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e.l.f. Beauty
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e.l.f. Beauty, Inc., a beauty company, provides cosmetics and skin care products worldwide. The company offers eye, lip, face, paw, and skin care products. It offers products under the e.l.f. Cosmetics, e.l.f.MoreShow less
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e.l.f. Beauty (ELF) Stock Analysis: Compare AI Forecasts & Scenarios

e.l.f. Beauty has 14 published AI advisor reports. Compare stock forecasts, individual ratings, price targets and bull/bear scenarios, separately from the consensus AI rating.

Updated on 26 October 2026Deep analysis 21 September 2026

Approved byRusslan Ramdowar, Editor-in-Chief
25 min readAudit All Past Forecasts

e.l.f. Beauty AI Forecast Summary

14 advisor opinions · Base subscription

Unlock the rating distributions, return ranges and advisor comparison with a Base subscription.

1 Year Ratings & Returns

Ratings: 5 Sell All · 3 Partial Sell · 6 Neutral

Return range: -47.1% to +10.8%

7 downside · 1 lateral · 6 upside

14 comparable price-return forecasts · Target

5 Year Ratings & Returns

Ratings: 2 Partial Sell · 10 Neutral · 2 Buy

Return range: -43.7% to +103.4%

2 downside · 0 lateral · 12 upside

14 comparable price-return forecasts · Target

From $112.95 · End Of Date

What do advisors disagree on

The sharpest analytical debate concerns whether fiscal 2026 margin compression was a temporary accounting distortion or structural margin degradation. Bullish perspectives emphasize that trailing twelve-month free cash flow reached $280 million, treating GAAP net margin contraction as transient earnout noise. Conversely, skeptical views argue that underlying operating margins contracted while Q1 FY2027 gross profitability was artificially flattered by roughly $50 million of non-recurring tariff refunds. Tracking underlying gross margins excluding tariff refunds over the next two quarters alongside retail scanner unit volumes will definitively resolve whether pricing power remains intact.

Compare all 14 opinions

1 Year & 5 Year ratings, targets & returns · Swipe table to compare

AdvisorModelResearch1 Year5 YearFull Report
Target dateRatingPrice targetPrice returnTarget dateRatingPrice targetPrice return
Universal Investor AI The Polymath FrameworkGemini 3.8 FlashResearcher Mode with Web Search UsedNeutral$117.15+3.7%Neutral$185.24+64.0%Full report
Universal Investor AI The Polymath FrameworkGPT-6 AstraResearcher Mode with Web Search UsedSell All$97.97-13.3%Neutral$143.63+27.2%Full report
Universal Investor AI The Polymath FrameworkClaude Opus 5Researcher Mode with Web Search UsedSell All$100.57-11.0%Neutral$135.61+20.1%Full report
J.P. Morgan AI The Titan FrameworkGemini 3.8 FlashResearcher Mode with Web Search UsedNeutral$124.04+9.8%Buy$229.69+103.4%Full report
Warren Buffett AI The Value Seeker FrameworkGemini 3.8 FlashThinker Mode with Web Search DisabledNeutral$114.98+1.8%Buy$227.87+101.7%Full report
Niccolo Machiavelli AI The Insider FrameworkGemini 3.8 FlashResearcher Mode but Web Search Wasn't UsedPartial Sell$113.86+0.8%Neutral$204.59+81.1%Full report
Universal Investor AI The Polymath FrameworkGemini 3.8 FlashThinker Mode with Web Search DisabledNeutral$125.15+10.8%Neutral$182.37+61.5%Full report
Superintelligence AI The Anthropologist FrameworkGemini 3.8 FlashResearcher Mode but Web Search Wasn't UsedNeutral$114.98+1.8%Neutral$177.21+56.9%Full report
Sherlock Holmes AI The Whistleblower FrameworkGemini 3.8 FlashResearcher Mode with Web Search UsedNeutral$114.92+1.7%Neutral$177.20+56.9%Full report
Ray Dalio AI The Strategist FrameworkGemini 3.8 FlashResearcher Mode but Web Search Wasn't UsedPartial Sell$108.28-4.1%Neutral$160.20+41.8%Full report
Warren Buffett AI The Value Seeker FrameworkGemini 3.8 FlashResearcher Mode but Web Search Wasn't UsedPartial Sell$106.43-5.8%Neutral$150.37+33.1%Full report
Superintelligence AI The Anthropologist FrameworkGemini 3.8 FlashThinker Mode with Web Search DisabledSell All$88.64-21.5%Neutral$124.78+10.5%Full report
Elon Musk AI The Visionary FrameworkGemini 3.8 FlashResearcher Mode with Web Search UsedSell All$94.02-16.8%Partial Sell$111.57-1.2%Full report
Michael Burry AI The Vulture FrameworkGemini 3.8 FlashResearcher Mode but Web Search Wasn't UsedSell All$59.73-47.1%Partial Sell$63.59-43.7%Full report
View all 14 opinions

All 14 opinions are displayed in the table above.

Prices, dates & return assumptions

1 Year and 5 Year identify the original published checkpoints. Current returns compare the dated close with each fixed target over its remaining horizon. Original quarterly tables use the publication-time anchor. Targets and observed prices share a split-adjusted basis.

Lateral means a price return from -1% to +1%, inclusive. Downside is below -1%; upside is above +1%. Ratings use the shared volatility-adjusted calculation and can differ from these price-direction categories.

Ranges and rating distributions use matching currencies, price bases and target dates. Missing or expired checkpoints are excluded; targets are never extrapolated. Shared frameworks and models can produce correlated opinions.

How this research is produced

iPulse AI analyzes each asset through structured investment frameworks using curated data and frontier models. Individual reports feed consensus, rankings, and reviewed selections. Past forecasts are preserved for evaluation as outcomes emerge.

e.l.f. Beauty Stock Analysis & Forecast — Universal Investor The Polymath Framework on Gemini 3.8 Flash Model

Universal Investor AI advisor icon

Universal Investor AI · The Polymath Framework

Gemini 3.8 Flash AI Researcher Web Search Used

5 Year Rating

Neutral

5 Year Price Return

+64.0%

Framework Description & Key Record Dates

Investment Framework

The Polymath Framework: Eight-Lens Investment Analysis Framework

Analysis Framework Description: Select the lenses with the greatest explanatory power, resolve their disagreements across horizons, and connect the evidence to a consistent thesis, scenario path, and verdict.

  • Ownership and value: examine economic rights, competitive advantage, capital allocation, and the price paid.
  • Regimes and constraints: connect credit, liquidity, policy, demand, and physical bottlenecks to the asset.
  • Innovation and adaptation: test adoption economics, AI and robotics exposure, substitution, and value capture.
  • Forensics and incentives: reconcile accounting, cash conversion, dilution, governance, and missing evidence.
  • Expectations and reflexivity: distinguish changes in fundamentals from changes in narratives and valuation.
  • Probabilities and resilience: use base rates, competing scenarios, catalysts, and the capacity to survive the wait.
  • Power and the rules of the game: assess political interests, regulatory influence, protection, and dependency.
  • Industry structure and consolidation: identify pricing power, chokepoints, alliances, and the economics of integration.
Full framework methodology
Model Producer:
Google
Model Version:
Gemini 3.8 Flash
Mode Used:
Researcher
Web Search Used
Forecast Target Date:
Latest Known Price Date for Return Estimate Refresh:
Forecast Published On:
Forecast Generated On:
Supplied Context Data, Prices & Events Cutoff:
Model knowledge cutoff:
Return calculation details

Current returns use the observed price and remaining time to the fixed published target. The quarterly table retains the original forecast anchor.

