Personal Investment Portfolio Stress Board

3.15

Derivation Chain

Step 1 Stock market surge + chaebol owner asset growth

→

Step 2 Individual investor portfolio concentration risk

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Step 3 Bull market portfolio risk stress testing service

Problem

With KOSPI surpassing 6,300 and Lee Jae-yong's stock holdings reaching $30 billion in a surging market, individual investors ($7,400–$370,000 portfolios) are heavily concentrated in a few stocks like Samsung Electronics and SK Hynix. Unlike institutional investors, retail investors lack portfolio stress testing tools (scenarios such as interest rate hikes, semiconductor downcycles, currency volatility) and cannot assess potential losses before a market downturn.

Solution

Users upload brokerage trade history to analyze current portfolio sector and stock concentration. The system simulates estimated loss rates across 10 scenarios (1%p interest rate increase, semiconductor downcycle, USD/KRW reaching 1,500, etc.). Includes concentration warnings and rebalancing recommendations.

Target: Individual investors aged 30–50 with $7,400–$370,000 portfolios, especially those concentrated in semiconductor and AI sectors

Revenue Model: Basic analysis Free (once per month), Premium at $29/month (unlimited simulations + rebalancing alerts), 25% discount for Annual Subscription

Ecosystem Role: Consumer

MVP Estimate: 2_weeks

NUMR-V Scores

N Novelty

3.0/5

U Urgency

3.0/5

M Market

4.0/5

R Realizability

3.0/5

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 (68%)

Tech Complexity

29.3/40

Data Availability

18.3/25

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 (54/100)

Competition

8.0/20

Market Demand

6.2/20

Timing

16.0/20

Revenue Signals

9.0/15

Pick-Axe Fit

7.5/15

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] Data Pipeline [low]

Dashboard