@CapitalismUSA @Theverypatientone In terms of EV for LNP $ABUS will get about 35%-40% and $ROIV 65%-60%. $140B * .12*.35 = $6B at the very minimum and as high as mid to high teens if $MRNS, $BNTX, $PFE dare to gamble and go to trail.
#SPMNOTES
EXAMPLES OF G-101 SPM AI's STOCK PICKS
As of January 2026, the G-101 SPM AI algorithm, co-authored by Christopher Netelkos at Northridge Company, has documented a certified history of 3,097 stock picks since its inception in March 2023.
The following are documented examples of stocks selected by the algorithm and their subsequent performance:
Documented Winners (Historical to 2026)
According to performance audits and strategy reports published in January 2026, the AI identified several major individual winners before significant rallies:
Thyssenkrupp (ETR: TKAG): Gained +223% after being selected by the AI.
Super Micro Computer (NASDAQ: $SMCI): Achieved a +185.8% return while active in the AI's strategy.
ABL Bio Inc (KQ: 298380): Increased by +170.30% following its selection.
ViaSat Inc (NASDAQ: $VSAT): Saw a +163% rise after being picked.
Colab Cloud Platforms (BO: COLA): Gained +111.80%.
Banco Santander (NYSE: SAN): Achieved a +104.45% return.
Nvidia (NASDAQ: $NVDA): Recorded a +226.7% gain while held within the AI strategy.
Specific Case Study: Marinus Pharmaceuticals ($MRNS)
A notable 2024–2025 case study from Christopher Netelkos’s "SPM Notes" highlights the algorithm's timing:
The AI issued a bid at $1.50.
The position was exited on January 29, 2024, at $10.26 after the "SPM tag" dropped, representing a substantial gain before the subsequent stock decline.
Current Strategy Performance (January 2026)
As of early January 2026, the AI's "Top Value" strategy has reportedly delivered an 83.20% return, outperforming its benchmark by 33.85%. The algorithm continues to process information from 145 unstructured data sources to identify "smart" data trends that prioritize non-human intervention over traditional conventional analytics.
