most citedADOL - Markovian approximation of rough lognormal model

1 citations · 1 across the 2 of their papers we have counts for

collaborators

6 papers

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

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

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…

q-fin.MF2019

A lognormal type stochastic volatility model with quadratic drift

Peter Carr, Sander Willems

This paper presents a novel one-factor stochastic volatility model where the instantaneous volatility of the asset log-return is a diffusion with a quadratic drift and a linear dis…

q-fin.CP2019

A model-free backward and forward nonlinear PDEs for implied volatility

Peter Carr, Andrey Itkin, Sasha Stoikov

We derive a backward and forward nonlinear PDEs that govern the implied volatility of a contingent claim whenever the latter is well-defined. This would include at least any contin…

q-fin.MF20191 cited

ADOL - Markovian approximation of rough lognormal model

Peter Carr, Andrey Itkin

In this paper we apply Markovian approximation of the fractional Brownian motion (BM), known as the Dobric-Ojeda (DO) process, to the fractional stochastic volatility model where t…