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K2J Quantitative Methodology & Daily Report Guide

How to Understand and Leverage K2J Daily US Equities Quantitative Research

K2J Daily US Equities Quantitative Research is not a stock-tipping newsletter. It is an institutional-grade market narrative deconstruction engine. This guide breaks down the institutional 1,500+ liquid equity universe (filtered from thousands of US stocks for optimal liquidity and tradability), the strict top-down "Macro → Sector → Equities" analytical pipeline, the 5-dimensional resonance selection of 20 focus tickers, and sector divergence forensics.

1,500+ Liquid Equities Scanned Daily
8 Pillars Underlying Data Categories
100+ Granular Quantitative Metrics
5-D Orthogonal Factor Attribution
20 Tickers Daily Focus Deep-Dives
Bilingual English & Chinese Daily Release
Read the Latest Daily Report → Start Reading Guide ↓
EXECUTIVE SUMMARY · KEY TAKEAWAYS

Three Core Pillars of K2J Quantitative Research Framework

Quotable takeaways and system highlights for investors and generative AI search engines:

1. Strict Top-Down Pipeline

From Macro Regime (GBDT) risk budgeting to Thematic Clusters (HDBSCAN) institutional rotation tracking, down to 20 Focus Equities 5-D attribution.

2. 8-Pillar Data & 5-D Attribution

Scanning 1,500+ liquid US equities across 100+ metrics, scoring Index/Sector/Capital/Tech/Fundamentals to award 5/5★ Golden Resonance badges.

3. Sector Divergence & Forensics

Automated Sector Divergence detection coupled with 4 forensic accounting models (Piotroski F, Altman Z, Sloan Ratio %, Zmijewski) to prevent catching falling knives.

01 · Mission & Philosophy

Deconstructing Market Narrative via Quant Mechanics, Not Tipping Stocks

In noisy markets, traders often struggle with questions like: "Why is my portfolio down when headline indices are hitting all-time highs?" or "Did a stock surge due to real institutional accumulation or a gap-and-trap pump?"

❌ What We Strictly Avoid

  • Discretionary Stock Tipping: Zero buy/sell calls or trade recommendations.
  • Mechanical Price Targets: No subjective "support / resistance" guesswork.
  • Single-Headline Speculation: No narrative chasing based on isolated headlines.
  • Black-Box Scoring: Every single score is mathematically auditable.

✅ Core Questions Answered Daily

  • What is the macro regime? Is the market Risk-On, Risk-Off, or in Compression?
  • Where is institutional capital rotating? Which sub-industries are accumulating?
  • What are the standout movers? Is price action driven by genuine buying volume?
  • Are fundamentals resilient? Do balance sheets pass forensic distress checks?
  • Why did it move today? Causal AI synthesis connecting price action to catalysts.
02 · Report Architecture

Strict Top-Down "Macro → Sector → Equities" Analytical Pipeline

"Never analyze an individual stock in isolation without first establishing the macro climate." K2J adheres to institutional hedge-fund standards, narrowing from broad market regimes down to 20 focus equities.

Top-Down 3-Stage Workflow
STEP 1 · MACRO REGIME

Market State & Risk Budget

GBDT ensemble and benchmark ETFs establish the macro regime, evaluating cross-sectional breadth across 1,500+ liquid equities to calibrate total portfolio risk budget.

STEP 2 · SECTOR THEMES

Thematic Clusters & Capital Flows

Unsupervised dynamic clustering identifies rising/falling theme clusters, measuring sub-industry win rates and capital velocity to locate institutional momentum.

STEP 3 · EQUITIES DEEP-DIVE

5-D Attribution & 20 Focus Tickers

Orthogonal factor attribution isolates Top 10 Bullish and Top 10 Bearish equities, augmented by AI causal reasoning on breaking news catalysts and forensic health.

The 8 Standard Report Sections Explained

00
Key Takeaways (GEO)

High-density AI executive summary detailing macro regime, primary long themes, divergent risks, and portfolio posture.

⏱️ 30s Executive Summary
01
Macro Regime & Environment

Macro state classification banner, 4 benchmark ETF quotes (SPY/QQQ/DIA/IWM), full-market advance-decline ratios, and systemic commentary.

🎯 Set the Stage: Wind at Back vs Headwind
02
Thematic Clusters & Rotation

Unsupervised clustering table showing cluster size, 1D/1M mean returns, alignment win rates, binomial Z-scores, and constituent movers.

🧭 Track Smart Money Migration
03
Executive Stock Summary

Actionable summary lists for Long Leaders and Short Pressures, with direct anchor links to deep-dive cards and sector divergence flags.

