> For the complete documentation index, see [llms.txt](https://tau-labs.gitbook.io/vault-dashboard/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://tau-labs.gitbook.io/vault-dashboard/tau-risk-framework/how-risk-informs-vault-strategies.md). # How Risk Informs Vault Strategies The results of our risk analysis (details [here](#_rhrzm64e1qju)) are used to filter assets and strategies, set parameters, and determine capital allocations. ## **Consideration Set** We apply maximum risk thresholds to disqualify strategies that exceed a vault’s risk tolerance before they are even considered for allocation. Thresholds are applied across overall risk, per risk dimension (e.g. asset), and individual risk elements (e.g. collateral of a stablecoin). > Example: A lending optimizer might not onboard a Morpho market for a new stablecoin as it exceeds the vault’s risk tolerance. *** ## **Maximum** **Allocations** To prevent "black swan" contagion, we enforce hard caps on exposure across several vectors based on assessed risks: * Chains * Protocols * Assets, including collateral assets > Example: A lending optimizer may cap its maximum allowed exposure to protocols (e.g. Morpho, Euler), supplied assets (e.g. USDC, USDT), markets (e.g. cbBTC-USDC, WBTC-USDC, WBTC-USDT), collateral assets (e.g. caps individually for cbBTC & WBTC, and collectively as exposure to BTC-related assets) across markets and protocols, and risk groups (e.g. risk group A, B, C). *** ## **Actual Allocations** Final allocations are determined by comparing the yield premium (yield above benchmark) against the modelled risk. We only increase exposure if the market offers a "Risk-Adjusted Return" that justifies the volatility. > Example: A lending optimizer compares the yield of a market to the benchmark (e.g. supply rate in the cbBTC-USDC Morpho market). *** ## **Parameter Selection** Risk factors inform a vault’s parameters. > Example: In a borrow loop, we set its LTV based on the market’s LLTV, oracle design, and the modelled price volatility between debt and collateral asset. *** ## **Operational Guardrails** Beyond the core models, we maintain strict operational constraints which influence allocations. For example, a lending optimizer may limit the share of supply it's willing to take in a market to a maximum 10% to preserve liquidity, and not allocate to markets with utilization over 93%. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## 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, and the optional `goal` query parameter: ``` GET https://tau-labs.gitbook.io/vault-dashboard/tau-risk-framework/how-risk-informs-vault-strategies.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. 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.