In this study we prove the existence of statistical arbitrage opportunities in the Black-Scholes framework by considering trading strategies that consists of borrowing from the risk free rate and taking a long position in the stock until it hits a deterministic barrier level. We derive analytical formulas for the expec…
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48 results for “Black-Scholes framework”
Enhanced Black-Scholes model for option pricing with stochastic volatility and interest rate variability.
problem Improving option pricing accuracy in volatile financial markets.
method Extended Black-Scholes model using finite difference method and LSTM machine learning.
result Finite difference method outperforms LSTM in computational efficiency but not in accuracy.
Modeling stochastic arbitrage bubbles in Black-Scholes framework.
problem Analyzing arbitrage bubbles in financial markets.
method Developed a generalized Black-Scholes equation with stochastic arbitrage bubbles.
result The Black-Scholes model is a low-energy limit of a stochastic model.
This research improves option pricing models using Heston, GARCH, and jump diffusion models.
problem Inaccurate option pricing due to Black-Scholes assumptions.
method Monte Carlo simulation, GARCH model, Heston model, Merton jump-diffusion model.
result Heston model produces estimates closer to market prices, Merton model performs well for volatile assets, GARCH model improves volatility forecasts.
Quantum mechanics models for financial Black-Scholes model.
problem Modeling financial derivatives using quantum mechanics.
method Noncommutative quantum mechanics applied to specific mechanical systems.
result Generalized noncommutative quantum mechanics of financial models.
Unified model integrates Bachelier and Black-Scholes-Merton for asset pricing.
problem Study of asset pricing in a natural world with negative prices or riskless rates.
method Unified framework combining Bachelier and Black-Scholes-Merton models.
result Unified model shows different option pricing depending on riskless instruments used.
Develops a new option pricing model under G-expectation framework.
problem Modeling uncertainty in financial markets and robust valuation under model uncertainty.
method G-expectation framework, logarithmic transformation, finite difference schemes.
result Unified risk-neutral valuation approach yielding G-Black-Scholes equation.
This paper analyzes hedge errors in Black-Scholes models using finite difference techniques.
problem Accurate hedging strategies in dynamic market environments.
method Asymptotic approach and finite difference techniques.
result Reduction of hedge errors and enhancement of option pricing model robustness.
Enhancing the Black-Scholes Model for Option Valuation via Lévy Processes and Malliavin Calculusq-fin.MF
Enhancing the Black-Scholes model with Lévy processes and Malliavin calculus
problem Improving option valuation by incorporating stochastic volatility and jumps
method Deriving a pricing formula and exact implied volatility using multidimensional Itô calculus and Malliavin calculus
result Better capture of empirical features like volatility smiles
Travelling wave solutions of an equation of Harry Dym type arising in the Black-Scholes frameworkmath.NA
The study finds solutions to a financial equation related to volatility.
problem Finding solutions to a financial equation related to volatility.
method Using a zero-curvature condition and soliton theory, the study derives a variant of the Harry Dym equation and finds its travelling wave solutions.
result A family of travelling wave solutions to a variant of the Harry Dym equation is found.
The Accardi-Boukas quantum Black-Scholes framework, provides a means by which one can apply the Hudson-Parthasarathy quantum stochastic calculus to problems in finance. Solutions to these equations can be modelled using nonlocal diffusion processes, via a Kramers-Moyal expansion, and this provides useful tools to under…
We consider a non-stochastic online learning approach to price financial options by modeling the market dynamic as a repeated game between the nature (adversary) and the investor. We demonstrate that such framework yields analogous structure as the Black-Scholes model, the widely popular option pricing model in stochas…
We discuss in this note applications of the Multidimensional Positive Definite Advection Transport Algorithm (MPDATA) to numerical solutions of partial differential equations arising from stochastic models in quantitative finance. In particular, we develop a framework for solving Black-Scholes-type equations by first t…
Deep learning enhances options hedging performance.
problem Improving delta hedging for options using neural networks.
method Learning residuals between hedging function and implied Black-Scholes delta using neural networks.
result Deep learning significantly improves hedging performance, often by more than 100%.
The paper challenges the notion that asset return doesn't affect Black-Scholes-Merton model.
problem The role of asset return in the Black-Scholes-Merton model.
method Refutation of the claim through simplified stochastic calculus approach.
result The expected rate of return of the underlying asset does affect the Black-Scholes-Merton model.
