Tag: volatility

When you use the Black-Scholes-Merton (BSM) model, you end up with theoretical prices that assumes that volatility affects all strikes uniformly. i.e., strikes have no bearing on implied volatility (IV). This was largely true in the market as well until the crash of 1987. However, after the October 1987 crash, the implied volatility computed from option prices using the BSM model started differing between puts and calls. This is called “volatility smile“, or the smirk, given its actual shape.

The reason for this is quite simple, markets take the stairs up and the elevator down. Fat tails, if you must. So, put options sellers require a little bit of an incentive to take on that risk.

How crooked is the smirk? If you take the ratio of the IVs of OTM puts to OTM calls and plot them, you’ll notice that as you get farther away from spot, the distribution flattens out.

Notice the area below 1.0? Those are the days when the calls were trading at a higher IV than the puts.

Also, unlike the stylized charts of IV you might have seen with sweet smiles, the reality is quite different.

If this tickles your curiosity, do read The Risk-Reversal Premium, Hull and Sinclair (SSRN)

Code and charts on github.

Currently, Indian markets are open for 6.5 hours. During that time, global commodity markets are largely closed and overnight US futures markets are barely coming to life. This exposes positions carried forward to the next day to event risks. How is this risk priced?

Surprisingly, Close-Open (next-day) (CO) volatility is less than Open-Close (same-day) (OC) volatility. This doesn’t quite jive with the intuition about large overnight risks. This holds even if you include pre-pandemic data.

If you believe that overnight risks are larger than what the market perceives, then buying strangles at the close surprisingly doesn’t cost you much. A naïve strategy should breakeven after costs and occasionally, you might get lucky.

The unknown-unknown is scarier than the known-unknown. However, it is the known-unknown that you should be worried about more.

Realized Semi-variance is a measure of intraday volatility. It is nothing more than the sum of squared high-frequency positive and negative returns.

It is typically used for forecasting volatility. However, can it be used for market timing? After all, volatility is said to be sticky and avoiding downside volatility is supposed to be desirable.

What if, you exit the market when the current volatility is more than the historical average (based on some lookback)?

Turns out, doing something like that would’ve worked on the pre-pandemic NIFTY 50. Maybe not higher returns but better Sharpe than buy & hold.

However, post-pandemic returns have been disappointing.

The same thing can be observed on the MIDCAP 50 index as well.

We’ll add this to the growing pile of disappointing results of using volatility for directional bets.