When to Buy & Sell Stocks?
Goldman Sachs & Citi project 12-month asset price targets for institutions
We automatically project, test & analyze 1-week/4-week/12-month price targets
See posts at PNN Asset Price Targets from PNN™ Terminal (in PROD)
PNN Terminal, an agentic investment innovation, helps allocators elevate alpha
PNN™ starts a paradigm shift to financial science of high fidelity predictions
PNN™ = High Fidelity (80-96%) Projections | Subscribe to PNN Production Output
AutoScore precisions of options-based projection lines using automated unbiased t-tests & charts (New Gold Standard of Stock Predictive Analytics)
Stock Resilience & Alpha
Generate YesRatio = ƒ(SharpeRatio, ResilienceMetric) to improve alpha with VUSS (validated uptrend steep smooth) projection lines (Innovation of Investment)
Agentic AI Integration
Generate Buffett & Munger agentic joint advice by RAG multi-agents collaboration with self-hosted LLMs on CUDA GPU (Innovation of Investment Engineering)
(SPY actuals match projections; validated by automated t-test; on CPMA bus)
We deliver concrete benefits (HF reference) to institutional allocators & CEOs, among them
Premium subscribers request projections of on-demand assets from PNN High Fidelity Projections. 4-week projection tables catch breakout stocks for actively-managed portfolios
Projection Bus Change can start a paradigm shift for investment research & practice: from backward finance to forward finance (financial science of high fidelity predictions)
Elevate Portfolio Performance: Leverage quantitative Weekly Return Projection table (catch breakout stocks) and VUSS lines for actively-managed portfolios to outperform market.
Improve Risk Management: Leverage qualitative joint advice of Buffett & Munger multi-agents using projection datasets. Forecast market corrections with PNN charts & precision metrics.
Improve Investment & Risk Strategies: Implement 'Buy the Dip'/'Do Nothing' strategies & manage fear/panic due to market correction, using V/IV-shape projection lines.
For CEOs – Capital Decision Timing: Elevate market cap through timely capital decisions (buyback, partnership, CEO capital agents) guided by the projection line of your stock.
Projection & YesRatio help manage fear & panic due to market dip (black swan/tariff shock)
Athena read, write, listen, speak, see, watch models & agents are building blocks of CEO agents, capital agents, growth agents, operation agents, and agent-to-agent collaboration for accelerating enterprise AI adoption.
Key Features of AgenticOS™
Scalable Cloud Deployment
Fast deployment with efficient scaling. Sizable use cases.
Custom LLM Creation
Tailored large language models with proprietary data. Agentic RAG & LLM API.
Base for PNN Products
Provide self-hosted LLMs for agentic products of PNN Capital
First-principle Question 1: When is the right time to buy and sell stocks? Use PNN Terminal's future-dated projection lines (incrementally validated) to gain crucial insight.
2: How to implement Agentic RAG AI for my project? Launch Athena AI platform from AWS Athena, then use PNN Terminal as the example to design and develop your target state.
Products on AgenticOS™
PNN Terminal
AgenticOS™ Investment Analytics (AIA) of asset allocation for investors & funds
Athena MAAC
AgenticOS™ collaborations displace ~25% human meetings by text & voice agents
1. PNN Terminal for Alpha Elevation. Implementation of USPTO # 19/245,322. Reference: Bloomberg Terminal
First Principle Problem: When is the right time to buy and sell stocks? Precise market timing is very hard but not impossible. Only a cadre of sophisticated asset managers may succeed at market timing; most retail investors and many fund managers are better off using timing-removed passive strategies (GPT/Gemini LLMs 2025)
Innovative Solutions to Improve Alpha: PNN Terminal's Future-dated Projections by Options Sentiment, YesRatio, Behavioral Investment Experiments, Agentic AI Integration, Agentic Technical Indicators (Ye 2011 2025, Black-Scholes 1997)
Asset Pricing Theories for Asset Allocation: paradigm shift from traditional asset pricing theories (Sharpe 1990) to options-based asset pricing & projection (Ye 2011 2025). The traditional asset pricing theories cannot solve the market timing problem because they have missed options data, technical indicators, and agentic AI integration.
Technical Indicators: provide high-level trend directions; PNN Terminal generates specific future-dated price points and projection lines.
Patent (Ye 2025): Implementation of USPTO # 19/245,322: System and Method for Agentic Investment Analysis Using Options Sentiment and Resilience Metrics
Stock Resilience: YesRatio = ƒ(SharpeRatio, ResilienceMetric) to improve stock picking.
Validity: PNN Terminal's future-dated projection lines & algos are incrementally validated with live automated unbiased back & forward tests.
How to Choose a Projection Line? Use CCA projection line if actuals self-validate CCA projections by live t-tests & charts. Corroborate with asset trends by TIs.
Get Evidence for Precise Projection Lines: projected/actual t-test results are generated automatically and incrementally (daily), accessible at a tab of PNN Terminal (Ye 2025).
Alpha strategy by PNN Terminal: pick asset based on validated projection line - uptrend steeper smooth | higer return lower beta (Ye 2025, Carhart 1997 momentum, Shiller 2013)
Beta strategy by PNN Terminal: pick asset based on validated projection line - less fluctuation | less covariance (Ye 2025)
Buy the V-shape Dip: projection line shows V-shape with future-dated higher prices after the dip
Reallocate Assets: switch flat or downtrend projection lines to VUSS projection lines
Improved CCA algo: Projection line of CCA algo is significantly closer to actuals than projection lines of the algos of USPTO#19/245,322
CPMA algo/projection line: Among 4 future-dated projection lines, the CPMA line is the closest to the actual prices based on the CPMA t-test means and p-value
LLM training on CUDA GPU: Tuning a new LLM on CUDA GPU for Buffett & Munger AI Agents of PNN Terminal with the 4th generation of LLM training and fine-tuning technology
2. AgenticOS™ Collaboration by Text and Voice Agents - USPTO # 19/216,814: System and method for AI agent-based meeting simulation and collaboration
3. AgenticOS™ LLM Security Posture - USPTO # 19/218,399: Cloud Large Language Model Security Posture Assessment System and Method
4. AgenticOS™ video understanding for Physical AI & 6G Edge AI - USPTO # 63/780,599: System and method for video large language model (LLM) agentic collaboration
"DroneAgent, what do you see?"
"DogAgent, send a human agent."
5. Athena AgenticOS™ for Elevating Market Cap - Implementation of USPTO # 19/321,197: System and Method for Elevating Corporate Market Capitalization Using an Agentic AI Framework on a Custom-tuned Large Language Model
1) Athena Read - Web-based LLM Customization (Pretraining & Finetuning) for Brands Digital Brains
2) Athena Speak - Text & Voice Agentic RAG Collaboration
3) Athena Listen - Automatic Speech Recognition (ASR) on Nvidia Nemo Audio-to-Text Model (AI Scribe adopted - Hopkins Medicine/Hospital)
The first practical implementation of Nvidia Nemo ASR model: Athena AI Audio Transcription for Enterprise AI Adoption
4) Athena See - OCR Image-to-Text Model
5) Athena Watch - Video Understanding Model (Hopkins hospital surgery room use case; DoD use case)
