Investors comparing APLD, CORZ, and WULF are essentially weighing three distinct approaches to the same high-stakes opportunity: delivering the power and physical infrastructure that AI workloads require. This comparison matters most for growth-focused traders and infrastructure investors who accept higher volatility and can evaluate long-term, capital-heavy projects. Each firm has moved quickly in the past year, and their relative results reflect changing views on the staying power of AI data-center demand rather than any single earnings release. I also checked this using Tickeron’s AI Screener to see how the group compares to other infrastructure names.
Applied Digital Corporation designs, builds, and operates data centers aimed at AI, cloud, and HPC workloads. The company has highlighted a repeatable “AI Factory” campus model and added long-term take-or-pay leases with U.S.-based investment-grade hyperscalers at its Polaris Forge and Delta Forge sites. Management has disclosed contracted baseline revenue in the tens of billions of dollars, with further upside if renewal options are exercised. Recent trading has been mixed. The shares have retreated from their 52-week high and sit well below prior peaks amid broader pressure on AI infrastructure equities and notable short interest. Positive developments, such as a joint venture with Soluna Holdings for a wind-powered AI data center in Texas, have been offset by concerns over financing costs and heavy capital spending. Analyst views stay generally positive, yet the stock’s sensitivity to interest rates and project milestones keeps risk elevated. From what I see, execution on those campuses will be the key variable ahead.
Core Scientific, Inc. is shifting from bitcoin mining into high-density colocation services for AI and compute-heavy clients. It is repurposing mining facilities in Texas, Oklahoma, Georgia, and elsewhere into AI-ready sites and has outlined plans for gigawatt-scale power at its Pecos, Texas campus. A partnership with AMD and the acquisition of bitcoin miner Polaris have expanded its customer and capacity options. Performance has tracked the group’s volatility. Revenue rose sharply year-over-year thanks to colocation services, though non-cash impairment charges produced a net loss. Shares climbed earlier in the year before pulling back recently with the wider selloff in AI landlord and neocloud names. Investors are balancing Core Scientific’s growing contracted pipeline against its sizable capital needs, which have been supported in part by senior secured notes and bank facilities.
TeraWulf Inc. develops and runs sustainable, industrial-scale data-center infrastructure and has been converting legacy bitcoin-mining locations into HPC capacity. Its Lake Mariner campus in New York supports a growing list of long-term tenants, including a Google credit-enhanced lease, while a 20-year lease with AI developer Anthropic at the Kentucky campus adds a multi-billion-dollar contracted revenue base. The company has also increased its borrowing capacity via a Morgan Stanley-led revolving credit facility. Recent results have lagged earlier highs, with the stock down substantially over the past month despite improved liquidity and rising HPC lease revenue. Net losses remain wide, driven mainly by non-cash fair-value adjustments and stock-based compensation. Leverage and construction risk continue to concern investors, though management maintains that power, tenants, and financing are secured before scaling builds.
From a business-model perspective, APLD stands out as the most direct AI data-center play given its hosting-oriented background rather than a mining legacy. CORZ and WULF both carry operational bitcoin-mining roots, which shape their cost and revenue profiles as they shift power to HPC tenants. Growth drivers differ as well. Applied Digital’s momentum centers on hyperscaler leases and campus-scale builds, while Core Scientific emphasizes colocation deals with partners such as CoreWeave and AMD. TeraWulf’s visibility rests on credit-enhanced tenants, including Google-backed arrangements and its Anthropic lease. All three face heavy capital expenditure and rising debt; short interest remains elevated, and the stocks stay sensitive to interest rates and the pace of AI deployment. Valuation debates focus on contracted-revenue multiples versus execution and funding risk rather than near-term earnings.
When analyzing volatile names like these, I sometimes turn to Tickeron’s AI Trading Bots to test automated strategies against historical patterns and current conditions. The platform offers a range of bots with different styles, timeframes, and performance records, allowing users to review metrics and see how various approaches might align with sectors such as AI infrastructure. This can provide an additional layer of perspective when weighing execution risks and revenue visibility across multiple tickers.
