Archived snapshot from 05 Sep 2026, 06:00 UTCclick here for the latest live data →

SentimentFeed

real time stock market sentiment dashboard

Generated 05 Sep 2026, 06:00 UTC
next refresh 07:00 UTC

A real time sentiment feed for equities. Every hour this stock market sentiment dashboard re-reads the entire market feed, scores it, and republishes the result as a plain ticker feed — a stock sentiment tracker covering momentum, sector and theme rotation, market regime and tail risk in one page. No login, no sign-up.

Fear & Greed53NeutralFearGreed
Systemic risk52NeutralCalmStressed
Market regimeBullBull 79% · Side 21% · Bear 0%
Volatility (VIX)14.5Forecast 11.1% ann.
Dollar regimeMIXED10Y 4.78% · DXY 99.2

Regime read: LONG · expected +2.84% ± 5.26% over an optimal 30-day hold · signal/noise 0.54 — inside one standard deviation of noise.

Modal state is Bull (78.7% posterior, +40.6%/yr drift), but the direction is the sign of the probability-weighted drift across all states. Bull contributes +0.1211%/day and dominates. Net +0.1229%/day.

Same hours, earlier readings — the fastest way to see whether today is unusual.

Stock sentiment tracker — strongest tickers

TickerScoreSectorFwd P/EPEGY52w posWhat is driving it
HOOD+19.3Financials37.02.1865%RIA referrals, tech and service: How TradePMRprofitableExtended FWD P/EExpensive PEGY (>2)
SNOW+13.2Information Technology113.882%Broadcom and Snowflake Perfectly Sum Up the AI TradeEV/EBITDA < 10Extended FWD P/EMean Reversion: Euphoria (Short)
UBER+12.3Information Technology17.36.4428%Uber to slash 10% of workforce in push to streamlineprofitableExpensive PEGY (>2)Mean Reversion: Euphoria (Short)
PLTR+9.8Information Technology75.31.7667%Palantir Stock Defies Red Flag and Skyrockets 8%profitableExtended FWD P/EMean Reversion: Euphoria (Short)
COIN+6.6Financials67.417%Coinbase files for SEC approval to offer equity perpetualsExtended FWD P/EMean Reversion: Euphoria (Short)

Score is a decayed sum of scored coverage over the last 24 hours (18-hour half-life). Valuation metrics are point-in-time.

Ranked watchlist

NO TRADE: every ranked play has a negative expected net gain after costs in the current regime. The table is a relative ordering, not a buy list.

#TickerSideP(win)EV 48hEV 1wEV 1mWhy
1METALONG46.0%-0.23-0.50-0.48Accelerating velocity +3.2 (2 mentions/12h)
2AILONG42.7%-0.32-0.50-0.14Accelerating velocity +2.2 (2 mentions/12h); ⚠ Weak fundamentals: F-score 1/9
3BELONG17.0%CIO meta-model current selection
4PLTRLONG22.5%-0.21-0.54-0.83Hot sentiment (decayed score 9.8); Accelerating velocity +3.3 (2 mentions/12h); ⚠ Extended FWD P/E; Mean Reversion: Euphoria (Short); Quality: F-score 8/9
5UBERLONG25.2%-0.21-0.54-0.83Hot sentiment (decayed score 12.4); Accelerating velocity +1.4 (3 mentions/12h); ⚠ Expensive PEGY (>2); Mean Reversion: Euphoria (Short)
6HOODLONG24.0%-0.21-0.54-0.83Hot sentiment (decayed score 19.4); Accelerating velocity +0.6 (6 mentions/12h); ⚠ Extended FWD P/E; Expensive PEGY (>2)
7COINLONG28.5%-0.18-0.58-1.21Hot sentiment (decayed score 6.7); ⚠ Extended FWD P/E; Mean Reversion: Euphoria (Short)
8SNOWLONG25.7%-0.18-0.58-1.21Hot sentiment (decayed score 13.3); ⚠ Extended FWD P/E; Mean Reversion: Euphoria (Short)

Engine hit rate 43.8% over 377 scored calls (lower bound 38.8%), average net alpha -0.190%. Serving: incumbent.

