Best Energy Stocks Based on AI: Returns up to 19.25% in 3 Days
Best AI Stocks Based on Machine Learning: Returns up to 15.80% in 7 Days
High Short Interest Stocks Based on AI: Returns up to 79.93% in 14 Days
Energy Stocks Based on AI: Returns up to 25.62% in1 Month
Energy Stocks Based on AI: Returns up to 44.52% in 3 Months
Top 10 Stocks Based on AI: Returns up to 196.51% in 1 Year
Walmart Inc (WMT) is up 8.33% since December 14th, 2025,driven by sustained momentum in its high-margin digital and advertising businesses amid resilient consumer demand. Key factors include explosive e-commerce growth (up 24-27% in recent quarters via omnichannel services like pickup, delivery, and faster shipping), Walmart Connect advertising surging 53% year-over-year as part of an "alternative profit flywheel" shifting earnings toward stable tech-driven streams, strong comparable sales (e.g., 4.6% in Walmart US), traffic gains across income levels, and margin improvements from Walmart+ memberships and marketplace expansion. This performance culminated in Walmart crossing the $1 trillion market cap milestone in early February 2026, fueled by consistent execution, analyst upgrades (with price target raises citing AI/retail synergies), share repurchases, and its Nasdaq listing switch in December 2025, which repositioned it as a tech-enabled powerhouse outperforming traditional retail peers in a choppy environment.
Lam Research Corporation (LRCX) is up 118.00% since June 29th, 2025,driven primarily by the explosive, sustained boom in AI infrastructure and advanced semiconductor manufacturing demand that has propelled wafer fabrication equipment (WFE) spending far beyond initial expectations. As a leading provider of critical etch and deposition tools essential for producing complex, high-performance chips (including those for AI data centers, high-bandwidth memory/HBM, advanced DRAM, and leading-edge foundry/logic nodes), Lam has benefited enormously from hyperscalers' massive capital expenditures on AI accelerators and the broader industry shift toward smaller process nodes, 3D architectures, and advanced packaging technologies; this translated into record quarterly revenues (e.g., climbing to over $5.3 billion in recent periods with year-over-year growth in the 20–34% range), exceptional gross margin expansion to multi-year highs around 50% (fueled by high-value AI-related sales and operational efficiency), consistent earnings beats, upward revisions to full-year guidance, and bullish 2026 WFE market forecasts reaching $135 billion (up significantly from 2025 estimates around $110 billion). Additional tailwinds included strong memory chip recovery cycles, partnerships (such as with IBM on sub-1nm and High-NA EUV advancements), geographic diversification efforts (e.g., investments in U.S. facilities amid China exposure concerns), and positive analyst upgrades emphasizing Lam's "best-in-class" positioning in deposition/etch criticality for AI-era chips, leading to outsized outperformance versus broader semiconductor indices and a rerating of the stock as a core "picks-and-shovels" play in the ongoing generative AI supercycle—though the rapid run has introduced valuation risks with elevated multiples and occasional pullbacks tied to profit-taking or sector rotations.
Eli Lilly (LLY) is up 21.77% since October 19th, 2025,fueled primarily by explosive ongoing demand for its blockbuster GLP-1 drugs Mounjaro (for type 2 diabetes) and Zepbound (for weight loss/ obesity). This momentum was reinforced by a strong Q3 2025 earnings beat in late October, which included raised full-year guidance reflecting robust global sales growth (e.g., Mounjaro and Zepbound revenues far exceeding expectations), positive pipeline updates like promising data for oral GLP-1 candidate orforglipron, easing policy uncertainties around drug pricing and tariffs, and broader market enthusiasm for Lilly's dominant position in the high-growth incretin/obesity market, which continued driving revenue and investor confidence into early 2026 despite later pullbacks from competition and valuation concerns.
