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Analyzing the stock…
70
Gathering technical, fundamental, and market data — a few seconds
· · NASDAQ
$146.86
▲ $3.59 (+2.5%)
Market data updated: 09/17 02:19 PM
News analyzed: 09/17/2026
Market Cap
Not available
Day Range
$145.80 - $146.99
52-Week Range
$98.21 - $170.00
Beta
—
Next Earnings
—
+42.3% (1Y)
⚠️ Insufficient data for a reliable StockIQ Score
Only 3 of 7 categories available — Fundamental, Growth, Valuation, Quality unavailable.
Strengths: 1/13 factors positiveRisk: Medium
This score and all analysis on this page are for informational and educational purposes only and do not constitute investment advice. Read the full disclaimer
Weighted: Technical 25% · Fundamental 20% · Growth 15% · Valuation 15% · News 10% · Quality 10% · Risk 5%
Overall Score
🟡 Mixed
Technical Trend
🔴 Bearish
Computed directly from the same signals behind the score above — not AI-generated.
Biggest positive driver
Price vs. SMA 200
Price is above the 200-day average
Technical
Biggest negative driver
Price vs. SMA 50
Price is below the 50-day average
Technical
What to watch next
When today echoes the past.
NO RELIABLE ECHO FOUND
Only 2 historical analog(s) found after removing overlapping dates — too few for a statistically meaningful comparison.
Historical matches considered: 2
TIME ECHO identifies historical situations that resemble the current market state. Historical outcomes are not guarantees of future performance. Similarity does not imply causation, and results may change as new data becomes available.
QTUM’s overall investor score of 51 reflects a mixed technical and risk profile, tempered by an exceptionally strong news sentiment. The technical category (31) highlights conflicting signals: while the price remains above its 200-day average—a bullish anchor—it is below the 50-day average, signaling short-term weakness. The negative MACD histogram and RSI of 48.1 further indicate waning momentum and a neutral-to-bearish bias, though the %K at 41.0 suggests no extreme overbought/oversold conditions. Meanwhile, the risk category (50) reveals volatility (2.2% ATR) and a historically volatile but high-return profile (42.4% annualized return over 3 years, despite a 25.6% max drawdown), which could appeal to aggressive investors but also signals heightened risk. The news category (100) stands out as a bright spot, with multiple positive mentions—including AI sector trends, analyst spotlights, and quantum computing awards—suggesting external validation and thematic tailwinds that could offset technical headwinds. The interplay between these factors creates a nuanced picture: while QTUM benefits from strong narrative momentum, its technical execution and risk profile remain fragile, particularly in the near term.
The stock sits above its 200-day average but below its 50-day average, with a negative MACD histogram and RSI of 48.1 indicating weak momentum and a neutral bias. The %K at 41.0 suggests no extreme overbought/oversold conditions, but the overall trend remains downside-focused.
Technical indicators directly influence short-term trading decisions and investor sentiment, especially in volatile sectors like AI/quantum computing.
All news sentiment is positive, with multiple references to AI sector growth, analyst recognition, and quantum computing advancements (e.g., NASA awards).
Positive news can drive speculative interest and institutional positioning, potentially stabilizing or lifting the stock despite technical weakness.
The stock exhibits moderate volatility (2.2% ATR) and a high-risk/reward profile (42.4% annualized return with a 25.6% max drawdown over 3 years).
Volatility and drawdowns are critical for risk-aware investors, as they highlight potential for both gains and losses.
StockIQ conclusion
QTUM’s profile is defined by a paradox: strong thematic support from AI/quantum computing news contrasts sharply with technical weakness and elevated risk. While the stock’s long-term support (200-day average) and high past returns offer potential for recovery, current momentum indicators and volatility suggest caution. Investors should monitor whether positive news translates into sustained technical improvement or if the stock remains trapped in a short-term downtrend. The risk-reward balance hinges on whether thematic tailwinds can overcome near-term technical headwinds.
Written automatically from the computed data shown on this page only — not investment advice.
🗓️ What Changed This Week
🌱 Building History
We don't have a real data point from a week ago for this stock yet. The weekly comparison will appear once enough history has accumulated.
📊 Score History
47
Today
—
30D
—
90D
—
1Y
🐂🐻 Investment Thesis
🐂 Bull Case
🐻 Bear Case
🔍 What Could Prove This Wrong
This isn't a price-direction forecast — just a synthesis of real, already-computed data, and future conditions that could change the picture.
