What is Implied Volatility?

To better understand Implied Volatility (IV), it’s best to have a quick look at Realised Volatility. We can very precisely measure what happened in the past, because, well, it’s already happened….

Realised Volatility measures, over a defined timeframe, how much a dataset has varied. Usually calculated using the variance of a dataset (think back to high-school level maths…). There are multiple methods to calculate the realised volatility but none allow us to extrapolate anything forward from past performance. Looking at past datasets, we can accurately determine the variance and volatility of a stock, but how do we measure the volatility of something that hasn’t happened yet?

If we also think about the past returns (and the variance of these returns) as a standard distribution, we’ll be able to fit them on a bell curve, and this is how we think about future volatility. 68% of the time, or one standard distribution, the market will not exceed X% returns (positive or negative). If we determine that one standard distribution is what we should reasonably expect from the market, then this is what we’ll use as the future volatility or, the Implied Volatility figure. But how do we know what +-X% is, if we cannot rely on any past data?

In the same way that single-stock markets govern themselves and remain efficient through supply & demand, we can measure how market participants are expecting the market to behave through the supply & demand of options.

The simple way to value an option of a stock/index/future is determined by the following inputs:

• Moneyness

• Days to Expiry (DTE)

• Supply & Demand

Moneyness & DTE are known entities, plus, as it’s almost guaranteed your counterparty will be a market-maker, supply isn’t relevant. Therefore, the unknown item affecting the price of an option is Demand.

As demand has a direct effect on the price of an option, it must be possible to measure this “demand”. When more options are bought, the price is pushed up, and this increased “demand” is what is used as an input into the equation used to determine the value of an option. This “demand” is a part of what we quanitfy as Implied Volatility (IV).

Thinking back to simple supply & demand in an efficient market, when market participants buy options, demand and therefore the expected future distribution of returns, go up, when they’re sold, demand and therefore future expectations of market movements, go down.

So why do market participants buy options? Typically to hedge an upcoming event which may cause a market shock (such as a FOMC rate decision or earnings reports for single stocks). If market participants are expecting more positive or negative movements of the market in the future, more options are bought, pushing up IV’s.

This wider expectation of future returns brings more eventualities (more possible outcomes for +-X% returns) into one standard distribution. And this is what causes Implied Volatility to rise and fall.

We can then use this Implied Volatility as the “Demand” input for the pricing model we use to determine the price of an option. This process is cyclical and can seem indeterminate and that’s what we try to simplify here at VolQ Capital.

Let’s not forget that no one knows what the future will bring, but using almost mob-mentality, we can estimate typical (one standard deviation) returns for a fixed forward-looking timeframe.

In future articles, we’ll explore how Implied Volatilities are calculated and how we use these in our trading.