Is It Insider Trading?
A continuation of our prediction markets series
A prediction market is already a derivatives market. Thus goes the claim we have made thus far: it does not “become” economically serious when it adds layers — it is economically serious from the moment two parties price a future outcome and stake capital on it. A prediction contract belongs to the same economic family as futures, options, and insurance: It is a tradable claim on a contingent event. The so-called “wager” is not a downgrade; it is the oldest financial instrument in existence, a social act: putting something at risk to settle uncertainty. Long before equity markets industrialized risk, two individuals could bet on a harvest, an election, or the weather. Modern finance did not invent this logic. It standardized it.
What derivative depth does is not rescue prediction markets from triviality, but reveal their true lineage. Once contracts can be layered, hedged, recombined, and traded across time, it becomes obvious that a prediction token is no more “gambling” than a stock option is gambling. Both are priced exposures to future states of the world. Both abstract uncertainty into tradable structure. Both rely on disagreement expressed through capital rather than rhetoric. The difference between them is largely aesthetic, with a faint trace of cultural memory attached to the word wager. Prediction markets do not aspire to become like traditional conventional capital markets that act as engines of credible price discovery and economic organization. They already are such markets. And their quality of open wagering only underscores that fact, if only because it strips the mechanism down to its oldest and most intelligible form: two sides pricing uncertainty by standing behind their convictions with capital.
But the ambition to build a fully fledged venue for pricing the future, not a novelty platform, but a financial core in its own right, carries a consequence. The moment a market becomes deep enough to resemble modern finance, it inherits modern finance’s central anxiety: informational asymmetry. Who knows what, when? What happens when they trade on it? And does that activity undermine the integrity of the venue itself?
Here is the situation. Insider trading exists in all (all) markets where information can be distributed unevenly. Let’s not pretend that insider trading can be abolished. No mature market makes that claim. Insider trading is not an anomaly; it is a byproduct of the simple fact that the future is unevenly distributed. If markets price outcomes before they occur, then those who know something earlier will attempt to monetize that knowledge. If ergo it can be and usually is present in virtually all markets, including prediction markets, this unexceptional matter must be addressed not by decrying the platform (nor the platform sow doubts as to whether insiders exist) but by analyzing to what degree the presence of insiders destabilizes the market itself. The question is not whether insiders exist. The question is whether insider knowledge becomes structurally dominant — whether it can reliably steer price formation in a way that collapses trust in the mechanism.
This distinction is not rhetorical. In mature financial systems, insider activity is understood as a participant-level problem, not a market-level failure. For a useful reference point, let’s take NASDAQ. Insider trading is illegal and policed there, but it is not blamed on the exchange because its effects are diluted by scale. The exchange itself is not treated as invalidated by the mere possibility of informational advantage. The reason is scale and structure. With thousands of assets, continuous trading, overlapping strategies, and deep liquidity, no single piece of information can reliably dominate price formation. In sufficiently deep markets, informational edges must compete through price against liquidity, overlapping instruments, time horizons, and arbitrage. Informational advantages exist, but they are absorbed by market breadth rather than attributed to the venue. The existence of asymmetry does not automatically imply systemic fragility. If anything, it implies competition, and the willingness some people have to cheat.
Sadly, prediction markets today mostly do not enjoy that structural insulation. Thin, binary, event-isolated contracts are uniquely sensitive to early information. In such environments, “knowing first” can look like controlling the market. That vulnerability is precisely what critics circle when they equate prediction markets with gambling venues. It is not that prediction markets inherently function as houses, but that market thinness amplifies the financial edge of anyone holding tomorrow’s news today. When liquidity is shallow and instruments singular, informational advantage appears absolute. In other words: when one party knows the outcome in advance and the other does not, the trade is no longer a contest of judgment but a near-certain transfer of capital.
A decentralized prediction market can only offer similar comfort to traders as those they enjoy on NASDAQ if it achieves comparable structural conditions to those on markets which are numerous, overlapping, and liquid; where private information is forced to compete through price rather than the “suckerification” of the opposing end of a wager. In such an environment, confidence shifts away from trust in an operator and toward trust in the market’s structure and depth.
This does not happen automatically. It must be designed. Market creation must be cheap and permissionless so information disperses across many contracts instead of concentrating in a few bottlenecks. Liquidity must be reusable across markets, and access to data, execution, and settlement must be uniform, so advantages are expressed competitively rather than structurally.
Here is how we address this now: Dex.Do’s designed alteration to this entire dynamic is not one only of moral appeal (though we try), nor do we see regulators having much success in fighting this phenomenon (though all such efforts are welcome)—no, the response to insider risk cannot assume universal or institutional virtue. Rather, the challenge here is to engineer market conditions under which informational edges must express themselves competitively rather than definitively.
