Knowledge series implied and realized volatility

Knowledge Series: Realised & Implied Volatility

© 2014 | All Rights Reserved Page 1

http://www.riskedgesolutions.com/



Introduction

This article is in continuation to our last Knowledge Series article wherein I wrote about the basics of

Volatility and the standard ways of calculating it. In this article, I will further distinguish between

Realised and Implied Volatility. Of late, at Risk Edge we are being frequently asked about the role of

Implied Volatility in Risk Management. So this article differentiates between the two - ‘Realised

Volatility’ generally called ‘Historical Volatility’ and the ‘Implied Volatility’.

Realised Volatility

Realised Volatility of an asset, as the name suggests is an estimate of the fluctuation observed in the

daily prices of the asset, represented in % terms. It is usually calculated on the daily close prices. In

some cases when the commodity benchmark price is not reported by a well known agency or an

illiquid commodity, daily average price is used for estimating the Realised Volatility. Our Knowledge

Series article on Volatility shows the standard ways of calculating Realised Volatility. The simplest

way of calculating Realised Volatility is the Standard Deviation.

𝑆𝐷 = 𝑥𝑖 − 𝑥 2𝑛

𝑖=1

𝑛 − 1 (1)

Implied Volatility (IV)

Implied Volatility (IV) on the other hand is the volatility “implied” from the option prices or a

Volatility Index (like VIX). It is seen as a general indication of what the market’s future volatility

would be. Observing Implied Volatility from Option prices is the common practice. Since most option

trade volume is usually in the at-the-money (ATM) Options, IV is derived from the prices of ATM

Options.

In simplest terms, knowing the ATM option price we could derive IV using the option pricing model

like Black-Scholes. I.e., the Volatility that results in the ‘known’ Option price will be the IV of the

Underlying; such IV will be in annualised terms (i.e., daily volatility × 252) and has to be scaled

down for the expiration period. Most price data providers and exchanges publish the implied

Volatility estimates regularly.

http://www.riskedgesolutions.com/knowledge-series-understanding-volatility/



Illustration

On 4th Aug 2014, ICE ARABICA COFFE FUTURES near month i.e, SEP 14 settled at 190.5 Cents/lb. And

the ATM Option 190.00 CALL SEP 14 settled at 5.83 Cents/lb, suggesting an implied Volatility of

51.26%. Assuming the price returns are normally distributed and have a zero average return, the two

Volatility estimates suggest two price ranges with 68% probability, for the underlying futures

contract ICE COFFEE SEP 14.

Realised Volatility: The one day Conditional EWMA Volatility is 2.8% suggesting a probable

price range of 185 – 196 Cents/lb. This is the expected price range of Coffee Futures if one

were to assume that the recently observed price variance will continue to be the same on

the next day as well.

Implied Volatility: The IV estimate for one day is 3.2% suggesting a probable range of 184 –

197 Cents/lb. On the other hand market participants think the price could be anywhere in

this range (68% probable)

Figure 1: Understanding what Realised & Implied Volatilities suggest

Like in this example, it is observed that mostly the implied volatility surface for a wide range of

options averages to a value greater than the realised volatility. This premium can be seen as

compensation to option sellers for the unlimited risk they are taking. Generally, the higher the IV,

the higher the Option Premium.

To summarize, Realised Volatility represents the past variance and Implied Volatility gives a sense of

the future volatility. Realised Volatility is used as a cue for option trading, by assuming that the past



volatility will repeat in future. But there could be a bias as it depends on the market conditions of

the particular sample period which was used for observing Volatility. While both the volatilities are

generally used as tools for option trading, there have been studies showing that Implied Volatility is

better at predicting the short-term future volatility. Spread between these two Volatilities is also

used as a trading cue. Such strategies are called Volatility arbitrage strategies, wherein the trader for

example buys options (straddles let’s say) at low Volatility and sells at high Volatility.

Following is a chart of Implied and Realised Volatilities of ICE Arabica Coffee Futures near month.

Figure1: Implied vs Realised Volatility Trend Chart of Coffee at ICE



This is an interesting example where the Implied Volatility for most part has been at par or lesser

than the Realised Volatility. That means the Option’s market price is less than the theoretical price

on such days and that the market participants perceived the future volatility to be lower than the

Realised Volatility. However a look at the trend over last 5 years tells us that the IV was largely at a

premium over RV during 2009-12.



Following is a snapshot of Implied v/s Realised Volatility trend in ICE RAW SUGAR near month

contract during the same period.



Volatility for Risk Management

Volatility is used for Risk Management – VaR computation, Derivative Pricing, hedging strategies and

in general for commodity procurement and sales decisions. Both Realised and Implied Volatilities are

used for Pricing, Hedging & Trade Strategies. For VaR Computation though, Realised Volatility is

generally used. In our next publication, we’ll analyse empirically if using Implied Volatility for VaR

brings additional benefits when compared to using the Realised Volatility. The idea is to check if we

can compute VaR considering the market’s perception of future Volatility. Some organizations use IV

for hedging decisions and for them, it will be important that the trading, hedging and risk

management decisions are all taken based on the same inputs.

About the Author: Santoshi Ippili

Santoshi has worked extensively in the Commodity Risk Management Domain for over 8 years and

has been instrumental in developing and implementing risk management software solutions for

several Fortune 2000 companies. She holds a post-graduate degree in Finance from BITS Pilani. At

RES, she is responsible for research and business analysis of the latest tools and techniques in Risk

Management and bringing them in a structured way into the product. She can be reached

on [email protected].

mailto:[email protected]



What is Risk Edge?

A Publication of

RiskEdge Software

An Integrated web-based Risk Analytics solution for managing Price /

Market Risks, with advanced Multi-Dimensional analysis capabilities

that can be customized to suit specific business requirements. It is

Easy-to-use, highly Configurable, and really Cost – Effective. It

automates Risk Processes and enables Deeper Business Insights.

More>>

Risk Consulting & Training

As part of our Risk Consulting practice, we work with clients to Define

and Implement their Risk Policy, with an aim to lower the Total Cost

of Risk (TCoR). Customized Risk Training programs help internal

people understand their role in risk management better. More>>

http://www.riskedgesolutions.com/risk-edge-software/

http://www.riskedgesolutions.com/risk-consulting/

http://www.riskedgesolutions.com/

Knowledge series implied and realized volatility

Economy & Finance

realised volatility

implied volatility iv

daily volatility

volatility estimates

low volatility

historical volatility

basics of volatility

volatility index