The step stochastic volatility model
Extreme short-dated skew can be obtained by decomposing it in two parts
CLICK HERE TO DOWNLOAD THE PDF
Peter Friz, Paolo Pigato and Jonathan Seibel propose a modification of a given stochastic volatility model ‘backbone’ capable of producing extreme short-dated implied skews, without adding jumps or non-Markovian ‘rough’ fractional volatility dynamics. A decomposition formula for the implied skew of a local stochastic volatility model suggests this can be achieved via a non-smooth leverage function, such as a step function. The resulting step stochastic volatility
Only users who have a paid subscription or are part of a corporate subscription are able to print or copy content.
To access these options, along with all other subscription benefits, please contact info@risk.net or view our subscription options here: http://subscriptions.risk.net/subscribe
You are currently unable to print this content. Please contact info@risk.net to find out more.
You are currently unable to copy this content. Please contact info@risk.net to find out more.
Copyright Infopro Digital Limited. All rights reserved.
As outlined in our terms and conditions, https://www.infopro-digital.com/terms-and-conditions/subscriptions/ (point 2.4), printing is limited to a single copy.
If you would like to purchase additional rights please email info@risk.net
Copyright Infopro Digital Limited. All rights reserved.
You may share this content using our article tools. As outlined in our terms and conditions, https://www.infopro-digital.com/terms-and-conditions/subscriptions/ (clause 2.4), an Authorised User may only make one copy of the materials for their own personal use. You must also comply with the restrictions in clause 2.5.
If you would like to purchase additional rights please email info@risk.net
More on Banking
Auto-encoding term-structure models
An arbitrage-free low-dimensionality interest rate model is presented
The relativity of the fractional Gamma Clock
Bank of America quant expands his Gamma Clock model with a fractional Brownian motion
Option market-making and vol arbitrage
The agent’s view is factored in to a realised-vs-implied vol model
Funding arbitrages and optimal funding policy
Stochastic control can be used to manage a bank’s net asset income
Market-making in spot precious metals
A market-making framework is extended to account for metal markets’ liquidity constraints
A comparison of FX fixing methodologies
FX fixing outcomes are mostly driven by length of calculation window
Backtesting correlated quantities
A technique to decorrelate samples and reach higher discriminatory power is presented
CVA sensitivities, hedging and risk
A probabilistic machine learning approach to CVA calculations is proposed
