Quantum Stocks Based on AI: Returns up to 10.51% in 3 Days
Stocks Under $5 Based on Machine Learning: Returns up to 15.99% in 7 Days
SOXX Stocks Based on AI: Returns up to 18.62% in 14 Days
Quantum Stocks Based on AI: Returns up to 27.84% in1 Month
SOXX Stocks Based on AI: Returns up to 70.58% in 3 Months
Top 10 Stocks Based on AI: Returns up to 203.54% in 1 Year
Eli Lilly and Company (LLY) is up 33.55% sinceOctober 19th, 2025,propelled by the announcement of positive Phase 3 clinical trial results for its oral GLP-1 drug in early October, which demonstrated strong efficacy in diabetes management and weight loss, reinforcing the company's leadership in the booming cardiometabolic therapy market and boosting investor confidence in its pipeline expansion beyond injectables like Mounjaro and Zepbound. This momentum was further amplified by a strategic drug-pricing agreement with Novo Nordisk and the Trump administration, slashing U.S. prices for key weight-loss drugs in exchange for tariff relief and broader Medicare/Medicaid access, alleviating regulatory pressures while highlighting sustained demand; bullish analyst upgrades, including buy signals from pivot bottoms around October 21, and robust international sales—such as Mounjaro becoming India's top-selling drug by value in October—have compounded the rally, with shares hitting an all-time high of $1,025.28 on November 14 amid calming volatility and favorable technical indicators like upward-trending Bollinger Bands and a retreating RSI from overbought levels.
Alphabet Inc (GOOGL) is up 25.04% since September 18th, 2025, driven by a pivotal shift in investor sentiment from viewing the company as an AI laggard to a leading beneficiary. The rally gained momentum after a September 2025 federal court ruling in the landmark antitrust case rejected forced divestitures of Chrome or Android, providing significant regulatory relief and removing a major overhang that had weighed on the stock. This was followed by robust Q3 2025 earnings in late October, where Alphabet reported its first-ever $100B+ quarterly revenue (up 16% YoY), fueled by resilient search advertising, accelerating Google Cloud growth (with a $155B backlog up 46% YoY and gaining share from rivals), and expanding subscriptions reaching over 300 million paid users across YouTube and Google One. Further boosting confidence were advancements in AI, particularly the late-2025 launches of Gemini 3 models (praised for superior multi-modal reasoning, speed, efficiency, and closing/exceeding gaps with competitors like OpenAI's offerings), which demonstrated successful monetization in Search and YouTube while dispelling earlier disruption fears. Combined with heavy investments in AI infrastructure paying off and a broader market re-rating amid low prior expectations, these factors propelled the sharp late-year advance.
Goldman Sachs Group, Inc (GS) is up 25.94% since August 4th, 2025, driven by a robust recovery in capital markets activity and strong execution across its core businesses. The rally accelerated in Q4 following strong Q3 earnings reported in mid-October 2025, where the bank posted record $15.18 billion in net revenues (up ~20% YoY) and EPS of $12.25 (beating estimates), fueled by surging investment banking fees from a resurgence in M&A (industry-wide up 22%) and IPOs, exceptional fixed-income and equities trading amid market volatility (influenced by policy shifts like tariffs), and record assets under supervision reaching $3.45 trillion with massive inflows into asset and wealth management. Further momentum came from strategic acquisitions (e.g., Innovator Capital Management for ETFs and others in alternatives/venture), optimistic guidance on a strengthening M&A pipeline into 2026, growth in prime brokerage and structured lending, and a broader re-rating of bank stocks amid easing regulatory pressures, resilient economic growth, and enthusiasm for dealmaking in a lower-rate environment. This combination solidified Goldman's position as a top performer among large banks, shifting perceptions toward its refocused strengths in institutional and investment banking franchises.
I Know First Webinar: Tuesday January 6th 11AM EST
Special One-Time Webinar: I Know First AI Predictive Algorithm Names Its Top 20 Stock Picks For 2026
What You’ll Learn
20 Top-Performing Stocks Selected by I Know First Advanced AI For 2026 The Top Investment Opportunities in the Stock Market
Special Report for 2026 Based on AI: Best S&P 500 Stocks, Top ETFs, Leading Aggressive Growth Stocks and Crypto stocks.
Uncover which Stocks the I Know First AI Identifies as The Best Picks For January 2026. AI-Powered Predictions For NVDA, RKLB, BTC/USD, SLV, and Many more.