ETCNN uses neural networks to price American options accurately.
problem Accurately pricing American options with inequality constraints.
method ETCNN framework solving BSM equations with exact terminal condition.
result ETCNN achieves high accuracy and robustness across various scenarios.
Derives Black-Scholes model without stochastic calculus or PDEs.
problem Deriving the Black-Scholes model without advanced math.
method Continuum limit of Binomial tree approach.
result Derives Black-Scholes model and exchange-option generalization.
The paper proposes a different method of solving a simplified version of the Black-Scholes equation. This paper will discuss the importance of the Black-Scholes equation and its applications in finance.
We analyze a generalized version of the Black-Scholes equation depending on a parameter . It satisfies the martingale condition and coincides with the Black-Scholes equation in the limit case . We show that the generalized equation is exactly solvable in terms of Hermite polynomials a…
The Pricing of Vanilla Options with Cash Dividends as a Classic Vanilla Basket Option Problemq-fin.PR
This paper uses basket option formulas to price vanilla options with discrete dividends.
problem Pricing vanilla options on stocks with discrete cash dividends.
method Uses existing basket option formulas for European options on a single asset with cash dividends in the piecewise lognormal model.
result Explains the use of basket option formulas for a specific problem in the piecewise lognormal model.
This paper extends static hedging for European options over multiple maturities.
problem Hedging European options over multiple time periods.
method Developed a spanning relation for multiple shorter-term options using a Markovian framework.
result Demonstrated a practical implementation using Gaussian Quadrature for finite sets of shorter-term options.
Generalizes Black-Scholes model for option pricing under uncertainty.
problem Traditional Black-Scholes model for option pricing under uncertainty.
method Generalized Black-Scholes model using non-symmetric Dirichlet forms and abstract PDE theory.
result Well-posedness of the generalized model established.
Gap Risk KVA and Repo Pricing: An Economic Capital Approach in the Black-Scholes-Merton Frameworkq-fin.PR
Although not a formal pricing consideration, gap risk or hedging errors are the norm of derivatives businesses. Starting with the gap risk during a margin period of risk of a repurchase agreement (repo), this article extends the Black-Scholes-Merton option pricing framework by introducing a reserve capital approach to …
Volatility clustering, long-range dependence, and non-Gaussian scaling are stylized facts of financial assets dynamics. They are ignored in the Black & Scholes framework, but have a relevant impact on the pricing of options written on financial assets. Using a recent model for market dynamics which adequately captures …
Modified perturbation method removes non-smoothness in solving Black-Scholes equations.
problem Non-smoothness in solving Black-Scholes equations.
method Variable transformations and homotopy perturbation method.
result Excellent agreement with exact solutions for Black-Scholes and multi-asset options.
Paper revisits Black-Scholes model, proving solution existence and measuring market uncertainty.
problem Proving existence of solution in inverse Black-Scholes model.
method Rigorous proof and empirical study using finite element method.
result New measure of market uncertainty developed.
Using Maple, we compute some analytical solutions of a modified Black-Scholes equation, recently proposed, in the case of the European put option. We show that the modified Black-Scholes equation with the European put option is exactly solvable in terms of associated Laguerre polynomials. We make some numerical experim…
We apply Gauge Theory of Arbitrage (GTA) {hep-th/9710148} to derivative pricing. We show how the standard results of Black-Scholes analysis appear from GTA and derive correction to the Black-Scholes equation due to a virtual arbitrage and speculators reaction on it. The model accounts for both violation of the no-arbit…
We show that the non Hermitian Black-Scholes Hamiltonian and its various generalizations are eta-pseudo Hermitian. The metric operator eta is explicitly constructed for this class of Hamitonians. It is also shown that the effective Black-Scholes Hamiltonian and its partner form a pseudo supersymmetric system.
Motivated by the work of Segal and Segal on the Black-Scholes pricing formula in the quantum context, we study a quantum extension of the Black-Scholes equation within the context of Hudson-Parthasarathy quantum stochastic calculus. Our model includes stock markets described by quantum Brownian motion and Poisson proce…
In the framework of path integral the evolution operator kernel for the Merton-Garman Hamiltonian is constructed. Based on this kernel option formula is obtained, which generalizes the well-known Black-Scholes result. Possible approximation numerical schemes for path integral calculations are proposed.
