Charentz Hovnanian on Prediction Markets and the Fight for Edge

I first met Charentz Hovnanian back in high school.

Even then, he had a clear instinct for markets. Whether it was running a sneaker reselling business or going deep into trading strategies, he approached things with a level of curiosity and intensity that stood out early.

Since then, he has gone deeper than most.

From working in high-frequency trading within crypto and prediction markets, to now building his own company focused on turning real-world events into tradable financial instruments, he has developed a perspective that sits somewhere between trader, builder, and market theorist.

Prediction markets are often framed as betting platforms. Charentz sees something else entirely.

We sat down to talk about why most people misunderstand prediction markets, who actually makes money in them, and why the real opportunity is not trading, but building the infrastructure for institutions.

Q&A:

Q1: Prediction markets have been around for a long time. Why are they only becoming relevant now?

Prediction markets are a concept which have actually been around for quite some time: in 1945, Friedrich Hayek introduced the notion of how dispersed information transforms to price signals in “The Use of Knowledge in Society”. Robin Hanson expanded upon this idea with “Idea Futures” in 1992, outlining that creating derivatives which enable an event’s outcome to be the underlying instead of an equity or a commodity, for instance, allows us to tap into this dispersed information directly.

The first feasible renditions of the markets, however, came in the form of PredictIt, Augur, and most interestingly, a CIA prediction market which was torn apart by congress for proposing ‘terrorism markets’! The latter most likely failed because of the unhinged nature of some of these markets, but the former two failed because they didn’t make a sufficient attempt to get regulated, perhaps in fear of a similar outcome to that of the CIA.

Then, Kalshi and Polymarket came. To keep it brief, Kalshi sought regulatory approval in the form of a DCM before introducing their first ever prediction market, and Polymarket leveraged blockchain technology to propose prediction markets ‘on-chain’, meaning that the contracts were created via blockchain, settled on decentralized oracles, and that stablecoins would be used to enter contracts.

Q2: At a fundamental level, what is a prediction market, and why does it matter?

Simply put, a prediction market is a peer-to-peer contract in which two parties enter opposite sides of a given event. It’s often referred to as a binary option due to the payoff structure: either side of the party receives $1 for each contract they own if the event resolves in their direction, and $0 if the event resolves in the opposite direction.

The proponents of prediction markets make a couple of main arguments as to its importance in modern society. Firstly, it enables ‘skin in the game’ to display the likelihood of events: in a world with an abundance of misinformation, having thousands of people and institutions ‘put their money where their mouth is’ on the likelihood of events is considered the best way to discern truth from falsehoods. Best of all, it’s interpretable: anybody can open up Polymarket or Kalshi to observe the likelihood of certain events which may impact their lives.

Additionally, for the finance nerds out there, large institutions and corporations may use these instruments in order to hedge or speculate upon previously inaccessible events. This opens up a new orthogonal element which portfolios can obtain as well as more ‘risky’ innovation from large corporations as unnecessary risks and financial exposures to unwanted events can be adequately removed using these contracts.

Q3: The biggest debate in the space is whether prediction markets are just gambling. How do you think about that distinction?

A long-lasting question with deep implications for prediction markets has been whether or not prediction markets are gambling. A large reason this question exists is because Kalshi has had roughly 90% of its volume coming from sports contracts and has had access to a larger portion of the U.S. consumer base due its classification as a financial derivative as opposed to a gambling product. In response, U.S. sportsbooks such as Underdog and Fanatics have opened their own prediction markets so they can take advantage of this ‘classification loophole’. And, traditionally speaking, sports = gambling, right?

Personally, I don’t know. But if we want to try to find an answer, I think that it’s first necessary to define gambling. From my view, gambling is the act of engaging in a financial event where you’re expected to lose on average (negative EV). This interpretation would, by definition,

include 99% of sports bettors and casino goers. Most of these people only engage in these sorts of financial events because it’s recreational. More dangerously, you have gamblers: those who may think their actions may produce positive outcomes over time but in fact do not.

On the other hand, you have sophisticated players. Let’s call them ‘sharps’. These are the guys who know that they have edge on the market through diligent research and will abuse this edge as long as it exists. When sharps find the gamblers, they will eat them alive on average.

