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Backtesting Engine

Test a strategy against years of market history.

A backtest is only useful if you can configure it honestly and interrogate it afterwards. Pulsar lets you set the capital, the window, the universe and the execution assumptions — then hands back every trade, not just a headline return.

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Signals on the price series Entry funnel and exit quality Trade distribution Composite scoring

A configurable engine

You control the assumptions, not a preset.

Default backtests flatter strategies. Pulsar exposes the settings that decide whether a result is real — so the run you keep is the one you actually believe.

01 — SCOPE

Capital, window and universe

Set the starting capital, the historical range and which instruments take part. Run a single symbol to understand behaviour, or a whole universe to see whether the edge generalises.

  • Starting capital and position sizing basis
  • Custom date ranges across years of data
  • Single symbol or multi-symbol universes

02 — EXECUTION

Costs and fill assumptions

Frictionless backtests are fiction. Configure the execution model so the simulated fills resemble what a broker would actually have given you.

  • Commission and fee treatment
  • Slippage assumptions
  • Order handling and fill behaviour

03 — EVIDENCE

Every trade, on the chart

Results are plotted onto the price series with entry and exit markers, so you can see exactly where the strategy acted — and where it sat on its hands through a move you expected it to take.

  • Entry, exit and signal markers on the series
  • Per-trade inspection
  • Timing analysis across the run

04 — DIAGNOSIS

Where the result came from

The engine breaks the run into signal generation, entry funnel and exit quality, so a disappointing number points at a stage you can fix rather than a strategy you must abandon.

  • Signal counts and filter attrition
  • Entry accuracy and conversion rate
  • Exit quality against the ideal exit

05 — DISTRIBUTION

Outcomes instead of averages

Trades are bucketed by return band so you can see the actual shape of the result. A strategy carried by two outliers looks very different here than it does in a mean.

  • PnL distribution by outcome band
  • Win and loss magnitude profiles
  • Hold-time and drawdown behaviour

06 — ITERATION

Compare, tune, run again

Backtesting is a loop, not a verdict. Adjust a parameter in the Strategy Creator, run it again, and hold the two results next to each other before you decide anything.

  • Re-run against an unchanged window
  • Compare variants side by side
  • Promote the version that survives

A word on backtests

Simulated results are evidence, not a promise.

A backtest describes how a rule set would have behaved on data that has already happened. It cannot account for every fill, every gap or every regime change ahead of it. Pulsar gives you the tools to test a strategy rigorously and to see its weaknesses — it does not tell you the future, and neither does any number it produces.

Put your strategy under pressure.

Pulsar is in closed beta. Create an account, or tell us what you are trying to build.

Backtested and simulated results are hypothetical and are not indicative of future results.