Investment Analysis Framework

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The Five Pillars — May 2026 Signals

Click any pillar to expand · Signals updated monthly

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Today’s Framework Question

One question per day, rotating through all five pillars

30-question bank · Date-seeded daily rotation · Streak tracked in your browser

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Unemployment is a classic lagging indicator; the yield curve is leading.’,l:’/macro-regime-detector-python-fred-api/’}, {p:’Macro Regime’,q:’If the composite regime score drops from +2 to −1 in one quarter, what does the framework suggest?’,o:[‘Stay fully invested’,’Trim equity 10–15% and shorten bond duration’,’Move entirely to cash’,’Double down — contrarian signal’],a:1,e:’A 3-point shift in a single quarter signals a regime transition. The framework prescribes trimming equity 10–15% and shortening bond duration as a measured, reversible defensive step.’,l:’/macro-regime-detector-python-fred-api/’}, {p:’Macro Regime’,q:’Which FRED series code represents the 10Y–2Y Treasury yield spread?’,o:[‘T10Y2Y’,’DGS10′,’FEDFUNDS’,’BAMLH0A0HYM2′],a:0,e:’T10Y2Y is the FRED series for the 10-Year minus 2-Year Treasury spread — the core yield curve inversion indicator used in the regime detector.’,l:’/macro-regime-detector-python-fred-api/’}, {p:’Macro Regime’,q:’Late-cycle macro regime typically shows which combination?’,o:[‘Inverted yield curve + falling unemployment + tight spreads’,’Steep yield curve + rising unemployment + wide spreads’,’Flat/slightly steep yield curve + stable unemployment + widening spreads’,’Deep recession + zero rates + QE’],a:2,e:’Late cycle: yield curve returning from inversion, unemployment still low but plateauing, credit spreads beginning to widen — exactly the May 2026 profile.’,l:’/macro-regime-detector-python-fred-api/’}, {p:’Macro Regime’,q:’What is the primary advantage of using a composite score over a single indicator?’,o:[‘It is more complex’,’It reduces false signals from any one noisy indicator’,’It always gives earlier signals’,’It eliminates qualitative judgment’],a:1,e:’No single indicator is reliable in isolation. Compositing 4–5 signals reduces false positives and smooths out noise in individual series.’,l:’/macro-regime-detector-python-fred-api/’}, {p:’Valuation’,q:’CAPE above 30 has historically been associated with what forward 10-year equity return?’,o:[‘Above 10% annualised’,’7–9% annualised’,’Below 5% annualised’,’Negative returns’],a:2,e:”Shiller’s data shows CAPE above 30 is associated with below-5% annualised 10-year real returns. At CAPE ~40, implied forward returns are very modest.”,l:’/stock-valuation-guide/’}, {p:’Valuation’,q:’A stock has fwd P/E 35x and FCF yield 1.2%. What does the framework say?’,o:[‘Strong buy’,’Avoid unless exceptional growth thesis’,’Hold — monitor revisions’,’Neutral — P/E is inconclusive’],a:1,e:’The framework requires BOTH fwd P/E below threshold AND FCF yield above ~3%. At 35x P/E and 1.2% FCF yield, the stock fails both tests.’,l:’/stock-valuation-guide/’}, {p:’Valuation’,q:’What does an accruals ratio above +0.05 suggest about reported earnings?’,o:[‘Earnings are highly cash-backed’,’Earnings are driven by accounting items, not cash’,’The company is rapidly growing’,’Margins are expanding’],a:1,e:’A ratio above +0.05 means earnings are being supported by non-cash accruals — a red flag that results may reverse.’,l:’/earnings-quality-analyzer-python-sec-edgar/’}, {p:’Valuation’,q:’Fwd P/E ~21x vs. 10-year average ~19x implies what about current valuations?’,o:[‘Markets are undervalued’,’Markets are fairly