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20012026
most citedSolving the Optimal Trading Trajectory Problem Using a Quantum Annealer

177 citations · 238 across the 18 of their papers we have counts for

collaborators

22 papers

q-fin.PR2026

When to Sell an Asset? - A Distribution Builder Approach

Peter Carr, Stephan Sturm

We consider the question of the optimal timing of the sale of an asset with stochastic dynamics. Our analysis is based on the method of the distribution builder introduced by Sharp…

q-fin.PR2022★ 1 cited

Semi-analytical pricing of barrier options in the time-dependent Heston model

P. Carr, A. Itkin, D. Muravey

We develop the general integral transforms (GIT) method for pricing barrier options in the time-dependent Heston model (also with a time-dependent barrier) where the option price i…

q-fin.MF2021

Robust Replication of Volatility and Hybrid Derivatives on Jump Diffusions

Peter Carr, Roger Lee, Matthew Lorig

We price and replicate a variety of claims written on the log price and quadratic variation of a risky asset, modeled as a positive semimartingale, subject to stochastic…

q-fin.CP2020

Semi-closed form prices of barrier options in the time-dependent CEV and CIR models

Peter Carr, Andrey Itkin, Dmitry Muravey

We continue a series of papers where prices of the barrier options written on the underlying, which dynamics follows some one factor stochastic model with time-dependent coefficien…

q-fin.PR2020★ 9 cited

Semi-closed form solutions for barrier and American options written on a time-dependent Ornstein Uhlenbeck process

Peter Carr, Andrey Itkin

In this paper we develop a semi-closed form solutions for the barrier (perhaps, time-dependent) and American options written on the underlying stock which follows a time-dependent…

q-fin.MF2019★ 12 cited

Using Machine Learning to Predict Realized Variance

Peter Carr, Liuren Wu, Zhibai Zhang

In this paper we formulate a regression problem to predict realized volatility by using option price data and enhance VIX-styled volatility indices' predictability and liquidity. W…