Overview
Gauntlet has a set of recommendations for perpetual trading fees and borrowing rates on Jupiter. Below is an analysis of the recommendations, along with an assessment of JLP expected risk-adjusted returns using the recommended parameters.
Trading Fees
Parameter | Current Value | Recommended Value |
---|---|---|
Increase/Decrease Position Fee | 10 bps | 7 bps |
Borrowing Rates
Asset | Current Max Hourly Borrowing Rate | Recommended Max Hourly Borrowing Rate |
---|---|---|
SOL | .01% per hour (88% APR) | .016% per hour (140% APR) |
ETH | .01% per hour (88% APR) | .010% per hour (88% APR) |
BTC | .01% per hour (88% APR) | .012% per hour (104% APR) |
USDC | .01% per hour (88% APR) | .003% per hour (23% APR) |
USDT | .01% per hour (88% APR) | .003% per hour (23% APR) |
Perpetual Fixed Trading Fees
Trading fees should reflect the cost of transferring risk to a market participant that doesn’t have a directional view on the asset. This is a function of the liquidity profile of the asset & its volatility. For lower liquidity and higher volatility assets, this “risk transfer” cost should be higher relative to a higher liquidity, less volatile asset. In addition, the more notional risk transferred to the participant, the higher the fee, as hedging exposure and its subsequent costs are a function of notional exposure.
Jupiter implements a fixed trading fee as a percentage of trade size (zero-impact price model). In an order book environment, all-in trading costs are a function of the trade size executed. Venues traditionally charge a fixed base fee, and one can view the total cost of trading as:
tradingFee =(baseFee + orderBookImpact) * tradeSize
Gauntlet has developed order book impact models that allow us to simulate estimated impact given some notional trade size. We leverage this model to advise on perpetual trading fee parameters on Jupiter.
Gauntlet modeled a historical distribution of trades across SOL, ETH, & BTC markets in the JLP. Using this distribution, we simulate the expected impact cost across all trades. Subsequently, we compute the jupiterFixedFee parameter by minimizing the distance of all trades’ notional order book impact from the jupiterFixedFee.
minimize (i=1N |(baseFee + orderBookImpactFeei) -jupiterFixedFee| *tradeSizei)
Using a baseFee = 5 bps, which is competitive with leading perpetual venues, minimization yields a jupiterFixedFee = 7 bps. This parameter is defined at the pool level, meaning it cannot be set specific for each market (SOL, ETH, & BTC).
Parameter | Current Value | Recommended Value |
---|---|---|
Increase/Decrease Position Fee | 10 bps | 7 bps |
Borrowing Rates
Borrowing rates should reflect a conceptual “cost-of-carry” and the cost of forcing a market participant without a directional view to warehouse inventory for an undetermined amount of time (alternatively known as delta/price and theta/time risk respectively). Protocols, like Jupiter, that implement a utilization based borrowing rate should ensure this aligns with asset volatility, realized utilization levels, and broader market sentiment/positioning.
Jupiter’s formula for the current borrowing for a JLP asset x:
hourlyBorrowRatex =utilizationx * maxHourlyBorrowRatex
It is vital to target a utilization rate that is below 100%. During periods of high utilization, there is less available liquidity for new positions, leading to decreased market volume. Excess realized utilization for a prolonged period also signals that borrowing costs may not be aggressive enough.
Broader market funding sentiment is important to monitor when modeling and recommending borrowing rates on Jupiter. Unlike traditional venues where funding payments are exchanged between long and shorts, Jupiter’s funding mechanism exchanges capital between traders and JLP holders. During periods of broad elevated positive funding rate levels, shorting on a venue like Jupiter will incur more costs than utilizing alternative venues where shorts receive funding payments. The JLP becomes less capital efficient as stable coin liquidity is not being put to work.
In recommending borrowing rates, Gauntlet utilizes asset volatility, historical realized utilization of assets, and broad market funding sentiment. Using asset volatility, Gauntlet derives a risk premium estimate intended to compensate JLP for taking on the exposure. Gauntlet overlays realized asset utilization levels relative to a target utilization to heighten or dampen the risk premium estimate.