valued’,’Markets are pricing in above-average earnings growth’,’Markets are in a bubble’],a:2,e:’At a premium to historical average, the market prices in above-average earnings growth. If growth disappoints, multiple compression is the primary risk.’,l:’/stock-valuation-guide/’}, {p:’Valuation’,q:’Which valuation metric is most useful for comparing companies across capital structures?’,o:[‘P/E ratio’,’Price-to-book’,’EV/EBITDA’,’Dividend yield’],a:2,e:’EV/EBITDA uses enterprise value (includes debt) and pre-interest earnings, making it capital-structure neutral. P/E is affected by leverage.’,l:’/stock-valuation-guide/’}, {p:’Valuation’,q:’FCF yield is calculated as:’,o:[‘Net income ÷ market cap’,’Free cash flow ÷ enterprise value’,’Free cash flow ÷ market cap’,’Operating income ÷ revenue’],a:2,e:’FCF yield = Free Cash Flow ÷ Market Cap — the cash equivalent of a bond yield. Higher is generally better as a quality and value signal.’,l:’/stock-valuation-guide/’}, {p:’Momentum’,q:’The composite 3/6/12-month momentum signal reduces what type of risk vs. single-period momentum?’,o:[‘Market risk’,’Currency risk’,’Noise and false signals’,’Liquidity risk’],a:2,e:’Using three lookback periods ensures a stock shows persistent momentum across multiple timeframes — not just a recent spike.’,l:’/python-stock-momentum-scanner-free/’}, {p:’Momentum’,q:’According to the framework, when should you skip the momentum scanner entirely?’,o:[‘When VIX is below 15′,’When SPY is below its 200-day moving average’,’When interest rates are rising’,’When earnings season begins’],a:1,e:’Momentum is only valid in uptrending markets. When SPY is below its 200-day MA, individual signals are unreliable with too many false positives.’,l:’/python-stock-momentum-scanner-free/’}, {p:’Momentum’,q:’Why is a hard drawdown stop of −15% important in a momentum strategy?’,o:[‘It limits upside’,’It prevents momentum stocks from compounding losses if the thesis breaks’,’It is required by regulation’,’It improves average returns across all positions’],a:1,e:’Momentum stocks reverse sharply when sentiment shifts. A −15% stop limits downside on any single position, preventing one bad pick from dominating negative returns.’,l:’/python-stock-momentum-scanner-free/’}, {p:’Momentum’,q:’yfinance returns adjusted closing prices. Why does this matter for momentum calculations?’,o:[‘It inflates momentum scores’,’It accounts for dividends and splits, giving accurate historical returns’,’It removes volatility’,’It only affects intraday data’],a:1,e:’Adjusted prices account for splits and dividends so the calculated return reflects what an investor actually earned. Unadjusted prices create artificial gaps.’,l:’/python-stock-momentum-scanner-free/’}, {p:’Momentum’,q:’In the momentum scanner, why filter to S&P 500 constituents only?’,o:[‘They are always better investments’,’Reduces survivorship bias vs. small caps’,’Limits liquidity risk and avoids micro-cap noise’,’Both (b) and (c)’],a:2,e:’S&P 500 stocks are liquid, well-covered, and avoid micro-cap issues like wide bid-ask spreads and extreme volatility that distort signals.’,l:’/python-stock-momentum-scanner-free/’}, {p:’Momentum’,q:’Running the momentum scanner monthly rather than daily is recommended primarily to:’,o:[‘Reduce server costs’,’Limit overtrading and transaction costs’,’Increase number of signals’,’Match earnings frequency’],a:1,e:’Momentum is a medium-term phenomenon. Daily rebalancing creates excessive turnover and transaction costs that erode returns.’,l:’/python-stock-momentum-scanner-free/’}, {p:’Earnings Quality’,q:’Cash conversion ratio below 0.80 means:’,o:[‘Company generates $1.20 cash per $1 net income’,’Less