The method
This product is built on the idea that retail investors lose money for behavioural reasons more than analytical ones. The literature on that is large. The short version below is what informed every screen — and how the research maps to the 30-second decision check, your personal rules, cooldowns after losses, a discipline trend, and an AI coach for the emotional side. The primary KPI is decisions saved, not trades entered.
1. Prospect theory (Kahneman & Tversky, 1979)
Losses hurt roughly twice as much as equivalent gains feel good. That asymmetry makes traders cut winners early and let losers run. The fix isn't motivation — it's a stop and an invalidation level decided before the trade, captured as fields in the decision check, and a process that rewards the decision rather than the P&L.
2. Illusion of control (Langer, 1975)
Active choice creates the feeling of control even when the outcome is random. Every additional trade you place increases that feeling — and the risk. The Decisions saved counter (avoided, postponed, sized down) reframes inactivity as a positive outcome, and shows up on the dashboard right next to your weekly discipline score.
3. Base-rate neglect (Tversky & Kahneman, 1973)
People weigh the vivid story ("this chart looks like 2020") and ignore the base rate ("most setups in this regime don't work"). The 5-question check exists to make you state the base rate before you place the trade, and the Insights screen calibrates your stated confidence against actual outcomes over time.
4. Pre-mortems (Klein, 2007)
Imagining failure before committing surfaces risks that post-hoc analysis misses. The check captures a single line — "if this fails, the most likely reason is…" — and the debrief re-surfaces it after the trade closes, so calibrated intuition builds faster than journaling P&L alone.
5. Discipline as a composite score
The Weekly Discipline Score on the dashboard combines three things: Decision Quality(the 0–100 score from your checks), Emotional Calm (the inverse of your stated emotional intensity), and Rule Compliance (the share of plans with zero rule violations). None of these is P&L. That is intentional: P&L on any one trade is noise; process is the only thing you control.
How the Decision Quality score is calculated
The Decision Quality score is a deterministic, pre-trade assessment built from 7 weighted dimensions of your decision check. Higher is better. It evaluates the process, not the likely outcome.
- Risk:reward ≥ 215% weight
Whether the first target gives you at least 2× the risk distance from entry to stop.
How to improve: Tighten the stop or extend the target so R:R ≥ 2.
- Stop is set8% weight
Whether a hard stop price is defined before submitting.
How to improve: Always enter a stop. No stop = no trade.
- Position size set7% weight
Whether a dollar position size is entered.
How to improve: Size from the stop and risk %, not from how good the idea feels.
- Rule compliance25% weight
100 if no personal rules tripped. Each violation also deducts 15 pts from the total DQ.
How to improve: Define rules in Settings → Rules. The check enforces them inline.
- Emotional discipline25% weight
Inverse of the 3-question emotional check (FOMO, recovery, stress). Calm = full credit.
How to improve: Pause when answers show FOMO, recovery, or stress. Re-check after a break.
- Following a plan5% weight
Self-attestation: are you following a plan, or improvising?
How to improve: If no, write the plan down before answering yes.
- Clear reason5% weight
Self-attestation: can you articulate why this trade, why now?
How to improve: If you can't say it in one sentence, you don't have a reason yet.
- Information readiness10% weight
How many of the 4 Pre-Decision Awareness buckets you considered (catalysts, sentiment, risk, valuation).
How to improve: Tick the awareness items relevant to this trade.
- Thesis validation5% weight
Picking a primary thesis and confirming whether historical price context supports it (with optional note).
How to improve: Pick a thesis. Answer whether history supports it. A short 'why' note adds full credit.
- Pre-mortem5% weight
A one-line answer to 'if this fails, the most likely reason is…' before risking capital.
How to improve: Write 60+ characters describing the most likely failure mode.
6. The human side — the AI coach
Discipline isn't just rules; it's the emotional context around them. The built-in coach is a non-judgmental sounding board, not a signal service. It surfaces gently when the system detects a high-risk emotional state — a post-loss prompt after a red day, an intervention banner when you're about to plan a revenge trade, a check-in after a string of overconfident wins. You can always start a session yourself; nothing the coach says is financial advice.
7. Personal rules, cooldowns, and the morning ritual
You write your rules in plain language ("no trades in the first 15 minutes", "max 2 losses then stop"). The check enforces them inline and blocks plans that break them, with the reason shown. After a high-risk decision or a losing day, a cooldown auto-pauses new plans for a configurable window. An optional morning ritual asks for sleep, mood, and intent before you can plan that day — friction in the right place beats willpower.
What this product is not
It is not a screener, charting tool, copy-trading service, AI signal provider, or trading bot. Those tools optimise for entries. This tool optimises for the trades you don't take — and for staying calm, consistent, and honest about your own track record on the ones you do.