Read full advisor report

e.l.f. Beauty: Historical Prices & Published Forecast (The Polymath Framework on Gemini 3.8 Flash model)

e.l.f. Beauty: Historical Prices & Published Forecast (The Polymath Framework on Gemini 3.8 Flash model)Observed prices and the selected advisor's published projection share a split-adjusted price basis. Prices after the forecast start are later observations, not information known at publication. Values in USD.2.1659.14116.11173.09230.07Sep 2021Mar 2024Sep 2026Mar 2029Sep 2031Forecast startsToday (UTC)
  • Observed price
  • Published advisor forecast
Observed prices and the selected advisor's published projection share a split-adjusted price basis. Prices after the forecast start are later observations, not information known at publication. Values in USD.

e.l.f. Beauty: Quarterly Price Forecasts & Scenarios (The Polymath Framework on Gemini 3.8 Flash model)

Price targets, price returns and complete scenario reasoning

Forecast prices in USD. Price returns are cumulative from the original forecast anchor dated 2026-09-18; they exclude dividends. Swipe horizontally to read every column.

QuarterForecastPrice returnScenario
$101+5.0%

Holiday sell-through accelerates as Rhode's initial European Sephora rollout delivers explosive customer engagement. Despite lingering Section 301 replacement tariffs, resilient masstige demand expands market share, lifting quarterly gross margin trajectory and generating modest upward price re-rating.

$107+11.3%

Third-quarter fiscal 2027 earnings beat consensus as duty clawbacks and volume growth offset transport inflation. Strong teen category dominance and viral lip product traction drive retail inventory reorders across domestic and international retail partners.

$115+19.1%

Fiscal 2027 full-year results confirm annual sales surpassing $2.1 billion with international contribution reaching 22%. Operating leverage accelerates cash generation, prompting management to initiate post-acquisition debt deleveraging and boosting institutional equity confidence.

$117+21.5%

Summer consumer spending moderates amid sticky macro inflation, while digital marketing customer acquisition costs edge higher across key social channels. Moderate unit growth and Naturium shelf gains preserve positive momentum despite temporary multiple compression.

$123+27.5%

Holiday retail shipments expand as Sephora Europe adds Rhode across additional markets. Strong seasonal sell-through in mass channels and surging direct-to-consumer skincare bundles fuel double-digit revenue expansion and sequential gross margin improvement.

$122+26.3%

Post-holiday channel inventory rebalancing temporarily tempers factory reorders, while persistent policy rates near 4% constrain discretionary equity valuation multiples. Management absorbs slight working capital expansion without impairing core brand trajectory.

$129+33.8%

Fiscal 2028 reporting reveals non-China supply chain sourcing crossing 50%, sharply curtailing statutory tariff expenses. Consolidated gross margins reclaim 71.5%, unlocking substantial operating leverage and driving institutional earnings upgrades across Wall Street.

$134+39.2%

Naturium's rapid international retail penetration and Rhode's new color cosmetic launches drive elevated basket sizes. Strong consumer cash conversion reinforces balance sheet deleveraging, lowering net debt and expanding free cash flow margin.

$141+46.2%

Peak fourth-quarter holiday sales benefit from expanded Target and Ulta linear shelf space allocations. Robust direct-to-consumer margins and high viral product velocity generate record quarterly operating income, driving a sustained stock re-rating.

$142+47.6%

Capital deployment into automated regional distribution centers in Europe temporarily elevates capital expenditures. Core sales momentum remains solid, enabling the business to digest supply chain investment without experiencing meaningful multiple contraction.

$151+56.5%

Fiscal 2029 results highlight full integration of Rhode as annual purchase price amortization rolls off. Reported GAAP net margin expands dramatically toward 10%, generating exceptional return on invested capital and attracting quality-compounder funds.

$157+62.7%

International revenue approaches 30% of consolidated net sales, driven by Latin American market expansion and Boots UK dominance. Balanced geographic exposure insulates top-line performance from domestic retail cyclicality, supporting steady valuation expansion.

$163+69.2%

Omnichannel holiday sales hit record levels with strong contributions from prestige-adjacent Rhode skincare sets. High inventory turns and lean contract manufacturing deliver strong free cash flow, encouraging management to resume share repurchase authorizations.

$160+65.9%

Broader macroeconomic cooling in North American consumer spending prompts mass retail partners to moderate seasonal inventory replenishment. While e.l.f. maintains healthy retail sell-through rates, temporary wholesale destocking trims reported quarterly top-line expansion and compresses multiples.

$168+74.2%

Fiscal 2030 full-year results demonstrate resilient revenue surpassing $3.2 billion and record free cash flow exceeding $380 million. Substantial debt reduction returns net leverage near zero, unlocking expanded share repurchases and sparking an institutional rally.

$173+79.4%

Accelerated share repurchases shrink diluted share count while core brands capture incremental shelf space across global drug and grocery chains. Steady execution across mature categories reinforces the equity's defensive cash-generative credentials.

$180+86.6%

Holiday promotional campaigns capitalize on e.l.f.'s dominant Gen Z and Gen Alpha brand equity, achieving market-leading unit sell-through. Direct-to-consumer conversion rates remain high, generating robust operational cash flows heading into fiscal year-end.

$180+86.6%

Normal seasonal post-holiday consolidation matches expectations as retailers trim safety stocks. Steady gross margins and predictable operating expenditures keep valuation multiples stable, providing an orderly transition into the final forecast year.

$187+94.0%

Fiscal 2031 full-year results confirm operating margins sustaining at 15% on revenue approaching $3.8 billion. Continued international expansion and disciplined capital allocation cement e.l.f.'s status as an elite, diversified consumer goods compounder.

$185+92.1%

Late-cycle valuation consolidation emerges as revenue growth normalizes toward steady high-single-digit rates. Robust free cash flow and persistent share buybacks maintain high equity support, solidifying long-term horizon returns near multi-year highs.

Show remaining 18 quarters

All 20 quarters are displayed in the table above.

e.l.f. Beauty: Investment Thesis Base Case (The Polymath Framework on Gemini 3.8 Flash model)

The central tension lies between market fears of tariff-induced margin destruction and e.l.f.'s compounding market share gains across international and prestige-adjacent channels. While headline net margins were temporarily depressed by acquisition amortization and duty adjustments, the operational engine continues to scale rapidly. Sourcing migration to 45% non-China facilities, coupled with Rhode's global retail rollout across Sephora and Boots, structurally protects gross margins above 70%. As high-margin international and direct-to-consumer revenues outpace domestic mass retail, free cash flow generation accelerates, driving an institutional valuation re-rating from compressed multiples toward normalized consumer compounder levels.

