Holding Time Tab Guide

~6 min – the duration autopsy that finally proves whether you’re letting winners breathe… or strangling them before they can run, and whether your losers are cut fast enough or left to fester

You’ve already ranked your playbook tags by R. You’ve dissected exit quality and types. You’ve watched time-of-day bleed in Temporal Performance.

Now open Holding Time (ninth tab in CharterElite, Clock icon).

This tab ignores setups, regimes, and psychology in isolation. It obsesses over one variable: how long you actually hold positions (in hours), then slices performance by duration buckets, winner/loser averages, exit behaviors, regimes, and position management style.

It answers the question most traders never ask out loud: “Am I holding too long (greed), too short (fear), or just right… and does it change by day of week or regime?”

Where to Find It

• Sidebar → CharterElite
• Ninth tab → Holding Time (Clock icon)
• Expand tab help accordion (top) for quick benchmarks + pro tips (“peak performance holding periods”, “optimize exit timing”, “position management rules”)

Filters – Exit-Date Focused

Top card (all sections respect these):

• Portfolio — All or single
• Setup — Multi-select
• Side — LONG / SHORT / Both
• From / To — Date range on exit (exit_date / date) — not entry

Only completed trades count (they have exit and holding time data).

How Holding Time Is Resolved

• Preferred: holding_time_hours (canonical field) — positive finite number used as-is
• Fallback: `(exit_time - entry_time)` in ms → hours (if both times valid)
• ≤0 or missing? → excluded from distribution, chart, best/worst, optimal logic

Summary stats (avg/median/min/max/best/worst) use only positive holding times.

Six Summary Metric Cards – Instant Duration Snapshot

Top row:

• Average Holding Time — Mean of valid holding times (hours)
• Median Holding Time — 50th percentile
• Shortest Trade — Minimum positive holding time
• Longest Trade — Maximum holding time
• Best Holding Time — Duration of highest-PnL trade (among valid holding times)
• Worst Holding Time — Duration of lowest-PnL trade

PnL from pnl / net_pnl / gross_pnl.

Holding Time Distribution Chart – The Duration Shape

Bar histogram (10 bins):

• Bins auto-calculated: min → max range divided into 10 equal buckets
• If min = max → single bar 100%
• Y: trade count per bin
• Tooltip: time range, count, %
• Only trades with holding time >0 included

Empty? → Hidden + “No Holding Time Data Available”

Optimal Hold Time Analysis – Winner vs Loser Duration

Shown if ≥1 winning trade (PnL >0):

• Avg Winner Hold Time — Mean duration of positive-PnL trades
• Avg Loser Hold Time — Mean duration of ≤0 PnL trades (if any)
• Recommendation — Compares win rate of Q1 (shortest 25% holds) vs Q3 (longest 25% holds):

“Shorter holds win rate X% vs longer Y% — favor [shorter/longer] durations”

Insufficient winners? → “Insufficient data to generate recommendations”

Holding Time by Exit Behavior

(Requires EXIT taxonomy tags via trade_comment_ids + source_type = 'exit')

Table (≥3 trades per item):

• Exit Behavior (item_code or name)
• Count
• Avg Hold Time
• Median
• Range (min–max hours)

Sorted avg hold descending.

Empty? → “No EXIT taxonomy items found” + tag suggestion.

Holding Time by Market Regime

(Requires market_regime on trades)

Table (≥3 trades per regime):

• Market Regime
• Count
• Avg Hold Time
• Range (min–max)

Sorted avg hold descending.

Empty? → “No market_regime data found”

Position Management Impact – Scaled vs Single Duration

• Scaled — position_entries or position_exits array length >1
• Single — All others with valid holding time

Two cards:

• Scaled In/Out: count, avg, median
• Single Entry/Exit: count, avg, median

If both groups exist → insight line: “Scaled positions are held X.XX× longer on average”

Empty? → “No position management data found”

Quick Workflow – Duration Murder Ritual

1. Open Holding Time → set filters (last 6–12 months, main setups)
2. Read six summary cards → avg hold reasonable? Best/worst durations make sense?
3. Study Holding Time Distribution → most trades cluster where? (short scalps? long swings?)
4. Check Optimal Hold Time → shorter or longer holds win more? → adjust exit timing
5. Tagged EXIT? → Holding Time by Exit Behavior → panic exits short? Disciplined exits long?
6. Regime-tagged? → Holding Time by Market Regime → chop regimes held too long?
7. Position data? → Position Management Impact → scaled held longer → intentional or drift?
8. Action: avg winner hold short + high MFPE in PEE? → widen targets/trail. Long loser holds? → tighten stops.

Quick Reality Checks

• Avg hold <1h but strategy swing? → Over-trading or fear exits
• Distribution all short holds? → Scalping bleed—check R Distribution for small R
• Optimal says shorter wins? → Greedy holds killing you—force earlier partials
• No EXIT table? → Tag exit behaviors harder
• Scaled held much longer? → Adding to winners or losers? Cross to behavioral audit
• No holding time data? → Fill entry/exit times properly

Next: Episode 32 – Full Flywheel Mastery: Integrating Weekly Alpha → Calendar Analytics → CharterElite (Holding Time, Trade Management, Playbook Analysis, Exit Analysis, R Distribution, Temporal, Performance Ratios, PEE) → Council (Kill List, Reality Check, Setup DNA) → Evolution into the self-reinforcing compounding loop that turns monthly audits into weekly micro-kills and quarterly A-grade upgrades—without ever increasing risk % or chasing new shiny setups.

Or open CharterElite → Holding Time right now. Set last 12 months + your main setups.

Look at Avg Winner Hold Time vs Avg Loser Hold Time.

Winner shorter than loser? That’s greed holding losers and fear cutting winners.

Now check Optimal Hold Time recommendation.

It just told you which duration prints.

Obey it.

Adjust exits. Tag holding-time patterns. Re-run in 20 trades.

Your edge isn’t in entries. It’s in how long you let them live.

Give winners oxygen. Give losers a quick death.

The holding time chart doesn’t forgive. It measures.

Make the winners longer. Make the losers shorter.

One hold at a time.

Your future R-multiples are counting on it. 😈