Glossary of quantum-model, market-conditions, and risk terms

• Expected Growth: The expected growth is the probability-weighted average return across all simulated price paths produced by the Schrödinger-based quantum model. It represents the model's best single-number estimate of future return at the chosen horizon, but should always be read alongside the CI90 band to understand the distribution of outcomes.
• Current Price: The current price is the most recent share price our market-data provider reported for the stock. It is the reference point for every forward-looking figure we show: expected growth is the change from this price, the target price is where the model projects it may sit at the horizon, and the stop-loss and take-profit levels are set relative to it. It is the last reported price rather than a live tick, so a broker screen may show a slightly different number during market hours.
• Target Price: The target price is the mean of the quantum model's simulated price distribution at the forecast horizon. The accompanying CI90 band (q05–q95) captures 90% of simulated outcomes — prices outside this band are treated as tail events. A wide band signals high uncertainty; a narrow band signals strong model conviction.
• Chance of a gain (quantum paths): Growth probability is the fraction of Feynman path-integral simulated trajectories that finish above the current price at the forecast horizon. It is not a guarantee: even at 95% probability, 1 in 20 outcomes is a decline. This metric should be combined with MAPE and CI90 backtest accuracy to assess how trustworthy the probability estimate is for this specific ticker.
• Chance of a loss (quantum paths): The fraction of Feynman path-integral simulated trajectories that finish below the current price at the forecast horizon. It is the complement of the quantum growth probability (the two sum to 100%), computed from the same path simulation — not a separate model and not the Random Forest downside probability, which asks a different question (will the price breach a fixed threshold) and will legitimately disagree.
• Price-range check: CI90 backtest accuracy measures how well-calibrated the model's 90% confidence intervals are on historical data for this ticker. A value of 90% means the interval captured the realised price exactly as often as claimed, and we treat the closed 85–95% range as well-calibrated. Values below that range mean the model is over-confident — its bands are too narrow relative to actual price variability, so the real downside is wider than it looks. Values above it mean the opposite failure: a "90% band" that historically contained 99% of prices is simply too wide to tell you much. Both directions are miscalibration; only the middle earns a green badge.
• Typical error (MAPE): Mean Absolute Percentage Error (MAPE) measures the average magnitude of forecast errors as a percentage of the realized value, computed over the model's historical out-of-sample predictions — the realized price for a ticker, or the realized index level for the Fear & Greed forecast. Lower MAPE indicates a more accurate point forecast. It should be read alongside CI90 calibration: a low MAPE with poor CI90 coverage suggests the model is accurate on average but poor at expressing uncertainty.
• Forecast Range Width: Forecast range width is the span of the model's 90% confidence band at the selected horizon, expressed as a percentage of the current price. It measures how precise the forecast is — a 20% width is a confident, narrow call; a 150% width is the model admitting it has very little idea. Width on its own is NOT a quality score: any model can produce a narrow band by simply being overconfident. It must be read together with the range accuracy (how often prices actually land inside the band). A model that is both narrow AND accurate is genuinely informative; narrow and inaccurate is the dangerous combination.
• Range Quality Score: The range quality score (known in forecasting literature as the Winkler or interval score) grades a confidence band on the two things that trade off against each other: width and coverage. A band earns a penalty proportional to how wide it is, plus a much larger penalty whenever the realized price falls outside it. Lower is better. This is what stops the two obvious ways of gaming a forecast: a very wide band always contains the price but scores badly on width, while a very narrow band scores well on width but is punished hard every time it misses. It is the single fairest summary of whether our uncertainty estimates are honest.
• Moves vs the S&P 500 (Beta): Beta measures the sensitivity of a stock's returns to S&P 500 returns, estimated via OLS regression over a rolling 1-year window of daily returns. A beta above 1 amplifies both gains and losses relative to the index. Beta is an input to the quantum model's volatility calibration and to the Kelly position-sizing calculation.
