Tag: options

Short Straddle

Introduction

While discussing the subject of the Long Straddle, we touched upon three things:

  1. Most of the obvious uncertainties are priced in. So you better have a unique point of view.
  2. Time is not your friend.
  3. The lack of liquidity means that you are forced to put this trade on closer to expiry and that is exactly the time when θ-decay is at its highest.

What if you invert the trade? This is exactly what the short straddle is made of. You can enter this trade soon after an widely anticipated event occurs and implied-volatility is at its highest.

Construction

This strategy consists of selling a call option and a put option with the same strike price and expiration.

NIFTY 6750 short straddle

The θ-decay now works for you. Sell ATM nearest-expiration options, collect the carry and laugh all the way to the bank, right?

NIFTY 6750 short straddle payoff
NIFTY 6750 short straddle pl

Not so fast! If the NIFTY breaks-out above 6836.50 or below 6663.50, then you are exposed to ∞ loss. It is up to you to figure out if the Rs. 4325.00 you are getting is enough compensation for insuring against the likelihood of that breakout.

Exiting the trade

Time is your friend and volatility is your enemy. When you sell insurance of this kind, you are exposed to external events that may not have anticipated and that occur outside of market hours. If you see volatility creep up, its best to exit this trade, even if at a loss.

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Long Straddle

Introduction

If you are sure that the underlying stock/index is going to move strongly before expiration, then this is the option strategy for you. The move can be in any direction, as long as its violent. For example, you might be expecting an important court ruling, the outcome of which will be either very good news or very bad news for the underlying.

Remember that most of the obvious uncertainties are priced in. So you better have a unique point of view.

Construction

This strategy consists of buying a call option and a put option with the same strike price and expiration, making it relatively expensive. The options are struck ATM (at-the-money.)

With the NIFTY trading at ~6780, you can either buy the 6750 straddle or the 6800 straddle. Let’s walk through each trade.

May Nifty 6750 long straddle

nifty 6750 long straddle

Note the θ (-742.73) on the ITM call. Its a lot of time-decay if you are wrong. The model says that the market prices are too disjointed from the model price. Besides, the break-evens are 6161.00 and 7339.00 which means that you have to be absolutely convinced that something big is going to happen.

nifty 6750 long straddle payoff
nifty 6750 long straddle p&l

May Nifty 6800 long straddle

nifty 6800 long straddle

The θ situation has improved somewhat and the break-evens – 6217.20 and 7382.80 – look better. The trade costs Rs.29,140/- to put on and that caps your max-loss.

nifty 6800 long straddle payoff
nifty 6800 long straddle pl

Exiting the trade

Time is not your friend here. You can either exit the trade right before the event occurs – when implied volatility is at its highest or soon after the event (irrespective of the magnitude of the movement.)

The lack of liquidity means that you are forced to put this trade on closer to expiry and that is exactly the time when θ-decay is at its highest.

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The most important assumption

Prices and Returns

Prices don’t follow a statistical distribution (they are not ‘stationary’.) There is no obvious mean price and it doesn’t make sense to talk about the standard deviation of the price. Working with such non-stationary timeseries is a hassle.

NIFTY 2005-2014

But returns, on the other hand, are distributed somewhat like a normal (Gaussian) distribution.

nifty-histogram

And there doesn’t seem to be any auto-correlation between consecutive returns.

nifty-autocorrelation

If returns are normally distributed, then how are prices distributed? It turns out that the logarithm of the price is normally distributed. Why? Because

returns(t) = log(price(t)/price(t-1))

Now statisticians can magically transform a random time-series (prices) into something that is normally distributed (returns) and work with that instead. Almost all asset pricing models that you will come across in literature has this basic assumption at heart.

Fat tails

The assumption that returns are normally distributed allow mathematically precise models to be constructed. However, they are not very accurate.

In the normal distribution, events that deviate from the mean by five or more standard deviations (“5-sigma events”) have lower probability, thus meaning that in the normal distribution rare events can happen but are likely to be more mild in comparison to fat-tailed distributions. On the other hand, fat-tailed distributions have “undefined sigma” (more technically, the variance is not bounded).

For example, the Black–Scholes model of option pricing is based on a normal distribution. If the distribution is actually a fat-tailed one, then the model will under-price options that are far out of the money, since a 5- or 7-sigma event is much more likely than the normal distribution would predict.

Precision vs Accuracy

When you build models, the precision that they provide may lull you into a false sense of security. You maybe able to compute risk right down to the 8th decimal point. However, it is important to remember that the assumptions on which these models are build don’t led themselves to accuracy. At best, these models are guides to good behavior, and nothing more.

accuracy vs precision

Sources:
Fat-tailed distribution

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Analysis: Bhavin Desai’s Bull Spread on ITC

Bhavin Desai of Motilal Oswal Securities was on CNBC saying that one may buy ITC 350 Call and advises shorting 360 Call. This is a 350/360 long call spread on ITC. Let’s see how the trade works.

The greeks

ITC Bull Spread Greeks

The 360 call has a θ of -145.36 and it the model premium is 3.04. This means that the time decay will make the option worthless in a couple of days. Not bad since you are an option seller.

The 350 call is already ITM (the stock closed at 352.70) and the last traded price, Rs. 6.3 is less than the model price of Rs. 7.49. Not a bad deal.

Payoff diagram at expiry

ITC Bull Spread P&L

ITC Bull Spread Breakevens

 
 
ITC needs to be above Rs. 354.35 at expiry for this trade to break-even. Max loss is the premium paid upfront (Rs. 4350)

The right trade for the wrong reasons?

The transcript on moneycontrol says:

ITC has had some amount of shorts right from the beginning of this expiry and since then it has not done anything and once again since yesterday’s trade we have been seeing some amount of long additions. So, a call spread or rather a bull call spread is something that can be advised.

We are not really sure what that means. The reason why you would put a bull spread on is if you are moderately bullish about the stock and want to mitigate the cost of buying the lower strike by selling a higher strike.

Reference

Buy ITC 350 Call, short 360 Call: Bhavin Desai

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Options Liquidity

Liquidity (or the lack thereof)

Open interest is a measure of liquidity of a particular market. For each buyer of a contract there must be a seller. From the time the buyer or seller opens the contract until the counter-party closes it, that contract is considered ‘open’. OI refers to the total number of derivative contracts that have not been settled.

Other than a few select indices and stocks, there is absolutely no liquidity in the option market. Here’s a chart of the latest total OI for the nearest (April) expiry:

OI April

And its worse for the next series:

OI May

Bid-offer spread

The problem with trading illiquid options is that the bid-offer spread ends up killing your trade. Compare and contrast the spreads for UNITECH and DABUR:

UNITECH APRIL

UNITECH MAY

DABUR APR

DABUR MAY

Don’t stop at trade setups

When you conceive option trades, make sure you consider liquidity constraints. Otherwise, your trade is likely to remain on paper.

The liquidity footprint is not static. For example, RCOM, which was #8 in Jan is nowhere to be found in the liquid dozen in April:

OI Jan

Monitoring liquidity risk is as important as checking your deltas and P&L and can often make or break a trade.

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