StocksSG

Methodology

Every score, grade, and analytical signal on StocksSG uses publicly documented models with disclosed formulas and weights. No proprietary black boxes.

All models are computed on-demand from underlying data. See Data Sources for where that data comes from.

Governance Risk Score

A-F (0-100)

Multi-dimensional governance quality assessment. Evaluates 8 dimensions of board and corporate governance structure, weighted by their empirical association with shareholder outcomes.

DimensionWeightDetail
Board Independence20 ptsProportion of independent non-executive directors. Higher independence reduces agency risk.
Board Size10 ptsOptimal range 6-12 directors. Too small = insufficient oversight; too large = diffusion of responsibility.
CEO/Chair Separation10 ptsFull points if CEO and Chair are different people. Combined roles concentrate power.
Attendance15 ptsAverage board meeting attendance %. Below 75% is a red flag.
Auditor Independence10 ptsNon-audit fee ratio. High non-audit fees may compromise auditor objectivity.
Credential Density10 ptsAverage qualifications per director (CPA, MBA, CA, etc.).
Committee Coverage15 ptsPresence and staffing of Audit, Remuneration, and Nominating committees.
Pay Transparency10 ptsQuality of executive compensation disclosure — exact figures, $250K bands, or none.

Academic Basis

  • - SGX Code of Corporate Governance 2018
  • - Gompers, Ishii & Metrick (2003) — "Corporate Governance and Equity Prices"

Notes & Caveats

  • - Data completeness is reported alongside the score — low-coverage scores are flagged
  • - Sector-aware: REIT boards are expected to be smaller
View Governance Risk Score insights →

Management Credibility Score

A-F (0-100)

Evaluates management teams on consistency, transparency, and financial stewardship. Rewards teams that deliver predictable results and align incentives with shareholders.

DimensionWeightDetail
Earnings Consistency20 ptsRevenue and profit volatility over available years. Lower volatility = more predictable management.
Margin Stability15 ptsYear-on-year margin variance. Stable margins suggest disciplined cost management.
Capital Discipline15 ptsDebt trajectory and free cash flow quality. Improving or stable debt loads score higher.
Dividend Reliability15 ptsPayout consistency and dividend growth track record.
Pay Transparency15 ptsQuality of executive compensation disclosure.
Insider Alignment20 ptsNet insider buying/selling. Net buyers signal management confidence.

Academic Basis

  • - Jensen & Meckling (1976) — "Theory of the Firm: Managerial Behavior, Agency Costs and Ownership Structure"
  • - Lakonishok & Lee (2001) — "Are Insider Trades Informative?"

Notes & Caveats

  • - Insider data weighted by recency — recent trades carry more signal
  • - S-REIT dividend reliability assessed against MAS distribution requirements
View Management Credibility Score insights →

Accounting Quality Score

A-F (0-100)

Forensic accounting analysis combining five established models to detect potential earnings manipulation or deteriorating financial quality.

DimensionWeightDetail
Beneish M-Score30 pts8-variable model detecting earnings manipulation. M-Score > -1.78 flags potential manipulation. Variables: DSRI, GMI, AQI, SGI, DEPI, SGAI, TATA, LVGI.
Piotroski F-Score20 pts9-signal financial strength score. Profitability (4), leverage/liquidity (3), operating efficiency (2). F-Score ≥ 7 is strong.
Sloan Accruals Ratio15 ptsEarnings quality measure. High accruals relative to assets suggest less cash-backed earnings.
Cash Conversion15 ptsOperating cash flow / net income. Strong companies convert >80% of net income to cash.
Revenue Quality10 ptsRevenue growth sustainability analysis. Extreme growth may indicate channel stuffing.
Audit Flags10 ptsHigh non-audit fee ratios, auditor changes, or qualified opinions.

Academic Basis

  • - Beneish (1999) — "The Detection of Earnings Manipulation"
  • - Piotroski (2000) — "Value Investing: The Use of Historical Financial Statement Information"
  • - Sloan (1996) — "Do Stock Prices Fully Reflect Information in Accruals and Cash Flows?"

Notes & Caveats

  • - M-Score requires 2+ years of financial data to compute deltas
  • - Financial companies (banks, insurers) may produce misleading M-Scores due to balance sheet structure
View Accounting Quality Score insights →

Dividend Safety Score

A-F (0-100)

Evaluates the sustainability of a company's dividend using 8 components. SGX-specific logic accounts for S-REIT mandatory distributions and MAS leverage limits.

