# Simulate Market Events Omira’s 0.07 model may deliver predictions contingent on specific events or catalysts; In other words, **0.07 may adapt its price predictions & sentiment insights to hypothetical scenarios provided by users.** This is achieved via data-based simulations, where the occurrence of previous similar events are cross referenced with previous chart & sentiment patterns, the results of which are then used to simulate future chart movements & sentiment shifts on the specified asset. **For newer tokens with limited market data**, simulations are based on previous similar occurrences on other tokens with high similarity in both nature and social engagement. **For older tokens with greater market history**, simulations are based on previous similar occurrences on the specified asset, with data being drawn from other similar tokens where necessary. **Here are some examples of hypothetical scenarios which users may provide 0.07 with in order to receive event-adapted predictions:** * How is the release of X token’s utility likely to affect price? * What is likely to happen to X token’s price if the release of X token’s utility is delayed? * What is likely to happen to X token’s price if X marketer posts about it? * What is likely to happen to X token’s price if it gets listed on X place? --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://omira-documentations.gitbook.io/omira-documentations/0.07-agent-model/model-whitepaper/simulate-market-events.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.