Strategic Insights: Top U.S. Sectors & Stocks for 2026 Discover which sectors investors must focus on and the surprising “Mag 7” stock poised to lead the market.
Meet the Speakers
Yaron Golgher – CEO and Co-Founder of I Know First
The I Know First AI Portfolio, previously an institutional offering now available to retail investors, leverages advanced machine learning and quantitative analysis to identify high-potential stocks. Designed to deliver market-beating returns, this portfolio uses proprietary deep learning algorithms to create a monthly-rebalanced, long-only stock selection aimed at outperforming the market.
Since its inception, the I Know First AI Portfolio has achieved a +27.2% return, significantly surpassing the S&P 500’s +20.94% return, resulting in a +6.3% alpha. This performance highlights the portfolio’s ability to generate resilient investment strategies, even in volatile market conditions, showcasing the power of AI-driven investing.
The portfolio’s specific stock picks are exclusive to subscribers, ensuring the integrity of the signals and providing a competitive edge. Retail investors and experienced traders alike can access these institutional-grade tools by subscribing, gaining entry to the next AI-generated portfolio before the monthly rebalancing.
Imagine waking up on January 1, 2025, with a "Secret Report" listing top stocks like HOOD, GOOGL, SOFI, AVGO, CRWD, SLV, GLD, and NVDA—right before their huge gains.These delivered impressive 2025 returns.
I Know First AI. Your 2026 Roadmap — Our algorithms have mapped the next 12 months and just released the 2026 Opportunities Report—a full AI-driven guide to top stocks, ETFs, sectors, indices, FX, commodities, and crypto poised for big moves.Don't wait until 2027 to regret missing it. Get ahead now.
New Era of Stock Trading: AI, Technical Analysis, and Smarter Decisions
Artificial intelligence now powers approximately 70% of U.S. equity trading volume, enabling faster and more precise decisions for hedge funds and institutional investors. Technical analysis, used by about 60% of hedge funds, complements AI by providing tools to identify market trends and patterns through historical price data and indicators.
AI Dominance in Markets: AI and algorithmic systems execute ~70% of U.S. equity trading volume, a sharp rise from earlier decades, supporting high-frequency trading and portfolio optimization for institutions.
Role of Technical Analysis: Traders forecast price movements using charts, volume data, and indicators like moving averages, RSI, and Bollinger Bands, with around 60% of hedge funds integrating it into their strategies.
Synergy of AI and Technical Analysis: AI processes vast datasets to highlight high-probability stocks, allowing traders to apply technical tools for precise entry/exit timing and better decision-making.
I Know First's Solution: The platform's AI, trained on 15 years of global market data, delivers customized stock forecasts, which users can refine with technical analysis for stronger trade signals.
Combining AI's predictive capabilities with the timeless principles of technical analysis—through tools like I Know First—gives traders and funds a decisive edge in navigating today's dynamic and volatile markets.
Stock Market Predictions: Where In Your Feedback Loop Is Your Portfolio
Stock markets are neither fully efficient nor completely random but semi-efficient systems with exploitable patterns, allowing skilled traders and algorithms to consistently outperform over time despite occasional randomness. By identifying positive and negative feedback loops and ignoring short-term unpredictable events, investors can better position their portfolios to capture opportunities where others see only chaos.
Market Inefficiency and Exploitability: Contrary to classical theory claiming perfect efficiency, markets are inefficient because not all participants interpret information the same way, enabling some traders and institutions to consistently profit while others lose.
Not Random, But Predictable Patterns Exist: Markets are not chaotic; large firms generate steady profits year after year, proving systematic components and patterns that can be forecasted, similar to weather predictions that are useful even if not always perfectly accurate.
Positive and Negative Feedback Loops: Positive loops (e.g., rising prices fueling more buying, as in Apple product hype) drive strong trends upward, while negative loops (e.g., Blackberry's price oscillating around perceived fair value) create mean reversion, helping identify overall direction amid short-term noise.
Handling Randomness: Unforeseeable events like flash crashes or disasters should not alter sound decision-making; just as in poker, the correct strategy remains valid even after bad-luck losses, focusing instead on long-term probabilities.
I Know First's Algorithmic Approach: Advanced self-learning algorithms separate predictable signals from noise, assessing where assets sit in their feedback loops to generate stock predictions, as illustrated by identifying opportunities like XPO Logistics despite overlapping negative feedback periods.
