Results 1 to 10 of about 13,676 (25)

The early exercise premium representation for American options on multiply assets [PDF]

open access: yesAppl. Math. Optim. 73 (2016) 99-114, 2013
In the paper we consider the problem of valuation of American options written on dividend-paying assets whose price dynamics follow the classical multidimensional Black and Scholes model. We provide a general early exercise premium representation formula for options with payoff functions which are convex or satisfy mild regularity assumptions. Examples
arxiv   +1 more source

Quantum option pricing using Wick rotated imaginary time evolution [PDF]

open access: yesarXiv, 2021
In this paper we reformulate the problem of pricing options in a quantum setting. Our proposed algorithm involves preparing an initial state, representing the option price, and then evolving it using existing imaginary time simulation algorithms. This way of pricing options boils down to mapping an initial option price to a quantum state and then ...
arxiv  

Path Integral Method for Proportional Step and Proportional Double-Barrier Step Option Pricing [PDF]

open access: yesarXiv, 2021
Path integral method in quantum mechanics provides a new thinking for barrier option pricing. For proportional step options, the option price changing process is similar to the one dimensional trapezoid potential barrier scattering problem in quantum mechanics; for double-barrier step options, the option price changing process is analogous to a ...
arxiv  

Toward Discovering Options that Achieve Faster Planning [PDF]

open access: yesarXiv, 2022
We propose a new objective for option discovery that emphasizes the computational advantage of using options in planning. In a sequential machine, the speed of planning is proportional to the number of elementary operations used to achieve a good policy.
arxiv  

Option Pricing using Quantum Computers [PDF]

open access: yesQuantum 4, 291 (2020), 2019
We present a methodology to price options and portfolios of options on a gate-based quantum computer using amplitude estimation, an algorithm which provides a quadratic speedup compared to classical Monte Carlo methods. The options that we cover include vanilla options, multi-asset options and path-dependent options such as barrier options.
arxiv   +1 more source

American Exchange option driven by a Lévy process [PDF]

open access: yesarXiv, 2023
We consider the problem of pricing American Exchange options driven by a L\'evy process. We study the properties of American Exchange options, we represented it as the sum of the price of the corresponding European exchange option price and an early exercise premium.
arxiv  

Financial option insurance [PDF]

open access: yesRisk Management-Journal of Risk Crisis and Disaster, Vol. 19, No. 1, pp. 72-101, 2017, 2017
The option is a financial derivative, which is regularly employed in reducing the risk of its underlying securities. However, investing in option is still risky. Such risk becomes much severer for speculators who utilize option as a means of leverage to increase their potential returns.
arxiv   +1 more source

American Passport options in an exponential Lévy model [PDF]

open access: yesarXiv, 2023
In this paper we examine the problem of valuing an exotic derivative known as the American passport option where the underlying is driven by a L\'evy process. The passport option is a call option on a trading account. We derive the pricing equation, using the dynamic programming principle, and prove that the option value is a viscosity solution of ...
arxiv  

Recursive formula for arithmetic Asian option prices [PDF]

open access: yes, 2013
We derive a recursive formula for arithmetic Asian option prices with finite observation times in semimartingale models. The method is based on the relationship between the risk-neutral expectation of the quadratic variation of the return process and European option prices.
arxiv   +1 more source

Diversity-Enriched Option-Critic [PDF]

open access: yesarXiv, 2020
Temporal abstraction allows reinforcement learning agents to represent knowledge and develop strategies over different temporal scales. The option-critic framework has been demonstrated to learn temporally extended actions, represented as options, end-to-end in a model-free setting. However, feasibility of option-critic remains limited due to two major
arxiv  

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