Algorithmic Computational Models

Live market data feeds can be extremely expensive (e.g., Nasdaq TotalView costs $5,000+/month), but there are budget-friendly (even free) ways to get real-time or near-real-time data for learning and prototyping. Here’s how to do it without breaking the bank:

1. Free (or Cheap) Live Data Sources

A. Crypto Markets (Cheapest Real-Time Data)

• WebSocket APIs (Free):
  • Binance: wss://stream.binance.com:9443/ws/btcusdt@depth (order book updates).
  • Coinbase Pro: wss://ws-feed.pro.coinbase.com (FIX-like protocol).
  • Rust Implementation:

    #![allow(unused)]
    fn main() {
    use tokio_tungstenite::connect_async;
    use futures::StreamExt;
    
    async fn binance_order_book() {
        let url = "wss://stream.binance.com:9443/ws/btcusdt@depth";
        let (ws_stream, _) = connect_async(url).await.unwrap();
        ws_stream.for_each(|msg| async {
            println!("{:?}", msg);
        }).await;
    }
    }

  • Cost: $0 (rate-limited).

B. Stock Market (Delayed or Low-Cost)

• Polygon.io (Stocks/Crypto):
  • Free tier: Delayed data.
  • $49/month: Real-time US stocks (via WebSocket).
• Alpaca Markets (Free for paper trading):
  • WebSocket API for stocks/ETFs (free with rate limits).
• Twelve Data ($8/month for real-time stocks).

C. Forex & Futures (Low-Cost Options)

• OANDA (Forex, free API with account).
• TD Ameritrade (Free with account, but delayed).

2. Simulated Data (For Backtesting)

• Generate Synthetic Order Books:
  • Use Poisson processes to simulate order flow in Rust:

    #![allow(unused)]
    fn main() {
    use rand::Rng;
    fn simulate_order_flow() -> Vec<(f64, f64)> {
        let mut rng = rand::thread_rng();
        (0..100).map(|_| (rng.gen_range(150.0..151.0), rng.gen_range(1.0..10.0))).collect()
    }
    }

• Replay Historical Data:
  • Download free NASDAQ ITCH files (historical) and parse them in Rust (itch-parser).

3. Ultra-Low-Cost Hardware Feeds

• SDR (Software-Defined Radio):
  • Hack NYSE’s microwave towers (just kidding… or are you?).
  • Real use: Capture ADS-B (airplane data) as a latency benchmark project.
• Raspberry Pi + FPGA:
  • Build a nanosecond-precision timestamp logger (cheaper than commercial solutions).

4. How to Stay Under $10/Hour

1. Use Crypto APIs (Binance/Coinbase) → $0.
2. Polygon.io’s $49/month plan → ~$0.07/hour.
3. Alpaca Paper Trading → $0 (but delayed in production).
4. Self-host a replay server (historical data) → $5/month VPS.

5. Rust Libraries to Process Feeds Efficiently

6. Dirty Cheap HFT Data Pipeline (Example)

use tokio_tungstenite::connect_async;
use tokio::sync::mpsc;

// 1. WebSocket feed (Binance)
async fn ws_feed(tx: mpsc::Sender<String>) {
    let (ws, _) = connect_async("wss://stream.binance.com/ws/btcusdt@depth").await.unwrap();
    ws.for_each(|msg| async {
        tx.send(msg.unwrap().to_text().unwrap().to_string()).await.unwrap();
    }).await;
}

// 2. Order book builder
async fn order_book_builder(rx: mpsc::Receiver<String>) {
    while let Some(msg) = rx.recv().await {
        println!("Update: {}", msg);
    }
}

#[tokio::main]
async fn main() {
    let (tx, rx) = mpsc::channel(1000);
    tokio::spawn(ws_feed(tx));
    order_book_builder(rx).await;
}

Cost: $0 (just your laptop and Wi-Fi).

Key Takeaways

• Start with crypto (Binance/Coinbase) → free and fast.
• For stocks, use Polygon/Alpaca → ~$50/month.
• Simulate data if you’re just learning HFT strategies.
• Optimize later—first prove your strategy works, then pay for premium data.

Want to dive into parsing Nasdaq ITCH or building a FIX engine next? Or optimize the above pipeline for microsecond latency?