asian exercise styles.
problem Lack of pricing models for SOFR futures options post-LIBOR transition.
method Developed a new version of the GIT method to solve semi-analytically.
result Obtained option prices, exercise boundaries, and Greeks for American and Asian options.
Hamiltonian method applied to floating barrier options pricing.
problem Pricing of floating barrier options.
method Hamiltonian approach in quantum mechanics applied to barrier options.
result Analytical expressions for pricing kernel and option price derived.
Neural network learns to solve Black-Scholes for stock options.
problem Stock option pricing using the Black-Scholes Equation.
method Neural Networks applied to solve the Black-Scholes Equation.
result Neural network can accurately forecast stock option prices.
ANNs solve financial option valuation problems without numerical methods.
problem Valuation of European and American financial options.
method Unsupervised learning with artificial neural networks (ANNs) for solving PDEs.
result ANNs accurately compute option values for various stock scenarios.
Optimal hedging strategies for exotic options using vanilla options.
problem Hedging exotic options with illiquid vanilla options.
method Simple approximations and variational techniques in a market model and stochastic volatility model framework.
result Optimal Delta and Vega hedging strategies can be computed easily.
Paper proposes a Hellinger distance regularizer to disentangle options in reinforcement learning.
problem Temporal abstraction in reinforcement learning, specifically the mutual exclusivity of learned options.
method Introduces a Hellinger distance regularizer to disentangle options.
result Demonstrates the effectiveness of the Hellinger distance regularizer in disentangling options.
Fast probabilistic option price predictions using modular Bayesian inference.
problem Accurate probabilistic predictions of future option prices.
method Modular approximate Bayesian inference framework that combines multiple data sources.
result Accurate probabilistic option-price predictions in realistic scenarios.
New formulas for pricing Asian and basket options using stochastic expansion.
problem Pricing Asian and basket options under time-dependent parameters.
method Stochastic Taylor expansion around a log-normal proxy model.
result Highly accurate approximations for Asian options and vanilla options with discrete dividends.
Study optimizes reinforcement learning options under time constraints.
problem Learning useful options for diverse tasks with limited time.
method Directly searched for optimal option sets considering time budget.
result Discovered options outperform existing heuristics.
PODNet discovers plannable options from unstructured demonstrations.
problem Learning from unstructured, multi-objective demonstrations.
method Custom categorical variational autoencoder, recurrent option inference network, option-conditioned policy network, and option dynamics model.
result PODNet enables learning from demonstration for multiple tasks and planning.
Efficient method for pricing European and American options using Markov switching stochastic volatility model.
problem Modeling and pricing options under varying volatility and mean-reversion speeds.
method Discrete-time Markov switching stochastic volatility with co-jump model, computationally efficient approach for European options, and conversion to European option pricing for American options.
result Efficient and accurate methods for pricing options, including variance swap analysis.
New FX option interpolations impact implied volatilities.
problem Different interpolations of FX option quotes lead to varying implied volatilities.
method Analysis of various exact interpolations of broker quotes.
result Different interpolations result in different implied volatilities.
Derives pricing formulae for power binary and normal distribution standard options.
problem Developing pricing models for binary and standard options.
method Incorporates Buchen's formulae into power binary options and derives a formula for normal distribution standard options.
result Derives pricing formulae for power binary and normal distribution standard options.
Paper proposes method for generating paths of stochastic volatility CGMY process for option pricing.
problem Generating accurate sample paths for stochastic volatility models for option pricing.
method Monte-Carlo method for European and American options, least square regression for calibration.
result Calibrated model parameters to S\&P 100 index options market using path-dependent options.
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.
Panoptic trades options without oracles on Ethereum.
problem Trading options without relying on oracles.
method Perpetual, trustless, instant-settlement protocol on Ethereum.
result Trustless, permissionless trading of options on Uniswap v3.
Quantum method prices options by evolving a state in imaginary time.
problem Pricing options in a quantum setting.
method Prepares an initial state, evolves it using imaginary time algorithms, and maps to quantum state.
result Numerical verification for European options; extension to path-dependent options.