DimensionWeightDetail
Payout Ratio15 ptsEarnings-based payout ratio. Sector-aware thresholds — S-REITs expected at 90%+, industrials penalised above 80%.
Dividend Coverage15 ptsEarnings per share / dividends per share. Coverage below 1.0x indicates dividends exceed earnings.
FCF Coverage15 ptsFree cash flow / total dividends paid. Dividends must be funded by real cash, not debt.
Streak Consistency10 ptsConsecutive years of dividend payments. Long streaks indicate commitment.
Debt Health15 ptsDebt-to-equity and interest coverage. S-REITs: MAS aggregate leverage must stay below 50%.
Earnings Stability10 ptsRevenue and profit volatility — volatile earnings may force future dividend cuts.
S-REIT Health10 ptsREIT-specific: DPU trend, occupancy, WALE, gearing. Only scored for S-REITs.
Piotroski F-Score10 ptsUnderlying financial strength supports dividend sustainability.

Academic Basis

  • - Lintner (1956) — "Distribution of Incomes of Corporations Among Dividends, Retained Earnings, and Taxes"
  • - MAS Code on Collective Investment Schemes (S-REIT distribution requirements)

Notes & Caveats

  • - S-REIT payout ratios above 90% are expected (tax transparency), not penalised
  • - Singapore's one-tier tax system means no imputation/franking credits to track
View Dividend Safety Score insights →

Financial Distress Prediction

Low / Moderate / High / Severe

Three established distress prediction models combined. Altman Z-Score for industrial firms, Z''-Score (adjusted) for services/non-manufacturing, plus Piotroski F-Score for financial strength.

DimensionWeightDetail
Altman Z-ScorePrimaryZ = 1.2(WC/TA) + 1.4(RE/TA) + 3.3(EBIT/TA) + 0.6(MV Equity/TL) + 1.0(Sales/TA). Safe > 2.99, Grey 1.81-2.99, Distress < 1.81.
Altman Z''-ScorePrimaryNon-manufacturing variant excluding Sales/TA ratio. Better suited for SGX services and financial companies.
Piotroski F-ScoreSecondary9-point financial strength score. F ≤ 2 is weak, 3-6 is moderate, ≥ 7 is strong.

Academic Basis

  • - Altman (1968) — "Financial Ratios, Discriminant Analysis and the Prediction of Corporate Bankruptcy"
  • - Altman (2002) — "Revisiting Credit Scoring Models in a Basel 2 Environment"
  • - Piotroski (2000) — F-Score financial health signals

Notes & Caveats

  • - Z-Score originally calibrated for US manufacturing — interpretation for SGX financials/REITs should be cautious
  • - Companies with negative book equity may produce misleading Z-Scores
View Financial Distress Prediction insights →

Earnings Surprise Predictor

Likely Beat / Neutral / Likely Miss

8-factor model predicting whether a company is likely to beat or miss earnings expectations. Each factor scores -1 to +1 with SGX-tuned weights.

DimensionWeightDetail
Insider Activity10%Net insider buying/selling. Reduced weight for SGX — mandatory trading plans dampen signal quality.
Revenue Momentum20%Trailing revenue growth trend. Increased weight — SGX export-oriented companies show strong revenue-earnings correlation.
Margin Trend20%Operating margin trajectory. Increased weight — highly predictive for S-REITs and commodity-exposed industrials.
FCF Quality10%Free cash flow / net income quality. Cash-rich companies less likely to miss.
Analyst Sentiment10%Consensus revision direction (upgrades vs downgrades).
Working Capital Signal10%Changes in receivables, inventory, payables relative to revenue.
Debt Trajectory10%Leverage changes — deteriorating leverage may signal earnings pressure.
Historical Beat Rate10%Past accuracy of meeting/beating expectations. Reduced weight — near-random predictive power (44-45% in backtests).

Academic Basis

  • - Livnat & Mendenhall (2006) — "Comparing the Post-Earnings Announcement Drift for Surprises Calculated from Analyst and Time Series Forecasts"
  • - SGX-specific weight tuning based on NZXplorer D345 backtest results

Notes & Caveats

  • - Composite score maps to beat/miss probabilities via sigmoid function
  • - Confidence reflects data availability — low-coverage companies flagged
View Earnings Surprise Predictor insights →

Fair Value Estimation

SGD value + % upside/downside

Three-model valuation engine: Discounted Cash Flow (DCF), Dividend Discount Model (DDM), and EV/EBITDA relative valuation. SGX-calibrated with sector-specific discount rates from sector-profiles.ts.