• Typical daily swing: Daily volatility (σ) is the one-standard-deviation range of daily price changes in dollar terms, computed over a trailing 30-day window. It is the primary diffusion parameter driving how far the quantum model's simulated price paths spread. Higher σ directly widens the CI90 confidence band, reflecting greater uncertainty in the price distribution.
• Direction (model signal): The ML Signal is a three-class label (BULLISH / NEUTRAL / BEARISH) produced by a Random Forest model trained on a blend of technical, fundamental, and sentiment features. BULLISH means the model estimates a high probability of exceeding the return threshold; BEARISH means the probability is low and existing longs may be reconsidered. This is not a short-sell signal — the platform does not recommend shorting.
• ML upside probability (+5% move): Buy probability is the calibrated output of the Random Forest classifier, representing the estimated likelihood that the stock will exceed the configured return threshold (default +5%) within the forecast horizon (default 63 trading days). Calibration aims to align the stated probability with observed historical frequencies in aggregate — a 70% reading aims to correspond to roughly a 70% historical success rate — but per-ticker verification rests on small samples, so treat it as a best estimate, not a guarantee. It is the probability of a threshold event, not an expected return magnitude.
• Model Confidence: Model confidence is derived from the buy probability by measuring its distance from the 50% (coin-flip) baseline, then scaling to a 0–100% range. A buy probability of 80% yields 60% confidence. High confidence means the model has a strong view; low confidence means the signal is weak and position sizing should be reduced accordingly.
• BT Precision (BUY): Backtest precision (BUY) measures the historical accuracy of BUY signals for this specific ticker — of all past signals classified as BUY, how many were followed by a return at or above the threshold within the horizon. It is computed per-ticker from out-of-sample backtests and is a key input to the Kelly position-sizing formula.
• BT Win Rate: Backtest win rate counts the percentage of past BUY entries that resulted in any positive return by the end of the forecast horizon, regardless of whether the return threshold was met. It is distinct from precision (which requires meeting the threshold) and is used alongside avg return in the Kelly sizing formula.
• BT Avg Return: Backtest average return is the mean profit/loss across all historical BUY signals for this ticker, expressed as a percentage of entry price. It blends winning and losing trades and represents the expected value of a typical BUY entry. Together with win rate, it determines the Kelly criterion fraction for optimal position sizing.
• Recommended Position Size: Recommended position size combines the raw Kelly fraction with a confidence multiplier (so low-conviction signals get smaller allocations) and a hard portfolio cap (default 10% per position). A reading of 0% means the Kelly formula found no positive edge — either backtest edge is negative or confidence is too low to justify a bet.
• Kelly Size: Kelly size is the half-Kelly fraction: 50% of the full Kelly optimal bet, computed as f* = (p·b − q) / b where p is win rate, q = 1−p, and b is the average win divided by average loss. Using half-Kelly rather than full-Kelly reduces variance significantly with only modest reduction in long-run growth rate.
• Risk per Trade: Risk per trade is the fraction of portfolio capital lost if the position is stopped out AT the stop-loss level. It is computed as the recommended position size × the stop-loss percentage — an 8% position with a stop 15% below entry risks 8% × 15% = 1.2% of the portfolio. Keeping it to 1–2% per trade is a standard rule for surviving drawdowns. Treat it as a planning figure, not a guarantee: it holds only when the stop actually fills at its price. A gap through the stop fills lower and loses more, and in the worst case the whole position can be lost — so your true hard bound is the position size, not this number.
• Position Size: The share of portfolio capital to put into this position. It is a size, not a risk: a 10% position is not a 10% risk. The size is solved backwards from the stop — the further the stop sits below entry, the smaller the position, so that a stop-out costs roughly 1% of the portfolio — then capped at 10% of the portfolio. When that cap binds (a tight stop), the loss on a stop-out is smaller than 1%.
