dividend-analysis
The dividend-analysis skill evaluates whether dividend stocks offer sustainable income or represent yield traps by examining payout coverage, balance-sheet strength, management history, and total-return potential. Use this skill when analyzing dividend stocks, building income portfolios, screening for dividend growth, assessing payout safety, checking ex-dividend mechanics, or determining whether elevated yields signal opportunity or distress.
git clone --depth 1 https://github.com/HKUDS/Vibe-Trading /tmp/dividend-analysis && cp -r /tmp/dividend-analysis/agent/src/skills/dividend-analysis ~/.claude/skills/dividend-analysisSKILL.md
# Dividend Analysis ## Purpose Use this skill when the user asks about dividend stocks, income portfolios, dividend growth, high-yield screening, payout safety, ex-dividend dates, or whether a dividend is sustainable. The goal is to separate durable shareholder returns from yield traps. Dividend analysis should never stop at headline yield. A good answer explains how the dividend is funded, how stable the underlying business is, whether management has room to keep paying, and how valuation changes the expected total return. ## Core Questions 1. What is the current cash yield, and is it normal for this company or sector? 2. Is the payout covered by earnings, operating cash flow, and free cash flow? 3. Is the balance sheet strong enough to absorb a down cycle? 4. Has management grown, held, cut, or suspended the dividend across cycles? 5. Does the valuation still leave room for total return after taxes and reinvestment assumptions? ## Key Metrics | Metric | Formula | Healthy Signal | Warning Signal | |--------|---------|----------------|----------------| | Dividend yield | annual DPS / current price | Above peer median with stable coverage | Extremely high vs history or peers | | Earnings payout ratio | dividends / net income, or DPS / EPS | 30-70% for mature non-financials | Above 90%, negative earnings | | Free-cash-flow payout | dividends / FCF | Below 70% through a cycle | Dividend exceeds FCF for 2+ years | | CFO coverage | operating cash flow / dividends paid | Above 1.5x | Below 1.0x | | Dividend CAGR | DPS growth over 3/5/10 years | Positive and below EPS/FCF growth | Growth funded by leverage | | Net debt / EBITDA | net debt / EBITDA | Sector-appropriate leverage | Leverage rising while payout rises | | Buyback plus dividend yield | (dividends + net buybacks) / market cap | Balanced capital return | Buybacks funded by debt at high valuation | For REITs, utilities, banks, MLPs, and insurers, adapt the payout metric to the sector. For example, use AFFO payout for REITs, distributable cash flow for MLPs, and regulatory capital ratios for banks and insurers. ## Analysis Workflow ### Step 1: Normalize the Dividend - Use forward indicated dividend for recurring payments. - Separate ordinary dividends from special dividends. - Check whether the latest declared dividend is annual, semiannual, quarterly, monthly, or irregular. - For ADRs and cross-listed shares, account for depositary ratios, withholding tax, and FX conversion. ```python annual_dividend = regular_dividend_per_period * payments_per_year dividend_yield = annual_dividend / current_price ``` ### Step 2: Check Coverage Start with earnings coverage, then confirm with cash coverage. ```python earnings_payout = dividends_paid / net_income fcf_payout = dividends_paid / free_cash_flow cfo_coverage = operating_cash_flow / dividends_paid ``` Interpretation: - Good: net income, CFO, and FCF all cover dividends across multiple years. - Watch: earnings cover dividends but FCF does not, especially during capex-heavy periods. - Avoid: dividends are paid while both earnings and FCF are negative, unless there is a clear one-time reason and a strong balance sheet. ### Step 3: Diagnose Dividend Growth Quality Dividend growth is high quality when it follows business growth. ```python dividend_cagr = (dps_end / dps_start) ** (1 / years) - 1 eps_cagr = (eps_end / eps_start) ** (1 / years) - 1 fcf_cagr = (fcf_end / fcf_start) ** (1 / years) - 1 ``` Quality