A relative ordering produced by the model, not a recommendation. Expected values are net of a 0.15% round-trip cost.

Catalyst watch

  • RAREBearishRegulation85

    A 44% drop following a failed drug trial is a fundamental re-rating of the company's valuation based on lost projected cash flows, not a temporary dip.

    2026-09-04 23:49
  • PATHBearishEarnings82

    A revenue beat is a backward-looking metric; the market is pricing in a structural growth slowdown and the potential obsolescence of traditional RPA in the face of Generative AI.

    2026-09-04 15:03
  • SNOWBullishEarnings82

    Snowflake's 23% surge on AI-fueled guidance raise is a powerful catalyst, but conviction is capped to avoid the 'strategic narrative trap' by accounting for the gap between projected guidance and realized execution.

    2026-09-03 14:41
  • PYPLBearishRegulation82

    The loss of a $53 billion safety net represents a significant removal of liquidity and financial cushioning, exposing the company to competitive pressures and lack of innovation, which the market typically views as a a catastrophic removal of life support rather than a strategic pivot.

    2026-08-30 20:02
  • WENBearishBuyout85

    The removal of a speculative buyout premium creates a vacuum in the valuation, as the stock was trading on a rumor-driven floor rather than organic fundamentals.

    2026-08-29 01:21
  • VREXBullishBuyout82

    VREX is a bullish catalyst due to the acquisition by Teledyne, but the majority of the premium is likely already priced in, limiting further upside potential and now shifting the risk-reward profile to an arbitrage play rather than a a growth story.

    2026-08-28 06:20
  • SNAPBearishRegulation82

    While Meta's settlement caps the legal risk for the sector, the asymmetry of the balance sheet risk creates an existential threat for Snap, as any similar liability would be liquidated by a fraction of the cost Meta can absorb.

    2026-08-28 04:16
  • ROKUBullishBuyout82

    None

    2026-08-25 18:03
  • BABABearishEquity_Dilution82

    A $10.2B share placement for AI funding is a significant equity dilution event that the market is currently pricing as a high-risk capital expenditure rather than a strategic growth catalyst.

    2026-08-25 05:23
  • AAOIBearishEquity Offering85

    A $600M equity offering represents massive dilution and a signal of liquidity stress, which the market is already pricing in via a 12% drop and sympathetic sector-wide declines.

    2026-08-24 13:52

Discrete events extracted from the last 14 days of coverage, with a model conviction score out of 100.

Ticker feed — accelerating now

TickerVelocityVolStory
PLTR+3.32Palantir Stock Defies Red Flag and Skyrockets 8%
META+3.22Meta Rises 4% as Muse Spark 1.3 Claims Parity With Anthropic and OpenAI
AI+2.22C3.ai Bookings Jumped 73% and Free Cash Flow Turned Positive. Is the $7 Bear Case Breaking?
UBER+1.43Uber to slash 10% of workforce in push to streamline
HOOD+0.66RIA referrals, tech and service: How TradePMR

Change in scored coverage over the last 12 hours versus the prior 12.

Under pressure

RARE-9.6Ultragenyx Drug Fails Trial. 2 Reasons the Stock Could Bounce Back From 44% Drop.
CRDO-8.6Why Credo Technology Sank This Week
BX-5.1Cliffwater, Blackstone Private Credit Funds Cap Redemptions
PATH-3.7BMO Capital Markets Forecasts Strong Price Appreciation for UiPath (NYSE:PATH) Stock
SNAP-2.7Meta Platforms May Have Escaped the Worst of a Landmark Teen-Safety Lawsuit. But the Ramifications Could Be Much Worse for Snap.

Most negatively scored names in the same window.

