Overview
Markets entering the late spring rally have shown a pronounced tilt toward firms capturing AI-related spending and the underlying infrastructure that supports cloud, communications and analytics. Throughout May, a range of companies spanning regional airlines, satellite communications and enterprise software recorded meaningful jumps in share price after reporting stronger results or clearer growth paths tied to AI adoption and infrastructure demand.
Notable movers and what drove them
Several names stood out for their May performance and the operational or strategic developments cited by investors as reasons for the rallies:
- Republic Airways Holdings (RJET) - The regional carrier logged a more than 35% surge in May, driven by a reported 34% jump in quarterly revenue and management’s decision to reaffirm full-year guidance above $2 billion. Market participants highlighted the integration of Mesa Air, the expanding Embraer fleet and improving operational metrics as supportive of longer-term revenue capacity. Since the point at which certain AI-driven models first flagged the stock, shares have moved up +41.70%.
- Iridium Communications (IRDM) - Shares climbed sharply after Iridium announced plans to acquire the remaining 61% of Aireon. Management and investors flagged the transaction as expected to add more than $100 million in annual service revenue and over $30 million in annual OEBITDA, while long-term contracts extending through 2035 were cited as strengthening the company’s footprint in aircraft surveillance and aviation analytics. The stock was up +27.18% in May alone.
- Fair Isaac (FICO) - FICO’s stock advanced steadily after reporting a 39% increase in quarterly revenue to $692 million and boosting full-year revenue guidance to $2.45 billion, following strong demand for analytics and decisioning software. Shares rose +21.67% in May alone.
- Teradata (TDC) - Teradata reported $0.88 in earnings per share versus $0.69 expected on $444 million in revenue, and investors rewarded the company for positioning to benefit from rising enterprise AI and cloud spending. The share price gained +19.24% in May alone.
Each of these moves reflected a combination of reported results, management guidance and investor appetite for companies positioned to supply the software, connectivity and analytics layers required by enterprise AI deployments.
Why the regional airline moved so much
Republic Airways’ rally illustrated how improving operating metrics, balance-sheet repair and long-term contract structure can change the investment case for a transportation operator. Key data points that helped support the stock’s momentum included:
- Trading below book value even as fundamentals and operational efficiency improved.
- Acceleration in EBITDA driven by integration of Mesa Air Group, which expanded the carrier’s Embraer fleet and long-term revenue capacity.
- Multi-year agreements with major network carriers that provide an unusually stable cash-flow profile relative to many transportation peers.
- Balance-sheet improvements and stated debt-reduction targets that increased investor confidence as capital rotated into economically sensitive growth areas.
Those elements combined to sharpen the narrative that the company could sustain improved cash generation and structurally better margins as fleet integration advanced.
Iridium’s transaction and its implications
Iridium’s decision to secure the remaining Aireon stake represented a concrete step toward expanding recurring service revenue and OEBITDA at levels management signaled were meaningful to the business’s long-term profile. The announced expectations - more than $100 million in added annual service revenue and over $30 million in additional annual OEBITDA - created a clearer line of sight for investors viewing Iridium as more than a satellite provider, but as a provider of aviation surveillance and analytics underpinned by long-term contracts through 2035.
Enterprise analytics winners
Demand for analytics and decisioning platforms was a common thread behind rallies in FICO and Teradata. Both companies delivered results that reinforced investor confidence in structural demand for enterprise AI and cloud projects:
- FICO: Revenue growth of 39% quarter-over-quarter to $692 million and a raised full-year revenue guide to $2.45 billion pointed to durable demand for analytics-driven decisioning tools.
- Teradata: A beat on EPS - $0.88 versus $0.69 expected - on $444 million in revenue underscored the firm’s exposure to the enterprise AI and cloud-budget cycle.
Investors appeared to be rewarding both companies for translating near-term AI spending into tangible revenue and margin outcomes.
A case study in model-driven trading: ViaSat
ViaSat (VSAT) offered a useful example of how quantitative models and rebalance discipline can capture multi-stage gains while managing valuation risk. The models consistently rotated into and out of ViaSat as earnings expectations, valuation and market momentum evolved. The timeline presented by market observers and model summaries included these phases:
- Initial model entry when the stock traded at roughly 0.48x book value, with revenue topping expectations at $1.15 billion and EBITDA growth accelerating roughly 23% - the position later produced a move of more than 95%.
- Subsequent removal after a roughly -9.37% pullback following a sharp run, with the stock having surged more than 230% over three months and moving beyond many fair-value estimates.
- Re-entry in October after another earnings beat that reported $1.17 billion in revenue and positive free cash flow of about $60 million, alongside accelerated defense backlog growth of 49% year-over-year and potential settlement upside of $568 million tied to Ligado - this preceded another +35.81% advance.
- Final exit after the stock had climbed more than 312% over a one-year period, delivering cumulative gains exceeding 164% before models rotated out again as valuation stretched and profitability metrics - including negative earnings and slim operating margins alongside roughly $7 billion in debt - continued to present longer-term risks.
The ViaSat example emphasized portfolio discipline: models trimmed or removed the position when valuation risk outweighed incremental upside despite improving demand for satellite infrastructure.
How the selection process works
The underlying quantitative process that identified these opportunities applies a repeatable monthly evaluation across thousands of global equities. The system uses more than 15 years of financial history and leverages in excess of 150 quantitative models to assess valuation signals, historical performance and forward-looking growth metrics. From that universe, the methodology can identify up to 20 high-conviction names per strategy, then apply an equal-weighting scheme across selected stocks to maintain a transparent benchmark for model performance.
Each monthly rebalance purposefully adds new opportunities, retains strong performers and removes positions that no longer meet momentum, valuation or performance thresholds. The goal is to keep capital positioned in firms showing the strongest combination of upside potential, valuation appeal and momentum tied to structural demand drivers like AI infrastructure and enterprise analytics.
What to watch going into the next rebalance
With May behind us and the next monthly rebalance imminent, attention has shifted to the fresh set of names that models may rotate into as earnings season delivers new information. Investors monitoring these AI-selected portfolios will be watching for: persistent revenue and EBITDA acceleration, credible free cash flow generation, and contractual or structural revenue visibility that reduces cyclicality risk.
As demonstrated by the Republic and Iridium examples, balance-sheet improvement and long-dated contractual revenue streams can materially alter the risk-reward calculus for investors in sectors typically viewed as cyclically sensitive.
Bottom line
May’s strongest movers were concentrated among companies tied to the infrastructure and analytics layers that underpin enterprise AI adoption. The rallying names delivered better-than-expected results, clearer guidance or strategically meaningful transactions that created a more predictable cash-flow outlook. Quantitative models that systematically evaluate valuation, momentum and operational metrics played a central role in identifying these opportunities and refining portfolio exposure as conditions changed.
Investors should continue to monitor earnings momentum, valuation dispersion and any changes in long-term contract structures that affect cash-flow visibility when assessing companies that claim exposure to AI-driven demand.