• Max Loss if Stop Hits: The share of portfolio capital lost if this trade is stopped out at the stop price: position size × the entry-to-stop distance. It is computed from the actual levels rather than assumed, so it lands at or below the 1%-per-trade budget. It is a conditional figure, not a floor: stops are not guaranteed fills, and a gap through the stop loses more. Worst case, a long position can lose its entire value, so the true hard bound on your loss is the position size itself.
• Stop Loss: The stop-loss level is the price at which a position should be exited to limit further downside. It is set using the most conservative of three rules: recent support level, 2× ATR below entry, or a fixed percentage floor. Breaching this level is a signal to exit, not to add — the model's thesis is considered invalidated.
• Take Profit: The take-profit level is the price target at which gains should be locked in. It is sized to achieve at least a 2:1 risk/reward ratio relative to the stop-loss. A partial-exit ladder (e.g. 33% at TP1, 33% at TP2, trail the remainder) is recommended to capture most of the move without sacrificing all upside.
• Reward vs risk: The risk/reward ratio compares the potential gain to the potential loss for a given entry. Computed as (first profit target − entry) ÷ (entry − stop-loss). A ratio below 2 means the upside does not justify the downside; the platform filters out any signal where R:R < 2 before showing a BUY verdict.
• Planned reward vs risk: The swing plan's planned reward-to-risk is (target 2 − entry) / (entry − stop-loss). Because target 2 is placed at a fixed multiple of the risk leg for the current market regime, this ratio equals that multiple by construction and is the same for every signal in that regime. It is a parameter of the take-profit ladder, not an assessment of an individual trade. The conservative, forecast-derived reward-to-risk that the sizing gate judges is published separately as "Reward vs risk".
• R-Multiple: An R-multiple expresses a trade's profit or loss as a multiple of the initial dollar risk ("1R") rather than as a raw dollar amount or percentage — a +2R trade made twice what it risked; a -1R trade lost exactly the planned stop-loss amount. Realized R-multiples across many closed trades reveal the actual distribution of outcomes, not just the plan — tracking the average R-multiple alongside win rate is what reveals whether a strategy has positive expectancy over time.
• Total Signals: The total signal count is every paper-traded call logged since tracking began — the sum of open (still running) and closed (finished) positions. Nothing is deleted or excluded after the fact, so this number is the honest denominator behind every other paper-trading statistic on the card.
• Open Positions: Open positions are paper-traded calls that have not yet closed — the price has not reached the stop-loss, the final take-profit rung, or the position's time limit. This count is directional-neutral: a large or small number of open positions says nothing about performance on its own, only how many calls are currently being tracked.
• Closed Positions: Closed positions are paper-traded calls that have fully resolved — exited at a stop-loss, a take-profit target, or a time limit — and are the trades that feed Hit Rate, Avg R and Total R. An open position only moves into this count once it actually finishes; nothing is closed early or excluded to flatter the statistics.
• Hit Rate: Paper-trading hit rate is the percentage of closed paper trades that ended profitable, counted from the forward log: every signal is recorded when it is published, tracked in real time, and closed at its stop, take-profit or time limit — no trade is added or removed after the fact. That makes it a forward result rather than a backtest, which re-runs the rules over past data and can flatter itself through hindsight. Its honest failure mode is that it says nothing about the SIZE of wins and losses: a strategy can win most of its trades and still lose money if the few losses are large, so read it together with the average R-multiple, and treat it as noisy until a meaningful number of trades have actually closed.
• ML downside probability: Sell probability is the calibrated Random Forest probability that the stock will decline beyond the configured threshold within the forecast horizon — the complementary read to ML Buy Probability, not a separate model. A high ML downside probability alongside a rising ML upside probability usually signals conflicting features (high variance) rather than a confident bearish call.
• Risk Floor: The risk floor is the more conservative (higher) of two downside reference levels: the 25th percentile (Q25) of the quantum-forecast terminal-price distribution, and a volatility-based stop 1.5 standard deviations below the current price. It marks where the forecast band's downside sits, not a trade-specific stop-loss — the Position & Exits region above uses its own Stop Loss level for that.