Sector heat

Sector1W trend1D1W1M
Energy+87+1,456+2,158
Financials+187+586+2,253
Information Technology+150+523+2,218
Communication Servicesbullish reversal+42+144-31
Materials+28+138+439
Health Carebearish reversal-20+109+53
Consumer Staples-53-75-612
Industrials-48-127-466
Consumer Discretionary-89-616-1,473
Utilities-107-755-1,493
Real Estate-179-1,380-3,048

Industry cuts (1W)

  • Artificial Intelligence+1,384
  • Electric Vehicles-382
  • Crypto & Digital Assets+331
  • Gold & Commodities-313
  • Cybersecurity-310
  • Biotechnology-305
  • Aerospace & Defense-277
  • Oil & Gas+276

Net sentiment balance per sector across each lookback window.

Theme momentum

ThemeVelocityLevel
Interest Rates+116.3-168
Artificial Intelligence+114.2+333
Employment+88.7+86
Monetary Policy+86.0+53
Geopolitical Risk-14.5-31
Mortgage Rates-14.8-21
Tokenization-14.8+6
Oil Prices-70.2+31

Velocity is the rate of change in theme coverage; level is its net sentiment balance.

Structural themes

ThemeSourcesConviction
defense security19973
healthcare policy18365
transport mobility15271
geopolitics14482
financial regulation13976
monetary policy12779
agriculture food12167
education skills10465
banking9479
infrastructure7165

A slower reading than the panels above. Sources counts the documents behind a theme; conviction weighs how many independent sources agree, how recent they are and how strong the signal is. Moves over weeks, not hours.

Companies in the structural record

TickerCompanyWeightShort-termRead
BLKBlackRock1,019
Its Aladdin platform is a primary tool for institutional risk management amid monetary policy shifts.
banking, capital markets, financial regulation, monetary policy
LMTLockheed Martin997
Development of AI-driven military weapons subject to binding controls
defense security, financial regulation, geopolitics, trade policy
NEENextEra Energy693
Major utility with renewable infrastructure projects reliant on stable long-term financing.
climate policy, energy policy, financial regulation, geopolitics
PLTRPalantir Technologies580+9.8aligned
AI-driven data analytics for conflict monitoring and early warning systems
defense security, financial regulation, geopolitics, industrial policy
MUFGMitsubishi UFJ Financial Group562
Large Japanese bank exposed to Bank of Japan monetary base and liquidity operations.
banking, capital markets, financial regulation, monetary policy
HDBHDFC Bank559
Strong deposit base reduces reliance on volatile wholesale funding during liquidity tightening.
banking, financial regulation, monetary policy
DEDeere & Company546
Agricultural equipment demand grows domestically as US farm subsidies expand under protectionist policies.
agriculture food, financial regulation, geopolitics, trade policy
JPMJPMorgan Chase & Co511
Major bank with compressed net interest margins due to extended low-rate environment from stable core inflation policy.
banking, financial regulation, monetary policy
MSCIMSCI Inc470
Provides risk management and governance indices used by institutional investors to monitor regulatory compliance.
banking, financial regulation
ICEIntercontinental Exchange443
Operates global exchanges and clearing houses benefiting from modernized market plumbing.
capital markets, financial regulation, monetary policy

Weight is how prominently a company features across the document corpus, with the reason for its exposure underneath. These are the names that recur in policy and regulatory material, which is a different population from the tickers moving on today's news. Where a name also has a current sentiment score, both are shown: aligned means they point the same way, diverging means one horizon has not caught up with the other.

Forward view

RBI liquidity absorption likely to increase short-term borrowing costs and bond yields

Confidence 85/100

The RBI's use of VRRR auctions removes excess cash from the commercial banking system. This reduction in available liquidity typically puts upward pressure on overnight interbank call rates. As banks have less surplus capital to deploy, demand for government securities (G-Secs) may soften, leading to higher yields and lower bond prices. Consequently, entities relying on short-term wholesale funding or bank credit fac

Better placed: short-term money market funds, banks with high CASA ratios, floating rate debt instruments

More exposed: non-banking financial companies (NBFCs), highly leveraged corporate borrowers, long-duration government bond holders

Named: HDB, BAJAJFIN, LICI, SBIN

What would break this: A sudden surge in government spending or a massive influx of foreign portfolio investment (FPI) could offset the VRRR absorption, maintaining liquidity levels.

