Daily US Stock Signals: Post-Close Signal Dashboard

These four figures describe the most recent completed scan. They are counts produced by the rules below — not performance results, and not a forecast.

⚡ Active Signals — BUY Only

Showing stocks with a BUY decision only (22 or more of 30 signals bullish). WATCH stocks are hidden. Session scored: 2026-09-03

End-of-day data. Signals reflect the prior close, not real-time prices.

48 of 179 scored equities (26.8%) reached the 22-of-30 confluence threshold on 2026-09-03. The same scan drives the Signal Breadth Index and Sector Confluence, and is published as JSON.

How to Read Today's Stock Signals

The table above shows every stock with 22 or more active bullish signals as of the most recent market close. Here is how to interpret each row:

1. Check the Decision column. Every row shown is BUY. Stocks below the threshold (WATCH) are hidden.
2. Look at the Signals count. A stock showing 26/30 has broader technical agreement than one showing 22/30. Higher counts mean more of the 30 checks are simultaneously bullish — they do not imply a better outcome.
3. Read RSI(14) as context, not as the trigger. RSI is one of the 30 inputs. It is displayed because it is the most widely recognised of them, but it never decides BUY or WATCH on its own.
4. Treat Ref. Stop and Ref. Target as volatility bands, not orders. They are derived from the stock's own 14-day Average True Range (stop = close − 2.0 × ATR, target = close + 1.5 × ATR), so a volatile stock gets a wider band than a quiet one. They are not execution prices and carry no guarantee.
5. Read 20D Up-Rate as a base rate. It is the share of overlapping 20-session windows in the trailing year in which that stock finished higher. It describes the stock's own recent behaviour — it is not a win rate for these signals and not a backtest of this strategy.

What Is Quantum Signals?

Quantum Signals is a research-focused, post-close multi-factor technical signal engine for US equities. Every trading day after market close, the system scores 180 liquid US-listed equities against 30 technical signals per ticker using end-of-day open/high/low/close/volume data.

The decision rule is straightforward: if 22 or more signals are simultaneously bullish (at least 73% agreement of 30), the stock is flagged as BUY. Stocks below the threshold are classified as WATCH (no active setup) and are not shown in the dashboard.

The engine is fully rules-based with no discretionary override. It is designed for research and informational use.

Why 180 stocks and not the whole S&P 500?

Two separate reasons, and it is worth being precise about both because the distinction matters for interpreting the output.

The universe is a liquidity list, not an index. It is a fixed, hand-maintained set of 180 US-listed tickers chosen for continuous quotation and deep daily volume. It is not the S&P 500 and does not track index membership: it deliberately includes high-volume names that are not S&P 500 constituents — Coinbase, Robinhood, Nu Holdings, Agnico Eagle, Brookfield and similar — while omitting several hundred smaller index members whose thinner order books make end-of-day technical signals noisier and less reproducible. Screening a smaller, consistently liquid universe produces signals that behave more stably from one session to the next.

A daily eligibility gate can reduce that number further. Each ticker must return at least 60 completed daily sessions of clean OHLCV data within the trailing one-year download window. Any name that fails to download, is halted, has recently listed, or comes back with gaps is skipped for that day rather than being scored on incomplete history. The “Stocks Scored” figure at the top of this page is therefore the count that actually passed the gate on the most recent run, which is normally the full 180 and occasionally slightly fewer.

How BUY and WATCH Decisions Are Made

The core principle is multi-factor confluence. No single indicator is reliable on its own. The system counts how many signals are currently bullish for each stock. If 22 or more are active (out of 30), the stock is flagged BUY. Otherwise it is WATCH.

def generate_decision(signals_count, confluence_threshold=22):
    """
    signals_count: number of currently active bullish signals
    confluence_threshold: minimum required for BUY (currently 22 of 30)
    Returns: 'BUY' if threshold met, else 'WATCH'
    """
    if signals_count >= confluence_threshold:
        return "BUY"
    return "WATCH"

Why 22 of 30, and what the threshold does not do

The threshold is a deliberately blunt instrument: count the bullish checks, compare to 22, publish or don't. It is not optimised against past returns, which means it is not fitted to any particular market period — but it also means it carries no claim of being the “best” cut-off. A stock at 22/30 and a stock at 27/30 both appear as BUY; the Signals column is there so you can see the difference rather than having it hidden behind a single label.