• Where the model puts price: Q60, Q75 and Q90 are percentiles of how far the quantum forecast's simulated paths REACH before the horizon ends: Q60 is the level 40% of those paths trade up through at some point, Q75 the level 25% reach, Q90 the level 10% reach. They are measured on the touch, because that is the event a limit order fills on — the chance of the price still sitting above the level at the end is lower. They are a different convention from the swing-trade take-profit ladder (TP1/TP2/TP3), which is R-multiple based and shown separately.
• Profit target: A take-profit ladder splits an exit into staged rungs instead of one all-or-nothing target. Quantustik's exit plan suggests trimming 50% of the position if TP1 is reached, a further 30% at TP2, and letting the remaining 20% ride a volatility-based trailing stop toward TP3. Locking in most of a move beats holding out for a full exit that can round-trip back to breakeven.
• Trailing stop: A trailing stop follows price higher (for a long position) but never moves down, locking in a growing share of unrealized gains as the trade works. Quantustik ties the trail distance to volatility (1.5x ATR14) rather than a fixed percentage, so it stays proportionate whether the underlying is calm or turbulent, and only activates once a tracked position has advanced past TP2.
• Invalidation level: The invalidation level is the price or condition that, if breached, means the setup that justified this trade no longer holds. It is distinct from the stop-loss (which caps dollar risk): breaching it is a signal that the thesis itself was wrong, not just that the trade moved against you — the correct response is to exit and reassess, not to average down.
• Google Interest: Google Interest scores the relative search volume for "<TICKER> stock" via Google Trends over the trailing month, normalised to 0–100 where 100 is peak interest in the period. Spikes in retail search interest often precede elevated volume and price volatility, making this a useful leading indicator of crowd attention.
• Interest Δ 7d: Interest Δ 7d measures the momentum of retail attention: the percent change in Google search interest over the most recent 7-day window vs the prior 7-day window. A sharp positive reading often coincides with news catalysts or social-media amplification; a declining reading may signal fading interest after an initial spike.
• Social Hype Score: Social Hype Score is a composite indicator combining Google Trends momentum and (when enabled) Twitter/X sentiment into a single 0–100 normalised score. 50 represents neutral; readings above 70 indicate elevated crowd attention that can amplify price moves in either direction. It is an input feature to the ML classifier.
• StockTwits Sentiment: StockTwits sentiment is the fraction of messages tagged as "bullish" on the StockTwits platform over the trailing 24-hour window. It reflects the real-time mood of retail traders who self-classify their sentiment. Extreme readings (>80% or <20%) can indicate crowded positioning and potential mean-reversion.
• Analyst Rating: Analyst rating is the mean Wall Street consensus score, where 1 = Strong Buy and 5 = Strong Sell. Consensus ratings are a lagging indicator — they reflect institutional opinion but are slow to update. The platform uses them as one input among many rather than a primary signal.
• Analyst Target Upside: Analyst target upside is the percentage difference between the consensus 12-month price target and the current market price. A positive value indicates the street collectively expects appreciation. This metric can diverge significantly from the quantum model's target — both are shown so the user can assess the spread between model and consensus.
• Upgrades (30d): Upgrades (30d) counts the number of analyst rating improvements (e.g. Hold → Buy, Sell → Hold) published for this ticker in the trailing 30-day window. Multiple upgrades in a short period can signal a turning point in institutional sentiment and often precede increased fund inflows.
• Analysts Covering: Analyst coverage is the count of sell-side analysts who have an active rating on this ticker, aggregated from FMP's consensus feed. It is a neutral metric — it does not itself indicate bullish or bearish sentiment, only how much Street attention the name gets.
• Avg Price Target: The average (consensus) 12-month price target published by covering analysts. Shown alongside the current price so the reader can triangulate against the quantum model's own target — this is the exact number competing SERP results (MarketBeat, TipRanks, StockAnalysis) lead with, so it is surfaced here for direct comparison.
• Buy Ratings: Count of analysts with an active Buy or Strong Buy rating on this ticker. A high buy count relative to hold/sell counts indicates a bullish sell-side consensus — a lagging, herd-following signal that is shown for cross-reference against the model's own signal, not as a standalone recommendation.