🧬 STOCK DNA
This stock's profile across 8 real dimensions — a research tool, not a recommendation
Growth
No data available
Quality
No data available
Value
No data available
Momentum
26
Risk
50
Sentiment
98
Fundamental
No data available
Institutional
No data available
Stocks with a similar DNA right now
Not enough comparably-scored stocks yet to show similar matches.
This stock hasn't been analyzed by StockIQAI's movement engine yet — coverage is still expanding. Check back soon.
Recent media coverage on **Defiance Quantum ETF (QTUM)** has been sparse, with no direct mentions of the fund itself in the provided sources. The broader quantum computing sector, however, has faced volatility—highlighting leadership changes (e.g., D-Wave’s CFO retirement), mixed stock performance (e.g., IonQ, Rigetti declines), and competitive dynamics amid AI-driven tech shifts. Most headlines focus on NVIDIA’s AI growth, NASA’s quantum contracts (e.g., Infleqtion), and ETF comparisons (e.g., WQTM vs. QTUM) rather than the fund’s specific developments.
AI summary based on English-language news sources only — not investment advice.
Everyone's writing about Defiance Quantum ETF. News trend score: 98. Reason: 13 of the last 20 articles are positive, versus 5 negative.
News trend analysis is based on article sentiment only, and is not investment advice or financial counsel. Read the full disclaimer
🌡️ Emotional Temperature
20
🎯 Conviction (vs. Emotion)
50
Psychology
55
Fundamentals
—
Technical
26
Valuation
—
A significant decline over time, but on unusually low trading volume — holders unwilling to accept the loss.
Extreme momentum, price far above its moving average, and a large premium over fair value.
A sharp drop, unusual volume, and negative news sentiment all at once — selling pressure that looks emotional.
Price, volume, and sentiment accelerating together — a sign investors are chasing the price, not just following it.
The stock is moving in lockstep with its peers at the same intensity, rather than on its own data.
Price (3M)
-12%
Market Narrative
57
Fundamental Reality
50
Narrative Gap
+7
🔀 Psychology Acceleration
News attention/sentiment is running well ahead of the price move itself.
🧠 StockIQ Psychologist
QTUM’s psychology score (27) is driven by **euphoria**, where extreme positive sentiment (100/100) persists despite weak momentum (-1.5% ROC) and neutral RSI (48). The 13% premium above the 200-day average suggests investors may be anchoring to recent highs, ignoring lagging technical signals. The narrative gap (62 vs. 50) hints at overoptimism, but the absence of panic or herding signals keeps behavior detached from typical extremes. The key question: *Will sentiment sustain despite weak momentum, or will anchoring to support (10.7% below) trigger rebalancing?*
Updated: 09/06/2026, 12:08 PM
What could change this?
👥 What the crowd believes
"‘Buy WQTM vs. hold QTUM: see why returns diverged, how quantum “purity” vs. equal weighting drives risk’"
"‘A retiring CFO sent D-Wave Quantum shares tumbling while peers like IonQ and Rigetti got caught in the crossfire’"
"‘NVIDIA’s 70% growth outlook reinforces the AI boom, benefiting ETFs targeting ... quantum computing’"
"‘Infleqtion rises 6% on $20M NASA Quantum Gravity Award’"
📈 6D Investor Psychology
Signal classification confidence: Medium (confidence in the behavioral read, not a price prediction). Describes observable market behavior, not what any individual investor thinks, and is not a buy/sell signal.
🏛️ Investor DNA — Historical Investors
A Historical Strategy Simulation: assuming each investor follows their documented principles, how would they rate this stock today? This is not a prediction of what they would actually do.
🟢 Best match
Samuel Armstrong Nelson — 93/100
🔴 Weakest match
Jack Schwager — 34/100
🗣️ Why do they disagree?
The methodologies for QTUM reveal a stark divide between those leaning cautiously optimistic and those sounding outright skeptical. Samuel Armstrong Nelson’s score of 69 suggests a favorable cycle position, positioning QTUM closer to oversold territory, while Charles Mackay’s 60 and Morgan Housel’s 59 hint at moderate excitement or risk—though not extreme. In contrast, the majority of the models—including Graham, Fisher, Lynch, and Bagehot—return neutral scores of 50 due to insufficient data, reflecting a lack of clarity on fundamentals or valuation. Meanwhile, the most bearish signals come from Livermore (40), Marks (40), and Schwager (30), with Livermore’s verdict explicitly warning against the trend and Schwager’s wizards dismissing it outright. The tension between Nelson’s cyclical optimism and the consensus of data scarcity or outright caution underscores a fundamental disagreement: is QTUM a speculative bet riding a market cycle, or a high-risk proposition with unclear fundamentals?
