Expiry day swings in OTM options: Hunter algos may be triggering stop-losses, say players

Stop-loss hunting is a fairly known concept in financial markets. The strategy, usually deployed by large institutions or algorithmic traders, involves driving prices to a certain level which then triggers stop-loss orders and results in a torrent of selling or buying activity.

Derivatives traders say this is not a foolproof strategy and need not always result in profits. That is because after driving prices higher or lower, the position needs to be squared off quickly and profitably. And that will depend on multiple factors, liquidity being the most important. Whether or not the hunter makes money, the sudden move can easily burn the pockets of traders whose stop losses get triggered because of the sudden wave of buying or selling.

So far it is options writers, many of them amateur traders, who have been at the receiving end of such stop loss hunting algos.

The mechanism

So, how does a stop-loss hunting algo work?

Assume a group of traders have sold (or written) OTM options on an index on expiry day. These options will be priced cheap, say Rs 0.5, because the strike price is far away from the spot price of the index. The options writers are betting that the contracts will expire worthless and they will get to keep the money collected as premium.

At the same time, they would also have entered a stop-loss limit for their trade, just in case the price of the option was to shoot up suddenly. Assume most of the traders put in a stop-loss limit between Rs 4 and Rs 5. This means if these price points are crossed, the option sellers have to square up their positions.

Enter the hunter algo, which will analyse the order book containing the list of buy and sell orders at different price levels. It will deduce the potential stop-loss levels based on the concentration of orders. Having spotted them, the algo will execute a series of buy orders that pushes the price of the OTM contract beyond the stop loss levels. Once the stop-loss gets triggered, option sellers who sold the contract at Rs 0.5 will scramble to square up their positions, driving prices even higher. There have been instances where OTM options have jumped 10-20 times on expiry day.

Since OTM strikes lack liquidity beyond a certain price point, a hunter algo can force the option sellers to cover at a much higher price. Once the positions are squared off, the price of the option price returns to the price at which it should be trading. All this happens in a matter of a few seconds. During this time, the underlying index has not moved at all.

Price bands

Unlike stocks, options prices do not have fixed intra-day price bands. The price bands for options are calculated dynamically. That is because movement in option premiums depends on the price changes in the underlying, and the move is never linear. The way options are priced involves complicated math. There are many factors at play, such as the time-to-expiry and traders’ perception of future prices. A 1 percent move in the underlying can trigger a 100 percent move in the option premium.

Free lunch no more

The recent emergence of these hunter algos has made life difficult for a lot of amateur option sellers who were so far accustomed to making small profits consistently on expiry days by writing OTM options.

“There was easy money for many novice traders for far too long,” said a derivatives trader who did not want to be named. “Many people used to brag that they would sell OTM options in the morning on expiry day before heading to work, and then collect their profit at the end of the day. That has suddenly become a dangerous strategy.”

Many amateur traders feel that a stop loss is a sufficient safeguard against sharp adverse price movements. But seasoned traders warn that stop-loss orders will get filled only if there is sufficient liquidity in those contracts. If not, the positions will have to be squared off at much higher (or lower) prices.