• Hold Ratings: Count of analysts with an active Hold rating. A large hold count relative to buy/sell suggests the Street sees limited near-term catalyst in either direction.
• Sell Ratings: Count of analysts with an active Sell or Strong Sell rating. A high sell count relative to buy/hold counts indicates a bearish sell-side consensus, shown for cross-reference against the model's own signal.
• News Sentiment: News sentiment is the average tone score of recent news headlines for this ticker. Each headline is scored by a language model on a scale from −1 (strongly bearish) through 0 (neutral) to +1 (strongly bullish), and the scores are averaged over the trailing 7-day headline window. It is an input feature to the ML classifier. It is a level, not a change — see Sentiment Trend for whether the tone is improving or deteriorating.
• Sentiment Trend: Sentiment Trend measures the direction of travel in news tone rather than its level. Headlines in the trailing 7-day window are split at a 3-day boundary and the trend is mean(recent scores) − mean(older scores). A stock can carry a negative sentiment level and a positive sentiment trend at the same time: the news is bad, and it is getting less bad. Small values are noise, which is why the ±0.10 dead band is left uncoloured.
• News Count (7d): News Count is the number of news headlines about this ticker, published in the trailing 7 days, that were found and successfully scored for tone. It measures how loudly the market is talking about a company and says nothing about whether the talk is good or bad — a scandal and a record quarter generate headlines alike. Because the count is capped at 20 and not deduplicated, a single heavily-syndicated event can push it to its ceiling. Read it alongside News Sentiment, which supplies the direction that this number deliberately does not.
• Call/Put Ratio: The call/put ratio divides total call open interest by total put open interest across all strikes and expiries. A high ratio suggests traders are positioning for upside (or hedging short positions); a low ratio suggests hedging or bearish positioning. Extreme readings can indicate crowded positioning that may reverse.
• Smart Money Flow: Smart money flow is a directional indicator that attempts to isolate large-lot institutional order activity from retail noise. A positive reading suggests institutional buying pressure; negative suggests institutional selling. It is derived from intraday tape analysis and is inherently noisy on individual days.
• Concentration (HHI): The Herfindahl-Hirschman Index (HHI) sums the squares of your portfolio weights, producing a number between 0 and 1. A portfolio of 10 equally weighted names scores 0.10; putting everything in one stock scores 1.00. Its inverse (1 / HHI) is the "effective number of names" you actually hold — a useful reality check when a few positions dominate. High concentration is not automatically wrong (conviction has to be expressed somehow), but it does mean a single company's bad news becomes your portfolio's bad news, so we flag it as a caution rather than an error.
• Unusual Call Activity: Unusual call activity flags when call-option volume for this ticker significantly exceeds its rolling 20-day average. It is expressed as a multiple of the average (e.g. 3× = three times normal volume). Elevated readings can indicate informed positioning before earnings or catalysts, but may also reflect retail speculation.
• Short % of Float: Short percentage of float measures the fraction of the available share float that is currently sold short. High short interest (>20%) reflects significant bearish conviction but also creates potential for a short squeeze if positive catalysts emerge. It is updated bi-monthly from FINRA data and is inherently lagged.
• P/E Ratio: The price-to-earnings ratio divides the current share price by trailing 12-month earnings per share (TTM EPS). It is the most widely used valuation multiple. A very low P/E can indicate distress or deep value; a very high P/E implies the market is pricing in strong future growth. Comparison across sectors is misleading — use sector-relative percentiles.
• Quality Score: Quality Score is a heuristic screen of how profitable a company is, blending return on equity (profit earned on shareholders' money) with profit margin (share of each sales dollar kept). Higher is better; it is a fundamental sanity check, not the quantum forecast and not a probability, and it ignores leverage — a high score does not mean low debt.
• Growth Score: Growth Score is a heuristic screen of how fast a company is growing, blending recent revenue and earnings growth. Higher is faster; it is backward-looking and can be lumpy year to year, and it is a fundamental sanity check, not the quantum forecast and not a probability.