The first line of defense on Dex.Do is designed to prevent an insider from shaping the market simply by showing their hand early and pushing others to follow. Each event begins in a Pari-Mutuel Pool where participants stake funds and receive outcome tokens in proportion to their contribution, with no fees and no visible order book. Because there are no public bids or offers, early positions do not broadcast intent or invite imitation. When this phase closes, the token split is fixed. From then on, no one can mint just one side; new capital must mint both sides in the established ratio, and redemption requires returning that same ratio. This ensures that any informational edge must play out through open trading rather than through restricting supply at the outset.
That trading layer is not a conventional transparent order book…
This is a Dark Order Dex.
No open positions are broadcast. No intent leaks before execution. No size is revealed in advance. Finality precedes disclosure. This is not a cosmetic feature; it is an anti-extraction mechanism. Transparent decentralized venues have historically converted order flow into an asset in itself, enabling front-running, sandwiching, and behavioral inference. When traders primarily react to other traders rather than to underlying events, markets devolve into reflexivity. This prevents insiders or large traders from turning visibility itself into an advantage. On a dark, decentralized order book, orders are not shown before they are executed, so trades reveal only that a transaction happened, not who placed it, how large their position is, or what strategy they are running. This means an informed trader cannot spark a rush simply by signaling conviction to others. Any edge they have must be expressed through price, not through spectacle.
Let’s not reject the “all trades add information” principle that is often used as a defense by traditional prediction markets. Let’s instead narrow its scope, as is done on Dex.Do, where dark execution preserves the informational value of trades by suppressing meta-signals that cause belief-about-belief loops. In other words, on Dex.Do trades are informative about outcomes, not about who traded. This doesn’t reduce information in the market; it reduces noise masquerading as information. The more precise claim then becomes: “All trades add information when the market structure prevents traders from trading primarily on other traders.” It’s a mouthful, so we will stick to: “Trade in the dark, trade in reality.” It’s worth noting that, while darkness reduces pre-trade information leakage, it does not remove all informational advantage. Our point is: the market must abstract this advantage through mechanisms that remove, as much as possible, any destabilizing effect on the market.
Regular investment market exchanges like NASDAQ have recently been trying quite hard to curb the advantages that big hedge funds can gain through the use of high frequency trading and dark pool market making. Dex.Do, on the other hand, extends those advantages to any and every user on the platform. If a market becomes too lopsided in the benefits offered to institutions, regular investors avoid participating. Our description of asymmetric access on traditional and centralized prediction platforms stands in as far as it is unarguably true that privileged connectivity, tooling, and operational latitude do systematically advantage professional market makers. Even most prediction market platforms have back-end trading interfaces with a range of features that are not available to regular users—broad-market data, low latency connectivity, bulk order management, drop copy, and IP whitelisting. On Dex.Do all of these features can be available to all users of the platform. It is built on open source code, with its interfaces being built directly by developers in the community, meaning there can be many varieties of interfaces, with everything from different designs to different features. Users will be able to select which interface to use, with no single party able to offer preferential treatment to one or another. There is no such thing as an ‘institutional partner’ on Dex.Do. No such thing as asking a platform if you can access a feature. Eliminating as many structural differences between a ‘regular’ and institutional investors should be the aim: and we believe that empowering individuals is far more important than curbing groups. This is very much at odds with what most current (centralized) prediction markets have been doing of late, as they now offer the perfect environment for sophisticated market makers to profit off regular traders. But the very absence of a single point of control, censorship, and preference means that ontologically speaking, there is no difference between a maker, a taker; a wager of one opinion against another; in other words, those inclined to using tricks against fools, as well as those who could be fooled unjustly, will instead have a fair level-playing field on which to trade, meaning the prediction market itself resumes being true to its name anew.
Another structural dimension: speech.
Designed to prevent people from shaping the market through commentary while having nothing at stake, on DexPress, anyone who publishes has to take a clear position and back it with a live market exposure. Influence must be tied to financial risk. An insider can still trade quietly, but they cannot publicly steer opinion without showing that they stand to gain or lose from being right, changing the incentives for those who hold valuable information: they can keep it private and trade in a thinner market, or they can disclose it to attract more participation in a market where they already hold a position. And unlike on social media, where information can be released for attention alone, here disclosure can increase liquidity and improve trading conditions while the author remains exposed. Speech and position are linked. Being wrong carries an ongoing financial cost, and lying just ensures reputational damage. Over time, visibility accrues to those who maintain positions rather than those who make loud, short-lived claims. The system does not eliminate insider trading, but it reduces the benefit of influence without exposure and shifts the advantage toward sustained, accountable conviction.
But the most consequential safeguard…
Is derivative depth itself. The way to reduce the impact of insider trading over time is not to suppress information, but to expand the number of ways it can be traded. Tokens created in the opening phase become tradable assets. Markets can be structured around more than simple yes-or-no outcomes. Additional contracts can be built on top of base positions. Events can be broken into stages or overlapping timelines, spreading exposure across time instead of concentrating it in one final moment. In that setting, the edge shifts away from simply knowing something early and toward managing positions well: sizing risk properly, hedging across related markets, and providing liquidity. Private information still matters, but it competes with strategy.
