Key Concepts

Key Concepts

This glossary provides definitions for the key terms and concepts used on the Zeitgeist platform. Understanding these terms is essential for navigating the markets, providing liquidity, and participating in governance.

Narratives:

Narratives are the evolving stories, discussions, and trends that shape public opinion and influence real-world events. They are often driven by social media, news, and online conversations. Zeitgeist identifies and tracks these narratives, using them as the basis for its prediction markets. Examples include: "The future of electric vehicles," "The rise of AI in healthcare," or "The next major social media trend."

Narrative Markets:

Narrative markets are exchange-traded markets where users can buy and sell contracts that pay out based on the outcome of future events. The prices of these contracts reflect the market's collective belief about the probability of each outcome. They are a powerful tool for aggregating information and forecasting future events.

YES/NO Shares:

Zeitgeist prediction markets are primarily based on binary outcomes: YES or NO. Users buy and sell shares representing these outcomes.

• YES Share: A contract that pays out $1 if the event occurs (the outcome is YES) and $0 if it does not.

• NO Share: A contract that pays out $1 if the event does not occur (the outcome is NO) and $0 if it does. The prices of YES and NO shares always add up to $1 (before fees).

Liquidity Provision:

Liquidity providers (LPs) are users who supply the YES and NO shares that traders buy and sell. They provide the "depth" of the market, making it possible to trade at reasonable prices. LPs earn trading fees and potentially staking rewards in exchange for providing this service.

DLMM (Dynamic Liquidity Market Maker):

Zeitgeist uses DLMM, a sophisticated market-making mechanism built on Solana. DLMM allows for concentrated liquidity at specific price points (bins) and offers several advantages over traditional AMMs, including higher capital efficiency and single-sided liquidity provision.

Bins:

In DLMM, liquidity is provided in discrete "bins." Each bin represents a single price point. An LP can deposit liquidity into one or more bins. This allows for very precise control over where liquidity is concentrated.

Active Bin:

At any given time, there is one "active bin" in a DLMM market – the bin that contains the current market price. Trades are executed against the liquidity in this bin.

Liquidity Shapes:

DLMM offers pre-defined "liquidity shapes" that determine how an LP's liquidity is distributed across bins. These shapes represent different risk/reward profiles:

• Spot: All liquidity is concentrated in a single bin (the currently active bin). Highest capital efficiency, highest risk.

• Curve: Liquidity is distributed across multiple bins, following a curve (similar to Uniswap v3). Balances capital efficiency and risk.

• Bid-Ask: Liquidity is concentrated on both sides of the current price (like a traditional order book). Good for capturing fees from market fluctuations.

• Flat: Liquidity is evenly distributed across a specified range of bins. Lowest capital efficiency, lowest risk.

Single-Sided Liquidity:

A key feature of DLMM. LPs can provide liquidity in either YES or NO shares, without needing to hold both. This makes it easier to express a specific market view.

Time-Decaying Liquidity Bins (TDLB):

A Zeitgeist-specific modification to DLMM. The value (or "weight") of liquidity in each bin decreases over time as the market's expiration date approaches. This incentivizes early liquidity provision and discourages last-minute manipulation.

Dynamic Fees:

Trading fees on Zeitgeist are not fixed. They adjust dynamically based on:

• Time to Expiration: Fees increase as the market's deadline approaches.

• Information Content: Fees increase during periods of high information flow, volatility, or potential manipulation (as measured by the "Information Score").

Information Score:

A quantitative measure, calculated by Zeitgeist's AI agents, that reflects the level of "information content" surrounding a particular narrative and its associated prediction market. It combines data from Twitter (sentiment, volume, influencer activity) to assess the likelihood of new information impacting the market price. A higher score leads to higher trading fees.

Outcome Resolution:

The process of determining the final outcome (YES or NO) of a prediction market after the event's expiration date/time. This is typically done by a designated oracle.

Oracle

The trusted source of information that determines the outcome of a prediction market. On Zeitgeist, the market creator initially acts as the oracle, subject to a multi-stage dispute resolution process.

Staking Rewards (OSSR)

Rewards (in TIME tokens) paid to liquidity providers based on the accuracy of their liquidity provision. The OSSR system considers factors like:

• Brier Score

• Time-Weighted Accuracy

• Confidence-Weighted Accuracy

• Narrative Relevance Bonus

TIME Token

The native governance and utility token of the Zeitgeist platform. TIME token holders can participate in platform governance, earn fee discounts, receive staking rewards, and access premium features.

Agent Tokens

Tokens associated with specific AI agents on Zeitgeist (e.g., XMUSK for the ADHDElon agent). These tokens provide access to premium features, voting rights (within limited scope), and other engagement opportunities related to the agent.

Governance

The process by which TIME token holders can propose, vote on, and implement changes to the Zeitgeist platform. This includes adjusting parameters, approving new features, and managing the platform's treasury.

Impermanent Loss:

A potential risk for liquidity providers. It occurs when the price of the assets in a liquidity pool changes relative to when they were deposited. While DLMM's single-sided liquidity and TDLB mitigate this somewhat, it's still a factor to consider. More detailed explanation will appear in the Liquidity Provision section.

Narrative Relevance Score:

A score assigned to users (who opt-in by connecting their Twitter account) that reflects their engagement with the specific Twitter community surrounding a particular narrative. Used for OSSR bonuses and potentially Agent Token utility.