by Rajeeva L. Karandikar and Ajay Shah.
Financial markets and the Trump victory
Donald Trump’s election victory was an unpleasant surprise for the financial markets:
On equity index futures markets, the NASDAQ and S&P e-mini futures hit their price limits and for some time, effectively stopped trading. These are dangerous situations, for as is well known in the field of risk management, these `circuit breakers’ convert price risk into liquidity risk, which is in many ways a bad deal. When a market stops trading, all risk management stops.
Financial markets in the Indian general elections
On 17 May 2004, when the UPA won the election, this was quite unexpected; most people had expected five more years for the NDA. Nifty crashed dramatically and the risk management systems of financial market infrastructure institutions were tested like never before (or after). High frequency data for that episode is presently not available, hence we’re not able to look inside that day.
In 2009, the election result was a positive surprise, when the UPA made it across the finish line with a weakened CPI(M). We have decent data for this day, so here are some pictures. The market was ecstatic:
The turnover on the equity index derivatives market surged:
This reminds us how important trading on such days is to financial market participants, and to the managers of financial market infrastructure institutions. These were also turbulent times, with wide fluctuations of the spot-futures basis and violations of put-call parity on options markets.
Experiences in state level elections
In November 2015, the Bihar elections threw up a surprise. Till about 10am (two hours after counting started), most TV channels were reporting that BJP and allies are ahead of JDU-RJD. Only after about 11 am, a stable picture emerged.
The early hours of counting have been misleading many times. In the last UP elections (in 2012), till about noon (4 hours after counting started) it appeared that the SP would fall well short of the majority mark and BJP would do rather well. By 10 AM, NDTV and Times Now were projecting 180 seats for SP and 100 seats for BJP. There were celebrations at the BJP HQ. In the end SP got 225 seats and BJP 50.
Can elections overwhelm financial markets infrastructure?
Imagine if, on 15th May 2014, when the counting of votes for the Lok Sabha elections had begun, the early picture as reported on TV stations was very different from final outcome. Imagine if the early indicators were showing that we were headed towards a hung Parliament. The market would have crashed. Later in the day, when the full picture emerged, the market would have swung dramatically.
Even with state elections, sometimes, the stakes are very high. Consider the coming UP elections. The BJP won 73 of 80 seats from UP in 2014. The possibilities for the BJP in 2019 critically hinge on their being popular in UP. The market will thus be watching UP closely, interpreting it as a leading indicator about the 2019 general elections.
Why might early results diverge from the final answer?
Before 1999, when elections worked with pieces of paper, early trends were a statistically good predictor. The counting methodology was to first mix all the ballot papers, and divide them in 10-12 parts which would be counted, one at a time, over roughly two days. Each of these lots (which was called “a round”) was a large random sample of votes from each constituency. It is not surprising that early trends often prevailed. In 1998 and 1999, we (Rajeeva Karandikar and Yogendra Yadav) had done well by making predictions on Doordarshan about the national tally based on early counting trends.
Things have changed with the induction of Electronic Voting Machines (EVMs). They now take up one booth at a time, which is not random sampling.
Most TV channels get the counting data from one syndicated source. Viewers see the same message in numerous channels, and get lulled into the feeling that the answer is correct as it has come from multiple sources. However, this one source has had methodological problems. This is also introducing errors in the early trends.
This appears to have been at work in the surprises of the UP election in 2012. A similar situation prevailed on the counting day in Bihar 2016 elections, the difference being that on TV channel which was using its own reporters were able to report the correct picture early on.
The way forward
This article is a plea to participants in financial markets to use early trends more carefully. Wait till noon before believing what you are seeing.
Alternatively, the risk management system of clearinghouses may find it useful to have larger collateral for these few days. After all, the only day when the modern Indian financial market system was really stressed was 17 May 2004.
With EVM-based elections, the counting process is pretty rapid. Perhaps we are better off with a brief pause in trading from the start of counting to its end. The Election Commission, and the exchange institutions, should think about these possibilities.
Rajeeva L. Karandikar is Director at Chennai Mathematical Institute. Ajay Shah is a resarcher at the National Institute for Public Finance and Policy.