Typical output (varies by random seed):
for _ in range(num_trades): # Simulate random order flow: +1 (buy market order), -1 (sell market order), 0 (none) flow = np.random.choice([-1, 0, 1], p=[0.3, 0.4, 0.3]) daemon goldsmith - order flow trading for fun and profit.pdf
Minus exchange fees (e.g., 0.1% taker fee on the exiting trade) → net ~$0.08. Below is a simplified backtest of a Daemon Goldsmith trading against random order flow. Typical output (varies by random seed): for _
pnl = []
# Mark-to-market PnL mtm = cash + inventory * mid_price pnl.append(mtm) final_pnl = pnl[-1] - 10000 print(f"Final PnL: $final_pnl:.2f") print(f"Total trades executed: num_trades") | Risk | Description | |------|-------------| | Adverse
Final PnL: $42.30 Total trades executed: 1000 Note: This ignores fees, slippage, and real market impact – for educational use only. | Risk | Description | |------|-------------| | Adverse selection | Informed traders buy before a drop or sell before a rise. | | Inventory risk | Holding a large long position when price falls. | | Latency | Slower daemons get picked off by faster HFT firms. | | Exchange risk | Downtime, API changes, or withdrawal halts. | | Regulatory | Market making may require registration in some jurisdictions. |