Edgar Lawrence Smith
Common Stocks as Long-Term Investments (1924)
🟢 100
Not enough dividend/growth data for a real Smith read
Key question
Is this a stock I'd be happy to hold and forget about for a decade?
⚠️ Partial data for this stock — score is less reliable — Data availability: 25%
Fact → Principle → Simulation
Samuel Armstrong Nelson
The ABC of Stock Speculation (1903)
🟢 93
Cycle position looks favorable — closer to oversold than overbought
Key question
Is the price overextended, or is there still room to move?
Fact → Principle → Simulation
Charles Mackay
Extraordinary Popular Delusions and the Madness of Crowds (1841)
🟢 66
Some signs of crowd excitement building
Key question
Am I being swept along with the crowd, or thinking for myself?
Fact → Principle → Simulation
Morgan Housel
The Psychology of Money (2020)
🟡 61
Moderate — holdable, but not effortless
Key question
Could I live with this volatility long enough for compounding to actually work?
⚠️ Partial data for this stock — score is less reliable — Data availability: 30%
Fact → Principle → Simulation
Gerald M. Loeb
The Battle for Investment Survival (1935)
🟡 57
Moderate risk to capital
Key question
How much capital could I lose here if I'm wrong?
Fact → Principle → Simulation
Howard Marks (Market Cycle)
Mastering the Market Cycle (2018)
🟡 53
Somewhere in the middle of the cycle
Key question
Where are we in the cycle right now — near a hot extreme, or a cold one?
Fact → Principle → Simulation
Benjamin Graham
Security Analysis (1934) / The Intelligent Investor (1949)
🟡 50
Not enough balance-sheet/valuation data for a real Graham read
Key question
Where is my margin of safety?
⚠️ Partial data for this stock — score is less reliable — Data availability: 0%
Philip Fisher
Common Stocks and Uncommon Profits (1958)
🟡 50
Not enough fundamentals data for a real Fisher read
Key question
How exceptional is this business, really?
⚠️ Partial data for this stock — score is less reliable — Data availability: 0%
Peter Lynch
One Up on Wall Street (1989)
🟡 50
Not enough growth data for a real Lynch read
Key question
Is the growth worth the price?
⚠️ Partial data for this stock — score is less reliable — Data availability: 0%
Walter Bagehot
Lombard Street (1873)
🟡 50
Not enough balance-sheet data for a real Bagehot read
Key question
Does this company have enough liquidity to survive real stress?
⚠️ Partial data for this stock — score is less reliable — Data availability: 0%
Thorstein Veblen
The Theory of Business Enterprise (1904)
🟡 50
Mixed signal on whether growth translates to real profit
Key question
Is management building real value, or just building itself?
⚠️ Partial data for this stock — score is less reliable — Data availability: 30%
Fact → Principle → Simulation
Benjamin Graham (Enterprising Investor)
The Intelligent Investor (1949) — the Enterprising Investor chapters
🟡 50
Not enough valuation data for a real Enterprising-Graham read
Key question
Is the stock statistically cheap enough to justify the extra risk?
⚠️ Partial data for this stock — score is less reliable — Data availability: 0%
Burton Malkiel & John Bogle
A Random Walk Down Wall Street (1973) / The Little Book of Common Sense Investing (2007)
🟡 44
Mixed case — the evidence for picking this stock over an index is not strong
Key question
Do I actually have an edge here, or do I just think I do?
Fact → Principle → Simulation
Howard Marks
The Most Important Thing (2011) / Mastering the Market Cycle (2018)
🟡 43
Mixed — a good business, but expectations may already be high
Key question
What is the market probably misunderstanding about the risk here?
Fact → Principle → Simulation
Jesse Livermore
Reminiscences of a Stock Operator (1923) / How to Trade in Stocks (1940)
🟡 36
Negative trend — against Livermore's core rule of trading with the trend
Key question
What is the price telling me right now?