RBI liquidity absorption likely to elevate short-term borrowing costs and pressure NBFCs

Confidence 85/100

The RBI's use of VRRR auctions removes excess cash from the banking system, reducing the supply of loanable funds. This typically leads to an increase in interbank call money rates. As funding becomes tighter, banks may raise lending rates to maintain net interest margins (NIMs), which increases the cost of capital for corporate borrowers and Non-Banking Financial Companies (NBFCs) that rely on bank credit rather tha

Better placed: short-duration fixed income, high-quality banks with strong deposit franchises, cash-rich corporations

More exposed: non-banking financial companies (NBFCs), highly leveraged corporate borrowers, banks with high reliance on wholesale funding

Named: HDB, SBIN, BAJAJFIN, RELIANCE

What would break this: A sudden shift toward monetary easing or an unexpected surge in foreign portfolio investment (FPI) inflows could offset the RBI's absorption efforts.

RBI liquidity absorption via VRRRs likely to tighten short-term credit conditions

Confidence 85/100

1. RBI uses VRRR auctions to remove excess cash from the banking system. 2. Reduced systemic liquidity typically puts upward pressure on interbank call money rates and short-term yields. 3. As banks face tighter liquidity, they may increase lending rates to maintain net interest margins (NIMs). 4. This increases the cost of capital for corporate borrowers and reduces available credit for highly leveraged sectors.

Better placed: short-term debt instruments, banks with high CASA ratios, liquid fund managers

More exposed: highly leveraged corporates, non-banking financial companies (NBFCs), real estate development, wholesale funding dependent sectors

Named: HDB, SBIN, BAJFINANCE, DLF

What would break this: A sudden shift in RBI policy toward accommodation or a massive influx of foreign portfolio investment (FPI) could offset the liquidity absorption.

RBI liquidity absorption tightens monetary conditions and pressures banking net interest margins

Confidence 85/100

1. The RBI uses Variable Rate Reverse Repo (VRRR) auctions to remove excess cash from the commercial banking system. 2. This reduction in systemic liquidity typically leads to an increase in short-term interbank lending rates. 3. As banks face higher costs for funding and liquidity management, their cost of funds increases. 4. If these increased costs cannot be immediately passed on to borrowers via higher loan rates

Better placed: short-duration debt funds, money market instruments, liquid fund managers

More exposed: commercial banking sector, highly leveraged corporate borrowers, credit-sensitive sectors like real estate

Named: HDB, IBN, SBIN, RELIANCE

What would break this: A sudden influx of government spending or foreign portfolio investment (FPI) inflows could offset the RBI's absorption efforts, maintaining liquidity levels.

Regulatory clarity boosts digital payment innovation and crypto compliance

Confidence 85/100

Regulators are developing frameworks to foster payment innovation while extending oversight to AI-driven tools and crypto services. Australia's A2A Payments Roadmap enables real-time interoperability, UK mandates drive bank-led innovation, and HMRC reporting rules create structured crypto compliance requirements. This reduces uncertainty for compliant digital payment providers and crypto platforms that integrate regu

Better placed: real-time payment infrastructure, crypto compliance solutions, digital wallet platforms

More exposed: legacy bank payment systems, non-compliant crypto service providers

Named: PYPL, COIN, FIT, MA

What would break this: Overly restrictive regulations stifling innovation (e.g., excessive transaction fees), or global regulatory fragmentation causing compliance costs to exceed market growth potential.