DimensionWeightDetail
DCF (Discounted Cash Flow)Primary5-year projected free cash flows discounted at WACC. Terminal value via Gordon Growth Model. SGX risk-free rate, sector-specific equity risk premium and credit spread.
DDM (Dividend Discount Model)SecondaryOnly used for dividend-paying companies. DPS grown at estimated rate, discounted at cost of equity. Particularly relevant for S-REITs.
EV/EBITDA RelativeSecondaryCurrent EV/EBITDA vs sector median. Derives implied fair value from peer multiples.

Academic Basis

  • - Damodaran — "Investment Valuation" (DCF and relative valuation frameworks)
  • - Gordon (1959) — "Dividends, Earnings, and Stock Prices" (DDM)

Notes & Caveats

  • - Composite value is a weighted average of available models (DCF dominant)
  • - Confidence: high = 3 models, medium = 2, low = 1
  • - NOT FINANCIAL ADVICE — Educational tool only. Estimates rely on simplified assumptions
  • - Uses Singapore risk-free rate, SGX sector profiles, and SG corporate tax rate (17%)
View Fair Value Estimation insights →

Greenwashing Detection

Low / Moderate / High / Insufficient Data

Compares ESG claims (narrative) against evidence of actual environmental and social performance. Flags companies where sustainability narrative outpaces substance.

DimensionWeightDetail
Framework Adoption20 pts (Narrative)TCFD, ISSB, SASB, SDG framework claims. High claims without evidence increase the gap.
Emissions Evidence20 pts (Evidence)Actual Scope 1/2/3 emissions data disclosed. Quantitative data scores higher than narrative claims.
Diversity Evidence20 pts (Evidence)Female board/workforce %, workplace safety records (TRIFR, LTIFR).
Target Setting20 pts (Evidence)Specific, measurable ESG targets with progress tracking.
External Assurance20 pts (Evidence)Third-party verification of ESG claims (e.g., ISAE 3000, limited/reasonable assurance).

Academic Basis

  • - Lyon & Maxwell (2011) — "Greenwash: Corporate Environmental Disclosure under Threat of Audit"
  • - SGX Practice Note 7.6 on Sustainability Reporting (mandatory from 2022)

Notes & Caveats

  • - Gap = Narrative Score - Evidence Score. Large positive gap = greenwashing risk
  • - SGX mandates sustainability reporting — companies without reports score "insufficient data"
View Greenwashing Detection insights →

Auditor Quality Score

A-F

Evaluates external audit quality through fee analysis, auditor reputation, non-audit fee ratios, and partner rotation compliance.

DimensionWeightDetail
Audit Firm TierPrimaryBig 4 (Deloitte, EY, KPMG, PwC) vs mid-tier vs small firm. Big 4 audit scores higher due to resources and scrutiny.
Non-Audit Fee RatioPrimaryNon-audit fees / total fees. High ratios (>50%) may compromise auditor independence.
Fee TrendSecondaryYear-on-year change in total fees. Sharp increases may signal audit complexity or disputes.
Partner RotationSecondaryYears since audit partner rotation. Singapore requires rotation every 5 years.

Academic Basis

  • - DeAngelo (1981) — "Auditor Size and Audit Quality"
  • - ACRA Practice Monitoring Programme guidelines

Notes & Caveats

  • - Red flags include: non-audit ratio > 50%, recent auditor switch, no rotation data
  • - Big 4 market dominance in Singapore means most STI companies score well on firm tier
View Auditor Quality Score insights →

Important Disclaimers

All scoring models use simplified assumptions and publicly available data. They are designed as analytical tools to surface patterns and risks — not as investment recommendations.

Models are calibrated for SGX-listed companies using Singapore-specific parameters (MAS regulations, SGX Code of Corporate Governance, SG risk-free rates, SFRS(I) accounting standards). Results may not be comparable to scores computed for other markets.

Data completeness varies by company. Scores based on limited data are flagged — always check the confidence/completeness indicator before relying on any score.

StocksSG is not licensed by the Monetary Authority of Singapore (MAS) and does not provide financial advisory services. All analytics are for informational and educational purposes only.

Questions about our methodology? Contact data@stockssg.com. See also: Data Sources.