  • Revenue expands at an 18% compound rate toward $3.8 billion by 2031 with operating margins recovering to 15%.
  • Normalized earnings per share reach $7.50, supporting a 24x price-to-earnings multiple as tariff and integration risks clear.
  • Implied enterprise value reaches $11.5 billion, delivering an approximate 87% total equity return over the five-year forecast horizon.

e.l.f. Beauty: Scenarios & Signals (The Polymath Framework on Gemini 3.8 Flash model)

Bull Case

The bull case activates upon seamless international adoption of Rhode across European and Asian Sephora doors, driving foreign revenue past 35% of total sales by 2028. This premiumization surge expands consolidated gross margins above 73%, while accelerated non-China supply chain migration neutralizes tariff friction entirely. Operating leverage doubles adjusted net income to $450 million by 2029, re-rating the stock toward $220 and generating over 125% upside for equity investors.

Bear Case

The bear case materializes if retaliatory Section 301 tariffs escalate past 25% while Gen Z consumer backlash against price hikes halts domestic volume growth. Inability to pass cost increases compresses gross margins below 66%, while integration missteps with Rhode cause major distributor inventory write-downs. Under these conditions, free cash flow contracts, leverage ratios breach covenant thresholds, and multiple compression drags the share price down toward $55, representing a 43% capital loss.

Behavioral Alpha Signals

Sentiment, repricing cycle, crowd narrative, catalyst, and macro alignment.

Expected Volatility Regime: High

Greed and Fear Index: -25 / 100 (Fear)

-25

Cycle Position: Stabilization

The reset is mostly complete and price drifts toward fair value.

EarlyAwareMomentumOvershootReversalCapit.StabilizeSTABILIZATION
Figure: Advisor position within the seven-stage market-recognition cycle. The highlighted point marks Stabilization.
What does Media Tell? (Crowd Consensus)

Consensus views e.l.f. as an ex-growth pandemic darling whose hyper-expansion has permanently stalled under crushing China tariffs, consumer price fatigue, and short-seller scrutiny. Sell-side models anchor on compressed fiscal 2026 GAAP operating margins and high debt from the Rhode buyout, pricing the company as a vulnerable commoditized mass player rather than an agile, multi-brand global beauty platform.

What Crowds Get Wrong? (Alpha/Value Gap)

The crowd materially underestimates the structural earnings power of e.l.f.'s evolving multi-brand platform. Skeptics focus on headline GAAP net margin contraction from $79.4 million in D&A and one-off tariff shocks, ignoring underlying cash generation—exemplified by $280 million in TTM free cash flow and a 4.86% FCF yield. Furthermore, the market fails to price the velocity of Rhode's global Sephora rollout across Europe and Latin America, where higher price points and lower China sourcing exposure will structurally expand margins, driving substantial upward earnings revisions.

When will Value Gap Repricing Happen? (Repricing Catalyst)

The decisive catalyst will be fiscal 2027 second-half earnings in early 2027, demonstrating sustained organic revenue growth above 30% alongside sequential gross margin recovery toward 71%. The first observable sign of repricing will appear in Nielsen retail sell-through data confirming market share gains across European Sephora doors and American mass retail.

How is Asset Influenced by Macro Regime?

The prevailing macro regime of sticky core inflation and Fed policy rates near 4.0% acts as a net tailwind for consumer trade-down demand, driving traffic to masstige cosmetics. However, tight credit and elevated interest expense create moderate headwinds for debt servicing following e.l.f.'s Rhode acquisition, marginally constraining valuation multiples.

e.l.f. Beauty: Positive & Negative Factors, Risks & Opportunities (The Polymath Framework on Gemini 3.8 Flash model)

Base-Case Forces

Top Drivers / Tailwinds

Base-case positive forces

Structural or operating forces that support this advisor thesis. Base-case means above 70% probability of occurrence. Probabilities are model estimates; unquantified forces retain their published group.

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Top Drivers / Tailwinds with asset-specific estimated impacts and thesis rationale
Driver / TailwindCategoryEst. stock-price impactEst. earnings impactWhy it matters
Global Omnichannel Sephora DistributionCompetitive Positioning+40%+50%International expansion represents an underpenetrated growth vector, substantiated by sequential retail rollouts across Sephora Europe's 19 countries, Sephora Brazil, and Boots UK. Overseas revenue expanded over 90% year-over-year, climbing toward 25% of total sales mix. This geographic broadening deepens shelf allocation, diversifies currency exposure, and scales distribution efficiency, driving sustained double-digit earnings growth and multiple expansion as global execution de-risks domestic concentration.
Prestige TO MASS Trade DOWN Structural TSector And Industry+35%+45%Persistent inflationary pressures and elevated interest rates compel consumers to trade down from prestige department-store cosmetics to masstige alternatives. Forensic audit of retail scan data confirms e.l.f. captures market share across income cohorts, fortified by 38% teen category dominance. This behavioral migration accelerates baseline volume growth across mass doors, compounding top-line revenue and expanding operating leverage over the five-year investment horizon.
Rhode Portfolio Integration AND PremiumiInnovation And Product+30%+38%The integration of Rhode elevates average order value and injects high-margin prestige skincare formulas into e.l.f.'s proven commercialization engine. Evidence from initial direct-to-consumer drops, delivering $27 million in a single day, proves authentic viral monetization. This transaction accelerates portfolio premiumization, structurally lifting gross margins above 71% and generating incremental operating cash flows as retail shelf space expands globally throughout the multi-brand architecture.
Supply Chain DE Risking AND Geographic DOperational Efficiency+20%+25%Management's aggressive diversification away from mainland China manufacturing—increasing non-China sourcing from 1% to 45%—mitigates systemic tariff vulnerability under replacement trade regimes. Forensic cost analysis shows contract manufacturing reallocation dampens duty burdens without sacrificing speed-to-market. This operational flexibility protects unit profitability, stabilizes gross margins against geopolitical frictions, and eliminates the valuation discount previously imposed by markets skeptical of China supply-chain reliance.
Top Frictions / Headwinds

Base-case negative forces

Expected frictions that can slow, cap, or damage this advisor thesis. Base-case means above 70% probability of occurrence. Probabilities are model estimates; unquantified forces retain their published group.

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Top Frictions / Headwinds with asset-specific estimated impacts and thesis rationale
Friction / HeadwindCategoryEst. stock-price impactEst. earnings impactWhy it matters
Tariff Regime Persistence AND Import DUTRegulatory-18%-22%Although Supreme Court rulings invalidated emergency IEEPA levies, replacement Section 301 actions enforce 10% to 12.5% baseline tariffs across consumer goods. With 55% of production still tied to Chinese suppliers, e.l.f. faces persistent margin friction. Management cannot pass all duty costs to price-sensitive consumers without triggering volume elasticities, which structurally caps gross margin expansion and creates recurring friction on operating profitability.
Prestige Beauty Pushback AND Price PointCompetitive Positioning-15%-18%Legacy beauty conglomerates like L'Oreal and Coty are retaliating with aggressive promotional pricing and accelerated copycat product cycles in mass retail. Concurrently, consumer resistance following e.l.f.'s prior one-dollar price hike demonstrates clear demand elasticity among Gen Z shoppers. This intensified shelf-space rivalry threatens inventory turns in domestic mass doors, forcing higher promotional allowances that dilute incremental sales growth and trim operating margins.
Acquired Intangible Amortization AND LEVCapital Allocation-14%-20%The balance sheet expansion accompanying the $1 billion Rhode acquisition escalated leverage, lifting debt-to-equity to 0.81 while annual depreciation and amortization spiked to $79.4 million. In a regime where the Federal Reserve benchmark rate sits at 3.75%-4.00%, elevated debt service and non-cash purchase amortization compress GAAP earnings. This capital structure overhead suppresses reported return on equity and limits discretionary share buyback capacity.
Influencer Marketing Inflation AND PlatfInnovation And Product-12%-15%E.l.f.'s growth model relies heavily on digital engagement and viral social media marketing, exposing it to rising digital customer acquisition costs and platform algorithmic volatility. Furthermore, Rhode introduces acute key-person risk centered on Hailey Bieber's cultural prominence. Any degradation in social conversion efficiency or disruption to brand sentiment immediately impairs direct-to-consumer sales momentum, increasing marketing expense-to-sales ratios and dragging down cash flow conversion.

