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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.

168,742 papers · 148 categories

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48 results for power 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 ↗

Paper introduces a model to capture power option volatility.

problem Capturing the volatility of power options with overlapping futures.
method Additive two-factor model based on Normal Inverse Gaussian Lévy processes, calibrated to no-arbitrage constraints.
result Model accurately reproduces different IV profiles of power options.

Develops European power option pricing under correlated interest rate and asset processes.

problem Pricing European power options under correlated interest rate and asset processes.
method Martingale method and Girsannov transform.
result Derives European power option pricing formulae under two market assumptions.

Reliability Options are capacity remuneration mechanisms aimed at enhancing security of supply in electricity systems. They can be framed as call options on electricity sold by power producers to System Operators. This paper provides a comprehensive mathematical treatment of Reliability Options. Their value is first de…

2019-09-12abs ↗pdf ↗

\begin{abstract} The aim of this paper is to study the spanning power of options in a static financial market that allows non-integrable assets. Our findings extend and unify the results in [8,9,18] for LpL_p-models. We also apply the spanning power properties to the pricing problem. In particular, we show that prices …

2016-03-03abs ↗pdf ↗

Paper solves multi-dimensional passport option pricing problem using machine learning.

problem Pricing multi-dimensional passport options in correlated markets remains unsolved.
method Discrete-time solution for multi-dimensional BS markets with uncorrelated assets; machine learning approaches.
result Machine learning-powered approaches successfully price passport options in both 1D and multi-dimensional uncorrelated BS markets.

The paper calculates Bachelier option prices using Taylor expansions and applies it as a variance reduction technique.

problem Calculating Bachelier option prices and variance reduction in correlated cases.
method Taylor expansions and classical Itô calculus to derive option prices, uses negative powers of future mean volatility.
result The paper provides a new method to calculate Bachelier option prices and applies it to reduce variance in Monte Carlo simulations.

Study proves duality in exotic option pricing under uncertain model and delayed information.

problem Pricing and hedging of multi-action exotic options under nondominated model uncertainty and delayed information.
method Reformulated superhedging problem as a European option problem, proving duality results.
result Superhedging price equals model-based price with future look-up power.

In this paper we propose a closed-form approximation for the price of basket options under a multivariate Black-Scholes model, based on Taylor expansions and the calculation of mixed exponential-power moments of a Gaussian distribution. Our numerical results show that a second order expansion provides accurate prices o…

2014-04-11abs ↗pdf ↗

The paper models cryptocurrency price and volatility with jumps and fractional volatility.

problem Empirical evidence shows jumps in cryptocurrency price and volatility.
method Fractional stochastic volatility model with jumps and short-term volatility dependency.
result Fractional stochastic volatility models outperform other models in pricing and hedging cryptocurrency options.

It is well known that any sufficiently regular one-dimensional payoff function has an explicit static hedge by bonds, forward contracts and lots of vanilla options. We show that the natural extension of the corresponding representation leads to a static hedge based on the same instruments along with traffic light optio…

2010-11-22abs ↗pdf ↗

This paper compares machine learning models for pricing European options.

problem Pricing European options using traditional methods like Black Scholes Model.
method Google AutoML Regressor, TensorFlow Neural Networks, and XGBoost Gradient Boosting Decision Trees.
result All models outperformed the Black Scholes Model in terms of mean absolute error.

The paper provides approximations for pricing Asian options using a mixed fractional Brownian motion with jumps.

problem Pricing Asian options under a mixed fractional Brownian motion with jumps.
method Approximate closed-form solutions for arithmetic Asian options and power options.
result Analytical formulas for pricing arithmetic Asian options and power options are derived.

We build a methodology that takes a given option price in the tails with strike KK and extends (for calls, all strikes > KK, for puts all strikes <K< K) assuming the continuation falls into what we define as "Karamata Constant" over which the strong Pareto law holds. The heuristic produces relative prices for options…

2019-08-06abs ↗pdf ↗

Enhanced volatility forecasting using options data and rough volatility model.

problem Improving realized volatility forecasting accuracy.
method Infer spot volatility from options data using rough stochastic volatility model, accelerate estimation with deep learning, benchmark against traditional models.
result Augmented HAR-RV-RHeston model outperforms traditional models in daily and long-term forecasting.

We propose a general framework for the simultaneous modeling of equity, government bonds, corporate bonds and derivatives. Uncertainty is generated by a general affine Markov process. The setting allows for stochastic volatility, jumps, the possibility of default and correlation between different assets. We show how to…

2010-12-01abs ↗pdf ↗

Framework optimizes PV-battery investment timing to maximize value.

problem Optimizing investments in residential PV-battery systems under uncertain market conditions.
method Real options valuation framework with multi-stage compound options, incorporating Monte Carlo simulation.
result Optimal timing of PV-battery investment increases overall value.

