Settlement Values & The Model Price Oracle

Settlement value is the price RAVA is willing to pay for an asset at any moment. It is generated using tradeable market data, not by applying simple haircuts to stale NAV.

Traditional finance keeps these models private. Every bank, prime broker, and NAV lender maintains their own internal settlement model to determine how much they will lend, when they call margin, and how they handle defaults.

RAVA makes this transparent through a Model Price Oracle that generates synthetic, tradeable prices for assets without live markets. The system starts with the last known reference value, then adjusts it using only observable, tradeable inputs: volatility, liquidity stress, yield curves, credit indices, sector benchmarks, and correlation shifts. These adjustments reflect how a comparable, liquid market would revalue the asset under current conditions.

The result is a real price RAVA will transact at, backed by capital ready to settle. The discount component expresses illiquidity and uncertainty, but the output is a settlement price, not just a haircut.

The Settlement Value Formula

Settlement value is calculated using a transparent two part discount model:

V_settlement(t) = NAV(t) × (1 − [S + D(t)])

Where: NAV(t) = reported net asset value at time t S = Static Discount (structural factors that cannot be hedged) D(t) = Dynamic Adjustment (market factors that can be hedged)

Two Types of Discounts

The total discount is broken into two transparent components:

Static Discount (S) Structural characteristics of the asset itself Examples: legal complexity, asset structure layers, manager quality, underlying liquidity These factors are locked they cannot be changed or hedged Range: typically 2 to 10% depending on asset type Shown as round numbers (e.g., 5%, 9%, 8%)

Dynamic Adjustment (D(t)) Market wide factors that respond to tradeable signals Examples: credit spreads, interest rates, market volatility, liquidity premiums, equity beta These factors can be hedged through liquid derivatives markets Varies by asset sensitivity to each market input Shown with precision (e.g., 7.28%, 5.81%, 8.47%)

Asset Sensitivity

Different asset types have different sensitivities to dynamic market factors:

Hedge Funds: 104% sensitivity liquid holdings mark to market daily Private Equity: 83% sensitivity long term holds less affected by short term moves Venture Capital: 121% sensitivity valuations highly correlated to public market multiples

If credit spreads contribute 2.5% to the base discount: Hedge fund discount increases by 2.5% × 1.04 = 2.60% PE fund discount increases by 2.5% × 0.83 = 2.08% VC fund discount increases by 2.5% × 1.21 = 3.03%

What Drives the Discount

The total discount combines two distinct types of factors:

Static Discount Factors (Cannot Be Hedged)

These are structural characteristics inherent to the asset:

Legal Unwind Complexity Time required for legal liquidation process Based on fund structure, jurisdiction, and precedent Hedge funds: ~30 45 days, PE/VC: 60 90+ days

Asset Structure Layers Number of legal entities between asset and investor Each layer adds friction: Master fund → Feeder → LP More layers = higher static discount

Manager Quality Track record, operational history, governance Top tier managers (score 90+) reduce discount History of defaults or operational issues increases it

Underlying Asset Liquidity Liquidity of the fund's portfolio holdings Hedge funds with liquid positions: lower discount VC/PE with illiquid private holdings: higher discount

Embedded Leverage Fund level leverage and derivatives exposure Higher leverage amplifies losses in stress scenarios

Dynamic Adjustment Factors (Can Be Hedged)

These respond to tradeable market signals and can be hedged through liquid derivatives:

Credit Spreads (CDX HY Index) Widening spreads → higher illiquidity premium Can hedge by shorting credit indices Reduces sensitivity from ~2.5% to near zero

Risk Free Rate (SOFR / UST Futures) Rising rates → higher discount rates on future cash flows Can hedge with rate swaps or treasury futures Stabilizes interest rate sensitivity

Market Volatility (VIX Index) Higher volatility → greater mark uncertainty Can hedge with VIX futures or variance swaps Reduces adjustment sensitivity during volatile periods

Liquidity Premium (HYG / LQD Spread) Stressed markets → wider liquidity spreads Can hedge through relative value trades Protects against market liquidity shocks

Equity Market Beta (S&P 500 / NASDAQ) For funds with equity correlation Can hedge with index shorts or options Neutralizes directional market exposure

The dynamic component D(t) updates continuously as these tradeable signals change. Holders can reduce or eliminate dynamic discount sensitivity by hedging the underlying factors in liquid markets.