Risks & Opportunities

Tail Risks

Plausible downside scenarios

Less likely downside scenarios that could materially hurt the outcome if they occur.

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Tail risks with plausibility, asset-specific potential impact and scenario rationale
Tail scenarioChance of OccurringStock Price ImpactWhy plausible / what changes
Severe China Trade Embargo OR Sanctions20%-45%An acute geopolitical crisis in the Taiwan Strait during late 2027 could trigger retaliatory embargoes or emergency 100% tariffs on Chinese imports. Because e.l.f. still relies on China for 55% of finished goods, this supply disruption would spark catastrophic inventory stockouts across mass retail doors. Gross margins would collapse under expedited air-freight and contract-cancellation charges, cutting annual earnings by half. This severe scenario carries a 20% probability given heightened Pacific geopolitical tensions.
Rhode Brand Dissociation AND Founder Scandal25%-35%A sudden public relations crisis or abrupt departure of key-person founder Hailey Bieber in mid-2027 could severely impair Rhode's cultural cachet. Triggered by reputational controversy or creative rupture, direct-to-consumer sales would plummet, causing mass inventory write-downs and triggering a mandatory impairment test on e.l.f.'s $1 billion acquisition goodwill. The resulting non-cash write-downs and lost earnings contribution would depress valuation multiples. We estimate the probability at 25%, reflecting inherent volatility in influencer-dependent beauty enterprises.
Tail Opportunities

Plausible upside scenarios

Less likely upside scenarios that could materially improve the outcome if they occur.

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Tail opportunities with plausibility, asset-specific potential impact and scenario rationale
Tail scenarioChance of OccurringStock Price ImpactWhy plausible / what changes
Accelerated Prestige Retail Takeover AT Sephora35%+45%Sephora could grant e.l.f. Beauty's portfolio—specifically Rhode and Naturium—permanent flagship endcaps across 2,000 global doors by late 2027. Triggered by record sales per linear foot during European trials, this would transform e.l.f. into a prestige fixture. Such placement would unlock $350 million in high-margin revenue, driving operating margins toward 16% and expanding valuation multiples. Probability sits at 35% due to counter-lobbying from entrenched European luxury conglomerates.
Bilateral Trade Detente AND ZERO Tariff Resolution25%+30%A formal US-China trade agreement in mid-2028 could comprehensively dismantle Section 301 duties on manufactured consumer cosmetics. Triggered by bilateral diplomatic detente, this policy reversal would immediately eliminate approximately $40 million in annualized duty burdens for e.l.f.. Operating margins would expand by 200 basis points overnight, releasing substantial trapped working capital and igniting share buybacks. The scenario holds a 25% probability given entrenched bipartisan protectionist sentiment and ongoing geopolitical friction in Washington.

e.l.f. Beauty: References & Context (The Polymath Framework on Gemini 3.8 Flash model)

Research Provenance23 sources · 4 search terms
Researcher modeWeb Search Used

Web Search was used. The retained search terms and consulted sources are shown below.

Context supplied to the model

Public-safe inputs retained with this immutable forecast publication.

  1. Market datainmemory_base_placeholders__latest_eod_close_price_with_stats_and_fundamentals__var1
  2. Global context in this runUsed
    2025 Full-Year Global Market and World-Events Context

    This full-year context package covers the principal geopolitical, economic, monetary-policy, technology, trade, energy, and institutional developments that shaped global markets during 2025. It gives the forecasting model a chronological account of major world events together with their likely transmission into growth, inflation, interest rates, supply chains, commodities, currencies, public markets, and sector-level investment conditions.

    2026 Year-to-Date Global Market and World-Events Context Through September 20

    January 1-September 20, 2026: monetary tightening, energy security, trade restrictions, AI financing and divergent growth; five leading market themes.

  3. Fundamental data in this runUsed
    Fundamental Context Passed as Input to the Models

    Time range: Annual fiscal periods: 2015-12-31–2026-03-31, 12 periods; Quarterly fiscal periods: 2023-09-30–2026-06-30, 12 periods. Currencies cited: USD (quote USD; primary reporting USD; converted/valuation USD).

  4. Global contextStandard global market and cross-asset context
  5. Subject contextEquity-specific subject and market context
  6. Task frameworkStandard investment-forecast task guidelines
  7. Advisor frameworkUniversal Investor The Polymath
  8. Forecast output requestedEquity Extended Investment Thesis (4 Quadrants and Alpha Asymmetry) + Pct Change Timeseries for Close Price with Rationale, (5Y Quarterly)

Search terms retained

  1. 1."ELF Beauty" short seller Muddy Waters Carson Block 2024 2025
  2. 2."e.l.f. Beauty" international expansion retail shelf space Sephora Target
  3. 3."ELF Beauty" tariffs China supply chain
  4. 4."e.l.f. Beauty" acquisition 2024 2025 2026

Sources retained for this advisor

  • [1]tradingview.com
  • [2]femfounded.org
  • [3]simplywall.st
  • [4]thestreet.com
  • [5]tikr.com
  • [6]elfbeauty.com
  • [7]freedom24.com
  • [8]cosmeticsbusiness.com
  • [9]echemi.com
  • [10]latimes.com
  • [11]substack.com
  • [12]cosmeticsbusiness.com
  • [13]supplychaindive.com
  • [14]supplychaindive.com
  • [15]benzinga.com
  • [16]jingdaily.com
  • [17]elfbeauty.com
  • [18]everything-pr.com
  • [19]jpmorgan.com
  • [20]stocktitan.net
  • [21]tradingview.com
  • [22]northwiseproject.com
  • [23]forbes.com

Original Published Forecast

Inspect the original revision and its sealed receipt.

How to understand these AI forecasts

How does an AI-generated forecast for e.l.f. Beauty differ from Wall Street analyst consensus?

Wall Street consensus aggregates estimates from human analysts. For listed companies, these typically include brokerage price targets, earnings forecasts and ratings. iPulse AI's forecast for e.l.f. Beauty is a separate AI consensus generated through its own research workflow. Different inputs, forecast dates, assumptions and weighting can therefore produce different targets.

We believe the era of investment research conducted only by human analysts is drawing to a close. Frontier models increasingly match or exceed expert work on selected professional benchmarks, including evaluations covering financial analysis. Research on multi-model synthesis also shows that combining model responses can improve on a single model's output in the tasks studied.

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For a research cycle covering 426 assets with 14 perspectives per asset, our internal workload model estimates approximately 114,000 hours of traditional analyst work. It assumes 16 hours per individual research report, 28 hours per consensus for synthesis and validation, plus shared data preparation. Parallel AI execution allows a deep-analysis cycle across hundreds of assets to complete in up to one day. The human-hours figure is an illustrative workload estimate, rather than measured time savings. Our research methodology explains the automated workflow.