Requiring roughly three-quarters agreement across trend, momentum, volume and volatility families means a stock generally has to be in a broad, confirmed uptrend to qualify. The direct consequence is that the engine produces few or no signals in choppy and falling markets. That is the intended behaviour, not a fault — but it also means the output is structurally biased toward trend continuation and will be least useful precisely at turning points.

What the Engine Evaluates

The engine evaluates 30 technical signals per stock. Each produces a binary output (1 = bullish, 0 = not active). The BUY/WATCH decision is based solely on the count of active bullish signals vs. the confluence threshold (currently 22 of 30). Categories include:

Momentum Oscillators

RSI (multiple periods), Stochastic RSI, Williams %R, CCI, MFI. These measure whether a stock is in an oversold, neutral, or overbought zone. RSI(14) is displayed in the dashboard for context but does not independently gate the BUY/WATCH decision — it is one of 30 signals.

Trend & Moving Averages

SMA/EMA crossovers (multiple pairs), ADX trend strength, price vs. 50-day and 200-day SMA. These identify whether a stock is in an uptrend, downtrend, or transition.

Volatility & Mean Reversion

Bollinger Bands (position, squeeze), ATR-based regime detection, Keltner Channel interactions. These identify whether current price is statistically extended relative to recent ranges.

Volume Analysis

Volume ratio vs. moving averages, OBV trend, accumulation/distribution. Volume confirmation helps distinguish genuine moves from low-participation noise.

Regime Filters

Two of the 30 checks act as a volatility sanity filter: they confirm that the stock's 14-day ATR sits inside a workable band relative to price — not so quiet that the reading is meaningless, not so violent that a technical setup is unlikely to hold. Important: these are counted like any other signal. There is no separate veto stage, no discretionary override, and no hidden filter layer that removes stocks after scoring. The confluence count is the entire decision.

Strategy Parameters

The following parameters define the current dashboard variant. These are fixed and transparent.

Signal Dashboard Column Definitions

Risks, Limitations, and How to Interpret Backtest Data

• BUY ≠ “Buy immediately”: A BUY flag means 22 or more of the 30 checks are currently bullish. It is not a trade recommendation, a call to action, or personalised advice.
• WATCH = Below threshold: Stocks with fewer than 22 active bullish signals are not shown. WATCH means “no active setup,” not “hold your existing position” and not “sell.”
• Purely technical, purely backward-looking: Every input is derived from past price and volume. The engine has no knowledge of earnings dates, guidance, litigation, index changes, or any fundamental data.
• Trend-following bias: Requiring broad agreement means signals cluster in rising markets and disappear in falling ones. The engine will be least informative at inflection points.
• Reference levels are volatility bands: Derived from ATR at the prior close. They are not live execution prices and do not account for overnight gaps, spreads, or liquidity.
• Signals are end-of-day: All data reflects the prior close. Intraday price movements may invalidate signals before the next update.
• Combine with your own research: Quantum Signals is purely technical. Earnings, regulatory events, macro shifts, and other catalysts can override any technical setup.
• No system is infallible: Even high-signal-count stocks can decline. Risk management and position sizing remain the investor's responsibility.

Data Sources & Refresh Cycle

• Price data: End-of-day OHLCV candles from Yahoo Finance via the yfinance library, split- and dividend-adjusted. Each ticker needs at least 60 completed sessions in the trailing 1-year window to be scored.
• Signals: 30 binary technical checks computed after each close by scripts/daily_update.py.
• Refresh schedule: Monday through Friday at 23:30 UTC, after the 16:00 ET close. Signals reflect the most recent completed trading session. There is no intraday update and no weekend run.
• Universe: 180 US-listed equities across all major sectors. Tickers that fail the data-completeness check are skipped for that day.
• If the scan does not run: the previous output is retained and the session date above continues to show the date it actually belongs to. The page will say the data is delayed rather than presenting an old scan as current.