By understanding feedback loops, embracing market inefficiencies, and leveraging AI-driven tools like I Know First to filter out randomness, investors can systematically uncover hidden opportunities and build portfolios positioned for long-term outperformance in seemingly unpredictable markets.
The January Barometer anomaly suggests that the S&P 500's performance in January can predict returns for the rest of the year, with historical data from 1971–2025 showing that positive January returns are followed by stronger average monthly gains than negative ones. Although a linear regression on January's exact return lacks statistical significance, the directional effect (positive vs. negative January) is significant at the 5% level, offering investors limited but useful predictive insight.
January Barometer Definition: The anomaly posits that if the S&P 500 rises in January, the rest of the year tends to be positive, and vice versa, providing a simple rule for anticipating annual market direction.
Linear Regression Results: Over 1971–2025, each additional 1% return in January correlates with an extra ~0.057% average monthly return for the remaining months, but the relationship is not statistically significant (p-value ~0.1266), failing to reject the null hypothesis of no effect.
Directional Test Results: When splitting by sign, positive January returns are followed by ~0.0102% average monthly returns for the rest of the year, versus ~0.0024% after negative Januarys—both coefficients statistically significant at the 5% level, supporting a meaningful January Barometer effect.
Limitations and Risks: Market anomalies can appear or disappear unpredictably, and improper testing risks data snooping; the January Barometer offers guidance but is not a reliable standalone predictor.
I Know First's AI Advantage: The company's self-learning algorithm, based on chaos theory, neural networks, and 15 years of data, systematically detects and exploits viable anomalies (including patterns like the January effect) that are hard for individual investors to identify, delivering strong outperformance as shown in strategies yielding over 1054% returns from 2020–2025 versus the S&P 500.
While the January Barometer provides statistically supported directional insight into full-year S&P 500 performance, leveraging advanced AI tools like I Know First's predictive algorithm offers a more robust and adaptive way for investors to identify and profit from market anomalies that beat the market consistently.
Why You Should Listen: The AI Just Predicted Friday's +10% Pop
The market is already validating our algorithms. On the very first trading Friday of 2026, the semiconductor sector sent a loud signal—exactly as predicted.
Micron Technology (MU) popped more than 10% in a single session, and Nvidia (NVDA) climbed over 1%.
This is exactly what our AI predicted.
In accordance with our self-learning algorithms, the semiconductor sector (SOXX) was flagged for a breakout—but the AI went deeper. Micron (MU) and Nvidia (NVDA) were explicitly identified as the Top Stock Picks in this forecast.
Tech was the trade of the year, lifting the Nasdaq +20% and the S&P 500 +16%. But while the indices did well, our AI identified outliers crushed the benchmarks.
Subscribers who followed our 1-Year Forecasts saw triple-digit returns that far outpaced the market:
Don't Guess. Get the Roadmap. We have taken the same algorithms that identified ONDS, HOOD, and MU, and applied them to the year ahead.
The 2026 Opportunities Report is not just a list of stocks; it is a strategic roadmap combining our deep learning forecasts for Equities, Commodities, and Crypto. Get The Report Here: Watch The Video Breakdown Here:
Venezuela Conflict: How will that Effect the Market? The ongoing Venezuela crisis, escalated by the January 2026 US military strikes and capture of President Nicolás Maduro, is expected to inject short-term volatility into global markets, particularly around energy stocks and oil prices. I Know First Energy Forecast:
Apple's stock outlook heading into 2026 reflects a cautious yet potentially rewarding strategy across AI, supply chain stability, and regulatory challenges. The company is adopting a restrained approach to AI spending amid signs of a market bubble, preserving over $130 billion in cash for possible acquisitions while preparing a major Siri overhaul—likely powered by Google's Gemini—to enhance conversational capabilities and multi-step tasks, leveraging its integrated iPhone ecosystem as a key advantage over competitors. On tariffs, Apple secured an 18-month reprieve keeping Chinese semiconductor import rates at zero percent until mid-2027, avoiding immediate cost increases for critical components despite ongoing reliance on Chinese suppliers. Meanwhile, Apple is appealing a £1.5 billion UK fine over allegedly excessive App Store commissions of up to 30%, arguing the fees support platform safety and privacy for 36 million users, with consumer payouts at stake if the appeal fails. Overall, these developments position Apple to capitalize on prudence in AI while navigating trade and antitrust risks.
