Gamma hedging and rough paths

Abstract We apply rough-path theory to study the discrete-time gamma-hedging strategy. We show that if a trader knows that the market prices of a set of European options are given by a diffusive pricing model, then the discrete-time gamma-hedging strategy enables them to replicate other European options so long as the underlying pricing signal has finite $p$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>p</mml:mi> </mml:math> -variation for $p&lt;3$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>p</mml:mi> <mml:mo>&lt;</mml:mo> <mml:mn>3</mml:mn> </mml:math> , with the error in the discrete-time replication strategy tending to zero as the length of the largest hedging interval tends to zero. This is a sure result and does not require that the underlying pricing signal has a quadratic variation corresponding to a probabilistic pricing model. We show how to generalise this result to exotic derivatives when the gamma is defined to be the Gubinelli derivative of the delta by deriving rough-path versions of the Clark–Ocone formula. We illustrate our theory by proving that if a stock price path has finite $p$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>p</mml:mi> </mml:math> -variation for $p&lt;3$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>p</mml:mi> <mml:mo>&lt;</mml:mo> <mml:mn>3</mml:mn> </mml:math> and if the implied volatility process for a European derivative on the stock (with a smooth, convex, nonlinear payoff and maturity $T$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>T</mml:mi> </mml:math> ) has finite $q$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>q</mml:mi> </mml:math> -variation for $q&lt;2$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>q</mml:mi> <mml:mo>&lt;</mml:mo> <mml:mn>2</mml:mn> </mml:math> and $\frac{1}{p}+\frac{1}{q}&gt;1$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mfrac> <mml:mn>1</mml:mn> <mml:mi>p</mml:mi> </mml:mfrac> <mml:mo>+</mml:mo> <mml:mfrac> <mml:mn>1</mml:mn> <mml:mi>q</mml:mi> </mml:mfrac> <mml:mo>&gt;</mml:mo> <mml:mn>1</mml:mn> </mml:math> , one can use the gamma-hedging strategy to replicate any European derivative with smooth payoff and maturity $T$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>T</mml:mi> </mml:math> . This is a sure result which holds without assuming any probabilistic model for the trajectory of the stock price path.

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Publication Details

Journal
Finance and Stochastics
Published
2025-09-16
DOI
https://doi.org/10.1007/s00780-025-00576-2
Primary Topic
Stochastic processes and financial applications
Type
article
Field-Weighted Citation Impact
0.00

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article

Gamma hedging and rough paths

John Armstrong, Andrei Ionescu
Finance and Stochastics
Stochastic processes and financial applications
article

Gamma hedging and rough paths

John Armstrong, Andrei Ionescu
article en

Abstract

Abstract We apply rough-path theory to study the discrete-time gamma-hedging strategy. We show that if a trader knows that the market prices of a set of European options are given by a diffusive pricing model, then the discrete-time gamma-hedging strategy enables them to replicate other European options so long as the underlying pricing signal has finite $p$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>p</mml:mi> </mml:math> -variation for $p&lt;3$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>p</mml:mi> <mml:mo>&lt;</mml:mo> <mml:mn>3</mml:mn> </mml:math> , with the error in the discrete-time replication strategy tending to zero as the length of the largest hedging interval tends to zero. This is a sure result and does not require that the underlying pricing signal has a quadratic variation corresponding to a probabilistic pricing model. We show how to generalise this result to exotic derivatives when the gamma is defined to be the Gubinelli derivative of the delta by deriving rough-path versions of the Clark–Ocone formula. We illustrate our theory by proving that if a stock price path has finite $p$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>p</mml:mi> </mml:math> -variation for $p&lt;3$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>p</mml:mi> <mml:mo>&lt;</mml:mo> <mml:mn>3</mml:mn> </mml:math> and if the implied volatility process for a European derivative on the stock (with a smooth, convex, nonlinear payoff and maturity $T$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>T</mml:mi> </mml:math> ) has finite $q$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>q</mml:mi> </mml:math> -variation for $q&lt;2$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>q</mml:mi> <mml:mo>&lt;</mml:mo> <mml:mn>2</mml:mn> </mml:math> and $\frac{1}{p}+\frac{1}{q}&gt;1$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mfrac> <mml:mn>1</mml:mn> <mml:mi>p</mml:mi> </mml:mfrac> <mml:mo>+</mml:mo> <mml:mfrac> <mml:mn>1</mml:mn> <mml:mi>q</mml:mi> </mml:mfrac> <mml:mo>&gt;</mml:mo> <mml:mn>1</mml:mn> </mml:math> , one can use the gamma-hedging strategy to replicate any European derivative with smooth payoff and maturity $T$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>T</mml:mi> </mml:math> . This is a sure result which holds without assuming any probabilistic model for the trajectory of the stock price path.

Finance and StochasticsVol. 29(4)
King's College London (GB)
King's College London
Openalex Percentile: Top 68%
Stochastic processes and financial applications
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