> ## Documentation Index
> Fetch the complete documentation index at: https://kalpi.ai/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Total Trades

> Review the absolute frequency of transactions executed by your strategy.

**Total Trades** records the absolute number of individual buy and sell executions generated by your strategy over the course of the simulation.

This is a foundational execution metric that directly impacts transaction costs, tax liabilities, and the statistical validity of your backtest.

## Evaluating Trade Frequency

<CardGroup cols={2}>
  <Card title="Low Frequency (Under 30 Trades)" icon="turtle">
    Strategies with very few trades (like long-term rotational investing) incur minimal slippage and broker fees. However, if a backtest only triggers 12 trades over 5 years, the sample size is statistically insignificant. The results might be pure luck.
  </Card>

  <Card title="High Frequency (1,000+ Trades)" icon="rabbit-running">
    High-frequency systems provide excellent statistical confidence in their win rates and profit factors. However, they are highly sensitive to real-world friction. If slippage or taxes eat just 0.1% per trade, a high-frequency system can easily turn from profitable to negative.
  </Card>
</CardGroup>

## The Statistical Edge

Institutional quants generally look for a minimum threshold of **100 to 200 total trades** before trusting the output of a mathematical backtest. The higher the Total Trades, the more confident you can be that the strategy has survived multiple different market regimes (bull, bear, and sideways markets) and possesses a genuine structural edge.