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Sergey Savastiouk, Ph.D. has a degree in Applied Mathematics from Moscow University and has extensive experience as an entrepreneur, investor, manager, and mathematician. His professional expertise is in applied mathematics, mathematical modeling, system and pattern analysis, and software and hardware system integration. He has served as the CEO of several hi-tech start-up companies and nonprofit organizations, which has given him proven capabilities in business strategy for high-tech start-up companies, market assessment, company formation, team building, product development, marketing, and sales. He has published numerous articles in journals and magazines on related fields. As a retail investor, he spent 15 years developing his proprietary trading and quantitative algorithms (now Tickeron’s A.I.), which brought him significant returns in trading the stock market. His current work and goal in founding Tickeron is to bring professional, sophisticated stock market analysis capabilities to retail investors via an easy-to-use interface.
The RSI Indicator for APLD moved out of oversold territory on October 20, 2026. This could be a sign that the stock is shifting from a downward trend to an upward trend. Traders may want to buy the stock or call options. The A.I.dvisor looked at 25 similar instances when the indicator left oversold territory. In 23 of the 25 cases the stock moved higher. This puts the odds of a move higher at 90%.
The Stochastic Oscillator is in the oversold zone. Keep an eye out for a move up in the foreseeable future.
Following a +8.99% 3-day Advance, the price is estimated to grow further. Considering data from situations where APLD advanced for three days, in 254 of 291 cases, the price rose further within the following month. The odds of a continued upward trend are 87%.
APLD may jump back above the lower band and head toward the middle band. Traders may consider buying the stock or exploring call options.
The Momentum Indicator moved below the 0 level on September 30, 2026. You may want to consider selling the stock, shorting the stock, or exploring put options on APLD as a result. In 79 of 88 cases where the Momentum Indicator fell below 0, the stock fell further within the subsequent month. The odds of a continued downward trend are 90%.
The Moving Average Convergence Divergence Histogram (MACD) for APLD turned negative on September 30, 2026. This could be a sign that the stock is set to turn lower in the coming weeks. Traders may want to sell the stock or buy put options. Tickeron's A.I.dvisor looked at 46 similar instances when the indicator turned negative. In 41 of the 46 cases the stock turned lower in the days that followed. This puts the odds of success at 89%.
APLD moved below its 50-day moving average on September 23, 2026 date and that indicates a change from an upward trend to a downward trend.
Following a 3-day decline, the stock is projected to fall further. Considering past instances where APLD declined for three days, the price rose further in 50 of 62 cases within the following month. The odds of a continued downward trend are 89%.
The Aroon Indicator for APLD entered a downward trend on October 23, 2026. This could indicate a strong downward move is ahead for the stock. Traders may want to consider selling the stock or buying put options.
The Tickeron Valuation Rating of 52 (best 1 - 100 worst) indicates that the company is fair valued in the industry. This rating compares market capitalization estimated by our proprietary formula with the current market capitalization. This rating is based on the following metrics, as compared to industry averages: P/B Ratio (4.274) is normal, around the industry mean (2.658). P/E Ratio (0.000) is within average values for comparable stocks, (16.591). Projected Growth (PEG Ratio) (0.000) is also within normal values, averaging (2.284). Dividend Yield (0.000) settles around the average of (0.119) among similar stocks. P/S Ratio (10.977) is also within normal values, averaging (139.965).
The Tickeron Profit vs. Risk Rating rating for this company is 87 (best 1 - 100 worst), indicating that the returns do not compensate for the risks. APLD’s unstable profits reported over time resulted in significant Drawdowns within these last five years. A stable profit reduces stock drawdown and volatility. The average Profit vs. Risk Rating rating for the industry is 93, placing this stock better than average.
The Tickeron Price Growth Rating for this company is 88 (best 1 - 100 worst), indicating slightly worse than average price growth. APLD’s price grows at a lower rate over the last 12 months as compared to S&P 500 index constituents.
The Tickeron SMR rating for this company is 95 (best 1 - 100 worst), indicating weak sales and an unprofitable business model. SMR (Sales, Margin, Return on Equity) rating is based on comparative analysis of weighted Sales, Income Margin and Return on Equity values compared against S&P 500 index constituents. The weighted SMR value is a proprietary formula developed by Tickeron and represents an overall profitability measure for a stock.
The Tickeron PE Growth Rating for this company is 100 (best 1 - 100 worst), pointing to worse than average earnings growth. The PE Growth rating is based on a comparative analysis of stock PE ratio increase over the last 12 months compared against S&P 500 index constituents.
The average fundamental analysis ratings, where 1 is best and 100 is worst, are as follows
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