Opinion: Kalshi’s American Power Index Is an Interesting Yet Flawed Concept
KPOW is a catchy abbreviation, I'll give them that.
In its latest attempt to demonstrate its relevance as a journalistic tool, Kalshi has introduced an American Power Index, which it abbreviates KPOW and says it hopes will become the “S&P 500 of politics.”
I have my doubts about that.
KPOW combines several of Kalshi’s most popular political prediction markets into one score representing future power. To that, it adds a separate score representing current power to arrive at a metric purportedly telling us which party has the upper hand. The future power metric incorporates markets on the next President, changes in control and seat numbers in the House and Senate, and the likelihood of government shutdowns.
Currently, that score is 2.5 points (out of a possible 50) in favor of Donald Trump’s Republicans. At the nadir of Iran War anxieties in late April, it got as far as 3.4 points in favor of Democrats. That’s an interesting way of measuring “power” when the November midterms are still six months out, and it’ll be at least two and a half years before we might see the next Democratic president.
Although the Standard & Poor reference suggests a stock market index, the “power” phrasing is a nod toward sports teams’ power rankings. Neither is really an apt analogy for politics, however. Stocks trade daily and a Week One NFL game matters exactly as much as one in Week Eighteen. Yet, in politics, actual power only depends on what people do on the day of an election. Measuring the ebb and flow of sentiment in the meantime is a worthwhile endeavor, but I’m not sure it makes sense to call it a “power” index.
Nomenclature aside, though, is KPOW a useful tool? It has potential as a concept, but also some questionable design choices that could limit its utility.
The Status Quo Baseline Doesn’t Add Much
The decision to account for both current and future situations in a single metric seems like the sort of decision that was made because it “feels” right. However, no one needs Kalshi to tell them who currently controls the House and Senate, or who the President is.
The advantage of doing it that way is that it avoids counterintuitive discontinuities in the aftermath of an election. Given that power tends to swing back and forth in American politics, a metric that only considers future potential will usually swing against whichever party just took power. Their advantage in that election would no longer count, as it is in the past. And they would be at a disadvantage in the next one due to being in the position of taking the blame for everything that happens until then.
But also, no one is likely to care about Kalshi’s markets or its power index in the immediate aftermath of an election. Where people are looking to prediction markets for insight is in the lead-up to one.
Meanwhile, there are more meaningful downsides to combining these two things. Firstly, how one weights current versus future power is somewhat arbitrary. Is one term equal to one term? Do we discount future power the way economists discount money? Do we prorate current power by the length of time left in the term?
Who is “winning” depends as much on those metric design choices as on world events.
Perhaps more importantly, it means the same score can describe qualitatively different situations. “Democrats +4.0” could mean they hold power but are in danger of losing it, or that they’re currently out of power but looking likely to sweep the next election. Do those situations produce policy outcomes that are similar enough to warrant treating them as quantitatively equivalent?
Changes in the Metric Are More Meaningful
That criticism doesn’t mean that there’s nothing useful being measured by Kalshi’s system, only that it’s a bit obfuscated. Kalshi’s political markets are legitimately useful for understanding future scenarios, arguably more so than polls. Aggregating them into a single metric is a worthy idea.
Indeed, the baseline barely matters, in that the absolute number conveys less insight than its change over time. Even if not mixed in with current power, “Democrats +4.0” on an arbitrary scale holds less meaning as a forecast than, say, their percentage chance of winning the House. The value of an aggregate metric is not in saying who is winning, but in looking at the impact of events in a holistic way.
Imagine, for instance, that a Senator for the ruling party encounters a scandal on the same day that favorable job numbers are released. The odds for control of the Senate drop slightly, while the President’s chances of re-election increase.
Reporting on those changes independently sends an ambivalent message. Conversely, saying that the party’s power index dropped by 1.5 points establishes that the damage of the scandal outweighs the benefits of the job numbers.
Liquidity Matters
Kalshi’s biggest challenge in making KPOW the gold standard of political analysis is ensuring that it remains similarly meaningful throughout the electoral cycle and not just on the eve of an election.
Prediction markets rely on the wisdom of crowds to generate forecasts, but the reliability of a crowd depends a lot on its size. Meanwhile, the platforms’ users are much more like sports bettors than investors when it comes to behavior and attention span. The bulk of the trading — and thus predictive power — on any market tends to come very close to its expected resolution date.
For instance, Kentucky’s high-profile primary between Thomas Massie and Ed Gallrein saw over $25 million in trading volume, but $18 million of that was on the day of the vote.
Kalshi does not appear to factor volume into its weighting, at least not very much. It does state that it uses a proprietary system to adjust markets’ weights based on their “salience,” but does not elaborate on what that means.
Similar Weights, Wildly Different Volumes
What we can say is that right now, the weight given to each of the markets is very similar, but their trading volumes vary widely.
| KPOW Weight | Trading Volume to Date | |
| Presidential race | 18% | $0.5M |
| Control of House | 16% | $13.7M |
| House Seats | 17% | $2.3M |
| Control of Senate | 16% | $5.0M |
| Senate Seats | 15% | $1.2M |
| Shutdowns This Year | 17% | $0.03M |
For instance, the number of shutdowns is currently considered more “salient” than who will win the House, yet Kalshi has 420 times more opinion data on the House race.
In other words, factoring in the difference in weighting, the opinion of a user betting on shutdowns is worth 445 times more than the opinion of a user betting on who will win the House.
Clearly, the weighting can’t be solely based on volume, either. The 2028 presidential election is an important consideration even two years out and with only half a million in trading. However, ignoring volume entirely means KPOW’s fluctuations may come to be dominated by volatility in low-participation markets, instead of reflecting consensus in those where Kalshi’s actual predictive power lies.
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