Example Calculation

Example: Apollo Infrastructure Fund IV (Private Equity)

Starting Values Reported NAV: $85M Asset Type: Infrastructure / Private Equity Last Update: 5 minutes ago

Static Discount Breakdown: 9.0% Legal Unwind Complexity: 2.5% Asset Structure Layers: 1.5% Manager Quality: 1.0% Underlying Asset Liquidity: 3.0% Embedded Leverage: 1.0%

Dynamic Adjustment Breakdown: 5.81% Credit Spreads (CDX HY): 2.08% (base 2.5% × 0.83 sensitivity) Risk Free Rate (SOFR): 1.00% Market Volatility (VIX): 1.49% Liquidity Premium: 0.83% Equity Beta: 0.41%

Total Discount: 14.81% Settlement Value: $85M × (1 − 0.1481) = $72.4M

Now Credit Spreads Widen 100bp and VIX Spikes 50%

Static Discount: 9.0% (unchanged structural factors don't respond to market moves)

Dynamic Adjustment: 9.15% (increased due to market stress) Credit Spreads: 4.15% (widened from 2.08%) Risk Free Rate: 1.00% (unchanged) Market Volatility: 2.24% (increased from 1.49%) Liquidity Premium: 1.25% (stressed markets) Equity Beta: 0.51% (higher correlation in stress)

New Total Discount: 18.15% New Settlement Value: $85M × (1 − 0.1815) = $69.6M

Key Insight: The dynamic portion increased from 5.81% to 9.15% (+3.34%) while static remained at 9.0%. If the fund holder had hedged credit spreads and volatility through liquid derivatives, their settlement value would have remained stable at ~$72.4M despite market stress.

Hedging the Dynamic Component

The holder can eliminate dynamic discount risk by hedging in liquid markets:

1. Short CDX HY Index → Removes 2.08% → 4.15% credit spread sensitivity
2. Buy VIX Futures → Removes 1.49% → 2.24% volatility sensitivity
3. Rate Swap → Removes 1.00% rate sensitivity

Result After Hedging: Static Discount: 9.0% (cannot hedge) Dynamic Adjustment: ~0.5% (residual after hedges) Total Discount: ~9.5% Stable Settlement Value: $76.9M (regardless of market conditions)

This demonstrates how transparent decomposition enables strategic risk management. Holders can see exactly which discount components are tradeable and hedge accordingly.

The Model Price Oracle Interface

RAVA's Model Price Oracle provides complete transparency into how settlement prices are calculated:

Protocol Health Dashboard

Shows aggregate metrics across all assets: Total NAV under management Total capital backing available Average discount rate across assets Capital utilization percentage

Per Asset Breakdown

For each tokenized asset, users can see:

1. Summary Metrics Asset NAV (accounting value) Standing Bid Price (executable price after discount) Total Discount percentage Last update timestamp

2. Static Discount Factors Shows top contributing structural factors Each factor displays its % contribution Marked as "LOCKED" cannot be changed or hedged Examples: Legal complexity 2.5%, Asset structure 1.5%, Manager quality 1.0%

3. Dynamic Adjustment Factors Shows ALL tradeable market inputs Each input shows precise % contribution to discount Asset sensitivity multiplier displayed Examples: Credit spreads 2.08%, Volatility 1.49%, Rates 1.00%

4. Markets Page Live prices for all dynamic input proxies 24 hour price changes and trends Links to trade these instruments Shows how to hedge each factor

5. Liquidations Page RAVA standing bid with capital backing Shows instant executable price Explains the liquidation mechanism Compares RAVA (liquidator) vs traditional lenders

Why This Transparency Matters

Traditional lenders maintain private models that estimate settlement value. These models are hidden. Borrowers cannot verify them. Protocols cannot integrate them.

RAVA's Model Price Oracle publishes the same logic in transparent form: Every input is verifiable Every calculation is auditable Users can see which factors are static vs tradeable Holders can hedge dynamic components to stabilize their settlement values Protocols can consume settlement prices like price oracle feeds

The oracle generates synthetic, tradeable prices for assets without live markets, backed by capital ready to settle at those prices. This makes illiquid tokenized assets safely composable for the first time.

