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. Quant Tech & AI Explained

Conclusion

Last updated 1 year ago

Our tests from the 2020 bull run through the first part of 2023 have been both profitable and enlightening, delivering impressive returns. Interestingly, when we reflect on the downturn experienced from 2021 to 2022, it provides insight into the remarkable potential returns that can be achieved.

Our strategy is not bound to perpetual investing, meaning we don’t aim for continuous investments or maximum time exposure. We prioritize maintaining liquidity efficiency, enabling diversification into other models or assets. Through portfolio simulation of the top 20 assets, we have maintained an average market exposure time of only 22.2%, safeguarding us against challenging market downturns.

While our system empowers us to capitalize on opportunities, it is equally proficient at minimizing losses, with our average drawdown resting at 20.7%. Detailed performance data can be found at the links below. Breakout long: Breakout short: Breakout performance:

Mean Reversion (long): Mean reversion (short):

Mean reversion (performance):

Trend following (long):

https://gamma.app/docs/dc89kipnd6m0ufv
https://gamma.app/docs/ke7ogvuyya67v88
https://gamma.app/docs/n24pj80m78rq62u
https://gamma.app/docs/ckp42afr9ma5hmi
https://gamma.app/docs/r48ya8qcbr4655m
https://gamma.app/docs/70rycsv6du6fccp
https://gamma.app/docs/j4diywwlrokc0qs