Seeing firsthand the sophistication of market making on prediction markets at my HFT internship, it became quite clear that a lot of individuals (apart from insider traders!) we were providing liquidity for were indeed either recreational gamblers, or gamblers who didn’t even know that they were gambling. We were the sharps.

“So story done, prediction markets = gambling right?” Not exactly.

By this definition, most retail traders and some institutions on financial markets would be gamblers. All entrepreneurs would technically be gamblers. And that just doesn’t sound right, does it?

The one thing that sportsbooks and casinos do is they monopolize the sharp. Their job is to ensure that a sharp is not only impossible to be their counterparty but that they are always, in fact, the sharp in any given financial engagement.

Prediction markets don’t do this. However, they don’t prevent individuals with negative expected value from interacting with their markets. That much is true. Sometimes, it may even be argued that they lure those types to their platform. This part I disagree with. But in my opinion, the notion that prediction markets are inherently gambling is inaccurate, as they don’t monopolize the sharp.

Q4: We’ve seen a wave of new “alternative” prediction markets recently. What’s actually interesting, and what is just noise?

Since the explosion of prediction markets in the summer of 2025, I’ve seen a subsequent chain reaction of ‘alt’ prediction markets emerging with a new spin on the asset class.

One of the most interesting I’ve seen is Melee: a prediction market where having early conviction in an event’s outcome is mechanically awarded by the exchange. This works via their innovation known as parimutuel markets: instead of a prediction contract being a match

between two counterparties as a central limit orderbook would do (practically all prediction markets match using this approach), parimutuel markets attempt to pool bets with weights being assigned of a participant’s share according to the recency of their bet, the maturity of the market along with other factors. Super nerdy, I know, but I think that this type of market has a bunch of potential for unlocking low-liquidity contracts and may potentially be an innovation which can carry into new, budding markets.

Another interesting market is called Noise, a market focused upon monitoring trends in social figures, activities, companies, and popularity as a whole. A super creative take upon the types of prediction markets which can exist.

Q5: You’ve been close to both trading and building in this space. What’s actually happening inside the builder landscape right now?

My main gripe with the builder landscape is the lack of originality in terms of what’s being built. I find that most people who are building within prediction markets at the moment have been trying to capitalize on the popularity of the asset class as opposed to unlocking the true value of the innovation.

Since I started following and working the space, I’ve seen way too many trading terminals, redundant analytics platforms, and prediction markets with no true moat.

With that being said, there are so many wonderful projects which have helped build the rails for prediction markets today: Dome API created a unified API for prediction markets with clear API docs, more data, and better built-in functionality, and as a result, they got acquired by Polymarket. Many such stories to come, as Polymarket and Kalshi can only do so much internally, and the notion of a prediction market entails a MASSIVE space of innovative things to do.

My advice is to tackle the ugly edges. Make a grand vision for what you think prediction markets can and should become, and build what’s necessary to push them to the finish line and make that happen. Be daring.

Q6: Where do you think the real opportunity lies in prediction markets over the next few years?

I think the largest opportunity for prediction markets, much like crypto, is institutional adoption, and currently, exchanges are flirting with this institutional usage, however, a couple of bottlenecks are planted as obstacles which prevent this phenomenon. Firstly, regulatory risks: since the idea of a prediction market is so new, compliance is skeptical, regulators worldwide are increasingly trying to suppress these markets, and financial institution C-suites don’t want to deploy large amounts of capital adopting these assets until the aforementioned risks are resolved. In addition to that, even if institutions wanted to use these products, liquidity serves as the largest constraint for this adoption.

In my mind, two things need to happen: a compromise between exchanges and regulators on what a prediction market should look like, and innovations on the liquidity side to make markets accessible to truly anyone and function similarly to other derivatives such as options and futures.

With that being said, anything you can build within this vein – risk models, margin systems, a ‘black-scholes’ for prediction contracts – will be immensely valuable in the years to come, and my belief is that building and owning the ‘machinery’ necessary for institutional adoption will trump any other opportunity in the space today.