Settlement Adjustments by Asset Class

Different asset classes require different adjustment factors based on their liquidity, appraisal frequency, and market dynamics:

Less liquid assets receive larger adjustments to reflect the greater difficulty and time required to liquidate them under stress.

Privacy Preserving Attestations

Some risk factors cannot be made fully public without revealing confidential information about fund holdings. RAVA uses encrypted attestations to verify private data without exposing it.

Example: A private credit fund holds 120 loans across 8 industries. Publishing the full portfolio would reveal competitive information. Instead, RAVA receives an encrypted attestation proving:

Concentration: No single loan exceeds 5% of NAV Diversification: At least 6 industries represented Leverage: Fund level leverage below 1.5x Performance: No loans more than 30 days past due

The attestation cryptographically proves these facts without revealing which specific loans exist or their terms. Protocols can verify the proof and adjust settlement values accordingly.

This allows private funds to participate in transparent credit markets without sacrificing confidentiality.

What Settlement Values Enable

Composable Lending Protocols integrate settlement values the same way they use price oracles Advance rates, margin calls, and liquidations operate automatically No need for each protocol to build custom valuation logic

Transparent Credit Standards All participants see the same settlement values No hidden internal models Consistent leverage limits across the ecosystem

Real Time Risk Management Settlement values update as market conditions change Positions can be margined daily or hourly Lenders know recoverable value under current stress levels

Settlement Values vs NAV

T+1 Settlement for Timing Attack Protection

For assets exposed to timing attacks, insider information, or stale marks, RAVA uses a T+1 settlement window to ensure fair pricing.

How it works:

When a lender triggers exit, only two things are locked immediately:

1. The right to exit
2. The current haircut level

The actual transaction price is not locked. Instead:

Price Setting at T+1

The settlement price is determined at the next pricing window using a VWAP (Volume Weighted Average Price) around T+1. The haircut floats with updated macro inputs until settlement.

Why This Matters

This prevents actors from pushing risk onto RAVA at stale prices. If someone has insider information that NAV is about to drop or market conditions are deteriorating, they cannot lock in an old price and force RAVA to settle at outdated values.

By the time settlement occurs (T+1), the model price reflects the most current, unbiased market conditions. RAVA always transacts at a price that incorporates the latest observable, tradeable data.

Example:

• Day 0, 3pm: Lender triggers exit. Right to exit is locked. Current haircut: 12%
• Day 0, 4pm: Market credit spreads widen significantly
• Day 1, 3pm: Settlement occurs using VWAP around this window. Haircut now: 15% (updated with new spreads)

The lender receives the T+1 price, not the stale Day 0 price. RAVA is protected from information asymmetry.

Result

RAVA transforms illiquid tokenized assets into safely composable collateral through three key innovations:

1. Model Price Generation

The Model Price Oracle generates synthetic, tradeable prices for assets without live markets: Observable inputs from tradeable markets (spreads, volatility, rates) Static components (structural, locked, cannot be hedged) Dynamic components (market driven, tradeable, can be hedged) Real settlement prices RAVA will transact at, backed by capital

Users see exactly what drives their settlement prices and which risks they can trade away.

2. Hedgeable Risk Exposure

By publishing asset specific sensitivities to each dynamic factor, RAVA enables: Selective hedging of specific market risks (rates, spreads, volatility) Stabilization of settlement values through liquid derivatives Reduction of dynamic discount from ~7% to near zero through hedging Clear cost/benefit analysis for each hedge

3. Protocol Composability

Protocols no longer build private valuation models. They integrate a shared settlement layer that: Updates continuously as market conditions change Provides consistent leverage standards across the ecosystem Enables safe, predictable lending against illiquid assets Works the same way for all participants

This is the foundation required for tokenized asset credit markets to scale.

RAVA is not just a discount oracle. It is a model price oracle that generates real, tradeable prices for assets without live markets. The system uses observable market data to calculate the exact price RAVA is willing to pay, backed by capital ready to settle. Traditional finance hides these settlement models. RAVA makes them transparent, tradeable, and composable.