‘Hot-start’ initialisation of the Heston model
Multi-factor models usually have hidden variables – for example, stochastic volatility – with unknown spot values. This suggests the initial value of such variables is actually random, with a distribution generated through stochastic evolution before formal modelling starts. Serguei Mechkov applies this approach to the Heston model and demonstrates its significant effect on the implied volatility smile
CLICK HERE TO VIEW THE PDF
A logical way of making a model more closely fit observed behaviour is to augment its dimensions by adding a hidden process that somehow affects the evolution of the principal observable value. The complete model specification then acquires the parameters of the hidden process and its possible correlation with the principal process. This also requires a description
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 Risk management
Why resilience goes beyond risk at StanChart
Risk Live: Reliability is “a business goal” that can involve difficult trade-offs, says Americas CEO DeFilippo
Agentic risk management could arrive ‘sooner than we think’
Risk Live: Models are capable, but banks lack platform and governance to safely run agentic systems
Supervisors becoming more demanding, say ERM teams
Risk Benchmarking: More than half report rising supervisory contact, despite unchanging requirements for an ERM function
Asian dealers may be more exposed than US in AI selloff scenario
Prime brokers face regional counterparty risk from huge flows in leveraged ETFs, say risk managers
Banks upgrade liquidity tests to cope with volatile world
Risk Live: Greater need to assess modern threats from technology transformation
Enterprise Risk Benchmarking 2026: explore the data
View interactive charts from Risk.net’s 52-bank study, covering enterprise risk governance, appetite setting, board reporting, scenario analysis, culture and resilience
Continuous verification holds key to keeping AI on track
Decision-by-decision testing will help users trust AI judgement calls
Banks try to prepare for – not predict – geopolitical shocks
Risk Live: HSBC and KeyBank frameworks were tested by Iran attacks
