RESEARCH TOOL · Vridhi applies systematic quality screening across the US, India, Australia and the UK.
Not financial advice — always verify before acting.
See methodology
Quality-first business research
A systematic framework for finding quality businesses.
Vridhi screens 800+ stocks across the United States, India, Australia and the
United Kingdom through a rigorous quality framework — one standard, four markets,
calibrated to each market's cost of capital and accounting rules.
813
Companies screened
4
Markets covered
5
Point quality gate
Weekly
Data updated
The Vridhi approach
Quality first. Price second.
The most enduring wealth in equity markets comes from owning businesses
with durable competitive advantages, high returns on capital, and genuine cash generation —
bought at prices that don't require heroic growth assumptions.
This isn't a new idea. It's the foundation of how the world's most successful
long-term investors have operated for decades. Vridhi makes this approach systematic,
repeatable, and accessible.
Four Markets. One Framework.
Most tools force you to use different screeners for different markets. Vridhi
applies a single quality standard across the United States (S&P 500), India (Nifty 100),
Australia (ASX 200) and the United Kingdom (FTSE 100) — calibrated for each market's cost
of capital, accounting standards, and sector structure.
Beyond Simple Screening
Traditional screeners filter by P/E or dividend yield — metrics that tell
you about price but nothing about business quality. Vridhi evaluates profitability, cash
generation integrity, valuation, and competitive durability independently, then combines
them into a single quality score.
AI-Powered Research
Every stock comes with an auto-generated research brief covering investment
thesis, key risks, and valuation assessment. For deeper analysis, our analytical layer
provides structured moat, disruption, and management quality analysis — institutional-grade
research at a fraction of the cost.
How Vridhi evaluates a business
Every stock goes through three stages: structural filters eliminate fundamental red flags before
scoring begins; quality scoring assesses multiple independent dimensions of business quality;
and a valuation overlay combines the quality score with relative and intrinsic value methods
to produce the quality verdict.
Research Score
Excellent
Top-tier quality (6–7/7) at fair value or below — strongest Research Score, both quality and valuation confirmed.
Very Good
Top-tier quality at slight premium, or solid quality (5/7) at fair value — quality confirmed, entry price slightly above ideal.
Good
Quality present but valuation elevated, or minimum quality (4/7) at fair value — monitor for improved quality or better price.
Developing
Does not meet the quality threshold (score <4/7) — business quality is still developing or data is insufficient.
These are Research Scores based on quantitative analysis of business fundamentals — not investment recommendations or financial advice.
Who is this for?
Self-directed investors
Who want a systematic, evidence-based approach to stock selection rather than relying on tips, news sentiment, or broker recommendations alone.
Multi-market investors
Investing across the US, India, Australia and the UK shouldn't require four different tools held to four different standards. One framework, one quality bar, four markets.
Quality-focused investors
Who believe that buying durable businesses at reasonable prices, held for the long term, is the most reliable path to wealth creation.
Known limitations
Vridhi is designed for established businesses with visible earnings and cash flow.
It is less suited for:
High-growth platform businesses — companies reinvesting heavily for market share
may score conservatively. We are developing a growth-quality overlay to address this.
Pre-profitability companies — businesses without a track record of positive
cash generation are excluded by design.
Complex conglomerates — consolidated financials may not reflect the quality
of individual business segments.
Banks and insurers — balance-sheet businesses are rated conservatively
by design; they are best evaluated alongside sector-specific measures such as P/TBV,
NIM, and capital adequacy.
Financial data accuracy — all metrics are sourced programmatically from
public financial statements. Always verify key figures from annual reports before acting.
Coverage: Over 800 large-cap and mid-cap companies — the S&P 500 (United
States), India's Nifty 100, the ASX 200 (Australia) and the FTSE 100 (United Kingdom).
Smaller companies and emerging markets are outside current scope.
Choose your market
Select a market to run the QARP quality screen. Results cached for 24 hours.
Type a company name or ticker — search updates as you type. Any stock globally: Zomato, Palantir, small-caps not in any index.
Screening
Fetching live financial data and applying Vridhi QARP factors across all stocks
Initialising...
First screen: US ~8–12 min · India/ASX ~8–12 min · Cached runs ~2–5 min
Important: Vridhi identifies businesses meeting quality criteria
from publicly available financial data. This is not financial advice and does not
constitute an investment recommendation. Valuation metrics use live market prices —
always verify from primary sources before investment decisions.
† Upside values above 80% are displayed as ≥+80% — this is the model's display ceiling. Projected returns of this magnitude require independent verification of the underlying financial inputs.
