A high-fidelity monitoring terminal for the USDT/IDR pair, built for liquidity analysis and execution simulation across Indonesian exchanges. This project focuses on minimizing latency and maximizing the visibility of order book depth through a "Terminal-as-a-Service" UI.
In the Indonesian crypto ecosystem, the USDT/IDR pair serves as the foundational gateway for digital asset trading. For a Business Operations team, the "ticker price" is often a surface-level metric. The real operational challenge lies in Liquidity Depth.
When a market is "thin" (low density of orders in the book), even a moderate trade can cause the price to move unfavorably. This phenomenon, known as Slippage, directly increases the cost of doing business and negatively impacts user experience.
Imagine a scenario where a Business Operations Associate must execute a 100,000,000 IDR sell order to rebalance company liquidity:
- The Ticker Price: 16,971 IDR.
- The Problem: There isn't enough immediate demand at 16,971 to fill the entire 100M IDR order.
- The Reality: To complete the sale, the order "walks" down the order book, filling at progressively lower prices.
- The Goal: This dashboard was built to predict this exact cost before the trade is executed, allowing for smarter, data-driven execution strategies.
This dashboard is a high-frequency monitoring tool that transforms raw exchange data into three actionable operational insights:
- Slippage Prediction: Calculates the Volume Weighted Average Price (VWAP) for any specific trade size in real-time.
- Liquidity Visualization: Provides a cumulative view of "Market Walls" to identify where buyers and sellers are concentrated.
- Spread Health: Monitors the gap between Bid and Ask to identify periods of market stress or inefficiency.
The top row of the dashboard displays the Pulse of the Market:
- Best Bid/Ask: The current highest buy and lowest sell prices available on the exchange.
- Spread (%): A critical health metric. A widening spread indicates a volatile or illiquid market where trading becomes expensive.
The Execution Simulation panel on the left allows you to act as an Ops Manager or Institutional Trader:
- Select Side: Choose Buy or Sell.
- Trade Amount: Input your target volume in IDR (e.g., 500,000,000).
- Analyze Impact: The dashboard instantly calculates the Execution VWAP and Est. Slippage.
- Operational Tip: If slippage exceeds 0.2%, an Ops Manager might choose to split the order into smaller "slices" or wait for a period of higher liquidity.
The Market Depth Chart (Green and Red areas) visualizes the future of price movement:
- The Green Area (Bids): Represents the "Floor." A steep green mountain indicates strong buy support; the price is unlikely to drop quickly.
- The Red Area (Asks): Represents the "Ceiling." A tall red mountain indicates heavy selling pressure.
- The Mid-Point: The narrow gap between these areas is where the spread exists.
The Price History and Spread History charts help identify correlation. For example, if the spread widens during a price drop, it indicates that liquidity is being pulled from the book, signaling a "Flash Crash" risk.
- Engine: Powered by the CCXT library for robust API communication with Indodax/Tokocrypto.
- Update Frequency: The dashboard utilizes a 1Hz (1 second) refresh rate to ensure order book data reflects the current market heartbeat.
The dashboard iterates through the Limit Order Book (LOB) to find the true execution price based on volume:
- Python 3.10+
- Streamlit: For high-performance, real-time UI/UX.
- Plotly: For interactive, financial-grade charting.
- Pandas: For real-time data frame manipulation and cumulative liquidity calculations.
- Clone the repository:
git clone https://github.com/handiko/USDT-IDR-Monitoring-Dashboard - Install dependencies:
pip install streamlit ccxt plotly pandas - From the python folder, launch the application:
streamlit run app.py
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