Dashboard

The dashboard gives you a high-level view of trading outcomes and process quality for a selected date range.

KPI blocks in depth

Win Rate

• Formula: winning trades / total trades
• What it shows: hit frequency, not outcome quality.
• Important: a high value can still lose money if average losses are too large.

Gross and Net PnL

• Gross PnL: result before fees and trading costs.
• Net PnL: result after fees and costs.
• What to monitor: increasing gap between gross and net often points to overtrading, poor sizing, or too much low-quality activity.

Profit Factor

• Formula: gross profit / gross loss
• Interpretation:
  • around 1.0: break-even zone
  • below 1.0: strategy loses over the selected period
  • clearly above 1.0: edge is present, but still check drawdown and sample size
• Use with caution: very small sample sizes can make this look artificially strong.

Drawdown

• What it shows: the worst equity decline from a prior peak in the selected period.
• Why it matters: this is your stress and risk tolerance metric, not just a number.
• Review angle: compare drawdown to net PnL; if drawdown grows faster than net PnL, risk efficiency is deteriorating.

Expectancy

• What it shows: expected value per trade over the selected sample.
• Interpretation:
  • positive: edge per trade is positive
  • near zero: results rely on noise and timing luck
  • negative: current execution or setup quality is not sustainable
• Best use: validate process changes after enough new trades are logged.

KPI relationships that matter

Read KPIs as a system, not as isolated values:

• High Win Rate + weak Profit Factor: winners are too small or losers too large.
• Strong Profit Factor + deep Drawdown: edge exists, but risk delivery is unstable.
• Positive Expectancy + flat/negative Net PnL: costs or execution discipline are likely eroding the edge.
• Rising Net PnL + falling Expectancy: performance may be driven by a few outsized trades, not repeatable quality.

Process analysis sections

Performance and equity

• Equity curve progression
• Winner vs loser behavior
• Gross vs net comparison

Process quality diagnostics

• Streak behavior (trades and days)
• Hold-time metrics
• Calendar, weekday, and hour breakdowns
• Symbol and ruleset performance splits

Use these sections to find the cause behind KPI moves. A KPI tells you what changed; diagnostics tell you why.

Date filtering workflow

1. Set a custom from/to range.
2. Compare with presets such as current month or all time.
3. Revisit metrics weekly to detect drift early.

Practical review routine (10-15 minutes)

1. Start with Net PnL, Profit Factor, and Drawdown together.
2. Check if Expectancy confirms the same direction.
3. Open weekday/hour/symbol splits to identify concentration risk.
4. Mark one weak pattern to fix in the next trading block.
5. Re-check after 20-30 additional trades instead of reacting after every session.