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Company
Sector
ROIC
GM
CAGR
FCF
ND/EBIT
EV/EBIT
Mom 6m
Research Score
DQ
Detail
Research Queue
Deep-dive candidates from your screens
QARP + Institutional overlay runs on queued names only — sector gates,
forensic checks (accruals, FCF, leverage), cyclicality flags, and compounder archetypes.
Bulk screens stay fast; use Refresh overlay for live data.
US stocks can also fetch SEC EDGAR (1–2 min per name).
Starting EDGAR fetch…
Final picks only — stocks that auto-qualified as Excellent Research Score + Strong quality.
Each "Run Due Diligence" below reads the company's actual 10-K text (real analysis cost, cached
per filing — re-opening a result already generated is free).
📊 Analyst Top Picks — QARP Validated
Stocks analysts love, filtered through Vridhi quality criteria
Click Run Screen to validate analyst top picks through QARP.
Forward Tracker
Cumulative Compelling + Notable signal performance vs local benchmarks
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The Vridhi Approach
Quality first. Price second.
The most enduring wealth in equity markets comes from owning businesses with durable
competitive advantages, high returns on capital, and genuine cash generation — bought at
prices that don't require heroic growth assumptions. Vridhi makes this approach systematic,
repeatable, and accessible.
How we evaluate a business
Stage 1 — Structural filters
Stage 2 — Quality scoring
Stage 3 — Valuation overlay
Research signals
Compelling
Exceptional quality, strict valuation.
Notable
High quality at a reasonable price.
Watchlist
Quality present, await better entry.
Pass
Quality not met or valuation stretched.
Research Tool · Not financial advice. Research signals are based on
published financial data and quantitative analysis. Always verify from primary sources
and consult a qualified financial adviser before making investment decisions.
Methodology
Vridhi Quality At a Reasonable Price (QARP)
Vridhi uses a proprietary multi-factor quality framework to identify fundamentally strong
businesses trading at reasonable valuations, and to filter out businesses with elevated
blow-up risk. The framework is grounded in peer-reviewed academic research on factor
investing and earnings quality, and its risk-screening behaviour has been examined in
long-horizon historical backtesting across two markets (see "What the backtesting shows").
How it works
Every stock is assessed in three stages:
Stage 1 — Pre-screening gates
Stage 2 — Quality scoring
Stage 3 — Valuation overlay
Research signals
The quality tier and valuation band together determine the Research Score:
Excellent, Very Good, Good,
Fully Valued (business passes the quality gate; price is the constraint),
or Developing (the business does not pass the gate).
These are descriptive research labels, not investment recommendations.
AI research commentary
The Research Brief tab on each stock shows a structured research narrative covering competitive moat,
investment thesis, and key risks. Commentary is cached for 30 days and refreshed automatically
via the nightly cron — news headlines are always fetched fresh regardless of commentary age.
For US Research Queue stocks, the Due Diligence tab grounds analysis in the actual 10-K filing text.
A risk-first research philosophy
Vridhi is built on a simple conviction: the most reliable way to compound capital is to
avoid the businesses that destroy it. Before any stock earns a quality label, it must clear
hard structural gates — sustainable leverage, genuine operating cash flow, earnings that
are backed by cash rather than accruals, and disciplined share issuance.
And it works. Across 25 years of market history in the US and Australia — including
the dot-com crash, the GFC and COVID — companies that cleared Vridhi's quality gate were
half as likely to suffer a severe decline as those that didn't.
We re-verify this every time our methodology evolves.
Vridhi is a research and screening platform. It identifies quality and flags risk — it does
not provide investment advice, portfolio management, or performance guarantees. Historical
research is based on backtested data with inherent limitations, and past patterns are not
indicative of future results.
Known limitations
Vridhi is designed for quality-value investing in established businesses with visible earnings
and cash flow. It is less suited for:
Pre-profitability or early-stage growth companies
Platform and network-economy businesses that reinvest heavily (FCF-light models)
Conglomerates where consolidated financials obscure segment-level quality
Financial sector companies (banks, insurers, NBFCs) — EV/EBIT and FCF-based scoring
does not apply to balance-sheet businesses. These stocks appear in results capped at "Good";
use P/TBV, NIM, and CAR metrics to evaluate them independently.
All financial data is sourced programmatically. Verify key figures from primary sources
(annual reports, regulatory filings) before acting on any research signal.
Not financial advice.
Vridhi Admin
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📖 Label Reference — two independent scales
One scale, two inputs. The Research Score is a 2D matrix:
quality tier (from qarp_points /7, accounting only) ×
valuation band (sector-relative EV/EBIT). Trajectory (0–2)
only ranks stocks within a tier — it never changes the label.
