Retail Trader Auto-Journal Bot

3.50

Derivation Chain

Step 1 KOSPI surge and semiconductor stock volatility

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Step 2 Retail investor trade journaling needs

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Step 3 Automated trade journal SaaS

Problem

With the KOSPI breaking 5,900 and SK Hynix hitting ₩1,000,000 (~$750), retail investors execute dozens of trades per day in volatile markets but fail to systematically record their rationale, emotions, and outcomes — repeating the same mistakes. Brokerage apps only show execution history without capturing the reasoning or market context behind each trade, leading to average recurring losses of $112-225/month.

Solution

Parses brokerage MTS notifications (via KakaoTalk/SMS) to auto-collect trade executions, then auto-attaches market context at the time of each trade (KOSPI index, sector performance, related news headlines) to generate a trade journal. Weekly/monthly Reports visualize recurring patterns (delayed stop-losses, FOMO buying, etc.) to drive behavioral correction.

Target: Active retail traders aged 20-40 with 20+ trades per month

Revenue Model: SaaS Monthly Subscription at $3.70/month per account (Basic Plan), Premium (with AI pattern analysis) at $7.40/month, 20% discount for Annual Subscription

Ecosystem Role: Supplier

MVP Estimate: 2_weeks

NUMR-V Scores

N Novelty

2.0/5

U Urgency

4.0/5

M Market

4.0/5

R Realizability

4.0/5

V Validation

3.0/5

NUMR-V Scoring System

N Novelty	1-5	How uncommon the service is in market context.
U Urgency	1-5	How urgently users need this problem solved now.
M Market	1-5	Market size and growth potential from proxy indicators.
R Realizability	1-5	Buildability for a small team with realistic constraints.
V Validation	1-5	Validation signal quality from competition and demand data.

SaaS N=.15 U=.20 M=.15 R=.30 V=.20 Senior N=.25 U=.25 M=.05 R=.30 V=.15

Feasibility (69%)

Tech Complexity

29.3/40

Data Availability

20.0/25

MVP Timeline

20.0/20

API Bonus

0.0/15

Feasibility Breakdown

Tech Complexity	/ 40	Difficulty of core implementation stack.
Data Availability	/ 25	Practical availability and cost of required data.
MVP Timeline	/ 20	Expected time to ship a usable MVP.
API Bonus	/ 15	Bonus for viable public API leverage.

Market Validation (56/100)

Competition

8.0/20

Market Demand

6.2/20

Timing

14.0/20

Revenue Signals

10.5/15

Pick-Axe Fit

10.5/15

Solo Buildability

7.0/10

Validation Breakdown

Competition	/ 20	Signal quality from competitor landscape.
Market Demand	/ 20	Demand proxies from search and mention patterns.
Timing	/ 20	Fit with current shifts in tech, behavior, and regulation.
Revenue Signals	/ 15	Reference evidence for monetization viability.
Pick-Axe Fit	/ 15	How well the concept serves participants in a trend.
Solo Buildability	/ 10	Practicality for lean-team implementation.

Technical Requirements

Backend [medium] Frontend [medium] AI/ML [low]

Dashboard