by Susan Thomas.
At 12:15 in the afternoon on 29 September, the Indian government said that `surgical strikes’ had been conducted in Pakistan-occupied-Kashmir in the early morning of 29 September. The graph above spans across the previous and the next trading days also, i.e. it runs from the start of trading on 28th to the close of trading on 30th.
There was a close-to-open positive jump from 28th close to 29th open. There is no hint that news had leaked, ahead of time. Nifty and the near month futures fell sharply the moment this news came out. It looks like by late 30th the market had digested the information and was more calm.
The best measure of overall equity market liquidity in India is the `impact cost’ faced when doing a portfolio trade on Nifty. We use the transaction size of Rs.5 million. In peacetime, the impact cost is very small, of around half a basis point. This tripled after the news was revealed at 12:15. By late 30th, we were back to the very low impact cost values of early 29th.
What about traded volume?
The blue dots are turnover on the Nifty futures and the gray dots are turnover on the ATM Nifty options. Turnover for the options jumped on 29th, once the news came out, but this was not the case with the futures. Futures turnover along with options turnover was enhanced on 30th. We don’t know why the futures turnover slumbered on 29th but not on the 30th.
Turnover was also very large on the morning of 30th. People seem to have slept over the news of 29th and come back with views on the 30th. This may partly reflect the slow decision processes of institutional investors, particularly foreign institutional investors.
Here, even by late 30th, the market had not found its pre-announcement levels.
We now turn to measures of deviation from no-arbitrage on the Nifty futures market. When very large turnover takes place, this can stress the limited capital of rational arbitrageurs.
It’s interesting to focus inside the 29th. There is a small violation of no-arbitrage and the basis was fluctuating to a modest extent. When the news broke, the violations got bigger and basis variability went up. This suggests there are `limits of arbitrage’ : there is not enough capital and not enough algorithmic trading to hold the futures price at the rational value in the aftermath of a news shock like the surgical strike.
Similar issues are visible in the deviation from put-call parity on the Nifty options market.
Put call parity holds quite well before 12:15. Once the news breaks, the volatility of the pricing error goes up, and large errors are visible in absolute terms. It’s interesting to see that with both the Nifty futures and the Nifty options, the largest pricing errors are found at the end of 30th.
The picture seems to be one where there was a huge surge in futures and options turnover, and during this process of price discovery, the garbage collectors of the market (the arbitrageurs) were a bit overwhelmed.
What about the USD/INR exchange rate?
The spot market for USD/INR trades 24 hours a day. That’s the blue line above. The gray line is the USD/INR futures contract at NSE, which only trades for limited hours of the day. We see that there was a bit of a depreciation in this market even before 12:15 and it went further on 29th and also on the 30th. The futures in particular moved more.
What happened to the turnover?
We see an enormous surge in turnover on the ATM options after 12:15. The extent of this surge is much bigger than that seen with Nifty. With Nifty, turnover went up by a factor of 5x. Here, options turnover seems to have gone up by 10x. It’s striking how almost nothing happened with the futures. The market seems to be using ATM options as a way to express views on USD/INR and not USD/INR futures.
With the Nifty futures and options, 30th was a very active day. With USD/INR, the market slumbered on 30th.
Finally, we look at violations of no-arbitrage on the USD/INR futures.
As with the Nifty futures, basis vol goes up after 12:15, the violations are larger in magnitude, and the ill effects are visible all the way to the end of 30th.
The author is at the Finance Research Group in the Indira Gandhi Institute for Development Research.