If iPulse AI produces thousands of investment reports - work estimated to require over 100,000 traditional analyst hours - isn't that just "AI slop" at scale?

No. iPulse AI produces AI-generated research at scale, but the purpose is depth of analysis, comparison, and accountability. The number of reports is a consequence of the research process; it is not the goal.

iPulse AI does not produce thin copies of existing websites, articles, or investment reports. We use frontier models as an Analytical Intelligence layer. Our Financial Experts select, validate, curate, and supply the input data, including proprietary inputs, so the models work from a prepared evidence base.

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Our process goes much further than asking ChatGPT to evaluate a stock. Our team designs structured investment frameworks inspired by the approaches of influential investors, economists, political thinkers, and technological visionaries. These are AI analytical frameworks, not reports written or endorsed by the people who inspired them.

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This explains the volume. The value comes from what we do with the analysis.

A second layer synthesizes the individual reports into an asset-level consensus. This is where we recommend starting when researching a particular asset: it brings together the central thesis, supporting evidence, risks, and disagreements while preserving access to the underlying opinions.

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We publish research on our website, arXiv, and Zenodo, alongside explanatory writing on Medium. We use the evidence to refine our data, frameworks, validation, and workflows, and document important findings in Lessons Learned.

The standard we ask users to judge us by is the reasoning, evidence, and historical record behind the research.

What do the individual AI forecasts for e.l.f. Beauty represent?

Each report presents one AI advisor configuration's analysis of e.l.f. Beauty, including its investment framework, assumptions, forecast path, drivers, and risks. The reports provide different analytical perspectives on the same asset so you can examine the reasoning behind their conclusions.

How are these forecasts different from the AI Consensus?

The individual forecasts show each advisor's reasoning and outlook. The AI Consensus synthesizes those views into an overall assessment of e.l.f. Beauty. Start with the consensus for an overview, then explore individual reports to understand the strongest supporting arguments, objections, and disagreements.

Are the named AI advisors the actual investors or public figures?

No. They are AI analytical frameworks inspired by publicly documented investment approaches or broader schools of thought. Their reports are generated by AI within the iPulse AI research workflow. The names do not imply participation, endorsement, or a personal forecast from those individuals.

What is the difference between Thinker and Researcher mode?

Thinker mode reasons over the supplied data and context without external web search. Researcher mode can investigate additional external evidence when needed. Being configured as Researcher does not necessarily mean a particular report used web search; consult the report's research details where available.

Why do the AI advisors disagree about e.l.f. Beauty?

Different frameworks emphasize different evidence and assumptions. One may prioritize valuation, another technological growth, and another macroeconomic or political risk. Disagreement helps identify which assumptions deserve closer investigation. Agreement can also reflect shared inputs or model behavior, so it should not be treated as proof of accuracy.

How often are the reports updated?

The analytical content is updated during deep-analysis batch runs. We run each batch across all covered assets within the same research cycle, providing a consistent basis for comparison, scoring, and ranking. Currently, these batches run every few weeks; our aim is to increase the frequency to once a week.

Between batches, we update price-based expected returns and ratings daily using the latest available market prices. For example, a sharp price increase can reduce an asset's expected upside and change a previously published Buy rating. This keeps the price-based assessment current without presenting the underlying analytical report as newly generated.

Editorial Top Picks receive an additional weekly review, providing another check on whether current evidence continues to support the selected investment theses.

What can I read without signing in, and what requires a subscription?

You can read the public preview and the methodology explanations available on this page. Additional advisor reports, comparisons, configuration details, and historical records may require signing in and a subscription that includes the relevant asset or feature. Access prompts explain what is needed.

How do these forecasts contribute to Live Rankings and Editorial Top Picks?

Individual forecasts contribute to the asset's consensus and quantitative scoring. Live Rankings compare assets using the published scoring methodology. Editorial Top Picks add a further review of selected candidates, current evidence, investment theses, and risks, followed by human editorial approval. For example, explore our Best Long-Term Investments.

Can I inspect previous forecasts for e.l.f. Beauty and see what happened?

Forecast History lets you inspect earlier published forecasts, subject to your subscription access. Read each forecast against its original publication date, assumptions, and target dates. As outcomes become observable, those records support evaluation of what worked and what did not. Broader findings and methodological changes appear in Research and Lessons Learned.

e.l.f. Beauty Stock Analysis & Forecast — Universal Investor The Polymath Framework on GPT-6 Astra Model

Universal Investor AI advisor icon

Universal Investor AI · The Polymath Framework

GPT-6 Astra AI Researcher Web Search Used

5 Year Rating

Neutral

5 Year Price Return

+27.2%

Framework Description & Key Record Dates

Investment Framework

The Polymath Framework: Eight-Lens Investment Analysis Framework

Analysis Framework Description: Select the lenses with the greatest explanatory power, resolve their disagreements across horizons, and connect the evidence to a consistent thesis, scenario path, and verdict.

  • Ownership and value: examine economic rights, competitive advantage, capital allocation, and the price paid.
  • Regimes and constraints: connect credit, liquidity, policy, demand, and physical bottlenecks to the asset.
  • Innovation and adaptation: test adoption economics, AI and robotics exposure, substitution, and value capture.
  • Forensics and incentives: reconcile accounting, cash conversion, dilution, governance, and missing evidence.
  • Expectations and reflexivity: distinguish changes in fundamentals from changes in narratives and valuation.
  • Probabilities and resilience: use base rates, competing scenarios, catalysts, and the capacity to survive the wait.
  • Power and the rules of the game: assess political interests, regulatory influence, protection, and dependency.
  • Industry structure and consolidation: identify pricing power, chokepoints, alliances, and the economics of integration.
Full framework methodology
Model Producer:
OpenAI
Model Version:
GPT-6 Astra
Mode Used:
Researcher
Web Search Used
Forecast Target Date:
Latest Known Price Date for Return Estimate Refresh:
Forecast Published On:
Forecast Generated On:
Supplied Context Data, Prices & Events Cutoff:
Model knowledge cutoff:
Return calculation details

Current returns use the observed price and remaining time to the fixed published target. The quarterly table retains the original forecast anchor.

Read full advisor report

e.l.f. Beauty Stock Analysis & Forecast — Universal Investor The Polymath Framework on Claude Opus 5 Model

Universal Investor AI advisor icon

Universal Investor AI · The Polymath Framework

Claude Opus 5 AI Researcher Web Search Used

5 Year Rating

Neutral

5 Year Price Return

+20.1%

Framework Description & Key Record Dates

Investment Framework

The Polymath Framework: Eight-Lens Investment Analysis Framework

Analysis Framework Description: Select the lenses with the greatest explanatory power, resolve their disagreements across horizons, and connect the evidence to a consistent thesis, scenario path, and verdict.