Why Post-Close Instead of Intraday?

Quantum Signals operates on end-of-day data rather than intraday ticks:

• Data stability: Closing prices are the most widely referenced and least noisy data point of the trading day. Intraday signals are more prone to whipsaws and false triggers.
• Indicator reliability: Most classical technical indicators (RSI, MACD, Bollinger Bands, moving averages) were designed and backtested on daily timeframes. Their statistical properties are better established at daily resolution.
• Accessibility: Post-close signals give users time to review the dashboard, conduct additional research, and make informed decisions before the next trading session — rather than reacting to real-time pressure.
• Transparency: End-of-day data is publicly available and verifiable. There is no ambiguity about which price point was used for signal generation.

Frequently Asked Questions About Daily Stock Signals

What are daily stock signals?

Daily stock signals are systematic, rules-based alerts generated after the market close. They identify stocks where multiple bullish signals are active on the same day. Quantum Signals scores 180 liquid US-listed equities each evening and flags stocks with 22 or more active bullish signals (out of 30) as BUY.

How does a post-close stock signal dashboard work?

A post-close signal dashboard processes end-of-day price and volume data after the US market closes at 4:00 PM ET. It evaluates each stock's signals, counts how many are bullish, and flags stocks that meet a minimum confluence threshold (22 of 30 signals). Results are published as a daily signal table.

What does BUY mean in this stock signal dashboard?

BUY means 22 or more bullish signals (out of 30) are currently active for that stock. It is a research signal, not investment advice or a trade recommendation. Stocks below the threshold are marked WATCH and hidden from the dashboard.

Are these stock signals free?

Yes. The Quantum Signals dashboard is free and updated daily after market close. It is provided for research and informational purposes only and does not constitute financial advice.

What is the difference between BUY and WATCH?

BUY = 22 or more of the 30 signals are active (shown in the dashboard). WATCH = fewer than 22 active signals (hidden). WATCH means no active setup — it is not a recommendation to hold or to sell an existing position.

How often are daily stock signals updated?

Every trading day (Monday through Friday), after the US market closes at 4:00 PM ET. The dashboard reflects the most recent completed session. Signals are not updated intraday.

Can I use these signals for day trading?

No. Quantum Signals is a post-close, end-of-day system. All data reflects the prior day's close. It is not designed for intraday or real-time trading decisions. The hold period used in backtesting is 60 trading days.

What stocks are included in the daily signal scan?

The universe is a fixed list of 180 liquid US-listed equities spanning every major sector. It is a curated liquidity list rather than an index — it includes large-cap S&P 500 names alongside high-volume growth, fintech, semiconductor, mining and alternative-asset tickers that are not S&P 500 constituents. Each stock must return at least 60 completed daily sessions of clean OHLCV data in the trailing one-year window to be scored on any given day; names that fail that check are skipped rather than scored on partial history. See why 180 and not the whole S&P 500 for the reasoning.

Does this system use quantum computing or AI?

No. The name “Quantum” is metaphorical, referring to the layered, multi-factor signal stacking approach. The engine uses classical technical indicators and a simple confluence-counting rule. It does not use quantum computing, machine learning, or artificial intelligence.

Related Research & Tools

• QuantMedia Signal Breadth — How much of the universe qualifies today, and the historical series
• QuantMedia Sector Confluence — Where technical agreement is concentrated by sector
• What is signal confluence? — How the 30-signal score is built and why the threshold is 22
• Signal engine methodology — The same parameters documented alongside every other data source on the site
• US equities screener — Sector rotation and factor context for the names in the table above
• Sector rotation guide — Why several BUY signals clustering in one sector is worth more than any single name
• Market data dashboard — Index, forex and crypto snapshots for macro context
• VPIN & Order Flow Toxicity — Microstructure signals that complement technical analysis
• Probabilistic Sharpe Ratio — Statistical framework for evaluating signal engine performance
• Slippage & Latency Modeling — Understanding execution costs for signal-based strategies
• Genetic Algorithm Alpha — Evolutionary optimization in signal generation
• Bid-Ask Spread Dynamics — How spreads affect entry and exit quality
• All Research Papers — Full library of quantitative research