Strat Example 1 (IF Single Condition Execution)
Strategy Mechanics
This example illustrates a momentum fade strategy utilizing RSI divergences to capture mean reversion opportunities in the ETH/USDT pair.
Signal Generation
The strategy monitors RSI indicators for extreme readings:
Buy Signal: RSI crosses below 30 (oversold threshold) indicating potential upward reversal
Sell Signal: RSI crosses above 70 (overbought threshold) suggesting downward reversion
Execution Logic: Market orders triggered automatically upon signal confirmation
Position Sizing: Predetermined percentage of pool capital per trade
Capital Flow
Base Currency: Investors deposit USDT into the strategy vault
Trading Cycle: USDT → ETH (buy signal) → USDT (sell signal)
Idle Capital: USDT remains in vault between trades earning no yield
Compounding: Profits automatically reinvested in subsequent trades
Performance Distribution
Return Calculation Scenario
Assuming the strategy generates +20% return over its epoch:
Gross Performance: +20% on deposited capital
Fee Waterfall:
Performance Fee (to Creator): 10% of profits = 2% of capital
Platform Commission: 20% of performance fee = 0.4% of capital
Net to Investors: 20% - 2% - 0.4% = 17.6% return
Mathematical Breakdown
For 10,000 USDT deposited:
Gross Profit: 2,000 USDT
Creator Fee: 200 USDT (10% of profit)
Platform Fee: 40 USDT (20% of creator fee)
Investor Receives: 11,760 USDT (17.6% net return)
Fee Structure Deep Dive
Performance Fee Model
High-Water Mark: Fees charged only on profits exceeding previous peaks
No Management Fee: Creator earns solely from successful performance
Aligned Incentives: Creator profits only when investors profit
Platform Revenue Share
The 20% commission on performance fees funds:
Infrastructure Maintenance: Execution servers, data feeds, gas costs
Protocol Development: Continuous platform improvements
Token Holder Dividends: 50% of platform revenues distributed to $RANK holders
Treasury Growth: Strategic reserves for ecosystem expansion
Risk Considerations
Strategy-Specific Risks
Whipsaw Markets: RSI can remain extreme during strong trends
False Signals: Oversold can become more oversold in bear markets
Execution Slippage: Large trades may impact market prices
Correlation Risk: RSI effectiveness varies across market regimes
Mitigation Mechanisms
Stop Losses: Maximum loss per trade capped at predetermined percentage
Position Limits: Maximum exposure prevents catastrophic losses
Timeout Periods: Minimum time between trades prevents overtrading
Drawdown Limits: Strategy pauses if losses exceed threshold
Advanced Implementation
Signal Refinement
Production strategies typically incorporate:
Multi-Timeframe Confirmation: RSI alignment across different periods
Volume Filters: Ensuring sufficient liquidity for execution
Trend Filters: Avoiding counter-trend trades in strong markets
Volatility Adjustment: Dynamic thresholds based on market conditions
Execution Optimization
Limit Orders: Reducing market impact through patient execution
Time-Weighted Averaging: Splitting large orders across time
Cross-Exchange Routing: Finding best prices across multiple venues
Gas Optimization: Batching operations to minimize transaction costs
This example demonstrates how simple technical indicators transform into sophisticated trading systems through Rank's infrastructure, with transparent fee structures ensuring aligned incentives across creators, investors, and the platform.
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