Part 1: Fundamentals of Prediction Market Trading

Key Insights: Prediction markets are platforms to trade on the outcomes of future events. Traders buy contracts on a “Yes” or “No” outcome, which will pay 100 satoshis if correct or 0 if wrong. The contract’s price reflects the market’s perceived probability of the event occurring. Even with few participants, Glimpse’s automated market maker (the LS-LMSR model) continuously provides prices and liquidity so you can always buy or sell at some price.

Introduction to Prediction Markets

Prediction markets are online exchanges where people trade on future events. Each market poses a binary “yes or no” question with a resolution date (e.g., “Will X happen by Y date?”). The trading instrument is an event contract with a fixed payoff value (100 sats on Glimpse). Traders can buy a “Yes” position if they think the event will happen, or a “No” position if not. When the outcome is decided, contracts pay out 100 satoshis to correct predictions and 0 to incorrect ones. For example, if you buy 1 contract predicting gold outperforms Bitcoin and you are correct, then you receive 100 sats; if you’re wrong, you get nothing (losing the cost you paid for the contract). This binary payoff structure is simple – you either win a fixed amount or lose the cost which you paid.

How Event Contracts Work (0 or 100 sats)

An event contract is essentially all-or-nothing. Event contracts have a nominal value (100 sats on Glimpse) that is paid out in full if the outcome occurs, or pays zero if the outcome does not occur. The market price of the contract (some number of satoshis between 0 and 100) represents the cost to buy that contract. This price can be interpreted as the implied probability of the event happening. For instance, if a contract is trading at 25 sats, that implies roughly a 25% chance of the event happening (since 25/100 = 0.25, or 25%). If you purchase such a “Yes” contract at 25 sats and the event indeed occurs, you’d receive 100 sats at settlement – netting a profit of 75 sats (100 payoff minus 25 cost). If the event fails to occur, your contract expires worthless (0 sats) and you lose the 25 sats you paid. In summary: you pay the current market price to buy a prediction contract, and you either lose that entire stake or win the full 100 sats depending on the outcome.

This payoff mechanic ensures limited risk – you can never lose more than the price you paid for the contract. Glimpse further enforces this by requiring that users cannot lose more than their chosen risk limit (Bankroll Limit). There are no margin calls or debt; the worst case is losing your initial purchase amount on an incorrect prediction.

Understanding Market Probabilities

Prediction market prices correspond to probabilities. A contract’s price (in sats) divided by 100 is the market’s collective belief that the event will happen. If a contract trades around 50 sats, the market is effectively saying “we think there’s a 50% chance of this outcome.” A higher price (e.g. 80 sats) indicates the crowd thinks the event is very likely (~80%), whereas a low price (e.g. 10 sats) suggests the event is seen as unlikely (~10% chance). This interpretation allows you to read the market’s mind: the price synthesizes all traders’ information and opinions into an implied probability.

Crucially, as new information comes in or traders update their views, prices will move. If favorable news about an outcome breaks, buyers will drive up the price, indicating a higher perceived probability. Conversely, if something makes the outcome seem less likely, selling pressure will push the price down. Over time, prediction markets tend to be efficient at aggregating information, often surpassing polls or expert forecasts in accuracy. However, they are not infallible – mispricings can occur, which skilled traders can attempt to exploit (see Part 2 on finding positive expected value).

How to Interpret Prices as Crowd Beliefs

Because prices map to probabilities, you can think of a market price as the “crowd’s prediction”. It’s a real-time consensus of everyone’s expectations. For example, if a presidential election market has the incumbent’s contract at 60 sats, that implies roughly a 60% chance of the incumbent winning. This doesn’t mean the crowd is always right, but it’s the aggregated wisdom (and money) of all participants at that moment. If you disagree with the implied probability, that’s your opportunity – you might believe the true odds are higher or lower than the market says.

Suppose the market price is 50 sats (50% implied probability), but you are confident the event has a 70% chance. This is an opportunity to capture positive expected value. Your belief is that the contract is underpriced relative to is true probability. If you’re right and the true probability is higher, the price should rise over time toward 70, or you’ll win at settlement more often than the market suggests. Consistently finding such discrepancies is key to profitable trading.

Conversely, if a contract is priced at 80 sats (80% probability) but you believe the real chance is only 60%, the contract is overpriced. In this case, the smart move is to take the opposite side, which is the underpriced belief. On Glimpse, this can be done by buying the “No” side. If you are right that the event is less likely than the market thinks, you profit when the price falls or if the outcome indeed fails to occur.