In simple terms, thin binary markets make single pieces of news extremely powerful because there is only one direct way to express a view. Deeper markets create multiple ways to express and manage exposure. Positions can be split, combined, or offset. As the number of possible strategies grows, the value of any single informational advantage shrinks. The rule is: it cannot depend on morality, it must depend on market design.
What, then, of “NASDAQ-style safeguards”? Surveillance, audit trails, reporting windows, enforcement regimes: these are institutional instruments. Dex.Do is not an operator with discretionary authority. It cannot summon traders for questioning or freeze accounts by fiat. But the spirit of those safeguards can be translated into protocol-compatible equivalents.
A further difference is that, on legacy venues, the exchange itself is an information source. Traders do not only trade on “tomorrow’s news,” they trade on the venue’s next move: listing decisions, halts, rule changes, enforcement priorities, the quiet timing advantages of those who sit closer to the pipes. That is a real category of edge, and it is structurally unavailable when the venue is a protocol that does not speak, cannot selectively intervene, and cannot grant “special handling.” In that sense, one of the most underrated safeguards here is simply that the market cannot become an insider in its own market.
The objective is not to replicate regulatory bureaucracy on-chain, nor can any market eliminate private information. Dex.Do does not claim to. What it claims is narrower and more defensible. Insider knowledge, in isolation, should be insufficient to dominate price formation over time. For that to hold, what must happen is: the market must grow broad and liquid enough that no single trade can set the tone, contracts must overlap enough that information disperses across multiple ways to express it, and the rules of creation, trading, and settlement must remain fixed and legible so that advantage comes from competing inside the market rather than gaming the venue. When those conditions are satisfied, the market ceases to be a stage for informational spectacle and becomes what it was always meant to be: a competitive arena for pricing uncertainty. Insider trading remains possible. But it is diluted by scale, fragmented by structure, and forced to compete in the open logic of price rather than in the shadows of privilege.
Let us also be explicit and remember: removing platform-granted advantages does not flatten the world. Strategy, capital, and private infrastructure will still separate participants, and no design can make everyone equally skilled. What design can do is refuse to add unfairness on top of those inevitable differences, by ensuring that access, execution, and market rights are not distributed by the venue. That same move matters for insider risk as much as it matters for “retail” versus “institutional” actors: when the market cannot privilege certain pipes or signal order flow in ways that only some can read, informational edges are pushed into the only place they can legitimately exist — price. And if the system also makes room for pure speculation, it is not indulging frivolity; it is inviting liquidity, and liquidity is precisely what turns any single informational advantage from a dominating force into one competing input among many, which is the condition under which derivative markets create wealth rather than collapse into extraction.
When information is not forced through a single bottleneck contract with one moment of maximum sensitivity, even if there is one canonical market per discrete event; when the event can still be traded through related contracts that lead, lag, slice, or condition the outcome (i.e. intermediate milestones, ranges, timelines, and price-at-time instruments); when that happens, it disperses informational advantage across instruments and time, and it lets other participants respond by adjusting exposure rather than being trapped in an all-or-nothing bet. Shared collateral then matters because it increases usable liquidity: capital is not stranded in isolated positions, so traders can hedge and re-balance without having to “exit the whole system” to free funds. This structure does not need to identify insiders to reduce their dominance; it just needs to make it costly for any single informational edge to become the only thing that moves the market.
It’s worth stating the criticism as plainly as possible, because it is widely repeated: that prediction markets are plagued by issues of insider trading and manipulation. And the risks are described as real and growing in the legal commentary now tracking the space. A lot of the public case against prediction markets collapses into a single claim: they are uniquely exposed to insider trading, because the thing being traded is “the news” itself. Commentators point to the most obvious scenarios: a government employee with advanced knowledge of an action, a corporate insider who knows tomorrow’s numbers, or anyone close to a decision with a clean yes/no settlement. In thin contracts, that informational lead can turn into a near riskless profit against uninformed counterparties, which then reads less like “forecasting” and more like extraction. That is why mainstream coverage keeps pairing the sector’s growth with repeated warnings about insider trading and manipulation, and why recent reporting has highlighted exactly this kind of misuse.
The Dex.Do answer is not to deny the problem, and not to play the fantasy that you can force truth out of people. It is to do what almost no other prediction market can honestly boast of. Dex.Do removes the structural channels that turn private knowledge into guaranteed extraction. Dex.Do expands each event into a tradable surface, not a single choke point; it keeps capital reusable instead of trapping it in isolated bets; and it makes the venue incapable of quietly granting better access, better tools, or better execution to anyone. Under those conditions, inside information can theoretically still be monetized, but it is priced into a competitive market, not converted into a standing advantage that repeatedly transfers value from everyone else. In this regard, Dex.Do, built to be trustless, is just like any other trusted traditional market.