AQTIS Documentation
  • Introduction to AQTIS
  • QSD
    • What is QSD?
    • How does the yield work?
    • How do I buy QSD?
    • How do I generate yield?
    • How do I claim my rewards?
    • A deeper dive into how the yield works
    • QSD pricing dynamics
    • Permissionless Exit
    • How do I sell my QSD?
    • Quant Technology’s role in QSD
    • Compliance
    • In summary
  • QRT
    • Securing the quant tech
    • How do I claim my rewards?
    • Claiming Mechanics
    • Quant Tech Liquidity Management
    • Difference with Other LSTs
    • Compliance
    • In Summary
  • Quant Tech & AI Explained
    • Why we use quantitative techniques
    • The Investment Strategy Portfolio
    • The AQTIS Investment Thesis
    • Why we use Machine Learning/AI in our portfolio
    • How we manage risk
    • Quant Tech Workflow
    • Quant Tech Strategies - the AQTIS secret weapon
    • Conclusion
  • Quant Performance
  • Tokenomics
  • Ecosystem Liquidity Insurance Fund (ELIF)
  • Ecosystem Liquidity Aggregator
  • Calculations
    • Testing Performance
    • Total Value Locked
    • Liquidity Utilization
    • Position Sizing
    • The impact of slippage on performance
    • In summary
  • What is the AQTIS Buyback Process?
  • AQTIS FAQ
    • AQTIS Protocol TL:DR
    • What are Liquid Staking Tokens (LSTs)?
    • What is Quant Trading?
    • What are Composable Yields?
    • What is the Token Buyback Process and how does it contribute to Token Value?
    • Can AQTIS Freeze My Assets? What about Permissionless Exits?
    • What is the Maximum Supply of the AQTIS Utility Token?
    • What is the Maximum Transaction Amount for the AQTIS Utility Token?
    • Where Can I Buy AQTIS LSTs and the AQTIS Token?
    • What Blockchain Network Does AQTIS Utilize?
    • Is AQTIS Regulation Compliant?
    • How Does AQTIS Generate Revenue?
    • How Are Liquidity Rewards Distributed in AQTIS?
    • What’s the Minimum Staking Period?
    • Where Can I Find the AQTIS Utility Token Contract Address?
    • Why has AQTIS capped the TVL?
    • Why implement LSTs? Why not simply use a reward pool where people can withraw their "dividends"?
    • Why is there a standardized yield?
    • Why is the team not doxxed?
    • Why is AQTIS sharing its strategies with the community?
  • Disclaimer
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  1. Calculations

The impact of slippage on performance

Understanding the Impact of Slippage on Performance

While our current calculations consider the balance between utilization and performance, it's important to note that capping TVL to maintain high performance is crucial. Larger position sizing can negatively impact profits, particularly when accounting for slippage—the difference between expected and actual execution prices of trades.

To illustrate this, let's assume the following parameters:

  • Win rate: 30%

  • Risk-to-Reward ratio: 4:1 (for every 1% risked, we aim for a 4% return)

  • Profit per trade: 4%

  • Loss per losing trade: 1%

  • Extra slippage per trade: 0.22% (as indicated by performance reports)

Out of 100 trades, 30 are profitable, yielding a 4% return per trade, while the other 70 hit the Stop Loss at 1%, with both types of trades affected by slippage. Let's calculate the expected performance with and without slippage based on these assumptions.

1. Without Slippage:

  • Profitable trades (30%): 30 trades × 4% profit = 120%

  • Losing trades (70%): 70 trades × 1% loss = 70%

  • Net performance: 120% - 70% = 50%

Without slippage, the expected net performance over 100 trades would be 50%.

2. With Slippage (0.22% per trade):

  • Profitable trades (30%): 30 trades × (4% - 0.22%) = 30 trades × 3.78% = 113.4%

  • Losing trades (70%): 70 trades × (1% + 0.22%) = 70 trades × 1.22% = 85.4%

  • Net performance: 113.4% - 85.4% = 28%

With a 0.22% slippage rate per trade, the expected net performance is reduced to 28%.

3. With Increased Slippage (0.44% and 0.66%):

Let’s calculate the impact of higher slippage rates—0.44% and 0.66% per trade.

a. Slippage at 0.44%:

  • Profitable trades (30%): 30 trades × (4% - 0.44%) = 30 trades × 3.56% = 106.8%

  • Losing trades (70%): 70 trades × (1% + 0.44%) = 70 trades × 1.44% = 100.8%

  • Net performance: 106.8% - 100.8% = 6%

With 0.44% slippage, the net performance drops to 6%, indicating a drastic reduction in profitability.

b. Slippage at 0.66%:

  • Profitable trades (30%): 30 trades × (4% - 0.66%) = 30 trades × 3.12% = 93.6%

  • Losing trades (70%): 70 trades × (1% + 0.66%) = 70 trades × 1.88% = 131.6%

  • Net performance: 93.6% - 131.6% = -38%

With 0.66% slippage, the strategy results in a negative performance of -38%, indicating significant losses.

Conclusion:

This analysis demonstrates how slippage can have a profound impact on trading performance:

  • Starting with a baseline net performance of 50% without slippage, even a small slippage rate of 0.22% reduces the net performance to 28%.

  • As slippage increases to 0.44%, net performance declines to 6%, and at 0.66%, performance turns negative (-38%).

Minimizing slippage is crucial for maintaining profitability. Even with a high win rate and favorable risk-to-reward ratio, slippage can erode gains, emphasizing the need for efficient execution strategies to maximize the effectiveness of the overall trading strategy.

Last updated 7 months ago