Platform Features

HyperTrade aims to democratize algorithmic trading and crypto analytics by combining the power of LLMs with community-driven insights on a scalable blockchain infrastructure. By integrating HyperTrade proven technology, providing robust backtesting and deployment of live algorithmic trading, and building a vibrant marketplace around proven strategies, HyperTrade aspires to become a cornerstone in the rapidly expanding digital asset ecosystem.

Platform Features

HyperTrade has four core components:

1. No-Code Strategy Builder

   • Users describe a strategy in plain language (e.g., “Buy RSI below 30 and sell when RSI above 70”). Integrate a Large Language Model (LLM) that interprets user prompts and auto-generates code snippets for Freqtrade-based strategies.

   • The system interprets the description, generates the underlying trading logic, and visualizes it.

   • Users can adjust parameters (timeframe, Assets, risk settings & trade size) through dropdowns settings.

2. Backtesting Engine

   • Runs strategies on historical data from major exchanges (Binance, Hyperliquid).

   • Data is sourced directly from each exchange’s official APIs or archives.

   • Results include profit/loss curves, drawdowns, and key metrics (Sharpe ratio, win rate).

   • Users can compare multiple versions of a strategy side by side.

3. Live Deployment Module

   • Connects to user exchange accounts via API keys.

   • Deploys strategies in a containerized environment on Kubernetes.

   • Monitors positions, orders, and risk in real time.

   • Provides a dashboard showing live performance and logs.

4. Marketplace

   • Strategy creators publish their models with descriptions and performance stats.

   • Buyers or subscribers can browse by category, performance, or fee structure.

   • HyperTrade I handles subscription payments and access control.

   • Creators set their own prices; HyperTrade takes a 2–5% commission per sale or subscription.

---

4. Core Components in Detail

4.1 No-Code Strategy Builder

• Natural Language Processing

  • Users enter plain‐language descriptions of buy/sell rules.

  • The NLP engine maps keywords (“RSI,” “MA,” “crossover”) to technical indicators.

  • It proposes a draft strategy script in Python/Freqtrade format.

• Visual Interface

  • Users can link blocks to define logical flows (e.g., “If RSI < 30 AND price > 20‐day MA, then buy”).

  • Parameter panels let users set values for lookback periods, risk %, position size.

• Templates & Examples

  • Built‐in templates for common strategies (momentum, mean reversion, breakout).

  • Example scripts show best practices for risk management.

  • Users can clone and tweak examples.

4.2 Backtesting Engine

• Data Sources

  • Official OHLCV (open, high, low, close, volume) feeds from each exchange.

  • Minute‐level and hour‐level data stored for up to two years.

  • Automatic updates every day to keep the dataset fresh.

• Simulation Framework

  • Uses Freqtrade’s backtesting module.

  • Supports backtesting on multiple timeframes (5 m, 15 m, 1 h, 4 h, 1 d).

  • Accounts for fees, slippage, and order types (market, limit).

• Result Metrics

  • Net profit and loss (PnL).

  • Maximum drawdown.

  • Sharpe ratio.

  • Win rate and profit factor.

  • Charts: equity curve, drawdown curve, distribution of returns.

• Reporting

  • PDF or CSV export of detailed logs.

  • Side‐by‐side comparison of up to five strategies.

  • Downloadable backtest configurations.

4.3 Live Deployment Module

• Exchange Integration

  • Support for HyperLiquid

  • Users generate API keys with read/write permissions and input them in HyperTrade.

  • Secure key storage: encrypted at rest and in transit.

• Containerized Strategy Runners

  • Each user deployment spins up a separate pod running Freqtrade.

  • Pods auto‐restart on failure.

  • Health checks monitor order placement and connectivity.

• Monitoring & Alerts

  • Real‐time dashboard shows open orders, filled orders, PnL.

  • Logs streamed to Cloud Logging.

  • Alerts for connectivity issues, API rate limits, or failed orders.

4.4 Marketplace

• Listing Strategies

  • Creators submit a name, description, and performance summary.

  • They upload backtest reports and any supporting documentation (PDF, screenshots).

  • They select a pricing model: flat fee or subscription.

  • HyperTrade verifies the backtest report for data validity but does not guarantee performance.

• Browsing & Discovery

  • Users filter by asset class (e.g., BTC, ETH, altcoins), timeframe, risk profile, or price.

  • Sorting by highest return, lowest drawdown, popularity, or newest.

  • Ratings and reviews from subscribers.

• Purchase & Subscription

  • Buyers pay with SOL or HyperTrade tokens.

  • HyperTrade holds payment in escrow for a trial period (e.g., 7 days).

  • If the buyer keeps the strategy live after the trial, funds release to the creator minus a 2–5% fee.

• Creator Dashboard

  • View subscription counts, revenue, and churn rate.

  • Options to update or delist strategies.

  • Analytics on user engagement and feedback.