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  • Introduction
    • About B3X
  • World Market
    • Introduction
    • Problems with Current Markets
      • DeFi's Never-Ending Cold Start Problem
      • Limited Utility for Existing Assets
      • CeFi Dominates with 100x Volume
      • Outdated DeFi Perps Offerings
      • Consistent Battle for Liquidity
      • Stablecoins with No Use-case
      • Unfair LP Treatment
      • No Settlement Venue is Best
  • Introducing: The World Market
    • Solving the Crypto UX Nightmare
    • Purposeful Stablecoins
    • Unlimited Open Interest
    • Enabling Deep Liquidity
    • LPs as 1st Class Citizens
    • First-Principle Orderbook Design
  • World Modules
    • Delta-Neutral Stablecoin
    • Yield-Bearing Stablecoin
    • Long-Only Vault
    • Short-Only Vault
    • Long vs Short Vault
    • Lending
    • Funding Rate Collector
  • Future: Supercharged DeFi
    • User-Centric Intent, Action, and Execution Marketplace
    • Yield Trading
    • Simplified Market Experience
    • LPs as First-Class Citizens: Mini DAOs
    • Building Distribution for all — Chains, Protocols and Users
    • Resolving Cold-start Problem
    • Launching New Markets
    • Building Solutions with Derivatives as a First Principle
    • Bootstrapping TVL Growth: Unlocking DeFi’s True Potential
    • Boosting Token Utility
    • Meaningful Second-order Incentives
    • Boosting Economical Security of DeFi protocols
  • Our Call to Action
  • Technical Specs
    • Architectural Design
    • Pricing Mechanism
    • Risk Management
      • Risk Factors
      • Price Protection
      • Auto Deleverage
      • Liquidation
    • Settlement Design
    • Asset Management
    • Market Management
  • Fees
  • Testnet
    • World Market (Rise)
  • World Fund
    • Introduction
    • The Problem
    • Architecture
      • User Layer
      • Human-driven Application Layer
      • AI-driven Application Layer
      • Infrastructure Layer
    • Core Components
      • Fund Builder
      • Quant Agent
      • Strategy Framework
    • Decentralized Architecture
    • Execution Layer
    • Conclusion
    • References
    • Original Whitepaper PDF
  • Economics
    • World Market
    • World Fund
  • External Links
    • Website
    • Twitter
    • Discord
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  • Quantitative Finance
  • Artificial Intelligence and Machine Learning
  • Decentralized Finance and Blockchain
  • Large Language Models and Financial Applications

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References

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Last updated 13 days ago

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This document draws on a wide range of research and foundational work in quantitative finance, artificial intelligence, and decentralized systems. The following references provide additional context and background for the concepts presented in this litepaper.

Quantitative Finance

  • Bailey, D. H., Borwein, J. M., López de Prado, M., & Zhu, Q. J. (2014). Pseudo-Mathematics and Financial Charlatanism: The Effects of Backtest Overfitting on Out-of-Sample Performance. Notices of the American Mathematical Society, 61(5), 458-471.

  • López de Prado, M. (2018). Advances in Financial Machine Learning. Wiley.

  • Aronson, D. (2006). Evidence-Based Technical Analysis: Applying the Scientific Method and Statistical Inference to Trading Signals. Wiley.

  • Kakushadze, Z., & Serur, J. A. (2018). 151 Trading Strategies. SSRN Electronic Journal.

Artificial Intelligence and Machine Learning

  • Sutton, R. S., & Barto, A. G. (2018). Reinforcement Learning: An Introduction (2nd ed.). MIT Press.

  • Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep Learning. MIT Press.

  • Chollet, F. (2021). Deep Learning with Python (2nd ed.). Manning Publications.

  • Brown, T. B., Mann, B., Ryder, N., Subbiah, M., Kaplan, J., Dhariwal, P., ... & Amodei, D. (2020). Language Models are Few-Shot Learners. arXiv preprint arXiv:2005.14165.

Decentralized Finance and Blockchain

  • Buterin, V. (2014). Ethereum: A Next-Generation Smart Contract and Decentralized Application Platform.

  • Adams, H., Zinsmeister, N., & Robinson, D. (2020). Uniswap v2 Core.

  • Schär, F. (2021). Decentralized Finance: On Blockchain- and Smart Contract-Based Financial Markets. Federal Reserve Bank of St. Louis Review, 103(2), 153-174.

  • Peretz, G., O'Neil, R., & Krowiak, R. (2021). Automated Market Makers and Decentralized Exchanges: A DeFi Primer. Journal of Financial Transformation, 52(1), 47-59.

Large Language Models and Financial Applications

Wu, T., Li, Z., Yang, Y., Huang, Z., Ding, L., Yang, C., ... & Zhao, Z. (2023). BloombergGPT: A Large Language Model for Finance. arXiv preprint arXiv:2303.17564.

Yang, K., Gan, Z., Pang, P.N., Su, Y., & Dai, X. (2023). FinGPT: Open-Source Financial Large Language Models. arXiv preprint arXiv:2306.06031.

Wu, C., Raghunathan, A., Zhang, C., Benmohamed, P.R., & Hooi, B. (2023). Trading with Language Models: An Analysis of their Predictive Power and Limitations. arXiv preprint arXiv:2309.12别9.

https://www.ams.org/notices/201405/rnoti-p458.pdf
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3247865
https://www.deeplearningbook.org/
https://arxiv.org/abs/2005.14165
https://ethereum.org/en/whitepaper/
https://uniswap.org/whitepaper.pdf
https://research.stlouisfed.org/publications/review/2021/02/05/decentralized-finance-on-blockchain-and-smart-contract-based-financial-markets
https://arxiv.org/abs/2303.17564
https://arxiv.org/abs/2306.06031
https://arxiv.org/abs/2309.12819