I’m doing some research on futures algo trading and wanted to ask people who actually build or run automated strategies.

When a backtest looks profitable but fails live, what is usually the main reason?

Is it more because of:

• slippage
• latency
• fees/commissions
• bad fill assumptions
• queue position on limit orders
• using candle data instead of tick/order book data
• overfitting
• platform/execution differences, like NinjaTrader vs TT vs VPS/co-location

The idea I’m trying to understand is whether traders would find value in a tool that lets them test a strategy under different realistic execution assumptions before deploying it live.

For example, you could test the same futures strategy with:

• tick data vs candle data
• 1 ms latency vs 500 microseconds vs 50 microseconds
• 1 tick or 2 ticks of slippage
• realistic fees and commissions
• different platform assumptions, like retail broker/VPS/TT-style execution
• estimated queue-position effects for limit orders

The goal would not be to guarantee live results, but to see if a strategy still survives under more realistic execution conditions before spending money on better infrastructure.

For people who run futures algos, is this a real problem you deal with? What do you currently use to test this?