Random neural nets learn Black-Scholes PDEs without dimensionality issues.
problem Learning Black-Scholes type PDEs efficiently in high dimensions.
method Random feature neural networks applied to Kolmogorov PDEs.
result Random neural nets avoid the curse of dimensionality for Black-Scholes PDEs.
Study reviews Bachelier model for negative oil prices post-COVID.
problem Negative oil futures prices due to COVID-19.
method Literature review and model comparison.
result Connects Black-Scholes and Bachelier models for option pricing.
A Method of Reducing Dimension of Space Variables in Multi-dimensional Black-Scholes Equationsq-fin.CP
We study a method of reducing space dimension in multi-dimensional Black-Scholes partial differential equations as well as in multi-dimensional parabolic equations. We prove that a multiplicative transformation of space variables in the Black-Scholes partial differential equation reserves the form of Black-Scholes part…
Efficient numerical method for time-fractional Black-Scholes model.
problem Solving time-fractional Black-Scholes equations for European options.
method Crank-Nicolson discretization for time, exponential B-spline for space.
result The proposed method is unconditionally stable and superior to existing approaches.
Relativistic Black-Scholes modelq-fin.PR
Black-Scholes equation, after a certain coordinate transformation, is equivalent to the heat equation. On the other hand the relativistic extension of the latter, the telegraphers equation, can be derived from the Euclidean version of the Dirac equation. Therefore the relativistic extension of the Black-Scholes model f…
This paper analyzes the probability flow in the stock market using the Black-Scholes model.
problem The non-conservation of probability in the stock market.
method Expressed the Black-Scholes equation in Hamiltonian form and analyzed the flow of probability.
result Conditions under which probability might be conserved in the market, challenging the non-Hermitian nature of the Black-Scholes Hamiltonian.
A derivation of the Black-Scholes option pricing model using a central limit theorem argumentq-fin.GN
The Black-Scholes model (sometimes known as the Black-Scholes-Merton model) gives a theoretical estimate for the price of European options. The price evolution under this model is described by the Black-Scholes formula, one of the most well-known formulas in mathematical finance. For their discovery, Merton and Scholes…
Quantum Monte Carlo speeds up option pricing for complex payoff functions.
problem Efficiently pricing options with complex payoff functions using quantum computing.
method Developed a quantum Monte Carlo algorithm for multidimensional Black-Scholes PDEs.
result Proved polynomial computational complexity and speed-up over classical methods.
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.
Learning Agents in Black-Scholes Financial Markets: Consensus Dynamics and Volatility Smilesq-fin.MF
Black-Scholes (BS) is the standard mathematical model for option pricing in financial markets. Option prices are calculated using an analytical formula whose main inputs are strike (at which price to exercise) and volatility. The BS framework assumes that volatility remains constant across all strikes, however, in prac…
Options financial instruments designed to protect investors from the stock market randomness. In 1973, Fisher Black, Myron Scholes and Robert Merton proposed a very popular option pricing method using stochastic differential equations within the Ito interpretation. Herein, we derive the Black-Scholes equation for the o…
In this note, Black--Scholes implied volatility is expressed in terms of various optimisation problems. From these representations, upper and lower bounds are derived which hold uniformly across moneyness and call price. Various symmetries of the Black--Scholes formula are exploited to derive new bounds from old. These…
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 AI models improve financial hedging by reducing shortfall and tail risk.
problem Static model calibration gaps in derivatives markets.
method Two reinforcement learning frameworks: RLOP and QLBS.
result RLOP reduces shortfall frequency and improves tail risk in stress scenarios.
We determine the algebra of isovectors for the Black--Scholes equation. As a consequence, we obtain some previously unknown families of transformations on the solutions.
An investor faced with a contingent claim may eliminate risk by perfect hedging, but as it is often quite expensive, he seeks partial hedging (quantile hedging or efficient hedging) that requires less capital and reduces the risk. Efficient hedging for European call option was considered in the standard Black-Scholes m…
Paper solves bond option pricing with credit risk using Black-Scholes equations.
problem Pricing options on bonds with credit risk.
method Solution representations of Black-Scholes equations for specific problems.
result Pricing formulae for puttable and callable bonds with credit risk.