  • Ownership and value: examine economic rights, competitive advantage, capital allocation, and the price paid.
  • Regimes and constraints: connect credit, liquidity, policy, demand, and physical bottlenecks to the asset.
  • Innovation and adaptation: test adoption economics, AI and robotics exposure, substitution, and value capture.
  • Forensics and incentives: reconcile accounting, cash conversion, dilution, governance, and missing evidence.
  • Expectations and reflexivity: distinguish changes in fundamentals from changes in narratives and valuation.
  • Probabilities and resilience: use base rates, competing scenarios, catalysts, and the capacity to survive the wait.
  • Power and the rules of the game: assess political interests, regulatory influence, protection, and dependency.
  • Industry structure and consolidation: identify pricing power, chokepoints, alliances, and the economics of integration.
Full framework methodology
Model Producer:
Anthropic
Model Version:
Claude Opus 5
Mode Used:
Researcher
Web Search Used
Forecast Target Date:
Latest Known Price Date for Return Estimate Refresh:
Forecast Published On:
Forecast Generated On:
Supplied Context Data, Prices & Events Cutoff:
Model knowledge cutoff:
Return calculation details

Current returns use the observed price and remaining time to the fixed published target. The quarterly table retains the original forecast anchor.

Read full advisor report

e.l.f. Beauty Stock Analysis & Forecast — J.P. Morgan The Titan Framework on Gemini 3.8 Flash Model

J.P. Morgan AI advisor icon

J.P. Morgan AI · The Titan Framework

Gemini 3.8 Flash AI Researcher Web Search Used

5 Year Rating

Buy

5 Year Price Return

+103.4%

Framework Description & Key Record Dates

Investment Framework

The Titan Framework: Empire Dominance Assessment

Analysis Framework Description: The Titan looks for who sets the terms. It grades whether an asset controls price, infrastructure, distribution, capital flows, or ecosystem access, then asks whether that dominance is expanding or inviting a counterattack.

  • Measure pricing power and whether customers have credible alternatives.
  • Map infrastructure, distribution, data, supply, or capital choke points.
  • Evaluate whether acquisitions strengthen the moat or merely add complexity.
  • Identify antitrust, succession, and regulatory antibodies against dominance.
  • Ask whether the asset collects rent from the system or pays rent to someone else.
Full framework methodology
Model Producer:
Google
Model Version:
Gemini 3.8 Flash
Mode Used:
Researcher
Web Search Used
Forecast Target Date:
Latest Known Price Date for Return Estimate Refresh:
Forecast Published On:
Forecast Generated On:
Supplied Context Data, Prices & Events Cutoff:
Model knowledge cutoff:
Return calculation details

Current returns use the observed price and remaining time to the fixed published target. The quarterly table retains the original forecast anchor.

Read full advisor report

e.l.f. Beauty Stock Analysis & Forecast — Warren Buffett The Value Seeker Framework on Gemini 3.8 Flash Model

Warren Buffett AI advisor icon

Warren Buffett AI · The Value Seeker Framework

Gemini 3.8 Flash AI Thinker Web Search Not Used

5 Year Rating

Buy

5 Year Price Return

+101.7%

Framework Description & Key Record Dates

Investment Framework

The Value Seeker Framework: Value Ownership Framework

Analysis Framework Description: The Value Seeker turns market noise into an ownership decision: understand the asset, judge the moat, estimate owner economics, evaluate management or governance, compare price with value, and demand a financial fortress.

  • Treat every asset as a business to be owned, not a ticker to be traded.
  • Stay inside the circle of competence before assigning conviction.
  • Map the moat type, moat durability, and whether the moat is widening or eroding.
  • Estimate owner economics through cash generation, ROIC, and reinvestment runway.
  • Audit management integrity, governance, and capital allocation rationality.
  • Compare intrinsic value to the market price with a real margin of safety.
  • Stress-test the financial fortress before accepting long-term ownership risk.
Full framework methodology
Model Producer:
Google
Model Version:
Gemini 3.8 Flash
Mode Used:
Thinker
Web Search Not Used
Forecast Target Date:
Latest Known Price Date for Return Estimate Refresh:
Forecast Published On:
Forecast Generated On:
Supplied Context Data, Prices & Events Cutoff:
Model knowledge cutoff:
Return calculation details

Current returns use the observed price and remaining time to the fixed published target. The quarterly table retains the original forecast anchor.

Read full advisor report

e.l.f. Beauty Stock Analysis & Forecast — Niccolo Machiavelli The Insider Framework on Gemini 3.8 Flash Model

Machiavelli AI advisor icon

Machiavelli AI · The Insider Framework

Gemini 3.8 Flash AI Researcher Web Search Not Used

5 Year Rating

Neutral

5 Year Price Return

+81.1%

Framework Description & Key Record Dates

Investment Framework

The Insider Framework: Power Audit Framework

Analysis Framework Description: The Insider asks who has power over the asset, how durable that power is, and whether the market is pricing the protection, threat, or political optionality correctly.

  • Map who can protect, subsidize, regulate, restrict, or destroy the asset's economics.
  • Track lobbying, procurement, sanctions, antitrust, and strategic policy exposure.
  • Identify insiders, capital networks, and institutions that are quietly positioned.
  • Estimate whether political power creates a valuation premium or discount.
  • Separate visible business performance from invisible power structure risk.
Full framework methodology
Model Producer:
Google
Model Version:
Gemini 3.8 Flash
Mode Used:
Researcher
Web Search Not Used
Forecast Target Date:
Latest Known Price Date for Return Estimate Refresh:
Forecast Published On:
Forecast Generated On:
Supplied Context Data, Prices & Events Cutoff:
Model knowledge cutoff:
Return calculation details

Current returns use the observed price and remaining time to the fixed published target. The quarterly table retains the original forecast anchor.

Read full advisor report

e.l.f. Beauty Stock Analysis & Forecast — Universal Investor The Polymath Framework on Gemini 3.8 Flash Model

Universal Investor AI advisor icon

Universal Investor AI · The Polymath Framework

Gemini 3.8 Flash AI Thinker Web Search Not Used

5 Year Rating

Neutral

5 Year Price Return

+61.5%

Framework Description & Key Record Dates

Investment Framework

The Polymath Framework: Eight-Lens Investment Analysis Framework

Analysis Framework Description: Select the lenses with the greatest explanatory power, resolve their disagreements across horizons, and connect the evidence to a consistent thesis, scenario path, and verdict.

  • Ownership and value: examine economic rights, competitive advantage, capital allocation, and the price paid.
  • Regimes and constraints: connect credit, liquidity, policy, demand, and physical bottlenecks to the asset.
  • Innovation and adaptation: test adoption economics, AI and robotics exposure, substitution, and value capture.
  • Forensics and incentives: reconcile accounting, cash conversion, dilution, governance, and missing evidence.
  • Expectations and reflexivity: distinguish changes in fundamentals from changes in narratives and valuation.
  • Probabilities and resilience: use base rates, competing scenarios, catalysts, and the capacity to survive the wait.
  • Power and the rules of the game: assess political interests, regulatory influence, protection, and dependency.
  • Industry structure and consolidation: identify pricing power, chokepoints, alliances, and the economics of integration.
Full framework methodology
Model Producer:
Google
Model Version:
Gemini 3.8 Flash
Mode Used:
Thinker
Web Search Not Used
Forecast Target Date:
Latest Known Price Date for Return Estimate Refresh:
Forecast Published On:
Forecast Generated On:
Supplied Context Data, Prices & Events Cutoff:
Model knowledge cutoff:
Return calculation details

Current returns use the observed price and remaining time to the fixed published target. The quarterly table retains the original forecast anchor.

