AADD COLLATERAL
Give the position more room.
—Add cash collateral at a 100% weight.
Keep the debt principal unchanged.
CRYPTO + TOKENIZED STOCKS / ROBINHOOD CHAIN
A little room.
A stronger position.
Put your collateral under pressure.
See where it bends. Find the way back.
01 Your position
Initial parameters loaded. Your previous draft is kept on this device.
Initial study parameters · Assumed quantities, debt and risk inputs. Edit to match your position.
Collateral
Start with what you hold.
Add a crypto asset or stock token,then enter the quantity to study.
Debt assumptions +
Simple interest over the selected horizon. Collateral weights are your inputs, not a lender’s rules.
COVERAGE AFTER STRESSAwaiting your inputs
—weighted collateral
÷ debt at horizon
÷ debt at horizon
Eligible collateral—
Debt at horizon—
Room above target—
Add collateral and debt to see how much pressure your position can take.
0%50%100%
×
02 Two ways back
Same target. Different use of cash.
BREDUCE DEBT
Take some weight off.
—Repay principal today from external cash.
Keep your collateral intact.
Enter your position to compare the amounts needed at your target.
Changes apply to your study. Talvori does not borrow, deposit or repay funds.
03 Go beneath the ratio
MATRICES / RISK / WORKINGSInitial parameters loaded. Your previous draft is kept on this device.
YOUR INPUTS · EVERY PANEL
Your position starts here.
Start with a crypto asset, stock token or cash collateral.
Initial study parameters · Assumed quantities, debt and risk inputs.
No wallet required. Add your quantities and adjust the assumptions.
Changes recalculate immediately and stay in sync with Your position.
One position. Thirty-five outcomes.
Market decline across the columns. Debt horizon down the rows. Pick a cell to inspect the result, then apply its assumptions.
BUILD YOUR MATRIX
Give the numbers a starting point.
Add an asset using Add asset + above, then enter its quantity. Or enter cash collateral directly. Add debt to compare coverage and recovery amounts.
Your inputs generate 35 scenarios. Each cell opens a calculation you can apply to the study.
Meets your targetBelow your targetAll other assumptions stay fixed
Select a cell to inspect it.
Applying changes only the study’s market decline and debt horizon. Use Undo adjustment in the recovery section to return.
How do your assets move together?
Enter annual volatility, then edit each pair’s correlation. These are your assumptions, not estimates from historical prices. Cash collateral has zero volatility in this model.
All correlations are editable assumptions. Newly added asset pairs start at 0; initial-study pairs use 0.35. Edit the upper triangle; the lower triangle mirrors it. The diagonal stays 1.
Normal return model, zero expected return, √(days / 365) scaling. Results describe gross asset value, including cash, before the separate collateral stress. VaR is a loss threshold; ES is the model’s mean loss beyond it. Neither is a maximum loss or a liquidation forecast.
Annual covariance matrix Σ = diag(σ) · ρ · diag(σ)
Entries use decimal return squared per year. For example, annual volatility entered as 20% becomes 0.20 before multiplication.
Where portfolio risk comes from Euler contribution
Contributions sum to portfolio volatility. A negative contribution represents a hedge under your correlation assumptions, not a guaranteed protection.
Model references: Portfolio covariance · Normal expected shortfall · RiskMetrics
Show the workings.
The same inputs, written out. Symbols, substitutions and sensitivities remain attached to your study.
Collateral calculation matrix One row per asset
What changes the buffer? Local sensitivities
Partial derivatives hold all other inputs fixed. Values are changes in USD headroom for the stated unit; simultaneous changes can interact.
Symbol key Read the notation
- qᵢ, pᵢ
- Asset quantity and USD price
- cᵢ, eᵢ, s
- Collateral weight, asset shock and market decline, as decimals
- R, P, a, t
- Cash collateral, debt principal, annual APR and debt horizon in days
- τ, C, D, B
- Target coverage, eligible collateral, debt at horizon and headroom
- w, σ, ρ, Σ
- Market-value weights, annual asset volatility, correlation and covariance
- V, T, α, zα
- Gross asset value, risk horizon in days, confidence and its standard normal quantile
04 Keep your thinking
Pin a scenario, change one assumption, and compare the difference here.
Your draft stays on this device. Saved records use a private browser workspace on the server; export before clearing browser data or changing devices.
THE METHOD
The assumptions
are part of the answer.
Prices tell you what an asset trades for.
Collateral weights tell you how much of it counts.
What goes into coverage?−
For each asset: quantity × price × collateral weight × (1 − asset shock) × (1 − market decline). Add cash collateral, then divide by principal plus simple interest over your chosen horizon.
Where do prices come from?+
The asset directory uses LI.FI’s Robinhood Chain token references. Prices include their retrieval time and may be unavailable or delayed. Match token contracts before using them. Manual prices are labelled “Your price”; saved studies keep their original price snapshots.
What does wallet connection do?+
Connect OKX or another supported wallet to read balances for the assets you selected. Reading balances does not request a signature or move funds. Your debt remains a separate input.
Is this a liquidation price?+
No. The line shows when your chosen coverage target is crossed under a uniform market decline. Actual lenders may use different prices, weights, liquidation rules and fees. Tokenized stocks are on-chain tokens; the ticker alone does not establish shareholder rights.