Posts Tagged ‘OPTION TRADING’

VOLATILITY IN OPTION TRADING Final Part

Volatility Skew

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If we try to compute the volatility of an underlying by feeding in the required variables and the market prices of the options into the Black Scholes option pricing model, theoretically, options with same expiration date should have same implied volatility regardless of the strike prices we input.

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But in reality, the implied volatility we get across various strikes is different. This difference in volatilities across its respective strikes is known as volatility skew. When implied volatility is plotted against its respective strike price, the resulting graph can be a U-shaped or downward sloping.

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Volatility Smile, Reverse Skew, Forward Skew

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If the plotted graph is a U-shaped curve, as shown in Figure 1.1 below, this volatility skew pattern is also referred to as a volatility smile as it resembles a smile.

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The U-shaped volatility smile skew pattern is common for equity options which are near-term and options in the forex market. Volatility smile indicates that the demand is greater for options that are in-the-money or out-of-the-money.

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But, for longer term equity options and index options the reverse skew patterns are typical (Figure 1.2). In the reverse skew pattern, the implied volatility of options at the lower strikes is higher than the implied volatility at higher strikes.

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This reverse skew pattern implies that in-the money calls and out-of-the-money puts are more expensive and more in demand as compared to out-of-the-money calls and in-the-money puts.

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This pattern can arise in two cases; either, when the investors are worried about market falls, so they hedge their positions by buying puts for protection, or the other explanation can be, that in-the-money calls have become alternatives to outright stock purchases as they offer leverage and hence increased return on investment. In both cases greater demand is created for in-the-money calls and therefore it results in increased implied volatility at the lower strikes.

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As against reverse skew, forward skew is another type of the volatility smirk (Fig. 1.3), where, the implied volatility for options at the lower strikes is lower than the implied volatility at higher strikes.

In this case, the out-of-the-money calls and in the-money puts are in greater demand as compared to in-the-money calls and out-of-the money puts. The forward skew pattern is common for options in the commodities market where there can be a supply crunch, business houses would be ready to pay higher prices to secure supply than to risk supply disruption.

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Concluding, for option traders the best market direction assessment and option price evaluations can only be drawn by inter comparison of implied volatility with historical, current and forecasted volatilities, by assessing if they are over or under priced.

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This is the Volatility Smile of Nifty as on at the market closing of 11th June 2010. As mentioned above it is a typical long term index option, with the reverse skew pattern.

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VOLATILITY IN OPTION TRADING Part 1 :)

We calculate an option’s theoretical value by using option pricing models, two of the primary, well know models are the ‘Black-Scholes Model’ and the ‘Binomial Model’. To compute the value minimum five of the option and its underlying’s related variables are required to be fed in these models; these five necessary inputs are the option’s exercise price, the time remaining to expiration, the current price of the underlying, the risk free interest rate over the life of an option and the volatility of the underlying.

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Out of the above mentioned inputs, volatility plays an important role in actual trading situations. Volatility is a statistical measurement of the degree of fluctuation of a market or security. Volatility is computed as the annualized standard deviation of daily percentage price changes of the security and is expressed as a percentage. Changes in our assumptions and marketplace assessments about volatility can have significant effect on an option’s value.

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Though the option traders are affected by the direction of the market, they are extremely sensitive to the speed of the market. This speed of the market is measured through volatility. In low volatility markets, the market of the underlying fails to move at a sufficient speed, and therefore, the options on that underlying will have lesser probability to achieve the option’s exercise price or the strike price within its expiry. But in markets which move quickly or in other words, in high volatility markets the market of the underlying is likely to move at sufficient speed and accordingly options on that underlying will have greater probability to achieve the option’s exercise price within expiry.

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Every Option trader is well acquainted with three types of volatilities- Historical Volatility, Forecast Volatility and Implied Volatility (IV). Historical volatility measures how volatile the security has been in the past. We compute historical volatility over a defined historical period, which is usually a twenty day period as it approximates the number of trading days in a month. Forecast volatility is an attempt to forecast directional moves in the price of the underlying, i.e. future volatility; it is usually calculated using time-series methods.

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Finally, implied volatility of an option contract is the volatility implied by the market price of the option derived from an option pricing model. In other words, it is the volatility that, when fed in a particular pricing model, yields a theoretical value for the option equal to the current market price of that option. This means it is possible to have a unique implied volatility for each given market price of an option. This implied volatility is best regarded as a rescaling of option prices which makes doing comparisons between different strikes, expirations, and underlyings easier and more spontaneous.

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