rules: - Dividend CAGR below EPS and FCF CAGR usually leaves room for future increases. - Dividend CAGR above EPS/FCF CAGR means payout ratio is expanding. - Flat dividend with rising FCF may imply hidden capacity or conservative management. - Repeated small increases can still be fragile if leverage is rising. ### Step 4: Check Balance Sheet Flexibility Look for the ability to maintain dividends during stress. | Item | Why It Matters | |------|----------------| | Cash and short-term investments | Near-term cushion | | Net debt / EBITDA | Debt burden against operating earnings | | Interest coverage | Ability to service debt before shareholder returns | | Debt maturity wall | Refinancing risk in high-rate environments | | Credit rating or covenant language | External constraints on payout policy | ### Step 5: Separate Dividend Yield from Total Return Dividend stocks can underperform if the yield comes from a falling price. Always connect income to valuation and growth. ```python expected_total_return = dividend_yield + expected_eps_growth + valuation_rerating ``` Do not present this as a guarantee. Use it as a scenario framework. ## Yield-Trap Checklist Flag a potential yield trap when several of these are true: - Dividend yield is more than 2x the company's 5-year median or sector median. - Payout ratio is above 90%, or FCF payout is above 100%. - Revenue, EPS, or FCF has declined for 2+ years. - Net debt / EBITDA is rising while interest coverage is falling. - Management has recently issued equity or debt while maintaining dividends. - The stock price fell before the yield became attractive. - Dividend history includes cuts, suspensions, or frequent special dividends labeled as ordinary income. - Sector faces structural pressure, regulation risk, or commodity down-cycle exposure. ## Strategy Types ### Dividend Growth Prioritize moderate yield, strong dividend CAGR, low payout ratio, and durable business quality. Good for users seeking compounding and lower cut risk. ### High-Yield Quality Prioritize yield, but require cash coverage, balance sheet resilience, and sector-aware payout norms. Good for users seeking current income, but the answer must discuss cut risk. ### Shareholder Yield Combine dividends, net buybacks, and debt reduction. Useful when companies return capital mostly through buybacks rather than cash dividends. ```python shareholder_yield = dividend_yield + net_buyback_yield + debt_paydown_yield ``` ### Dividend Capture Buying before t
Professional finance research toolkit — backtesting (7 engines + benchmark comparison panel), factor analysis, Alpha Zoo (452 pre-built alphas across qlib158/alpha101/gtja191/academic), options pricing, 77 finance skills, 29 multi-agent swarm teams, Trade Journal analyzer, and Shadow Account (extract → backtest → render) across 7 data sources (tushare, yfinance, okx, akshare, mootdx, ccxt, futu).
ADR/H-share/A-share cross-listing premium analysis — track pricing gaps between US-listed ADRs, HK-listed H-shares, and A-shares for arbitrage signals, dual-listing valuation, and delisting risk assessment.
AKShare financial data aggregator (18k+ stars). Free, no API key. Covers A-shares, US, HK, futures, macro, forex. Primary fallback for tushare and yfinance.
Browse and bench the bundled alpha zoos — prebuilt cross-sectional factor libraries (Kakushadze 101, GTJA 191, Qlib 158, Fama-French / Carhart). Use when the user asks "which alphas exist", wants metadata on a named alpha, or wants to run IC/IR on a whole zoo over a universe.
A 股 ST/*ST 风险预测框架 — 基于最新中报/三季报或业绩预告/快报,预测下一财年是否会因营收、利润、净资产、分红不达标而被风险警示,并将新浪监管处罚记录作为独立证据面纳入风险等级。仅适用于 A 股,不预测财务造假。
Asset allocation theory and optimizer usage — MPT / Black-Litterman / risk budgeting / all-weather strategy, including guides for 4 optimizers and rebalancing rules.
Diagnose failed or underperforming backtests, locate the root cause, and fix the issue
Behavioral finance applications: theories of overreaction and underreaction, behavioral explanations for momentum and reversal, investor sentiment cycles, cognitive-bias checklists, and debiasing quantitative strategies.