Overlays can only downgrade: financial-sector stocks cap at Good (model not
validated for banks/insurers), and the negative-return / growth-saturation
gates drop a stock to its tier's Overvalued cell (Strong → Good,
Sound/Solid → Fully Valued).
Scoring mapping — quality tier × valuation band
Tier \\ Band
Deep / Fair Value
Slight Premium
Overvalued
Unknown
Strong (6–7/7)
Excellent
Very Good
Good
Good
Sound (5/7)
Very Good
Good
Fully Valued
Good
Solid (4/7)
Good
Fully Valued
Fully Valued
Fully Valued
Below gate (<4/7)
Developing — regardless of valuation (also: financial NPA/CAR disqualifier)
What each label means
Research Score
Meaning
Excellent internal: Compelling
Strong quality (6–7/7) at fair value or below — top-tier accounting quality and valuation both confirmed.
Very Good internal: Notable
Strong quality at slight premium, or Sound quality (5/7) at fair value — quality confirmed, entry price slightly above ideal.
Good internal: Watchlist
Quality present but valuation elevated or unverifiable, minimum quality (4/7) at fair value — or a financial-sector stock (hard cap: the v4 model is not validated for banks/insurers). Worth monitoring.
Fully Valued internal: Pass, quality ≥4/7
The business passes the quality gate but the price does not — Sound quality overvalued, minimum quality at a premium, or a projected negative return. Price, not quality, is the constraint.
Developing internal: Pass, quality <4/7
Does not meet the quality threshold (score <4/7), or fails a hard disqualifier. The business itself is the constraint.
Internal identifiers (Compelling/Notable/Watchlist/Pass) are stable keys used in storage
and code comparisons. Display labels (Excellent/Very Good/Good/Fully Valued/Developing) are
rendered via action_labels.display_label(action, qarp_points) — the Fully
Valued/Developing split is display-only (both are internally "Pass"). These are quality
assessments based on quantitative analysis of business fundamentals — not investment
recommendations or financial advice.
Source: recommendation_action → displayAction() (app.py) /
_sell_side_rating() (newsletter.py). Computed by the recommendation engine
(recommend.py): 2D matrix of quality tier (Strong/Sound/Solid) × valuation band assigns
the Research Score. Trajectory (0-2) is used for intra-tier ranking only. Shown in: main
table's Research Score column, the drawer's Vridhi Recommendation box, Newsletter,
Research Brief, and the Value Comparison tool's Research Score column.
Retired: separate timing-signal scale
forward_signal (Compelling/Watchable/Wait, price+momentum only, deliberately
ignoring quality) used to be shown as an independent scale in the Value Comparison tool's
Signal column, separately from the action scale used everywhere else — the exact
"Compelling means something different here than there" ambiguity that caused repeated
"looks broken" reports. For v4-scored rows, the Value Comparison tool now reads the same
action label every other surface uses, not this field. forward_signal itself
is kept only as an internal compatibility value (set equal to the action for v4 rows) for
a small number of older read-sites still being phased out — it is not meant to be read as
an independent signal anymore.
📌 Forward Tracker — Lock Newsletter
Lock the current newsletter cohort to the Forward Tracker for monthly performance tracking.
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💾 Saved Screens
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🔍 Internal Research Tools
Advanced tools — for internal analysis and audit use only.
🔄 Refresh Val Map Prices
Updates current price + 52W range for all cached stocks from yfinance.
Vridhi valuation columns are always re-computed live. Takes ~30–60 seconds.
🏛️ EDGAR-Validated Buy List (US)
Cross-checks every currently Notable/Compelling rated US stock against SEC EDGAR
filing data in one pass, instead of checking stocks one at a time in the
Research Queue. Shows whether the screen's recommendation (Yahoo-sourced)
still holds up against the filing-sourced rescore.
✦ Research Commentary — Pre-generate Cache
Generates research commentary for all screened stocks and stores on persistent disk.
Users then get instant cached results at zero per-user cost.
Run once after each weekly screen refresh. ~$20 for all 434 stocks × 3 horizons.
🧪 System Health — Offline Test Suite
Runs 20 offline unit + pipeline tests: scoring math, newsletter gating,
v4 label correctness, field-sync invariants, financial carve-out routing.
No API calls — completes in under 2 seconds.
📰 Monthly Newsletter
Generate the monthly quality research briefing from all cached screens. Opens in a new tab.
Admin session is browser-tab scoped and does not persist across reloads.
Click 🔍 Due Diligence to run the full checklist, grounded in this
company's actual 10-K text. Research Queue only — this run costs
real analysis cost, cached per filing so re-opening it later is free.