⚡ Scan All 20 Focus Tickers in 1 View
04
5-D Long Leader Studies

Deep-dive cards for Top 10 Longs: Causal News Intelligence, 5-D Microstructure Breakdown, 6-Pillar Moat, Analyst Targets, and Earnings Warnings.

🔍 Explain Why Longs Surged
05
5-D Short Pressure Studies

Deep-dive cards for Top 10 Shorts: Breakdown drivers, forensic accounting red flags, and dedicated AI Sector Divergence detective breakdowns.

🛡️ Forensics on Drops & Traps
06
Master Overview Table

Comprehensive 10-column comparison matrix across all 20 focus equities (Direction, Ticker, Industry, Score, Resonance, Price, 1D %, RelVol, Health, Earnings Date).

📊 Side-by-Side Factor Benchmarking
07
Quantitative Methodology

Mathematical formulas, 5-D weighting parameters, robust Z-score metrics, and forensic accounting threshold proofs ensuring zero black-box obscurity.

📐 Verify Algorithm & Math Integrity
03 · Institutional Data Foundation

8 Core Data Pillars Across 100+ Granular Metrics

A reliable quantitative report cannot rely solely on basic price percentages. To ensure tradability and statistical rigor, K2J applies institutional liquidity thresholds, ingesting and computing over 100 metrics across 8 institutional pillars for all 1,500+ liquid equities in our universe:

01 · Asset Metadata & Consensus ≈ 22 Metrics

Identification, Share Structure & Wall Street Outlook

💡 Solves: Which industry? What is the float size? What is Wall Street's expectation gap?
type, subtype, exchange, market, sector, industry, cusip, isin, figi, number_of_shareholders, total_shares_outstanding, float_shares_outstanding, float_shares_percent_calc, earnings_release_date, earnings_release_next_date, price_target_average, target_price_performance, Recommend.All

Quant Role: Gauges free-float concentration; enforces strict 3-day proximity alerts for upcoming binary earnings gaps; measures Wall Street target price upside dispersion.

02 · Multi-Period Price & Microstructure ≈ 52 Metrics

Intraday Candlestick Intent, Breakouts & Extended Hours

💡 Solves: Is capital genuinely driving the bid, or is it a fading gap-and-dump trap?
open, high, low, close, gap, change, change_from_open, volume, volume_change, average_volume_10d/30d/60d/90d, relative_volume, Value.Traded (Turnover), Volatility.D/W/M, beta_1/3/5Y, Perf.W/1M/3M/6M/Y/YTD, High/Low.1M/3M/6M/52W/ATH/ATL, premarket/postmarket_open/high/low/close/volume/gap

Quant Role: Powers D3 Capital Flow & Microstructure (labels `BULLISH_DRIVE` vs `FADING_GAP_DUMP` penalty); powers D4 Breakout Recognition (ATH, 52-Week High, 6-Month platform vs Breakdown).

03 · Technical Indicators & Pivot Matrix ≈ 56 Metrics

Moving Averages, Oscillators & 5 Pivot Systems

💡 Solves: How strong is trend persistence? Where is institutional average cost?
SMA 5/20/50/100/200, EMA 5/10/20/50/100/200, HullMA9, Ichimoku (Tenkan/Kijun/Span A/B), RSI (14), Stochastic, Stoch.RSI, ADX (+DI/-DI), ATR, ADR, CCI20, Williams %R, Momentum, ROC, UO, AO, BBPower, VWAP, VWMA, BB.upper/lower/basis, ChaikinMoneyFlow (CMF), MoneyFlow (MFI), P.SAR, Pivot Points (Camarilla, Classic, DeMark, Fibonacci, Woodie)

Quant Role: Orthogonal indicator de-noising; CMF > 0 verifies active institutional buying; closing above VWAP confirms institutional inventory is in positive territory.

04 · Financial Statements Deep-Dive ≈ 31 Metrics

Income Statement, Cash Flow & Balance Sheet (TTM & FQ)

💡 Solves: Does the company generate real organic free cash flow, or is it paper revenue?
total_revenue_ttm/fq, gross_profit_ttm/fq, ebit_ttm, ebitda_ttm/fq, net_income_ttm/fq, basic/diluted_eps_ttm, research_and_dev_ttm/fq, cash_f_operating_activities_ttm/fq, free_cash_flow_ttm/fq, capital_expenditures_ttm/fq, cash_n_equivalents_fq, total_assets_fq, total_liabilities_fq, net_debt_fq, total_equity_fq, goodwill_fq

Quant Role: Penetrates accrual accounting by validating earnings quality via Free Cash Flow (FCF) and Operating Cash Flow, filtering out revenue illusions.