In summary, market prices represent crowd consensus, but not gospel truth. Sharp traders will compare their own estimated probability to the market’s and look for edges. A price far from what you believe suggests an opportunity – either the crowd knows something you don’t (so research why), or you have an insight others haven’t acted on.

Role of the LS-LMSR Automated Market Maker (AMM)

Glimpse uses an automated algorithm to provide continuous prices and liquidity, known as the Liquidity-Sensitive Logarithmic Market Scoring Rule (LS-LMSR). This sounds complex, but the key idea is straightforward: there is always an available price to trade, even if no other person is on the opposite side. The AMM is your counterparty when needed. If you want to buy a contract, the LS-LMSR will sell it to you from the platform’s inventory, and vice versa for selling.

In a traditional order-book market, you need another trader to take the other side of your trade. But with a market maker like LS-LMSR, the platform’s smart pricing algorithm continuously updates odds based on trade volume. When you buy contracts, the price automatically ticks up; when you sell, the price ticks down. The size of the price move depends on the trade size and how much liquidity is already in the market. Early trades in a new market (with little money on either side) can move the price a lot, whereas in a heavily traded market, the same trade size will move the price less. This is what “liquidity-sensitive” means – the pricing adapts to the market’s depth. As more traders participate and more capital flows in, the market becomes deeper (more liquidity), and the LS-LMSR algorithm “adapts as real traders enter, solving the classic ‘thin market’ problem”. In other words, it starts out easy to move the odds with small trades (encouraging people to seed new markets), but as the market grows, it stabilizes.

One advantage of the LS-LMSR is that it guarantees continuous prices and liquidity, even with few traders active. You’ll never see a situation where you “can’t trade” due to lack of counterparties – the AMM is always there to quote a price. Additionally, LS-LMSR limits risk for the platform; it has a built-in parameter to prevent unlimited losses. The “liquidity-sensitive” upgrade over a basic LMSR means that the market maker’s pricing becomes more conservative (harder to move) as the market’s volume grows, thereby reducing excessive volatility once a lot of money is committed. The end result is an efficient, always-open market: traders can enter or exit positions at will, and prices update smoothly to reflect the balance of opinion.

(Technical note: LS-LMSR was introduced by researchers Othman et al. in 2013 as an improvement to Robin Hanson’s LMSR. It dynamically adjusts the core pricing parameter based on outstanding event contracts, thereby “bootstrapping” liquidity. For the ordinary customer, these math details aren’t needed – just know the AMM keeps markets running fairly and prices update based on market demand for the respective event contracts.)

As an example, we can go over the lifecycle of a market on Glimpse with no prior trades. Initially, the AMM might start the price at a neutral 50 sats = 50% probability. If you buy 100 “Yes” contracts, the LS-LMSR will raise the price by some amount (say to 60 sats) to reflect the increased demand/belief in “Yes.” If another trader then buys more, the price goes up further. The more contracts already bought (i.e., the more liquidity in the market), the less each additional purchase will shift the odds. This mechanism encourages early trading (you get better prices when the market is thin) and ensures that as markets mature, the odds become more stable and harder to sway by any single trade. The LS-LMSR essentially acts as an unbiased thermometer or balance scale which adjusts the odds whenever someone trades.

Quick Recap (Fundamentals)

• Prediction markets = trading on event outcomes. Contracts pay 100 sats if correct, 0 if wrong. Price reflects probability.

• Binary contracts limit risk. You can only lose what you paid for the contract; no further liability.

• Market price = implied probability. Treat the price in sats as the crowd’s % confidence. Use it to gauge sentiment or identify mispriced opportunities.

• LS-LMSR AMM provides liquidity. Glimpse’s markets always have a price and can’t “freeze up” – the algorithm continuously buys/sells to users and updates odds. Early trades can move the price more, while later trades face deeper liquidity.

• Interpreting price moves. Rising prices mean the market thinks the event is more likely (increased probability), falling prices mean lowered expectations. You can enter or exit positions based on these movements (e.g., sell for a profit if price moves in your favor before event resolution).

By grasping these fundamentals, you’ll understand how Glimpse’s platform works at its core. Next, we’ll build on this with probability and risk concepts to help you trade wisely within these markets.