Commodities 3 Days: Up to 11.65% Returns 7 Days: Up to 29.30% Returns 14 Days: Up to 27.36% Returns 1 Month: Up to 47.15% Returns 3 Months: Up to 48.59% Returns
Cryptocurrencies 3 Days: Up to 9.76% Returns 1 Month: Up to 31.31% Returns
Special Webinar: Ahead of the Curve: The Top 10 Stock Picks AI Has Identified for March
What You’ll Learn
The Top 10 stocks artificial Intelligence is identifying for the next 4 weeks– Before Wall Street catches on
Live & Unfiltered: One AI model scanned thousands of data points so you don’t have to -uncovering the best market opportunities for March
Get a first look at the AI-driven investment portfolio that outperformed the market by over 7.5% this past month
Comprehensive AI Analysis of the US Market: A deep scan of the US market reveals the sectors quietly building momentum right now and the updated forecast for NVDA, WDC, AMD and More
Meet the Speakers
Yaron Golgher – CEO and Co-Founder of I Know First
The I Know First AI algorithm demonstrated strong performance in forecasting long positions for energy stocks, outperforming the S&P 500 by 4.72% over a 1-year period with the Top 10 signals achieving a 19.48% average return. Across various time horizons from short-term to long-term, the AI generated positive returns and high hit ratios (up to 70% for 1-year forecasts), highlighting its effectiveness in predicting market movements in the energy sector.
The evaluation covered live forecasts for the Energy Stocks Package from December 1, 2024, to March 4, 2026, focusing on long positions using AI-generated signals and predictability filters.
Over a 1-year horizon, the Top 10 Signals delivered an average return of 19.48%, beating the S&P 500 by 4.72%.
In the 1-month horizon, the Top 20 Signals achieved a 3.35% average return, outperforming the S&P 500's 1.02% by over 3 times.
The algorithm's hit ratio (correct directional predictions) improved with longer horizons, reaching 70% for 1-year forecasts, with positive returns and outperformance in most evaluated signal groups and time periods.
Overall, the report underscores the I Know First AI's consistent ability to deliver market-beating results in energy stock forecasting, particularly over longer horizons, supporting its value as a data-driven investment tool.
Stock markets are complex chaotic systems—governed by chaos theory principles like the butterfly effect, feedback loops, and non-linear dynamics—rather than purely random or fully efficient, allowing for meaningful predictions despite inherent unpredictability and randomness from events like flash crashes. I Know First's self-learning AI algorithm leverages chaos theory insights, artificial neural networks, genetic algorithms, and 15+ years of historical data to identify patterns, forecast trends across over 13,500 markets, and generate daily signals with predictability indicators, enabling traders to gain an edge through disciplined risk management.
Stock markets are chaotic rather than completely random or efficient, featuring sensitivity to initial conditions (butterfly effect), positive/negative feedback loops that drive bubbles and stabilizations, and patterns that emerge over longer horizons despite short-term volatility and randomness (e.g., Flash Crash of May 6, 2010, and Apple's mini crash in 2011).
Common fallacies are debunked: markets aren't 100% unpredictable (as profitable trading exists) nor fully efficient (as anomalies and consistent gains occur at firms like Goldman Sachs).
I Know First's predictive algorithm is empirical and bias-free, analyzing non-linear factor interactions, ranking inputs, building/testing models on extensive historical data, refining daily, and producing forecasts for multiple time horizons (1 to 365 days) with trend signals, confidence levels, and heat-map visualizations (green for bullish, red for bearish).
Successful forecasting requires understanding market "regimes," monitoring predictability waves (low predictability signals instability), and applying strict risk management rules like focusing on strong signals, using non-correlated assets, and accounting for fat-tailed distributions to achieve consistent profits despite uncertainty.
Ultimately, chaos theory is the foundation for demystifying market behavior, and with I Know First's AI-driven approach demonstrating that disciplined, adaptive forecasting and risk control, it can overcome randomness to deliver a reliable trading advantage.
I Know First announced an updated, highly interactive user interface designed to enhance algorithmic trading by supporting user strategies and automating processes through new features accessible to annual subscribers. The article serves as a guide reviewing these enhancements, enabling traders to better utilize the platform's AI-powered forecasts, signals, and tools for more efficient decision-making and execution.
The I Know First R&D team introduced a new highly interactive user interface specifically to support algorithmic trading strategies and automate various processes.
This update includes features aimed at improving usability, such as interactive elements for viewing and applying daily AI-generated market predictions (signals and predictability indicators), heatmaps, and customized forecasts.
The new interface is exclusively available to all annual subscribers, positioning it as a premium enhancement for more advanced, hands-on use of the platform's self-learning algorithm.