05 · Advanced Enterprise Valuation ≈ 15 Metrics

Cash Flow Multiples & Enterprise Value (EV) Ratios

💡 Solves: What is the true margin of safety based on cash generation?
market_cap_basic, price_earnings_ttm (P/E), price_earnings_growth_ttm (PEG), price_sales (P/S), price_book_fq (P/B), price_free_cash_flow_ttm (P/FCF), ev_to_ebitda_ttm, enterprise_value_to_ebit_ttm, enterprise_value_to_revenue_ttm, enterprise_value_to_free_cash_flow_ttm, earnings_yield_recent, buyback_yield_recent

Quant Role: Powers D5 Fundamental Context; uses EV/EBITDA and P/FCF cash multiples instead of GAAP P/E distorted by non-operating one-offs.

06 · Multi-Period Growth Rates ≈ 8 Metrics

Revenue, Profitability & Balance Sheet Acceleration

💡 Solves: Is fundamental expansion accelerating, plateauing, or stalling?
total_revenue_yoy_growth_ttm, gross_profit_yoy_growth_ttm, ebitda_yoy_growth_ttm, net_income_yoy_growth_ttm, free_cash_flow_yoy_growth_ttm, capital_expenditures_yoy_growth_ttm, total_assets_yoy_growth_fq, total_debt_yoy_growth_fq

Quant Role: Detects marginal inflections in revenue and operating leverage, validating whether a stock's momentum has multi-quarter earnings backing.

07 · Financial Ratios & Quant Forensics ≈ 20 Metrics

Capital Efficiency & 4 Classic Forensic Risk Models

💡 Solves: Are there hidden bankruptcy risks, aggressive accruals, or manipulation?
return_on_equity (ROE), return_on_assets (ROA), return_on_invested_capital (ROIC), gross_margin, operating_margin, net_margin, current_ratio, quick_ratio, debt_to_equity, altman_z_score_ttm, piotroski_f_score_ttm, sloan_ratio_ttm, zmijewski_score_ttm

Quant Role: Forms an uncompromised defensive moat. Longs must pass Piotroski F ≥ 3, Sloan ≤ 10%, Altman Z ≥ 1.81 hard red lines; Shorts systematically isolate financially distressed targets.

08 · Dividends & Capital Allocation ≈ 8 Metrics

Shareholder Yield, Buybacks & Payout Consistency

💡 Solves: Does management allocate capital efficiently to shareholders?
dividends_yield, dividend_yield_indicated, dps_ttm, dps_common_stock_prim_issue_yoy_growth_fy, continuous_dividend_growth, continuous_dividend_payout, dividend_payout_ratio_ttm, total_cash_dividends_paid_ttm

Quant Role: Combines buyback yield with dividend yield to calculate Total Shareholder Yield, identifying quality defensive anchors during turbulent macro phases.

04 · Stock Selection Funnel

How the Daily 20 Focus Equities Are Selected

Out of 1,500+ eligible high-liquidity equities, how does the engine isolate the 20 most representative stories (Top 10 Longs + Top 10 Shorts) each day?

LAYER 1 · EXTREME MOVERS (2 SEATS)

Locking Market Extremes

The single largest gainer and single largest decliner in the market automatically take positions #1. If divergent from their sector, they are flagged as EXTREMA_DIVERGENCE to ensure no black swan is ignored.

LAYER 2 · 5-D RESONANCE ENGINE (18 SEATS)

Multi-Factor Ranking

The remaining 18 seats are strictly sorted by resonance tiers (5/5★ → 4/5 → 3/5), composite attribution score, and an Industry Alignment filter (≥50%) to eliminate isolated noise.

LAYER 3 · DIVERSITY CONSTRAINTS

Preventing Sector Clustering

A maximum of 3 tickers per thematic cluster and 3 tickers per sub-industry are permitted. This guarantees broad market representation rather than a single industry dominating the report.

What Characterizes the Selected Stocks?

🟢 Bullish Leader Characteristics

High factor resonance (`5/5★` or `4/5`), genuine intraday buying drive (`BULLISH_DRIVE`), closing price above VWAP, multi-period breakout (ATH/52W), robust balance sheet (Piotroski ≥ 3, Altman Z ≥ 1.81, Sloan ≤ 10%), and industry momentum tailwinds.