For stable coin assets, Gauntlet recommends a substantially lower borrowing rate as a result of realized utilization and broad funding sentiment. This ensures Jupiter remains attractive for shorting relative to other venues.
Asset | Current Max Hourly Borrowing Rate | Recommended Max Hourly Borrowing Rate |
---|---|---|
SOL | .01% per hour (88% APR) | .016% per hour (140% APR) |
ETH | .01% per hour (88% APR) | .010% per hour (88% APR) |
BTC | .01% per hour (88% APR) | .012% per hour (104% APR) |
USDC | .01% per hour (88% APR) | .003% per hour (23% APR) |
USDT | .01% per hour (88% APR) | .003% per hour (23% APR) |
SOL
ETH
BTC
Stables
Forward Looking JLP Fee APR & Volatility
Below outlines expected forward looking JLP returns through trading fees and borrowing costs with the recommended parameters as well as JLP volatility. The below does not include trading through spot swaps and liquidations.
Trading Fees
Gauntlet uses the concept of turnover when estimating trading fee APR. Turnover is defined as the amount of volume traded relative to the amount of liquidity in the JLP. Using the preceding three months of activity, Gauntlet uses a 2.5x turnover rate. At this turnover rate, the JLP is earning 64% APR through trading fees.
Trading Fee | 0.07% |
---|---|
Turnover | 2.5 |
JLP Trading Fee APR | 64% |
Borrowing Rates
A weighted borrowing rate is computed below using target utilization rates, recommended hourly borrowing rates, and current asset JLP rates. If all assets are at their respective utilization levels, the JLP is accruing borrowing fees at 58% APR.
SOL | ETH | BTC | Stables | |
---|---|---|---|---|
Target Utilization | 65% | 65% | 65% | 65% |
Borrowing Rate | 140% | 88% | 104% | 23% |
Borrowing Rate @ Util | 91% | 57% | 68% | 15% |
Weight | 44% | 10% | 11% | 35% |
JLP Borrowing Rate APR 58%
JLP Volatility
JLP volatility is computed using aggregated delta across spot and perpetual exposure in the JLP. Delta measures how much the JLP price will change for a one percent change in the price of the underlying asset. Net delta (aggregated spot & perpetual delta) is used in tandem with asset price return volatility and correlations to compute an aggregate volatility estimate for the JLP. At target utilization levels, the JLP has an expected annualized volatility of 36%.
SOL | ETH | BTC | Stables | |
---|---|---|---|---|
Spot Delta | 44% | 10% | 11% | 0% |
Perps Delta @ Target Util | -29% | -7% | -7% | 23% |
Net Delta | 15% | 4% | 4% | 23% |
JLP Expected Vol 36%
JLP Risk Adjusted Returns
Aggregating trading fee APR & borrowing rate APR, and applying a 30% haircut that the protocol takes, expected JLP annualized fee returns are 86%. This yields a risk adjusted return of 2.39 for JLP holders based on expected fees, and volatility due to risky asset price movements.
Net APR (70% of Fees) | 86% |
---|---|
JLP Expected Vol | 36% |
JLP Net APR / Vol | 2.39 |
Trading Fee APR | 64% |
---|---|
Borrowing APR | 58% |
Gross APR | 122% |
Net APR (70% of Fees) | 86% |
Forward-Looking Trader Fees - SOL Long Scenario
Below is a table outlining expected fees for traders putting on long exposure on SOL. For the purposes of computing borrowing rates, we use the current utilization rate for current parameter estimates and the target utilization rate for recommended parameter estimates.
SOL Long | (Total Fees / Exposure) | Current Parameters | Recommended Parameters | Fee Change |
---|---|---|---|---|
1 Day Holding Period | 0.44% | 0.43% | 0.42% | -0.01% |
7 Day Holding Period | 1.89% | 2.20% | 2.51% | 0.31% |
30 Day Holding Period | 7.43% | 8.96% | 10.95% | 1.99% |
60 Day Holding Period | 14.67% | 17.77% | 20.87% | 3.10% |