AlgoAgent
  • WHITEPAPER
  • 1. Digital Currency Quantitative Trading
    • 1.1 Quantitative Trading
    • 1.2 Digital currency and quantitative trading are a natural fit
    • 1.3 The prospects for digital currency quantitative trading are enormous
    • 1.4 The current situation of the quantitative trading market
      • 1.4.1 A large number of exchanges, chaotic trading rules
      • 1.4.2 The trading time is excessively long
      • 1.4.3 Extremely Immature Technology Infrastructure
  • 2. AI Agent Quantitative Intelligent Trading
    • 2.1 Artificial intelligence is the trend of the future
    • 2.2 Quantitative intelligent trading of digital currencies using AI Agents will become a trend
  • 3. AlgoAgent
    • 3.1 AlgoAgent Introduction
    • 3.2 AlgoAgent Development History
    • 3.3 Trading strategies and indicators supported by AlgoAgent
    • 3.4 AlgoAgent AI Agent Quantitative Trading Algorithms
      • 3.4.1 Sell-off Detection
      • 3.4.2 Wall Detection
      • 3.4.3 Variable shooting (buying spike kill)
    • 3.5 AlgoAgent Advantages
      • 3.5.1 Full range of management services
      • 3.5.2 Multiple security protections
      • 3.5.3 Asset appreciation
      • 3.5.4 Multi-language support
      • 3.5.5 Simple and convenient transactions
      • 3.5.6 Risk-Free High-Frequency Automated Quantitative Trading of Digital Assets
      • 3.5.7 Convenient Funding
    • 3.6 AlgoAgent Service Carrier
      • 3.6.1 AlgoAgent Intelligent Platform
      • 3.6.2 Digital Asset Bank Card
      • 3.6.3 AlgoAgent Contract Token
  • 4. Tokenomics
  • 5. Roadmap
  • 6. Team Introduction
  • 7. Risk Warning
  • 8. Disclaimer
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  1. 1. Digital Currency Quantitative Trading
  2. 1.4 The current situation of the quantitative trading market

1.4.1 A large number of exchanges, chaotic trading rules

With the explosion of digital currencies, the global crypto market now has thousands of exchanges. On the surface, this situation appears similar to the foreign exchange market, where retail brokers are ubiquitous, but there are significant differences in essence. In traditional financial markets, the secondary market sellers are mostly composed of two layers: the first layer consists of liquidity wholesalers (exchanges and large investment banks), and the second layer consists of liquidity distributors (securities firms and futures companies). The numerous retail brokers in the foreign exchange market belong to the second layer, and their ultimate liquidity still converges in the large investment banks of the first layer.

In contrast, crypto exchanges play the roles of both the first and second layers simultaneously. Each exchange directly faces customers and can only provide its own liquidity to them. There is no interconnectivity mechanism between different exchanges, and the market's liquidity is severely fragmented. Institutional investors with large orders may need to break them down into smaller orders and send them to different exchanges for execution; otherwise, they would have to wait a long time if using just a single exchange.

Another problem brought about by the large number of exchanges is the extreme confusion of trading rules: High-end exchanges support complex order types such as FAK (Fill and Kill), FOK (Fill or Kill), and OCO (One Cancels the Other), while some low-end exchanges may not even support basic market orders. Although almost all exchanges claim that their matching rules are "price priority, time priority," we have still seen instances where, on some top exchanges, the best bid price is higher than the best ask price on the order book.

The fragmentation of liquidity also leads to persistent price discrepancies for identical products across different exchanges, with price convergence needing to be achieved by arbitrageurs in the market. From another perspective, it can be said that arbitrageurs actually play the role of liquidity wholesalers in the crypto market. Therefore, the profitability of arbitrage strategies in the crypto market is likely to remain significantly higher than that in traditional financial markets over the long term.

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Last updated 4 months ago