🔴 Bearish Pressure Characteristics

Broad sector breakdown (`BEARISH_DUMP`), persistent capital outflow (CMF < 0), balance sheet vulnerability (low F-score, distressed Altman Z, Sloan accrual red flag), or sudden company-specific **sector divergence shocks**.

05 · 5-Dimensional Factor Model

Orthogonal Factor Risk Model & Attribution Formula

In K2J's architecture, 5-D resonance measures attribution completeness — how many independent market dimensions simultaneously support an equity's move:

Narrative Attribution Score = Φ( 0.20 D₁ + 0.25 D₂ + 0.25 D₃ + 0.15 D₄ + 0.15 D₅ ) × 100
D1 · INDEX ALIGNMENT Weight 20% · Macro Climate

Systematic Beta Co-Movement

Excess return vs market median + Beta sensitivity + Macro regime hard gating. In broad market rallies, short D1 is mathematically disqualified.

D2 · SECTOR CLUSTERING Weight 25% · Sector Tailwind

Industry Momentum & Cohesion

Pure industry residual Alpha + sub-industry alignment ratio (≥50%) + cluster Z-score. Severe sector divergence receives a -2.0 penalty.

D3 · CAPITAL FLOW Weight 25% · Microstructure

Real Buying vs Distribution

Change from open + Intraday Intent tagging + VWAP deviation + Turnover volume + Chaikin Money Flow (CMF).

D4 · PRICE ACTION Weight 15% · Technical Momentum

Multi-Period Breakout

Breakout badge tiers (ATH +1.0, 52W/6M +0.7, 3M +0.4, BREAKDOWN -0.7) + Moving average distance + Bollinger position + MACD acceleration.

D5 · FUNDAMENTALS Weight 15% · Cash Flow Moat

Valuation & Forensic Health

EV/EBITDA & P/FCF cash multiples + Piotroski F-score + Altman Z distress barrier + Sloan Ratio earnings penalty + sector adaptation.

Resonance Tier Legend: 5/5★ Five-Star Resonance (Highest Conviction Highlight) 4/5 Strong Attribution (Primary Focus) 3/5 Mainstream Attribution (Standard Entry)
06 · Forensic Alert Mechanism

Understanding Sector Divergence & AI Forensics

In equities trading, a stock collapsing while its entire industry surges represents one of the deadliest "falling knives." K2J built a dedicated quantitative divergence monitor and AI forensic engine to explain these anomalies.

⚠️ FORENSIC WARNING · SECTOR DIVERGENCE

Diverging from Sector Reality: Not a Standard Short Candidate

When a ticker moves in sharp opposition to its underlying sub-industry (e.g., gold miners rally +2.81% with 80% participation, but one specific miner plunges -9.35%), this is not normal cyclical pressure — it signals an isolated company-specific black swan.

⚙️ K2J Model Penalty Logic

  • D2 Sector Penalty: Assigns a mandatory punitive score of -2.0 (Sector Divergence), reflecting total lack of group support.
  • Composite Z-Score Deduction: Automatically deducts -0.50 from overall Z-score (compressing a 62.7 score down to 38.2), ensuring it is never misclassified as a "Resonant Short Leader".
  • Role Clarification: Front-end tags the ticker as EXTREMA_DIVERGENCE (Isolated Divergence Drop) rather than a group short.
  • Targeted AI Forensics: Triggers deep-dive news retrieval to uncover the exact corporate catalyst and embeds a prominent ⚠️ Divergent orange alert banner atop the card.

📌 Real Case Study · SA (August 24, 2026)

The Anomaly: The Gold & Silver Mining sector gained +2.81% (peers IAG, BTG surged), but SA plummeted -9.35%.

AI Forensic Finding: Targeted news retrieval uncovered a surprise dilutive secondary equity offering. The alert warned investors: Do not blind-buy SA just because gold is rallying!

07 · Real Report Case Studies

Real Stock Profiles & Factor Deconstruction

Real-world examples from the August 24, 2026 report demonstrate how 5-D attribution translates raw numbers into actionable intelligence:

CART +3.91%
🟢 Long Breakout Leader · 4/5 Resonance

52-Week Breakout + Bullish Intraday Drive

Logistics & Delivery. Broke out to 52-week highs with an intraday gain of +3.9% from open, closing +1.6% above VWAP. D3 Capital Flow and D4 Breakout confirm strong institutional backing.