Browse all 239 glossary guides A–Z →

All 239 glossary terms A–Z

A

• Are AI stock predictions accurate? An honest answer

C

• Cap-weighted vs equal-weighted: the same sector, two answers

F

• Filing language diff: reading what a company quietly reworded

G

• Growth vs. value investing: what's the difference?

H

• How does signal gating work (the "Safety checks" list)?
• How does the Schrödinger equation apply to stock forecasting?
• How is the high-yield credit spread a market-conditions signal?
• How to read a stock forecast — a plain-language guide

I

• Implied vs historical volatility — what's the difference?
• Index fund vs. ETF: what's the difference?

N

• News Count: what the headline counter actually counts

R

• Realised vs forecast correlation: the two heatmap modes

S

• Scan freshness: how old is the data you are looking at?
• Sentiment Trend: is the news tone getting better or worse?

W

• Weighted max drawdown: what your portfolio card is telling you
• What are Bollinger Bands?
• What are bonds, and how do they differ from stocks?
• What are capital gains?
• What are initial jobless claims?
• What are insider cluster buys?
• What are Q60 / Q75 / Q90 forecast percentiles in a stock forecast?
• What are shares outstanding (and float)?
• What are stop-loss and take-profit levels?
• What are support and resistance?
• What are the golden cross and death cross?
• What are the Quality, Growth and Value scores?
• What does the "Model Quality" panel actually measure?
• What does the VIX’s absolute level signal?
• What does Upgrades (30d) mean for a stock?
• What is "path momentum" (is the forecast in step with the stock)?
• What is a 401(k)?
• What is a bear market?
• What is a blue-chip stock?
• What is a breakeven stop (the "BE Stop" outcome)?
• What is a Brier score?
• What is a bull market?
• What is a call option?
• What is a CI90 confidence interval in a stock forecast?
• What is a discounted cash flow (DCF)?
• What is a Dividend Aristocrat?
• What is a Feynman path integral in stock forecasting?
• What is a forecast horizon?
• What is a fund expense ratio?
• What is a GICS sector?
• What is a holding period?
• What is a limit order?
• What is a margin call (and what is buying on margin)?
• What is a margin of safety?
• What is a market correction?
• What is a market order?
• What is a moving average?
• What is a NAV premium or discount?
• What is a put option?
• What is a qualified dividend?
• What is a Roth IRA?
• What is a stock buyback (share repurchase)?
• What is a stock split?
• What is a stop order (stop-loss)?
• What is a structural break in a stock's price history?
• What is a swing signal in stock trading?
• What is a t-statistic (and why does our track record show one)?
• What is a target price in a stock forecast?
• What is a target-date fund?
• What is a ticker symbol?
• What is a time stop?
• What is a traditional IRA?
• What is a trailing stop?
• What is alpha in investing?
• What is an activist investor (SC 13D/13G) alert?
• What is an earnings (EPS) surprise?
• What is an earnings report (and earnings season)?
• What is an entry plan?
• What is an equity curve?
• What is an IPO (initial public offering)?
• What is an R-multiple in trading?
• What is an SEC Form 10-K?
• What is an SEC Form 10-Q?
• What is an SEC Form 4 open-market purchase?
• What is an SEC Form 8-K?
• What is an unusually large insider buy?
• What is analyst coverage?
• What is analyst rating consensus, and how reliable is it?
• What is analyst target upside?
• What is anchoring bias?
• What is asset allocation?
• What is ATR (Average True Range)?
• What is backtest average return?
• What is backtest precision (BUY signals)?
• What is backtest win rate?
• What is beta (β) in stock investing?
• What is book value?
• What is CAGR (compound annual growth rate)?
• What is capitulation in the stock market?
• What is CI50 coverage?
• What is CI90 coverage (band calibration)?
• What is compound interest (and why start early)?
• What is confirmation bias?
• What is congressional trading disclosure data?
• What is conviction tier in a stock signal?
• What is correlation in investing?
• What is cost basis?
• What is daily volatility (σ) in a stock forecast?
• What is direction agreement (and what is Chronos-2)?
• What is directional hit rate?
• What is diversification in investing?
• What is dividend payout frequency?
• What is dividend yield?
• What is dollar-cost averaging?
• What is earnings per share (EPS)?
• What is earnings yield?
• What is EBITDA?
• What is entanglement (forecast co-movement) in stock forecasting?
• What is enterprise value (and EV/EBITDA)?
• What is EPS growth (year-over-year)?
• What is expectancy in trading?
• What is expected growth / target price in a stock forecast?
• What is FOMO (fear of missing out) in investing?
• What is forecast reliability in a stock signal?
• What is free cash flow (FCF)?