Read full advisor report

e.l.f. Beauty Stock Analysis & Forecast — Superintelligence The Anthropologist Framework on Gemini 3.8 Flash Model

Superintelligence AI advisor icon

Superintelligence AI · The Anthropologist Framework

Gemini 3.8 Flash AI Researcher Web Search Not Used

5 Year Rating

Neutral

5 Year Price Return

+56.9%

Framework Description & Key Record Dates

Investment Framework

The Anthropologist Framework: Civilizational Compute Framework

Analysis Framework Description: The Anthropologist observes the financial system from above human emotion and asks whether an asset is biologically anchored, thermodynamically improving, informationally central, civilizationally aligned, and resilient to AI/quantum/space displacement.

  • Score biological demand anchoring: what human or civilizational need does the asset serve?
  • Measure thermodynamic efficiency and whether the asset reduces waste or increases throughput.
  • Map information network position, density, and dependency within the broader system.
  • Assess long-arc alignment with technological, demographic, and infrastructure evolution.
  • Estimate displacement risk from superior substitutes and frontier-tech transitions across AI, quantum, and space.
Full framework methodology
Model Producer:
Google
Model Version:
Gemini 3.8 Flash
Mode Used:
Researcher
Web Search Not Used
Forecast Target Date:
Latest Known Price Date for Return Estimate Refresh:
Forecast Published On:
Forecast Generated On:
Supplied Context Data, Prices & Events Cutoff:
Model knowledge cutoff:
Return calculation details

Current returns use the observed price and remaining time to the fixed published target. The quarterly table retains the original forecast anchor.

Read full advisor report

e.l.f. Beauty Stock Analysis & Forecast — Sherlock Holmes The Whistleblower Framework on Gemini 3.8 Flash Model

Sherlock Holmes AI advisor icon

Sherlock Holmes AI · The Whistleblower Framework

Gemini 3.8 Flash AI Researcher Web Search Used

5 Year Rating

Neutral

5 Year Price Return

+56.9%

Framework Description & Key Record Dates

Investment Framework

The Whistleblower Framework: Forensic Deduction Framework

Analysis Framework Description: The Whistleblower turns analysis into a case file: what is claimed, what evidence must exist if it is true, what evidence is missing, and what verdict follows from the exhibits.

  • Define the theory of the case behind the market narrative.
  • List the evidence that should exist if management or market claims are true.
  • Inspect filings, footnotes, revenue quality, related parties, and omitted metrics.
  • Stress-test contradictions between narrative, numbers, incentives, and behavior.
  • Deliver a clear case-file verdict rather than vague suspicion.
Full framework methodology
Model Producer:
Google
Model Version:
Gemini 3.8 Flash
Mode Used:
Researcher
Web Search Used
Forecast Target Date:
Latest Known Price Date for Return Estimate Refresh:
Forecast Published On:
Forecast Generated On:
Supplied Context Data, Prices & Events Cutoff:
Model knowledge cutoff:
Return calculation details

Current returns use the observed price and remaining time to the fixed published target. The quarterly table retains the original forecast anchor.

Read full advisor report

e.l.f. Beauty Stock Analysis & Forecast — Ray Dalio The Strategist Framework on Gemini 3.8 Flash Model

Ray Dalio AI advisor icon

Ray Dalio AI · The Strategist Framework

Gemini 3.8 Flash AI Researcher Web Search Not Used

5 Year Rating

Neutral

5 Year Price Return

+41.8%

Framework Description & Key Record Dates

Investment Framework

The Strategist Framework: Economic Machine Framework

Analysis Framework Description: The Strategist treats markets as cause-effect systems. The page explains how this persona separates cyclical expansion from deleveraging, temporary policy support from durable productivity, and short-term noise from long-wave regime change.

  • Identify the current short-term debt cycle and whether liquidity is expanding or contracting.
  • Map long-term deleveraging pressure and the asset's sensitivity to credit stress.
  • Assess reserve-currency, empire-cycle, and geopolitical pressure around the asset class.
  • Separate temporary policy support from durable productivity-driven value creation.
  • Translate macro regime into asset positioning, expected catalysts, and horizon risk.
Full framework methodology
Model Producer:
Google
Model Version:
Gemini 3.8 Flash
Mode Used:
Researcher
Web Search Not Used
Forecast Target Date:
Latest Known Price Date for Return Estimate Refresh:
Forecast Published On:
Forecast Generated On:
Supplied Context Data, Prices & Events Cutoff:
Model knowledge cutoff:
Return calculation details

Current returns use the observed price and remaining time to the fixed published target. The quarterly table retains the original forecast anchor.

Read full advisor report

e.l.f. Beauty Stock Analysis & Forecast — Warren Buffett The Value Seeker Framework on Gemini 3.8 Flash Model

Warren Buffett AI advisor icon

Warren Buffett AI · The Value Seeker Framework

Gemini 3.8 Flash AI Researcher Web Search Not Used

5 Year Rating

Neutral

5 Year Price Return

+33.1%

Framework Description & Key Record Dates

Investment Framework

The Value Seeker Framework: Value Ownership Framework

Analysis Framework Description: The Value Seeker turns market noise into an ownership decision: understand the asset, judge the moat, estimate owner economics, evaluate management or governance, compare price with value, and demand a financial fortress.

  • Treat every asset as a business to be owned, not a ticker to be traded.
  • Stay inside the circle of competence before assigning conviction.
  • Map the moat type, moat durability, and whether the moat is widening or eroding.
  • Estimate owner economics through cash generation, ROIC, and reinvestment runway.
  • Audit management integrity, governance, and capital allocation rationality.
  • Compare intrinsic value to the market price with a real margin of safety.
  • Stress-test the financial fortress before accepting long-term ownership risk.
Full framework methodology
Model Producer:
Google
Model Version:
Gemini 3.8 Flash
Mode Used:
Researcher
Web Search Not Used
Forecast Target Date:
Latest Known Price Date for Return Estimate Refresh:
Forecast Published On:
Forecast Generated On:
Supplied Context Data, Prices & Events Cutoff:
Model knowledge cutoff:
Return calculation details

Current returns use the observed price and remaining time to the fixed published target. The quarterly table retains the original forecast anchor.

Read full advisor report

e.l.f. Beauty Stock Analysis & Forecast — Superintelligence The Anthropologist Framework on Gemini 3.8 Flash Model

Superintelligence AI advisor icon

Superintelligence AI · The Anthropologist Framework

Gemini 3.8 Flash AI Thinker Web Search Not Used

5 Year Rating

Neutral

5 Year Price Return

+10.5%

Framework Description & Key Record Dates

Investment Framework

The Anthropologist Framework: Civilizational Compute Framework

Analysis Framework Description: The Anthropologist observes the financial system from above human emotion and asks whether an asset is biologically anchored, thermodynamically improving, informationally central, civilizationally aligned, and resilient to AI/quantum/space displacement.

  • Score biological demand anchoring: what human or civilizational need does the asset serve?
  • Measure thermodynamic efficiency and whether the asset reduces waste or increases throughput.
  • Map information network position, density, and dependency within the broader system.
  • Assess long-arc alignment with technological, demographic, and infrastructure evolution.
  • Estimate displacement risk from superior substitutes and frontier-tech transitions across AI, quantum, and space.
Full framework methodology
Model Producer:
Google
Model Version:
Gemini 3.8 Flash
Mode Used:
Thinker
Web Search Not Used
Forecast Target Date:
Latest Known Price Date for Return Estimate Refresh:
Forecast Published On:
Forecast Generated On:
Supplied Context Data, Prices & Events Cutoff:
Model knowledge cutoff:
Return calculation details

Current returns use the observed price and remaining time to the fixed published target. The quarterly table retains the original forecast anchor.