The article functions as a practical guide that reviews some of the key new features and provides instructions on how to use them effectively for trading and portfolio management.
The launch of this interactive user interface represents an important step in making I Know First's AI-driven algorithmic forecasting more accessible and practical for subscribers, empowering them to automate and optimize their trading strategies with greater efficiency.
Unveiling The Power of Quant As A Service In Investment Strategies
"Quant as a Service" (QaaS) is a transformative approach that democratizes quantitative investing—previously reserved for hedge funds and institutions—by providing subscription-based access to advanced AI and machine learning algorithms through cloud platforms, enabling individuals and smaller firms to compete effectively. I Know First exemplifies QaaS with its self-learning, chaos-theory-inspired algorithm that forecasts over 13,500 assets across multiple classes, offering daily predictions, predictability indicators, customizable strategies, and proven outperformance in examples like high-return packages and a 576.72% strategy gain from 2020-2023.
Quant as a Service (QaaS) outsources complex quantitative analysis to third-party providers using AI, machine learning, cloud platforms, and APIs, reducing barriers like expertise and cost while delivering scalable, flexible, real-time, data-driven insights for portfolio management and automated/semi-automated/manual trading.
I Know First's QaaS offering features a self-learning algorithm based on chaotic systems, fractals, and neural networks, providing forecasts for stocks, ETFs, commodities, currencies, crypto, and more across six time horizons, with a predictability filter to prioritize reliable signals and holistic market modeling.
Key advantages include lower entry barriers, enhanced efficiency/transparency/security, customization (asset selection, time frames, strategies), accessibility via web/mobile, and two tiers: Tier 1 for daily long/short predictions and Tier 2 for tailored systematic strategies.
Performance examples highlight effectiveness, such as an S&P 500 package achieving 11.55% average return (vs. S&P 500's 0.69%) in a 7-day forecast with 9/10 correct predictions, a home builders package at 4.36% (vs. 1.54%), and the "Best Industries Strategy" delivering 576.72% cumulative returns from 2020-2023 (outperforming S&P 500 by 529.71%).
QaaS—and specifically I Know First's AI-driven platform—is the future of investing, empowering a wider range of users with institutional-grade tools to gain a competitive edge through objective, adaptive, and high-performing quantitative strategies.
Three consecutive weeks of losses for the S&P 500. The first such streak in nearly a year.
The Dow slid 2%. The Nasdaq fell 1.3%. The S&P shed 1.6%. Portfolios are bleeding.
Let me take you back to February 24th.
Oil was trading at $66 per barrel. The Iran situation was simmering but not yet boiling. Energy stocks were quiet. Nobody on Wall Street was pounding the table on crude. It was, by all appearances, an unremarkable week for commodities.
But the I Know First ai algorithm wasn't looking at appearances. It was looking at data -oil futures positioning, shipping anomalies, correlated asset stress signals, geopolitical pattern correlations built from decades of historical precedent. And on February 24th, it flagged something: USO (the oil ETF) and oil futures contracts were showing bullish signal strength on top of the entire commodities table.
Then, on March 5th -with oil having moved to around $74 -we held our live webinar and we told every subscriber watching to focus on the energy sector. We walked through the energy packages live on screen. We explained why the signals were strengthening, not weakening. We named the packages to watch.
Today, as I write this letter, crude oil is above $100 per barrel.
That is a 51% move from our first signal on February 24th. A 35% move from our March 5th webinar recommendation. Both called publicly, on record, before the Iran conflict fully erupted and before a single mainstream analyst had oil in their top ideas.
This is not a coincidence. This is what happens when a self-learning algorithm processes thousands of simultaneous signals - supply chain stress, futures curve behavior, geopolitical correlation data - faster and more completely than any human team ever could. It doesn't read the news. It reads the data that precedes the news.
The energy rally continued on Friday. The signals are still active:
With oil above $100 and the Strait of Hormuz situation far from resolved, the question isn't whether you missed the first leg of this move. The question is whether you're positioned for what comes next.
While the Market Lost 1.6%, Our Algorithm Found +57%
Now let me show you what was happening everywhere else while energy was surging.
Because here's the thing about a down market - it doesn't mean everything goes down. It means the average goes down. And the entire purpose of a self-learning forecasting system is to find the names that aren't average.
