Executive Summary
In an unprecedented experiment, TheDayAfterAI News tasked six of the world's leading AI chatbots with the same challenge: predict Netflix's stock price movement for the five trading days spanning January 21-27, 2026. Following Netflix's Q4 2025 earnings release on January 20, which beat expectations but offered muted guidance, combined with the dramatic news of its $82.7 billion all-cash bid for Warner Bros. Discovery, NFLX shares plummeted over 6% in after-hours trading.
We provided identical market data, technical indicators, fundamental analysis, and macroeconomic context to ChatGPT, Claude, Gemini, Grok, Perplexity, and Copilot. The results reveal fascinating divergences in how different AI models interpret the same financial data and arrive at markedly different conclusions.
The Context: A Perfect Storm of Uncertainty
Netflix closed at $87.26 on January 20, 2026, before releasing Q4 earnings that exceeded analyst expectations with EPS of $0.56 (vs. $0.55 expected) and revenue of $12.05 billion. However, the market's reaction was decidedly negative, driven by several factors:
- 2026 guidance of 12-14% revenue growth fell short of the 16% 'whisper number'
- The revised all-cash $82.7 billion Warner Bros. Discovery acquisition raised leverage concerns
- Share buybacks were suspended to preserve liquidity for the deal
- Geopolitical tensions (Trump's Greenland tariff rhetoric at Davos) added macro uncertainty
- Technical indicators showed extreme oversold conditions (RSI below 25)
Head-to-Head Predictions Comparison
| AI Model | Open (Jan 21) | Close (Jan 27) | Price Range | Direction | Probability Up |
|---|---|---|---|---|---|
| Grok | $82.50 | $85.00 | $80 - $90 | BULLISH | 60% |
| Gemini | $81.25 | $83.40 | $78.50 - $85 | BEARISH | 8% (vs Jan 20) |
| Perplexity | $83 - $84.50 | $88 - $90 | $81.50 - $94 | BULLISH | 62-68% |
| ChatGPT | $82 - $84 | $84.00 | $78 - $88 | BULLISH | 55% |
| Claude | $82.50 - $84 | $79 - $86 | $77 - $89 | BEARISH | 45% |
| Copilot | $83.00 | $86.50 | $80 - $90 | BULLISH | 60% |
| Average | $82.79 | $85.15 | $79.1 - $89.33 | BULLISH | 57% |
Individual AI Analysis Breakdown
Grok (xAI)
Stance: Moderately Bullish
Grok's analysis emphasized the extreme oversold technical conditions, citing an RSI of 14.88 and Stochastic at 3.29 as historically reliable bounce indicators. The model acknowledged the WBD deal uncertainty and weaker 2026 guidance but weighted technical factors more heavily, predicting a modest rebound from $82.50 to $85.00.
Gemini (Google)
Stance: Strongly Bearish
Gemini delivered the most bearish assessment with an explicit 'UNDERPERFORM / SELL' rating and 92% probability of a net price decrease versus the January 20 close. The model produced a comprehensive 13-page equity research report emphasizing the structural transformation of Netflix from a growth stock to a leveraged media conglomerate. Gemini highlighted the 'death cross' technical pattern and potential negative gamma squeeze dynamics.
Perplexity AI
Stance: Moderately Bullish
Perplexity provided the most optimistic closing price target of $88-$90, representing a 5-8% recovery from the predicted open. The analysis heavily weighted the historical mean-reversion behavior when RSI drops below 25, assigning a 45% probability to an 'Oversold Relief Bounce' scenario. Perplexity's 17-page report emphasized that institutional investors still own over 80% of shares, suggesting a potential floor.
ChatGPT (OpenAI)
Stance: Cautiously Bullish
ChatGPT took a measured approach, projecting a relatively flat outcome with the closing price matching or slightly exceeding the opening price. The model provided day-by-day estimates anticipating initial weakness followed by gradual stabilization, assigning a modest 55% probability to an upward move.
Claude (Anthropic)
Stance: Moderately Bearish
Claude was one of only two models to predict a net decline, assigning a 55% probability of price decrease. The analysis emphasized the binary risk profile created by WBD deal uncertainty and noted significant insider selling ($171 million over 90 days) as a concerning signal. Claude provided the widest potential price range ($77-$89), reflecting high uncertainty.
Copilot (Microsoft)
Stance: Moderately Bullish
Copilot delivered the most streamlined analysis, predicting a net gain from $83 to $86.50 with 60% confidence. The model focused on the technical setup and options positioning, noting that the expected move implied by options markets (±$6.35) suggested high volatility but not necessarily continued downside.
Key Observations and Divergences
Opening Price Consensus
All six models converged remarkably on the predicted opening price, clustering between $81.25 and $84. This consensus reflects the clear premarket signals available at the time of analysis.
Closing Price Divergence
The closing price predictions showed significant divergence: Perplexity's bullish $88-$90 target stands $5-$7 above Gemini's bearish $83.40 forecast. This 7-8% spread highlights how differently the models weigh technical bounce potential versus fundamental headwinds.
Technical vs. Fundamental Weighting
The bullish models (Grok, Perplexity, Copilot) emphasized oversold technical indicators and historical mean-reversion patterns. The bearish models (Gemini, Claude) focused more heavily on fundamental concerns: leverage, valuation compression, integration risk, and insider selling signals.
Statistical Summary
| Metric | Value |
|---|---|
| Average Predicted Open | $82.46 |
| Average Predicted Close | $84.88 |
| Average Expected Move | +2.9% |
| Models Predicting Increase | 4 of 6 (67%) |
| Models Predicting Decrease | 2 of 6 (33%) |
| Widest Price Range Forecast | $77 - $94 (Claude/Perplexity) |
Conclusion
This experiment reveals that even when provided identical information, leading AI models can reach substantially different conclusions about short-term stock price movements. The majority consensus (4 of 6 models) leans bullish, primarily driven by the compelling technical oversold setup. However, the two bearish outliers (Gemini and Claude) raise valid concerns about fundamental headwinds that could override technical signals.
The divergence underscores an important truth about financial markets: reasonable analysts can look at the same data and reach different conclusions. AI models, trained on different datasets and with different architectural designs, exhibit this same characteristic. Investors should view these predictions as one input among many rather than definitive guidance.
Methodology
Each AI chatbot was given an identical prompt requesting a five-day stock price forecast. The models used their own web-search and data-retrieval capabilities; no proprietary data was provided. Responses were collected without modification. Variations in depth, format, and analytical approach reflect each platform's native capabilities.