Factor Profile:
• Breakout Badge: 52W_6M
• Intraday Intent: BULLISH_DRIVE
• Composite Score: 88.4 / 4/5 Tier
• Confirmed: D1, D3, D4, D5 ✓
ALVO +18.51%
⚡ Catalyst Surge · 3/5 Attribution

Extreme Gain + Genuine Buying Volume

Biotechnology. Despite broad sector weakness, surged +18.5% on 3.4x average volume following an FDA regulatory resolution. While sector-divergent, strong intraday buying confirmed institutional demand.

Factor Profile:
• Relative Volume: 3.40x Surge
• Intraday Intent: BULLISH_DRIVE
• Catalyst: FDA Compliance Resolved
• Role: EXTREMA_DIVERGENCE
AAOI -13.82%
🔴 Bearish Breakdown · Forensic Warning

Platform Breakdown + Capital Outflow

Optical Technology. Unilateral selling saw price drop -7.8% from open. CMF accelerated into negative territory with multi-timeframe moving averages broken. Model warned of sharp downside liquidity traps.

Factor Profile:
• Technical Pattern: BREAKDOWN
• Intraday Intent: BEARISH_DUMP
• CMF: -0.12 Outflow Acceleration
• Role: EXTREMA_ALIGNED (Lead Drop)
08 · Step-by-Step Guide

The 4-Step 5-Minute Daily Report Reading Workflow

A comprehensive K2J quantitative report packs immense analytical depth. How can you extract maximum signal in minimum time?

STEP 01 · MACRO REGIME ⏱️ 1 Minute

Gauge Systemic Wind Direction

Open 01 Macro Environment: Is the market Risk-On or Compression? Are benchmark ETFs diverging? Is 1,500+ liquid stock breadth > 50%? Calibrate overall portfolio exposure accordingly.

STEP 02 · SECTOR THEMES ⏱️ 2 Minutes

Spot Capital Accumulation

Scan 02 Thematic Clusters: Which sub-industries are surging with high internal win rates (>70%)? Locate the dominant institutional sector rotations.

STEP 03 · 20 FOCUS TICKERS ⏱️ 2 Minutes

Scan the Multi-Factor Roster

Review 03 Executive Summary and 06 Master Table: Scan the Top 10 Long and Top 10 Short rosters, noting golden 5/5★ badges and ⚠️ Divergent alerts.

STEP 04 · DEEP-DIVES ⏱️ On-Demand

Verify Moats & Earnings Risk

Click ticker links to explore 04/05 Deep-Dive Cards: Read the AI causal synthesis (Why It Moved), 6-pillar business moat, Wall Street price targets, and binary earnings gap warnings.

09 · Quantitative Glossary

Core Quantitative & Forensic Indicator Glossary

Quick reference dictionary defining the key quantitative metrics and forensic thresholds used across the report:

CMF (Chaikin Money Flow) Capital Flow
Measures the volume-weighted accumulation and distribution over a 20-day period. Ranges between -1.0 and +1.0. CMF > 0 confirms active institutional buying pressure; CMF < 0 reflects continuous distribution.
VWAP Deviation % (Volume-Weighted Average Price Deviation) Microstructure
Measures the percentage difference between the closing price and the day's institutional volume-weighted average price (VWAP). Positive values indicate that intraday buyers are in profit (tailwind advantage); negative values signify trapped overhead supply.
Piotroski F-Score (9-Point Fundamental Health) Forensics
Stanford Professor Joseph Piotroski's 9-factor model assessing profitability, operational efficiency, and balance sheet leverage. F-Score ≥ 7 indicates top-tier fundamental health; F-Score < 3 signals structural deterioration.
Altman Z-Score (Bankruptcy Risk Model) Credit Risk
NYU Professor Edward Altman's classic formula forecasting corporate bankruptcy risk. Z > 2.99 indicates a safe financial zone; 1.81 ≤ Z ≤ 2.99 is a grey zone; Z < 1.81 alerts to severe distress and default probability.
Sloan Ratio % (Accrual Earnings Quality) Earnings Forensics
Developed by Professor Richard Sloan, this metric evaluates the proportion of earnings derived from non-cash accruals versus organic cash flow. Sloan Ratio > 10% raises an aggressive accounting red flag, warning of potentially inflated paper profits.
Relative Volume (10D Average Multiple) Volume Surge
Daily volume relative to the 10-day moving average volume. RelVol > 2.0x flags a significant volume anomaly; combined with candlestick intent, it distinguishes institutional accumulation from panic selling.
Total Shareholder Yield (Buybacks + Dividends) Capital Allocation
Sum of buyback yield and dividend yield. Compared to dividend yield alone, total shareholder yield gives a complete picture of management's organic cash return to shareholders.
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