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Assessing Implied Volatility Model Error Against Bid-Ask and Vega

Article Quant Q&A · Author: vanna

Summary

The document asks what implied-volatility fitting error is acceptable for an equity-index surface calibrated with stochastic-volatility models such as Heston or SABR. The replies do not establish a universal tolerance. One practical suggestion is to compare the model’s price for a contingent claim with a bid-ask interval under a bounded-volatility framework, which evaluates outcomes favorable to each side of the trade. This connects model uncertainty to stochastic control and can become technically demanding.

Another response frames the issue in trade-specific terms: translate a volatility error into a price impact using the position’s vega, then compare that impact with the market spread. A further caveat is that standard models may not fit volatility wings inside bid-ask quotes, particularly when the goal is to capture dynamics for exotic or variance products. The discussion is informal and gives no validated threshold; acceptable error depends on instrument, market liquidity, and use of the calibration.

Key ideas

  • There is no single implied-volatility error tolerance established for all models and products.
  • A bounded-volatility framework can relate model uncertainty to bid and ask prices.
  • Vega converts volatility error into an approximate price impact for a specific trade.
  • Market spreads vary by maturity and underlying, so error tolerance is context dependent.
  • Stochastic-volatility models may not fit volatility wings within observed bid-ask quotes.

Tags

Full text
# What is an acceptable error on implied volatility?


# What is an acceptable error on implied volatility?












Given an implied volatility surface (on equity indexes) and a calibrated model, what is the range of error on implied volatility a trader would accept ?

This obviously depends on the model used to calibrate. I am interested in classical stochastic volatility models (Heston, SABR, e.g.) to begin with.

## Answer by vanguard2k (score 1)

https://quant.stackexchange.com/a/4184

Dealing with model error under stochastic volatility (in a more formal way) you could use the UVM (Uncertain Volatility Framework). Here are what i think are the most seminal references:

Avellenada et al (1995) Pricing And Hedging Derivative Securities In Markets With Uncertain Volatilities http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.50.3736 Lyons (1995) Uncertain Volatility and the risk-free synthesis of derivatives http://it.scribd.com/doc/40177754/Lyons-Uncertain-Volatility-and-Risk-Free-Synthesis-of-Derivatives-Appl-math-Finance

But you can also find some review of the topic (just google UVM).

This answers somehow lead you into the field of stochastic control problems which can be quite technical. One thing i remembered is: If you assume your volatility to be bounded $\sigma_t \in [\sigma_{\min}, \sigma_{\max}]$ you can price a contingent claim under two different viewpoints. One that is beneficial for the long side and one that is beneficial for the short side (by simply assuming in each case that the "true" volatility always has the most beneficial value for the respective side). All else being equal this should give you the arbitrage-free bid/ask prices in this framework. So if you turn the problem around here you could price an existing contingent claim by means of your stochastic volatility model and end up somewhere between the bid and the ask i would say you should be okay.

## Answer by joelhoro (score 0)

https://quant.stackexchange.com/a/3862

Euh... why don't you ask him? You better make sure that the error is smaller than the bid-offer probably smaller than half of that. Now bid offer can vary on maturity and underlyer and can go from 0.1% to 5%...

Anyhow - the trader will look at the vega of any trade he needs to price and multiply that by the vol error and perhaps add the result to the price so he won't care really whether it's 0.01% of 0.5%.

And btw what product are you pricing, that requires stoch vol?

## Answer by Strange (score 0)

https://quant.stackexchange.com/a/4186

I presume you are trying to do that so you can price exotic variance? The general thought process is that no matter how hard you try, you would not be able to perfectly fit the wings using one of these models (not within the bid/offer). However, most probably you are just trying to replicate the dynamics, so best thing is to come up with some sort of adjuster framework. Anyway, my 0.02 Vega.

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This summary was written by Stratmill's research agent from the original; it is not a copy of the source.