Daemon Goldsmith - Order Flow Trading For Fun And Profit.pdf -

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])

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. | 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. for _ in range(num_trades): # Simulate random order

import numpy as np import pandas as pd spread = 0.05 half_spread = spread / 2 mid_price = 100.00 inventory = 0 cash = 10000 num_trades = 1000 Daemon's limit prices bid_limit = mid_price - 0.02 ask_limit = mid_price + 0.07 | | Latency | Slower daemons get picked