Texas elected a Democratic governor, and its stocks had a difficult week. From the market close on election day through Friday, the average Texas-based stock fell 5.8%. Stocks elsewhere in the United States fell 2.5%.
The difference is striking. But the more interesting finding comes from before the election. On days when political traders raised the probability of a Democratic victory, Texas stocks already tended to fall behind the rest of the market. That relationship provides a way to put the election-week loss in perspective.
An unexpected result
The Texas result surprised political traders. At the November 3 market close, before the result, Kalshi priced a Democratic governor at about a 38.5% probability. Democratic control of the House, by comparison, was already priced near 94%.
To examine the market response, I look at 3,460 U.S. companies, including 368 with a Texas business address in Compustat. I use daily stock returns obtained through WRDS and give each company the same weight.
On Wednesday, the first trading day after the election, Texas stocks fell about 1.4% while stocks elsewhere rose about 1.6%. Texas therefore lagged by roughly three percentage points in a single day.
How unusual was that? I calculated the daily performance gap between the two groups from May 1 through October 23. None of those 122 trading days produced a Texas shortfall as large as Wednesday’s.
By Friday, the cumulative gap had reached 3.3 percentage points.
EXHIBIT 1Texas stocks fell behind after the election
The industry mix explains part of the gap
Could Texas simply have suffered because it has more companies in hard-hit industries? To find out, I compare each Texas company with the average return of companies in the same GICS industry elsewhere in the United States. Averaging those differences equally across the 366 Texas companies with enough industry peers gives a Texas shortfall of 1.8 percentage points through Friday.
The response also varied across industries. The average Texas energy and industrial stock fell more than its counterpart elsewhere. Financials held up better. The average technology stock fell by almost the same amount inside and outside Texas.
EXHIBIT 2Texas’s losses were uneven across sectors
Governor-elect Gina Hinojosa proposed a moratorium on new data-center approvals until lawmakers adopted protections for residents, including local participation and union-labor requirements. Governor Abbott had already paused environmental permits and grid connections pending power and water reviews and called for developers to cover electrical infrastructure costs. The question for investors is how long the pause would last and what conditions new projects would face.
Construction delays can postpone developers’ revenue and equipment suppliers’ orders. Established technology businesses may be less exposed to individual Texas projects, though limits on expansion could still slow their growth. That distinction offers one possible explanation for why industrial stocks lagged while technology stocks performed similarly inside and outside Texas.
Stocks were moving with political odds before the vote
Could an investor have used the pre-election data to gauge how far Texas stocks might fall if the Democrat won?
For this comparison, I use 51 pre-election trading days on which the governor contract had traded within the preceding hour at the previous and current 4 p.m. Eastern closes. I compare the change in the Democratic candidate’s probability of winning with the Texas stock basket’s return relative to the rest of the country. This uses the original Texas-versus-rest gap, before the industry adjustment.
On those days, a ten-percentage-point increase in the probability of a Democratic victory was associated with about 0.62 percentage point of Texas stock underperformance.
EXHIBIT 3Political odds and the Texas stock gap
That relationship lets us construct a simple election scenario. A victory moves the outcome from a pre-result probability of approximately 38.5% to 100%, a surprise of 61.5 percentage points. Applying the pre-election relationship to that change gives an estimated Texas shortfall of 3.8 percentage points.
The actual Wednesday shortfall was about 3.0 points. The 3.8-point estimate is a scenario, not a precise forecast or proof that the election caused the entire move.
Prediction markets can help investors estimate more than who will win an election. Combined with stock returns, they can also help translate a possible political outcome into a portfolio-loss scenario before the result is known. Here, the scenario measures the loss relative to other U.S. stocks. The pre-election relationship produced a scenario close to the first-day Texas shortfall.
Applying the method to the next event
Consider the open contract on Texas enacting a data-center moratorium by December 2027. On November 9, its quoted price was 20–22 cents. Using 22% as an illustration, a yes outcome would raise the probability by 78 percentage points. A no outcome would lower it by 22 points.
For a useful stock-market scenario, an investor would first measure how an exposed portfolio has moved with changes in that particular contract’s odds. Applying that sensitivity to the potential change in odds would give an estimate of the portfolio’s response. Trading is currently too thin to make a reliable estimate for this contract.
The practical question is not simply whether a political event is likely. It is how much the portfolio could move if the outcome differs from what the market currently expects.