We develop series expansions in powers of q1q^{-1} and q1/2q^{-1/2} of solutions of the equation ψ(z)=qψ(z) = q, where ψ(z)ψ(z) is the Laplace exponent of a hyperexponential Lévy process. As a direct consequence we derive analytic expressions for the prices of European call and put options and their Greeks (Theta, Delta, and G…

2017-05-16abs ↗pdf ↗

Critical volatility triggers log-normal to power-law transitions in interconnected systems.

problem Understanding the transition from log-normal to power-law distributions in interconnected systems.
method Analyzing an infinite option-on-option chain model, deriving a critical volatility threshold.
result A critical volatility threshold of approximately 250.66% for unconditional cases, dropping to 125.3% with selective survival.

The paper derives formulas for option pricing and random walk expectations.

problem Calculating the price of barrier and lookback options.
method Inverse Z-transform, Fourier/Laplace inversion, Wiener-Hopf factorization, and numerical methods.
result Efficient numerical methods for option pricing are developed.

Efficiently values and computes sensitivities of Bermudan options using Method of Lines.

problem Valuation and sensitivities of Bermudan options.
method Method of Lines converting Black Scholes PDE to ODEs, spatial discretization, exponential matrix operation for efficiency.
result Computational efficiency and straightforward implementation for computing sensitivities.

The article prices exchange options using variance gamma-like models.

problem Pricing exchange options under specific stochastic processes.
method Derives formulas for variance gamma and variance gamma++ processes, constructs multidimensional versions, calibrates parameters with real data.
result Closed formulas and numerical methods for evaluating exchange options.

The paper analyzes binary option markets with exogenous information and price sensitivity.

problem Analyzing binary option markets with exogenous information and price sensitivity.
method Derive and analyze a continuous model of binary option markets with exogenous information, using Filippov surfaces and general assumptions on purchasing rules.
result Price always converges when exogenous information is constant, and price sensitivity affects price lag vs. information.

The paper solves European option pricing under Heston model using artificial boundary method.

problem Valuation of European call options under Heston stochastic volatility model.
method Asymptotic solution in powers of volatility, artificial boundary method for truncated domain, artificial boundary conditions.
result Artificial boundary conditions improve accuracy and outperform Heston's original boundary conditions.

One popular approach to option pricing in Lévy models is through solving the related partial integro differential equation (PIDE). For the numerical solution of such equations powerful Galerkin methods have been put forward e.g. by Hilber et al. (2013). As in practice large classes of models are maintained simultaneous…

2016-03-27abs ↗pdf ↗

We consider a financial market with liquidity cost as in Çetin, Jarrow and Protter [2004], where the supply function Sε(s,ν)S^ε(s,ν) depends on a parameter ε0ε\geq 0 with S0(s,ν)=sS^0(s,ν)=s corresponding to the perfect liquid situation. Using the PDE characterization of Çetin, Soner and Touzi [2010] of the super-hedging cost of a…

2012-08-18abs ↗pdf ↗

New method uses tensor networks to price multi-asset options efficiently.

problem Pricing multi-asset options via classical full-grid solvers is computationally infeasible due to the curse of dimensionality.
method Quantized tensor trains (QTT) transform the d-asset Black-Scholes PDE into a tractable high-dimensional problem.
result Full-grid prices and Greeks for correlated basket and max-min options in three to five dimensions can be computed with high accuracy.

Paper presents a new computational technique for finance using ERM and neural networks.

problem Efficient computation of financial derivatives and hedging strategies.
method Empirical Risk Minimization and neural networks applied to high-dimensional financial problems.
result Demonstrates the effectiveness and challenges of applying deep learning to financial models.

We fit the volatility fluctuations of the S&P 500 index well by a Chi distribution, and the distribution of log-returns by a corresponding superposition of Gaussian distributions. The Fourier transform of this is, remarkably, of the Tsallis type. An option pricing formula is derived from the same superposition of Black…

2007-08-22abs ↗pdf ↗

Quantum computing improves Monte Carlo option pricing for complex derivatives.

problem Complex financial derivatives require extensive computations in high-dimensional spaces.
method Developed a quantum algorithm for simulating many potential asset paths in parallel.
result Quantum algorithm provides highly accurate option pricing and risk analysis.

In this paper we use Bernstein and Chebyshev polynomials to approximate the price of some basket options under a bivariate Black-Scholes model. The method consists in expanding the price of a univariate related contract after conditioning on the remaining underlying assets and calculating the mixed exponential-power mo…

2014-04-11abs ↗pdf ↗

Study finds rough volatility models underperform in SPX option pricing.

problem Inconsistency of rough volatility models with SPX option prices.
method Empirical study using SPX options data, comparing rough and Markovian models.
result Rough volatility models with H(0,1/2)H \in (0,1/2) are inconsistent with SPX smiles, especially at short maturities.