10/30/2024 | News release | Archived content
The long-awaited presidential election is about a week away, and market pundits have been busy focusing on what the results may mean for the markets. Since presidential elections can bring widespread changes to economic policy, regulations, and spending, the consensus is that the financial markets will react accordingly, and often significantly. That conclusion seems to be a matter of common sense. But is it true?
To measure the effect on the equity market, we reviewed historical S&P 500 returns (SPY) and implied volatilities (VIX) since 1996 for both election years and non-election years. We then compared average and median returns and changes in implied volatility during the few months before and after presidential elections (September 1 - November 5, and November 5 - December 31) to those of non-election years. In addition, we also reviewed the period 10 trading days before election day to see if the most intense period of the election cycle had any effect. The results are below:
Accepting the results at face value, election year returns beginning on September 1 are negative, whether on an average or median basis, and yet are positive for non-election years. Post-election returns are positive, albeit greater in non-election years. As one would expect, implied volatility tends to increase in the 10 days before election years and then decrease after the election has passed.
However, some skepticism is merited. As the bar charts below indicate, the comparison between election years and non-election years, whether in relation to return or implied volatility, is inconsistent and partially skewed by the extreme results recorded in 2008. The difference between average and median results reflects this.
What may we conclude from the above?
It is important to note that the analysis above concerns only the SPY index, not individual stocks, sectors, or asset classes that may benefit from an election outcome. The prevalence in recent weeks of various "Trump trades" could be notable exceptions to our conclusions.
Divya Patel assisted in the preparation of this article. Ms. Patel is a M.S. candidate in financial engineering at the NYU Tandon Scholl of Engineering.