The paper proposes a principled method to discover useful sets of options in Markov Decision Processes.
problem Finding useful sets of options in Markov Decision Processes.
method Mathematical characterization using information theory to find optimal sets of options and an algorithm to output them.
result An algorithm that outputs a useful set of options and its illustration in simulations.
The paper calculates prices for special options using mixed-exponential jumps.
problem Pricing special options in a mixed-exponential jump-diffusion model.
method Derive joint distributions of a mixed-exponential jump-diffusion process and its occupation times.
result Various joint distributions derived for pricing options.
This work extends the options framework to learn at multiple temporal resolutions.
problem Autonomous creation of temporal abstractions from data in reinforcement learning.
method Developed a hierarchical option-critic architecture capable of learning at multiple temporal resolutions.
result Derived policy gradient theorems for a deep hierarchy of options.
In this paper we extend Buchen's method to develop a new technique for pricing of some exotic options with several expiry dates(more than 3 expiry dates) using a concept of higher order binary option. At first we introduce the concept of higher order binary option and then provide the pricing formulae of n-th order b…
Study on pricing American Exchange options using Lévy processes.
problem Pricing American Exchange options driven by Lévy processes.
method Represented American Exchange options as European options plus early exercise premium; studied properties of free boundary and provided an approximative formula.
result Developed an approximative formula for American Exchange options.
The paper prices options using a novel finite element method.
problem Pricing European and American options under the Heston model.
method Discontinuous Galerkin finite element method (dGFEM) with interior penalty and Rannacher smoothing.
result Efficient and accurate pricing of options, demonstrated through comparisons and experiments.
Tensor trains speed up option pricing for multi-asset options.
problem Speeding up option pricing for multi-asset options.
method Tensor train learning algorithms to compress functions with parameter dependence.
result The proposed method outperforms Monte Carlo-based pricing in computational complexity.
Paper presents a multinomial method for option pricing under Variance Gamma.
problem Option pricing under non-standard stochastic processes.
method Discrete time Markov chain approximation of continuous time Variance Gamma process.
result Pricing American and Bermudan options is feasible with this method.
The study finds no evidence of stochastic arbitrage opportunities in S&P 500 index options.
problem Identifying arbitrage opportunities in S&P 500 index options.
method Developed linear and mixed-integer linear programs to compute the maximum option premium.
result No evidence of systematic stochastic arbitrage opportunities in S&P 500 index options.
Study prices compound and extendible options using mixed fractional Brownian motion with jumps.
problem Pricing compound and extendible options under mixed fractional Brownian motion with jumps.
method Analytic formula derived under risk-neutral measure, applied to extendible options, discussed special cases, provided numerical results.
result An analytic formula for pricing compound options derived.
The study compares on-chain option prices with a model and finds significant differences.
problem Measuring and comparing on-chain option prices with a model-based benchmark.
method Used a two-regime MS-AR-(GJR)-GARCH model to estimate volatility and GLS to compare prices.
result On-chain option prices are significantly higher than model-based benchmarks, especially for call options.
New method improves barrier option pricing for high volatility assets.
problem Efficient pricing of barrier options on high volatility assets.
method Subset Simulation for barrier option pricing.
result The method outperforms standard Monte Carlo and multilevel Monte Carlo approaches.
Paper cleans option price datasets by removing outliers.
problem Unusual option prices in datasets.
method Statistical techniques to identify and remove outliers.
result Removes option prices violating no arbitrage assumption.
Using spectral decomposition techniques and singular perturbation theory, we develop a systematic method to approximate the prices of a variety of options in a fast mean-reverting stochastic volatility setting. Four examples are provided in order to demonstrate the versatility of our method. These include: European opt…
Paper approximates first passage time for tempered stable process for option pricing.
problem Pricing perpetual American options and barrier options using first passage time.
method Approximates characteristic function using martingale approach.
result Provides explicit or indirect numerical method for characteristic function of first passage time.