Read full advisor report

e.l.f. Beauty Stock Analysis & Forecast — Elon Musk The Visionary Framework on Gemini 3.8 Flash Model

Elon Musk AI advisor icon

Elon Musk AI · The Visionary Framework

Gemini 3.8 Flash AI Researcher Web Search Used

5 Year Rating

Partial Sell

5 Year Price Return

-1.2%

Framework Description & Key Record Dates

Investment Framework

The Visionary Framework: Paradigm Shift Framework

Analysis Framework Description: The Visionary asks whether the asset is building the future or clinging to the past, then validates physics, S-curve timing, execution velocity, and a forced AI/quantum/space disruption verdict.

  • Start from first-principles feasibility instead of consensus market extrapolation.
  • Run a mandatory frontier-tech disruption test for AI, quantum, and space exposure.
  • Estimate where the asset sits on an S-curve: early, inflecting, maturing, or saturating.
  • Model future TAM from deployment constraints, infrastructure, and adoption friction.
  • Grade execution velocity through iteration speed, talent density, and learning loops.
  • Separate real paradigm shifts from narratives that only sound futuristic.
Full framework methodology
Model Producer:
Google
Model Version:
Gemini 3.8 Flash
Mode Used:
Researcher
Web Search Used
Forecast Target Date:
Latest Known Price Date for Return Estimate Refresh:
Forecast Published On:
Forecast Generated On:
Supplied Context Data, Prices & Events Cutoff:
Model knowledge cutoff:
Return calculation details

Current returns use the observed price and remaining time to the fixed published target. The quarterly table retains the original forecast anchor.

Read full advisor report

e.l.f. Beauty Stock Analysis & Forecast — Michael Burry The Vulture Framework on Gemini 3.8 Flash Model

Michael Burry AI advisor icon

Michael Burry AI · The Vulture Framework

Gemini 3.8 Flash AI Researcher Web Search Not Used

5 Year Rating

Partial Sell

5 Year Price Return

-43.7%

Framework Description & Key Record Dates

Investment Framework

The Vulture Framework: Contrarian Forensic Framework

Analysis Framework Description: The Vulture starts with the crowd story and looks for the single fact, balance sheet pressure point, or dated catalyst that can force a repricing in either direction.

  • State the consensus story clearly before attacking it.
  • Search for balance sheet fragility, liquidity pressure, and hidden leverage.
  • Compare market narrative against hard evidence, filings, costs, and positioning data.
  • Identify the catalyst that could force the market to care.
  • Estimate upside and downside asymmetry if the crowd is wrong.
Full framework methodology
Model Producer:
Google
Model Version:
Gemini 3.8 Flash
Mode Used:
Researcher
Web Search Not Used
Forecast Target Date:
Latest Known Price Date for Return Estimate Refresh:
Forecast Published On:
Forecast Generated On:
Supplied Context Data, Prices & Events Cutoff:
Model knowledge cutoff:
Return calculation details

Current returns use the observed price and remaining time to the fixed published target. The quarterly table retains the original forecast anchor.

Read full advisor report

Global Events Context Provided to the Model

Gemini 3.8 Flash has a published knowledge cutoff of Mar 1, 2026. Curated global-events context covering events through Sep 20, 2026 was supplied to supplement its built-in knowledge with important developments.

2025 Full-Year Global Market and World-Events Context

Download Archived Snapshot

Coverage 2025-01-01 to 2025-12-31 · Knowledge cutoff 2025-12-31

This full-year context package covers the principal geopolitical, economic, monetary-policy, technology, trade, energy, and institutional developments that shaped global markets during 2025. It gives the forecasting model a chronological account of major world events together with their likely transmission into growth, inflation, interest rates, supply chains, commodities, currencies, public markets, and sector-level investment conditions.

Archived context covering 2025-01-01 to 2025-12-31. Its recorded scope includes technology and capital cycle; trade and industrial policy; monetary policy. Selected highlights reflect the analysis cutoff, not current world conditions.

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File size
90.8K bytes
Words
13.3K words
Characters
90.8K characters
Est. tokens (characters ÷ 4)
22.7K tokens

The package also includes monthly and quarterly macroeconomic and cross-asset reference tables spanning US and international growth, central-bank policy, sovereign yields, major equity indices, foreign exchange, energy, industrial and precious metals, and digital assets. Quarterly and full-year high-impact summaries are integrated; monthly quantitative series remain working values pending final audit, and that qualification is part of the preserved context.

Selected highlights from the archived 2025 Full-Year Global Market and World-Events Context snapshot
Selected highlights from this archived snapshotDateStatus
DeepSeek shock and AI economics reset2025-01-27OPEN ENDED TREND
US tariff regime escalation and trade-system rupture2025-02-01ACTIVE POLICY REGIME
Federal Reserve easing cycle after a prolonged hold2025-09-17ACTIVE POLICY REGIME

2026 Year-to-Date Global Market and World-Events Context Through September 20

Download Archived Snapshot

Coverage 2026-01-01 to 2026-09-20 · Knowledge cutoff 2026-09-20

January 1-September 20, 2026: monetary tightening, energy security, trade restrictions, AI financing and divergent growth; five leading market themes.

Archived context covering 2026-01-01 to 2026-09-20. Its recorded scope includes monetary policy and rates; geopolitics energy and shipping; trade and industrial policy. Selected highlights reflect the analysis cutoff, not current world conditions.

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84.8K bytes
Words
12.4K words
Characters
84.8K characters
Est. tokens (characters ÷ 4)
21.2K tokens

Fed raised rates to 3.75%-4.00%; ECB hike is in force and BOJ increase starts September 24. Markets through September 18, bitcoin through September 19.

Selected highlights from the archived 2026 Year-to-Date Global Market and World-Events Context Through September 20 snapshot
Selected highlights from this archived snapshotDateStatus
Renewed monetary tightening amid persistent inflation2026-01-30ACTIVE POLICY REGIME
Iran/Hormuz conflict and wider energy-security disruption2026-02-28ONGOING
Tariff legal reset and strategic supply restrictions2026-02-20ACTIVE POLICY REGIME

Representative Sources of the Context File

And more sources from the retained context package.

Fundamental Context Provided to the Model

Time range: Annual fiscal periods: 2015-12-31–2026-03-31, 12 periods; Quarterly fiscal periods: 2023-09-30–2026-06-30, 12 periods.

Currencies cited: USD (quote USD; primary reporting USD; converted/valuation USD).

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Income statement

9 fields

depreciationAndAmortization · ebit · ebitda · grossProfit · +5 more fields

Balance sheet

12 fields

cash · commonStockSharesOutstanding · longTermDebt · netDebt · +8 more fields

Cash flow

5 fields

capitalExpenditures · dividendsPaid · freeCashFlow · salePurchaseOfStock · +1 more field

Research datasets created by iPulse AI and published by Future Edge Group FZE. Use is subject to the iPulse AI Terms of Service and applicable source rights.