Today · Demo
Today's factor leaders
Quality and low-volatility factors continued to outperform this week; momentum cooled in high-beta names.
Daily market updates, quant finance education, a private community, and access to proprietary US equity rankings from a 118-factor accounting-data model.
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| # | Ticker | Composite | 7d |
|---|---|---|---|
| 1 | DMO.A | 94.2 | +3 |
| 2 | DMO.B | 92.8 | -1 |
| 3 | DMO.C | 91.5 | +5 |
| 4 | DMO.D | 90.1 | +8 |
| 5 | DMO.E | 88.7 | -2 |
| 6 | DMO.F | 87.4 | +4 |
Quality
Leading
Value
Neutral
Momentum
Mixed
netQuants helps you understand the data behind markets — from accounting fundamentals to factor rankings and daily model updates. Built around a proprietary 118-factor US equity model, netQuants turns raw financial data into structured research signals.
Every publicly traded US company is scored across ten factor categories combining accounting data and market data. Rankings update daily.
Value
Price relative to fundamentals
Quality
Profitability, stability, capital efficiency
Profitability
Margins and returns on capital
Growth
Revenue, earnings and cash flow expansion
Momentum
Trend and relative strength
Risk
Volatility, drawdown, beta
Balance sheet
Leverage, liquidity, solvency
Accounting signals
Accruals, restatements, red flags
Earnings stability
Consistency of reported results
Capital efficiency
Reinvestment discipline
Market and factor updates written for people who care about signals, not headlines.
Composite scores and category breakdowns across the US equity universe.
From reading a 10-K to building your first factor backtest — beginner to advanced.
Discuss factor rotations, accounting red flags, and Python workflows with peers.
Track tickers, save research signals, and revisit them as the model updates.
Today · Demo
Quality and low-volatility factors continued to outperform this week; momentum cooled in high-beta names.
Today · Demo
Composite quality ranks improved for balance-sheet-heavy industrials while cheap financials lagged.
Today · Demo
A screen of net-debt reduction combined with FCF expansion surfaces a small basket worth monitoring.
Accounting data
Difficulty: beginner
Factor investing
Difficulty: beginner
Reading financial statements
Difficulty: intermediate
Python / data science
Difficulty: beginner
Backtesting
Difficulty: intermediate
Portfolio construction
Difficulty: advanced
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Lars combines software engineering, financial economics, entrepreneurship, data science, and years of independent research into factor investing and market anomalies. netQuants builds on that cross-disciplinary foundation to make quant finance more understandable and useful for independent investors.
Researcher, builder, founder, and quant finance enthusiast.
Daily factor updates · 118-factor model · Education · Community · Watchlist
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API access · Datasets · Notebooks · Custom factors · Researcher tier
ETFs · International equities · Macro factors · Sector rotation · Regime detection
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