Humanitarian access pressures boost security and monitoring sectors

Confidence 85/100

The trend highlights weaponized maritime chokepoints, drone attacks on civilians, and AI-driven weapons as threats to humanitarian access. This increases demand for secure aid delivery systems (e.g., protected logistics routes) and real-time conflict monitoring tools to avoid danger zones. Consequently, security services for humanitarian actors and AI-based monitoring platforms gain traction. Conversely, maritime shi

Better placed: Humanitarian logistics & security, Conflict monitoring technology

More exposed: Maritime shipping (chokepoint routes), Defense contractors (AI weapons)

Named: ACM, PLTR, LMT, AI

What would break this: Rapid diplomatic resolution of conflicts or failure to implement binding controls on AI weapons would reduce demand for security services and monitoring tools while alleviating pressure on defense contractors.

Regional supply chain hubs boost manufacturing and energy infrastructure

Confidence 85/100

Nations are reducing reliance on single sources like China through trade policy shifts and new production capacity. Nigeria's seven-fold petroleum export surge after Dangote refinery demonstrates regional self-sufficiency in energy, indicating that regions building local capabilities (e.g., manufacturing/energy) will gain. Consequently, sectors enabling regional infrastructure development benefit, while centralized s

Better placed: Regional manufacturing infrastructure, Emerging energy infrastructure, Regional logistics networks

More exposed: China-centric export manufacturing

Named: CAT, TTE, UNP, FOXF

What would break this: Trade policy reversals or failure of new regional capacity (e.g., Nigeria's refinery) to meet export demands would undermine the trend.

Bilateral currency swaps support cross-border trade finance

Confidence 85/100

RBI maintaining unchanged rates prevents increased borrowing costs for businesses, supporting stable credit conditions. Australia-China bilateral currency swap reduces FX volatility and transaction costs for direct trade between the two nations, directly benefiting financial institutions facilitating these transactions and export-oriented sectors reliant on China trade.

Better placed: cross-border trade finance, international banking services

Named: CBA.AX, WBC.AX, BHP.AX

What would break this: Global economic shock forcing rate hikes or termination of Australia-China currency swap agreement

Readings drawn from the document corpus, not from price action. Each carries the case against it, because a view without a stated way to be wrong is not worth much. Nothing here is investment advice or a recommendation to buy or sell anything.

Model consensus

ModelVoteTrust
Markov Regime EngineUP83%
Macro Factor GateUP55%

Consensus: BULLISH

Benched

  • SPY Neural Net (1w) — failing validation (OOS error 0.8905% vs 0.4987% zero-baseline) — vote suspended

Model failed validation: out-of-sample error 0.8905% is worse than the 0.4987% predict-zero baseline. Projection withheld until a weekly retrain produces a model that beats the baseline.

Votes are weighted by each model's realised hit rate and suspended when it falls below its baseline.

Volatility & tail risk

Forecast volatility11.1% ann.
Percentile vs 6 months53%
Variance risk premium+3.0
Daily VaR (5%)-1.52%
Weekly VaR (5%)-3.41%
Weekly expected shortfall-5.51%

Premium in normal range — ⚠ LOW CONFIDENCE: the HAR fit (R²=0.07 in-sample / 0.18 OOS, worst 0.07) explains almost none of realized vol, so the forecast leg of this premium is weak

HAR realised-volatility forecast with a generalised Pareto tail fit.

Story cascades

ThemeBranchingHalf-lifeState
Oil & Gas0.931.1hCRITICAL
Geopolitical Tension0.922.1hCRITICAL
Bond Yields0.800.9hELEVATED
Interest Rates0.770.8hELEVATED
Artificial Intelligence0.700.6hELEVATED
Monetary Policy0.571.4hSUBCRITICAL
Cloud & Data Centers0.561.1hSUBCRITICAL
Crypto & Digital Assets0.481.0hSUBCRITICAL

Self-excitation of coverage per theme. A branching ratio near 1 means each story is spawning roughly one more.

Market feed volume

Scored today293
Yesterday, same hour1,425
Projected close of day882
Daily average1,338
Flow ratio vs normal1.11×
Total in corpus183,352

Volume of scored market coverage. Ratios below 1 mean a quiet tape.