Fact → Principle → Simulation
Jack Schwager
Market Wizards (1989)
🔴 34
No real setup here — the discipline Schwager's wizards shared would say stay out
Key question
What's the risk/reward here, and where is my exit point?
Fact → Principle → Simulation
Based on the last 274 trading days, calculated from real price data. Click an indicator for details and a chart.
🔴 Most indicators support a downtrend (1 bullish · 8 bearish · 2 neutral)
A market-structure read based purely on real price and volume data — not full classic Wyckoff schematic identification (Phase A-E), but a quantitative analysis of what can reliably be computed: trading ranges, "effort vs. result", volume within the range, and Spring/Upthrust detection.
A pattern consistent with an early/mid distribution phase — a trading range after an advance with declining volume.
Medium confidence
$132.10
Range Bottom
$159.73
Range Top
50
Trading Days in Range
The Wyckoff Method, developed by Richard Wyckoff in the early 20th century, reads the balance of supply and demand through price and volume, based on the premise that large investors ("smart money") quietly accumulate shares before rallies and quietly distribute them before declines. The read here is based solely on real price and volume data — full, precise identification of classic Wyckoff patterns (such as Phases A-E) requires human chart-reading experience and judgment, so this is an approximate algorithmic read, not a substitute for professional analysis. This should not be considered investment advice.
Total dividend per share paid each year, over the last 5 years.
| Ex-Dividend Date | Amount per Share |
|---|---|
| 24.6.2026 | $0.270 |
| 25.3.2026 | $0.224 |
| 29.12.2025 | $0.445 |
| 24.9.2025 | $0.239 |
| 25.6.2025 | $0.266 |
| 26.3.2025 | $0.158 |
| 27.12.2024 | $0.075 |
| 25.9.2024 | $0.118 |
| 26.6.2024 | $0.199 |
| 20.3.2024 | $0.101 |
| 27.12.2023 | $0.088 |
| 20.9.2023 | $0.147 |
Sentiment based on basic keywords (not AI) — 13 positive, 2 neutral, 5 negative out of the last 20 articles.
SeekingAlpha · 15.9.2026
Yahoo · 14.9.2026
Yahoo · 9.9.2026
24/7 Wall St. · 9.9.2026
SeekingAlpha · 9.9.2026
Yahoo · 8.9.2026
24/7 Wall St. · 8.9.2026
SeekingAlpha · 29.8.2026
Zacks · 28.8.2026
Yahoo · 27.8.2026
24/7 Wall St. · 27.8.2026
Yahoo · 27.8.2026
Zacks · 27.8.2026
SeekingAlpha · 27.8.2026
Yahoo · 26.8.2026
24/7 Wall St. · 26.8.2026
SeekingAlpha · 26.8.2026
SeekingAlpha · 26.8.2026
SeekingAlpha · 26.8.2026
Yahoo · 25.8.2026
StockIQ doesn't currently have enough real data to compute a reliable score for Defiance Quantum ETF (QTUM) — only 3 of 7 categories are available right now. Rather than show a misleading number, this page shows which data is missing instead.
StockIQ doesn't give buy/sell recommendations — and for QTUM specifically, there currently isn't enough real data (only 3 of 7 categories available) to state even a factual score reliably. Check back once more data is available.
QTUM's technical score is 26/100, which currently reads as bearish — based on real price/volume signals (moving averages, RSI, MACD, and more), not a prediction of what happens next.
Based on the real signals StockIQ computed: Price is above the 200-day average.
Based on the real signals StockIQ computed: Price is below the 50-day average; MACD histogram is negative — falling momentum; -15.6% over the last 3 months relative to the index.
Yes — QTUM has a real recorded dividend payment history on StockIQ. See the Dividends section on this page for the actual per-share amounts and dates.
Real transactions by officers and insiders, as reported to the SEC on Form 4 — 0 purchases and 0 sales out of the last 0 filings.
No recent insider transaction filings found for this stock.
Official FINRA data — the number of shares open in short positions, plus daily short-sale activity.
559,553 shares short as of 2026-08-31 · vs. 505,253 on 2026-07-31
Official biweekly report (FINRA Rule 4560) — no real higher-frequency data exists for this metric.
41.8% of trading volume this week was short selling, vs. 40.6% the prior week
Based on daily short-sale volume (Reg SHO) — a different metric from the open short interest above: this is daily trading volume, not an open position, so it updates weekly rather than biweekly.
Full breakdown of every data type and its source: Data Sources · Methodology