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Mathematical Finance
Article . 2023 . Peer-reviewed
License: CC BY
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zbMATH Open
Article . 2023
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SSRN Electronic Journal
Article . 2021 . Peer-reviewed
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https://dx.doi.org/10.48550/ar...
Article . 2021
License: arXiv Non-Exclusive Distribution
Data sources: Datacite
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The log‐moment formula for implied volatility

The log-moment formula for implied volatility
Authors: Vimal Raval; Antoine Jacquier;

The log‐moment formula for implied volatility

Abstract

AbstractWe revisit the foundational Moment Formula proved by Roger Lee fifteen years ago. We show that in the absence of arbitrage, if the underlying stock price at time T admits finite log‐moments for some positive q, the arbitrage‐free growth in the left wing of the implied volatility smile for T is less constrained than Lee's bound. The result is rationalized by a market trading discretely monitored variance swaps wherein the payoff is a function of squared log‐returns, and requires no assumption for the underlying price to admit any negative moment. In this respect, the result can be derived from a model‐independent setup. As a byproduct, we relax the moment assumptions on the stock price to provide a new proof of the notorious Gatheral–Fukasawa formula expressing variance swaps in terms of the implied volatility.

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Keywords

Probability (math.PR), moment formula, FOS: Economics and business, Derivative securities (option pricing, hedging, etc.), FOS: Mathematics, Pricing of Securities (q-fin.PR), variance swaps, Quantitative Finance - Pricing of Securities, 91B25, 60H30, implied volatility, Mathematics - Probability

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
3
Top 10%
Top 10%
Average
Green
hybrid