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Estimating Black–Scholes Implied Volatility

Article Quant Q&A · Author: jessica

Summary

The document explains why Black–Scholes implied volatility generally has no closed-form inverse, even though the option price itself has a closed-form formula. It presents a Brenner–Subrahmanyam expression as a quick estimate and starting point, then describes Newton–Raphson iteration: compare the model price with the observed option price and adjust volatility using vega until the pricing error is small. The method relies on a differentiable pricing formula with useful vega behavior.

For harder cases, including American options and exotic payoffs, the discussion recommends bracketing approaches such as bisection or Brent’s method, which do not depend on vega. It also mentions rational approximations as stand-alone estimates or as initial guesses for iterative methods, and cites further research on explicit and adaptive methods. The answers offer methods rather than a performance comparison; the best choice depends on the pricing model and desired accuracy.

Key ideas

  • Black–Scholes implied volatility usually requires numerical inversion because the pricing formula has no closed-form inverse.
  • A closed-form approximation can provide a quick estimate or an initial guess for an iterative solver.
  • Newton–Raphson updates volatility using the option pricing error and vega.
  • Bisection and Brent’s method are alternatives when vega-based iteration is unsuitable, including for some American and exotic options.

Tags

Full text
# A simple formula for calculating implied volatility?


# A simple formula for calculating implied volatility?












We all know if you back out of the Black Scholes option pricing model you can derive what the option is "implying" about the underlyings future expected volatility.

Is there a simple, closed form, formula deriving Implied Volatility (IV)? If so can you could you direct me to the equation?

Or is IV only numerically solved?

## Answer by yoonkwon (score 34, accepted)

https://quant.stackexchange.com/a/7763

Brenner and Subrahmanyam (1988) provided a closed form estimate of IV, you can use it as the initial estimate:

$$ \sigma \approx \sqrt{\cfrac{2\pi}{T}} . \cfrac{C}{S} $$

## Answer by Brian B (score 45)

https://quant.stackexchange.com/a/7765

The Black-Scholes option pricing model provides a closed-form pricing formula $BS(\sigma)$ for a European-exercise option with price $P$. There is no closed-form inverse for it, but because it has a closed-form vega (volatility derivative) $\nu(\sigma)$, and the derivative is nonnegative, we can use the Newton-Raphson formula with confidence.

Essentially, we choose a starting value $\sigma_0$ say from yoonkwon's post. Then, we iterate

$$ \sigma_{n+1} = \sigma_n - \frac{BS(\sigma_n)-P}{\nu(\sigma_n)} $$

until we have reached a solution of sufficient accuracy.

This only works for options where the Black-Scholes model has a closed-form solution and a nice vega. When it does not, as for exotic payoffs, American-exercise options and so on, we need a more stable technique that does not depend on vega.

In these harder cases, it is typical to apply a secant method with bisective bounds checking. A favored algorithm is Brent's method since it is commonly available and quite fast.

## Answer by Matt Wolf (score 19)

https://quant.stackexchange.com/a/7762

It is a very simple procedure and yes, Newton-Raphson is used because it converges sufficiently quickly:

- You need to obviously supply an option pricing model such as BS.

- Plug in an initial guess for implied volatility -> calculate the the option price as a function of your initial iVol guess -> apply NR -> minimize the error term until it is sufficiently small to your liking.

- the following contains a very simple example of how you derive the implied vol from an option price: http://risklearn.com/estimating-implied-volatility-with-the-newton-raphson-method/

- You can also derive implied volatility through a "rational approximation" approach (closed form approach -> faster), which can be used exclusively if you are fine with the approximation error or as a hybrid in combination with a few iterations of NR (better initial guess -> less iterations). Here a reference: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=952727

## Answer by jaehyukchoi49 (score 8)

https://quant.stackexchange.com/a/32532

There are some references on this topic. You may find them helpful.

Peter Jaeckel has articles named "By Implication (2006)" and "Let's be rational (2013)"

Li and Lee (2009) [download] An adaptive successive over-relaxation method for computing the Black–Scholes implied volatility

Stefanica and Radoicic (2017) An Explicit Implied Volatility Formula

## Answer by user34971 (score 4)

https://quant.stackexchange.com/a/55127

The bisection method, Brent's method, and other algorithms should work well. But here is a very recent paper that gives an explicit representation of IV in terms of call prices through (Dirac) delta sequences:

Cui et al. (2020) - A closed-form model-free implied volatility formula through delta sequences

## Answer by Alexander Fedorov (score 2)

https://quant.stackexchange.com/a/22797

To get IV I do the following: 1) change sig many times and calculate C in BS formula every time. That can be done with OIC calculator All other parameters are kept constant in BS call price calculations. The sig that corresponds to C value closest to the call market value is probably right. 2) without OIC calculator for every chosen sig I am using old approach: calculate d1, d2, Nd1, Nd2 and BS option value. Again calculated BS value closest to the market value probably correspond to correct IV.

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