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Business Proposal

NanoScalp Forecaster AI Crypto Auto-Trading Fund

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Executive Summary

NanoScalp Forecaster is an advanced cryptocurrency auto-trading fund system powered by cutting-edge AI technology. This system generates stable and sustainable returns through real-time market data analysis and machine learning algorithms.

  • Target monthly return: 5-10%
  • 24/7 automated trading system
  • Built-in risk management system

Business Model

Revenue Structure

  • • AI algorithm-based automated trading
  • • Accumulate small profits through nano-scalping strategy
  • • Arbitrage trading leveraging market volatility

Revenue Distribution

  • • Investor net profit: 70% of monthly net profit
  • • System usage fee: 30% of monthly net profit

Revenue Distribution Structure

Investor
70%
System
30%

Investment Example

₩9 Million Investment Scenario

Initial Investment₩9,000,000
Monthly Return (Target)5%
Monthly Profit₩450,000
System Fee (30%)-₩100,000
Net Amount₩350,000

Next Month Principal (with Reinvestment)

₩9,350,000

Projected Annual Principal
With compound reinvestment, Return: 56%

₩14,570,000

※ Important Notice: The above returns are based on target rates and actual returns may vary depending on market conditions. Past performance does not guarantee future returns, and there is a possibility of principal loss.

Risk Management

Loss Minimization

Loss minimization strategy applied

Diversification

Multi-coin portfolio

Reserve Fund

10% reserve for emergencies

Technology Stack

AI Algorithm

  • Nano-scalping strategy
  • Ensemble learning model
  • Volatility prediction

News Data Collection

  • Domestic & international financial news analysis
  • Social media sentiment analysis
  • Real-time indicator generation

Market Sentiment Analysis

  • Fear & Greed Index analysis
  • Trading volume pattern recognition
  • Global market correlation

Team

CEO

Finance & AI Expert

CTO

AI/ML Engineer

CFO

Risk Management Specialist

Grow Together with Investment

Generate stable returns with AI technology

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