Backtesting trading strategies starts with market-data quality

Backtests need more than a result number

A backtest can look precise while still being based on incomplete data. Missing candles, stale symbols, and unclear order assumptions can make a trading strategy appear stronger or weaker than it really is.

That is why a backtesting workflow should show the data state before the strategy run. Coverage, freshness, and open gaps are part of the research context, not secondary details.

What to check before trusting a run

Before comparing strategy variants, review:

• Market and timeframe coverage
• Open data gaps and stale candles
• Trade count, drawdown, and order-level outcomes
• Whether the test period matches the strategy idea

Umbre Trading brings those checks into the same workspace as the visual strategy builder, so a rule set can move from idea to data review to backtest without losing context.

Repeatable strategy research

The goal is not to make a backtest look good. The goal is to make strategy research repeatable enough that a result can be inspected, challenged, and improved.