than 80¢ of cash per $1 of reported net income’,’Company converts 80% of revenue to cash’,’Cash flow statement has errors’],a:1,e:’Cash conversion = CFO ÷ Net Income. Below 0.80 means reported earnings are running ahead of actual cash collected — a warning sign.’,l:’/earnings-quality-analyzer-python-sec-edgar/’}, {p:’Earnings Quality’,q:’The Sloan Accrual Anomaly shows that high-accrual companies tend to:’,o:[‘Outperform low-accrual peers over 1–3 years’,’Underperform low-accrual peers over the following 1–3 years’,’Show higher dividend growth’,’Trade at lower P/E multiples immediately’],a:1,e:”Sloan’s 1996 paper showed high-accrual firms systematically underperform over 1–3 years as accruals reverse and earnings disappoint.”,l:’/earnings-quality-analyzer-python-sec-edgar/’}, {p:’Earnings Quality’,q:’SEC EDGAR XBRL data is used in the earnings quality tool because:’,o:[‘It is the only source of financial data’,’It provides structured, machine-readable financial statements for free’,’It is faster than Bloomberg’,’XBRL data is audited separately’],a:1,e:”SEC EDGAR’s XBRL API provides free, structured access to financial statements for all US public companies. No API key needed.”,l:’/earnings-quality-analyzer-python-sec-edgar/’}, {p:’Earnings Quality’,q:’Before buying after an earnings beat, the framework says to check the accruals ratio. Why?’,o:[‘To confirm the beat was fully cash-backed’,’To determine if the CEO sold shares’,’To verify dividend sustainability’,’To check S&P 500 membership’],a:0,e:’An earnings beat driven by accruals (not cash) is lower quality and less likely to persist. Accruals ratio above +0.05 is a reason for caution.’,l:’/earnings-quality-analyzer-python-sec-edgar/’}, {p:’Earnings Quality’,q:’Cash conversion consistently above 1.1 means:’,o:[‘Company is over-investing in working capital’,’Company generates more cash than it reports as net income — high quality’,’The income statement has errors’,’Revenue recognition is being deferred’],a:1,e:’A ratio above 1.0 means more operating cash than net income — often conservative accounting or favourable working capital dynamics. A strong quality signal.’,l:’/earnings-quality-analyzer-python-sec-edgar/’}, {p:’Earnings Quality’,q:’Why run the earnings quality screen quarterly rather than after every release?’,o:[‘EDGAR only updates annually’,’Quarterly cadence matches the filing cycle and avoids single-quarter noise’,’Accruals only compound over multiple quarters’,’Daily data is unavailable’],a:1,e:’One quarter of high accruals may be noise. Running quarterly and looking for persistence across 2–3 quarters gives more reliable signals.’,l:’/earnings-quality-analyzer-python-sec-edgar/’}, {p:’Risk & Sizing’,q:’VaR 95% of −18% on a $100,000 portfolio means:’,o:[‘You will lose exactly $18,000 next year’,’In 95% of scenarios losses will exceed $18,000′,’In a bad-but-not-catastrophic year, expect to lose at least $18,000′,’There is a 95% chance of gaining money’],a:2,e:’VaR 95%: in 5% of simulated scenarios (the worst outcomes), losses exceed this threshold — the loss level you should be financially and emotionally prepared for.’,l:’/monte-carlo-portfolio-stress-test-python/’}, {p:’Risk & Sizing’,q:’In an RL allocation model, why apply a ±5% drift threshold before trading?’,o:[‘To satisfy SEC reporting requirements’,’To reduce transaction costs from overtrading on small signals’,’To match quarterly earnings reporting’,’To limit position size to 5%’],a:1,e:’The model generates continuous signals, but acting on every small shift incurs transaction costs. Only rebalancing when drift exceeds 5% filters noise and keeps costs low.’,l:’/reinforcement-learning-for-asset-allocation/’}, {p:’Risk & Sizing’,q:’In Monte Carlo simulation, which input most affects the VaR output?’,o:[‘Number of simulations (1,000 vs. 10,000)’,’Assumed correlation between assets’,’Assumed annual return (mu)’,’Time horizon’],a:1,e:’Asset correlations dominate — especially during stress when correlations spike toward 1.0, destroying diversification. Low stable correlation assumptions understate tail risk.’,l:’/monte-carlo-portfolio-stress-test-python/’}, {p:’Risk & Sizing’,q:’If your Monte Carlo VaR is larger than you can emotionally tolerate, the framework suggests:’,o:[‘Switch entirely to cash’,’Add leverage to improve expected returns’,’Shift 10–15% to short-duration bonds or cash before a downturn hits’,’Ignore it — VaR is just a model’],a:2,e:’The time to reduce risk is before volatility strikes, not during. Shifting 10–15% to bonds or cash is a measured, reversible de-risk.’,l:’/monte-carlo-portfolio-stress-test-python/’}, {p:’Risk & Sizing’,q:’Why is out-of-sample validation critical before deploying an RL allocation model with real capital?’,o:[‘Regulators require it’,’The model may be overfit to historical patterns that will not repeat’,’It reduces computation time’,’Out-of-sample data is more accurate’],a:1,e:’RL models can overfit to specific return patterns in training data. Validating on 2–3 unseen years tests whether the learned policy generalises.’,l:’/reinforcement-learning-for-asset-allocation/’}, {p:’Risk & Sizing’,q:’When VIX is above 25, the momentum framework says to:’,o:[‘Run the scanner more frequently’,’Skip or cut momentum position sizes by at least half’,’Increase equity allocation — fear creates value’,’Switch entirely to bonds’],a:1,e:’High VIX means elevated volatility and fragile momentum signals. Skip new entries or cut position sizes by half — the momentum factor historically underperforms in high-VIX regimes.’,l:’/python-stock-momentum-scanner-free/’} ]; var dayIdx=Math.floor(Date.now()/86400000)%30; var q=Q[dayIdx]; var todayStr=new Date().toDateString(); function getStreak(){var s=parseInt(localStorage.getItem(‘fwStreak’)||’0′);var last=localStorage.getItem(‘fwDate’);var yest=new Date(Date.now()-86400000).toDateString();if(last!==yest&&last!==todayStr){s=0;localStorage.setItem(‘fwStreak’,’0′);}return s;} function showStreak(){var s=getStreak();var el=document.getElementById(‘streak-el’);if(el)el.textContent=s>0?(‘🔥 ‘+s+’ day’+(s!==1?’s’:”)+’ streak’):”;} function renderQ(){document.getElementById(‘q-pillar’).textContent=q.p;document.getElementById(‘q-text’).innerHTML=q.q;var h=”;for(var i=0;i<q.o.length;i++){h+=' ‘+q.o[i]+’‘;}document.getElementById(‘q-opts’).innerHTML=h;} function showAnswered(ok){document.getElementById(‘q-btn’).style.display=’none’;document.getElementById(‘q-done’).style.display=’block’;var r=document.getElementById(‘q-result’);r.style.display=’block’;r.className=’quiz-result ‘+(ok?’ok’:’err’);r.innerHTML=(ok?’✅ Correct! ‘:(‘❌ The answer is: ‘+q.o[q.a]+’. ‘))+q.e+’ Read more →‘;document.querySelectorAll(‘#q-opts input’).forEach(function(i){i.disabled=true;});} window.quizSubmit=function(){var sel=document.querySelector(‘#q-opts input:checked’);if(!sel){alert(‘Please select an answer first.’);return;}var v=parseInt(sel.value);var ok=v===q.a;var s=getStreak();var last=localStorage.getItem(‘fwDate’);var yest=new Date(Date.now()-86400000).toDateString();if(ok){s=(last===yest)?s+1:1;localStorage.setItem(‘fwStreak’,s);}localStorage.setItem(‘fwDate’,todayStr);localStorage.setItem(‘fwCorrect’,ok?’1′:’0′);showStreak();showAnswered(ok);}; showStreak();renderQ(); if(localStorage.getItem(‘fwDate’)===todayStr){showAnswered(localStorage.getItem(‘fwCorrect’)===’1′);} })();