• What is Google search interest for a stock?
• What is gross margin?
• What is herd behavior in investing?
• What is institutional 13F flow?
• What is intrinsic value?
• What is Kelly size / recommended position size?
• What is liquidity in stock trading?
• What is loss aversion?
• What is MACD (Moving Average Convergence Divergence)?
• What is MAPE in a stock forecast accuracy check?
• What is market breadth?
• What is market capitalization?
• What is market-conditions position sizing?
• What is max drawdown?
• What is mean reversion?
• What is model confidence in a stock signal?
• What is operating margin?
• What is overconfidence bias in investing?
• What is overfitting (and why does it make backtests lie)?
• What is overtrading?
• What is paper trading?
• What is portfolio concentration (HHI)?
• What is portfolio rebalancing?
• What is profit margin?
• What is prospect theory?
• What is quantum forecast alignment?
• What is quantum tunneling probability in market sentiment analysis?
• What is Quantustik's Market Conditions score?
• What is random matrix theory in market analysis?
• What is realised return?
• What is recency bias?
• What is return on equity (ROE)?
• What is return on investment (ROI)?
• What is revenue growth (year-over-year)?
• What is risk per trade?
• What is RMSE (root-mean-squared error)?
• What is ROIC (return on invested capital)?
• What is sector rotation in the stock market?
• What is short percent of float?
• What is short selling?
• What is Smart Money Flow in a stock forecast?
• What is standard deviation?
• What is StockTwits sentiment?
• What is tax-loss harvesting?
• What is the "quantum direction" component?
• What is the "quantum tail risk" component?
• What is the 13F whale amount?
• What is the 5-year dividend CAGR?
• What is the 52-week high/low?
• What is the AAII Investor Sentiment Survey?
• What is the analyst buy-ratings count?
• What is the analyst hold-ratings count?
• What is the analyst price-target consensus?
• What is the analyst sell-ratings count?
• What is the analyst upgrade/downgrade shift?
• What is the AR(2) model on the Fear & Greed forecast?
• What is the AR(2) model on the VIX forecast?
• What is the average analyst price target?
• What is the bid-ask spread?
• What is the Calmar ratio?
• What is the chance of a gain in a stock forecast?
• What is the contrarian Fear & Greed signal?
• What is the conviction ledger?
• What is the conviction score?
• What is the current ratio?
• What is the debt-to-equity ratio?
• What is the disposition effect?
• What is the dividend payout ratio?
• What is the ex-dividend date?
• What is the Fear & Greed Index?
• What is the forward P/E ratio?
• What is the froth check (is the market overheating)?
• What is the growing count on a scan?
• What is the high-yield credit spread (HY OAS)?
• What is the invalidation level on a trade plan?
• What is the Macro-GBM model on the Fear & Greed forecast?
• What is the Macro-OU model on the Fear & Greed forecast?
• What is the Market Conditions forward trajectory?
• What is the Market Conditions model on the Fear & Greed forecast?
• What is the Market Conditions model on the VIX forecast?
• What is the MD&A section of a 10-K?
• What is the ML Buy Probability?
• What is the ML downside probability?
• What is the ML model on the Fear & Greed forecast?
• What is the ML Signal?
• What is the News Sentiment score for a stock?
• What is the Ornstein–Uhlenbeck process, and why use it as a baseline?
• What is the OU model on the Fear & Greed forecast?
• What is the OU model on the VIX forecast?
• What is the P/E ratio (price-to-earnings)?
• What is the PEG ratio?
• What is the per-ticker price-range check (CI90 coverage)?
• What is the price-to-book (P/B) ratio?
• What is the price-to-sales (P/S) ratio?
• What is the put/call ratio?
• What is the Q-PI (quantum path-integral) model on the Fear & Greed forecast?
• What is the Q-PI + ML (default) model on the Fear & Greed forecast?
• What is the quick ratio (acid-test ratio)?
• What is the Relative Strength Index (RSI)?
• What is the Risk Factors section of a 10-K?
• What is the risk floor in a stock forecast?
• What is the risk-free rate?
• What is the risk/reward ratio on a stock trade?
• What is the S&P 500?
• What is the scan aggregate signal?
• What is the Sharpe ratio (90-day estimate)?
• What is the Social Hype Score for a stock?
• What is the Sortino ratio?
• What is the sunk-cost fallacy in investing?
• What is the suppression-gate trace (the "Safety checks" list)?
• What is the VIX (Volatility Index)?
• What is the VIX term structure?
• What is the wash-sale rule?
• What is the Winkler (interval) score?
• What is the yield curve (10Y-2Y spread)?
• What is the Zweig Breadth Thrust?
• What is total return?
• What is unusual options activity?
• What is Value at Risk (VaR)?
• What is VWAP (volume-weighted average price)?

Educational research only — not investment advice.