This week, while the S&P 500 shed 1.6%, our implied volatility deep learning package delivered an overall return of +6.82% - a market premium of +8.42 percentage points in the same period.
The standout was HIMS, which exploded +57.37% in just 7 days. Not a typo. Fifty-seven percent. In one week. In a down market. AMPX and VRT added +9.92% and +7.07% respectively, with 6 out of 10 picks moving exactly as the algorithm predicted.
When the market falls 1.6% and your package returns +6.82%, you're not just outperforming. You're moving in a fundamentally different universe from the benchmark.
The Weapon Most Investors Forget They Have
I want to talk about something that I believe is one of the most underutilized capabilities we offer - and in a three-week losing streak, it has never been more relevant.
Short selling.
Most investors are wired to think in one direction: find good companies, buy them, wait. It's a fine strategy in bull markets. But we are not in a bull market right now. And the investors who are only thinking long are leaving an enormous amount of opportunity on the table - opportunity that our algorithm identifies with the same precision it applies to its long picks.
Think about what short selling actually means in practical terms: when you correctly identify a stock that is about to fall, down becomes up. The market's worst weeks become your best weeks. The panic that's destroying other portfolios is generating returns in yours.
Our self-learning algorithm identified a set of stocks positioned to decline - and 8 out of 10 moved exactly as predicted in just 3 days:
FWRD collapsed 28.31% in 3 days - a monumental move that short sellers captured entirely
HUBG fell 10.21%
SAIA declined 9.84%
The package delivered an overall average return of +7.3%
That's a +9.50% premium over the S&P 500's -2.2% return in the same period
Read that again. The market fell 2.2%. Our short-sell package returned +7.3%. An almost 10 percentage point swing - in three days - generated not despite the market falling but because our algorithm correctly identified which specific stocks would lead the decline.
This is what complete, directionally agnostic investing looks like. Not "is the market going up or down? but "where is the highest-conviction move - in either direction - and how do I position for it?"
In a three-week losing streak, the most sophisticated question you can ask isn't "when will it recover?" It's "what should I be short right now?
This Week’s Most Impressive Forecasts Across various sectors, our algorithms continue to generate "Alpha" where traditional methods fail:
196% in one year. From a pattern recognition system that started quietly flagging oil at $66 while the rest of the market was looking the other way.
The Only Two Decisions That Matter Right Now
The S&P 500 is in a three-week losing streak. Oil is above $100. Geopolitical risk is elevated and unresolved. The investors who navigate the next few weeks successfully will be the ones with tools that work in both directions - finding longs that rise against the tide, shorts that fall faster than the market, and energy positions that the algorithm was flagging when crude was still at $66.
Here is how to make sure you are one of them:
Daily AI Forecasts (6 Time Frames): Actionable stock picks every day. → View All Pricing Plans
The AI-Powered Monthly Portfolio: Our latest rebalancing happened this past Wednesday, and the AI is already outperforming! → Enroll in the Monthly Portfolio
The algorithm saw oil at $66. It saw $74. It's watching $100 right now and it's already generating the next signal.
The only question is whether you'll be reading it.
Warm regards, Yaron Golgher CEO, I Know First
I Know First Most Popular Package Of The Week
Top 10 Stocks Forecast Package
Includes daily forecasts for:
Top Energy Stock Forecast for long and short positions.
6 time ranges: 3 days, 7 days, 14 days, 1 month, 3 months and 1 year
Investment universe: Energy Sector
Check some recent forecasts' performances: 7 Days, and 1 Year!
Apple has reportedly scrapped plans for a clamshell-style foldable iPhone due to persistent design challenges, such as a central seam limiting internal space for components like batteries and cameras, opting instead for a more conventional reduced-size foldable model, according to MacRumors reports from March 10, 2026. Meanwhile, Apple significantly ramped up iPhone production in India by 53% in 2025 to 55 million units—representing one in four iPhones globally—to mitigate risks from US-China trade tensions and tariffs, with all iPhone 17 models now being manufactured there (MacRumors, March 10, 2026). Additionally, the budget-oriented iPhone 18e has reportedly completed development, featuring an A20 chip and potentially a Dynamic Island display, with an expected spring 2027 launch alongside the standard iPhone 18 series and iPhone Air 2 (MacRumors, March 9, 2026).
