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. |
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.
pnl = []
if flow == 1: # Aggressive buyer hits our ask cash += ask_limit inventory -= 1 elif flow == -1: # Aggressive seller hits our bid cash -= bid_limit inventory += 1
| Component | Description | |-----------|-------------| | | Buying at bid, selling at ask. | | Rebates | Some exchanges pay fees for adding liquidity (maker rebates). | | Adverse selection | Risk of being picked off by informed traders. | | Inventory management | Offsetting unwanted exposure. |
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
Gross profit = $100.07 – $99.98 = $0.09 per unit.
# 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")
Typical output (varies by random seed):
Profit.pdf: Daemon Goldsmith - Order Flow Trading For Fun And
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. |
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.
pnl = []
if flow == 1: # Aggressive buyer hits our ask cash += ask_limit inventory -= 1 elif flow == -1: # Aggressive seller hits our bid cash -= bid_limit inventory += 1
| Component | Description | |-----------|-------------| | | Buying at bid, selling at ask. | | Rebates | Some exchanges pay fees for adding liquidity (maker rebates). | | Adverse selection | Risk of being picked off by informed traders. | | Inventory management | Offsetting unwanted exposure. | daemon goldsmith - order flow trading for fun and profit.pdf
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
Gross profit = $100.07 – $99.98 = $0.09 per unit. Final PnL: $42
# 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")
Typical output (varies by random seed):
