Appearance
Key Terms Explained
| Term | Simple Explanation |
|---|---|
| Ticker | A stock's symbol (e.g., AAPL for Apple, TSLA for Tesla) |
| Pipeline | The 5-stage daily cycle: Collect → Analyze → Predict → Validate → Learn |
| Error % | How far off a prediction was. Green < 5%, Amber 5–10%, Red > 10% |
| Confidence | How sure the system is (0 to 1). Above 0.7 is strong |
| Confidence Band | A predicted price range (low to high) instead of a single number |
| Band Hit | Whether the actual price fell within the predicted range |
| Sentiment | How positive or negative the news is |
| Momentum | Whether sentiment is getting stronger or weaker (0–100) |
| Buzz | Social media engagement — how much discussion an article generates (0–100) |
| Relevance | How important an article is to the tracked stock (0–100) |
| Surprise | An unexpected event detected in the news (earnings beat/miss, economic shock, etc.) |
| Magnitude | How big a surprise is (0–100). 0–30 = minor, 30–60 = moderate, 60–100 = major |
| Direction | Whether a surprise is positive (beat) or negative (miss) |
| Cognitive Bias | An irrational thinking pattern (like FOMO) that affects decisions |
| Bullish | Expecting the price to go up |
| Bearish | Expecting the price to go down |
| OHLCV | Open, High, Low, Close, Volume — the standard daily trading data fields |
| Volume | Number of shares traded. Higher = more investor interest |
| RSI | A 0–100 score. Above 70 = might be overbought. Below 30 = might be oversold |
| EPS | Earnings Per Share — profit divided by all shares. Higher = more profitable per share |
| P/E Ratio | Price divided by annual earnings. High = growth expected, Low = possibly undervalued |
| Revenue | Total income from sales before any expenses are deducted |
| Net Income | Profit after all expenses, taxes, and costs — the bottom line |
| Gross Profit | Revenue minus the direct cost of producing goods or services |
| Operating Income | Profit from core business operations, excluding interest and taxes |
| EBITDA | Earnings Before Interest, Taxes, Depreciation, and Amortization — a proxy for operating cash flow |
| Income Statement | Financial report showing revenue, expenses, and profit over a period |
| Balance Sheet | Snapshot of what a company owns (assets), owes (liabilities), and shareholders' equity |
| Cash Flow Statement | Tracks actual cash coming in and going out from operations, investments, and financing |
| Assets | Everything a company owns that has value (cash, buildings, inventory, etc.) |
| Liabilities | Debts and obligations the company owes to others |
| Equity | Owners' stake: Assets minus Liabilities |
| Cash & Equivalents | Highly liquid assets like bank deposits and short-term investments |
| Long-term Debt | Borrowings due more than one year away |
| Operating Cash Flow | Cash generated from normal business operations — a sign of business health |
| CapEx | Capital Expenditure — money spent to buy or maintain fixed assets like equipment |
| Free Cash Flow | Cash left after CapEx — available for dividends, debt repayment, or reinvestment |
| Dividends | Payments distributed to shareholders from company profits |
| TTM | Trailing Twelve Months — the most recent four quarters of financial data rolled up |
| Annual | Financial data covering one full fiscal year |
| Quarterly | Financial data covering a three-month period |
| Horizon | How far ahead the prediction looks (short = 1-2 days, long = ~10 days) |
| Intermediate Prediction | A rough update made during the day as new news arrives |
| Final Prediction | The refined, complete forecast after all data is processed |
| Self-Correction | The system notices when it consistently over/under predicts and adjusts automatically |
| ADF Test | Augmented Dickey-Fuller test — a statistical test that checks whether a time series is stationary (i.e., its properties don't change over time). If the price series is non-stationary, the system differences it before fitting regression models to avoid spurious results |
| OLS Regression | Ordinary Least Squares — a method that fits a straight line through data points by minimising the sum of squared errors between predicted and actual values. Used to estimate trends, drift, and relationships in price data |
| MAPE | Mean Absolute Percentage Error — the average prediction error as a percentage. Used as a gating check: if MAPE exceeds a configured threshold, new predictions are withheld to prevent false outputs |
| RSS | A web feed format used to deliver news articles. FIN monitors RSS feeds from Google News, Yahoo Finance, Reddit, and corporate announcements |
| Snapshot | A saved record of a prediction and all the data that went into it |

