Recap
Hey guys! If you’re new here, I am running a 6 month long experiment to see if a Large Language Model (like ChatGPT) can be a skilled micro-cap portfolio manager. I give it daily closing data at the end of every trading day and it has full control over its assets. Also, once every week it gets to use Deep Research to completely reevaluate it’s account. Can ChatGPT carve consistent alpha in the dangerous world of micro-cap stocks? Lets find out.
Overview
ChatGPT’s definitely experienced a challenging week, marked by several setbacks and operational adjustments. Early in the week, the model had misinterpreted the cash balance, initially assuming the portfolio had $18 before the sale of MBOT rather than after. Once corrected, instead of adjusting its trades, ChatGPT chose to cancel the planned PRSO position entirely.
By Thursday, both remaining holdings hit their stop-loss levels and were sold, leaving the portfolio fully in cash with no active stock positions.
As of the latest update, the portfolio value stands at $67.10, representing a -32.9% decline from the starting value, a new low for the experiment.
Performance Graph
Max Drawdown: -50.33% on 2025-11-06
Sharpe Ratio (period): -0.7900
Sharpe Ratio (annualized): -1.1328
Sortino Ratio (period): -0.8739
Sortino Ratio (annualized): -1.2531
[ CAPM vs Benchmarks ]
Beta (daily) vs ^GSPC: 1.1890
Alpha (annualized) vs ^GSPC: -68.34%
R² (fit quality): 0.024 Obs: 91
Note: Short sample and/or low R² — alpha/beta may be unstable.
[ Snapshot ]
Latest ChatGPT Equity: $ 67.10
$100.0 in S&P 500 (same window): $ 108.44
Cash Balance: $ 67.10
Current Portfolio
(nothing..)
Portfolio Review
To see the full report: Click Here
Thesis Review Summary
Overview
The portfolio consists of three high-conviction, catalyst-driven biotech positions — each designed to balance risk, reward, and diversification across regulatory, clinical, and commercial catalysts.
The goal: close the performance gap vs. the S&P 500 by year-end through asymmetric upside potential.
1. Milestone Pharmaceuticals (MIST) – High-Conviction FDA Approval Play
Thesis:
- Awaiting FDA approval (PDUFA date: Dec 13, 2025) for etripamil (Cardamyst) — a nasal spray for Paroxysmal Supraventricular Tachycardia (PSVT).
- Would be the first-ever at-home treatment for PSVT, reducing ER visits and improving quality of life.
- Previous FDA issues were manufacturing-related, not efficacy/safety. Issues now resolved.
Upside Potential:
- Approval could double the stock (+100% or more) to ~$3–4.
- $75M financing lined up post-approval ensures funding for commercialization.
Risk Management:
- Stop-loss in place to cap downside on unexpected FDA rejection/delay.
- Binary, high-conviction bet — “swing-for-the-fences” catalyst independent of market conditions.
Why We Like It:
- Imminent and definitive catalyst with clear timeline.
- Provides true diversification vs. macro-driven market moves.
2. VistaGen Therapeutics (VTGN) – Binary Clinical Trial Catalyst in CNS
Thesis:
- Lead drug fasedienol (PH94B) is a pherine nasal spray for Social Anxiety Disorder (SAD) — a novel, on-demand therapy.
- Prior Phase 3 failures (2022) were due to placebo effects; new trial (PALISADE-3) redesigned for clearer results using the public speaking challenge test.
- Top-line data expected Q4 2025.
Upside Potential:
- Positive data could double or more the stock (~$8+) and revive the program.
- Potential for partnerships or acquisition by larger pharma.
Downside Risks:
- Failed trial could collapse thesis and valuation (down to cash value).
- Stop-loss in place to mitigate but cannot fully protect from gap-downs.
Why We Like It:
- Independent from MIST and AYTU (diversified risk).
- Strong cash position pre-results, avoiding dilution risk.
- Pure high-upside clinical catalyst with short-term timeline.
3. Aytu BioPharma (AYTU) – Undervalued Commercial Launch with Steady Upside
Thesis:
- Aytu recently launched EXXUA™ (gepirone ER) for Major Depressive Disorder (MDD), approved August 2025.
- First new antidepressant mechanism in decades; does not cause sexual dysfunction, a key differentiator from SSRIs/SNRIs.
- Market cap only ~$20M, despite large addressable market (20M+ MDD patients).
- Recent $16M raise and patent extension (to 2030) strengthen position.
Upside Potential:
- Modest success could lift valuation to $40M+ (stock $4).
- Potential +30–50% move on strong launch milestones.
Risk Management:
- Stop set near $1.60 to limit downside.
- Not binary — product already FDA approved, risk lies in execution and sales ramp.
Why We Like It:
- Provides stability and balance to a catalyst-heavy portfolio.
- Multiple near-term catalysts (launch updates, Nov 13 financials).
- Low float and institutional floor around $1.50 add support.
Portfolio-Level Summary
We have constructed a focused, catalyst-rich portfolio of three positions, each with independent drivers:
- Milestone (MIST): Regulatory catalyst (FDA decision). Binary outcome, very high reward.
- Stop-loss in place; could double on approval.
- VistaGen (VTGN): Clinical catalyst (Phase 3 results). Binary outcome, high reward.
- Provides a second independent “shot on goal.”
- Aytu (AYTU): Commercial catalyst (product launch). Gradual, lower risk, steady upside.
- Adds stability and diversification.
Common Themes:
- All are micro-cap healthcare stocks with near-term catalysts.
- Portfolio designed for asymmetric payoff — controlled downside, large potential upside.
- Timelines align:
- MIST: Mid-December FDA decision
- VTGN: Q4 2025 trial readout
- AYTU: Ongoing launch updates through December
Downside Considerations:
- Stop-losses set to limit catastrophic losses.
- Portfolio can withstand one major failure; AYTU provides cushion.
Upside Scenarios:
- One success (MIST or VTGN) + modest AYTU gain could match or beat the S&P 500.
- Two successes could triple portfolio value (best-case).
Conclusion
This portfolio is optimized for risk-adjusted return in the final stretch.
Three independent catalysts — regulatory (MIST), clinical (VTGN), and commercial (AYTU) — provide multiple chances for strong outperformance.
Each position has clear risk controls, upside drivers, and a defined timeline.
Execution discipline and a bit of luck could yield a strong finish vs. the S&P 500.
This project is purely educational and research-focused. Nothing here should be taken as financial advice. Full disclaimer: Here
GitHub Page and Email:
To see all past deep research reports and summaries: Here
Full chats: Here
Have a question? Check out: Q&A
If you’d like to see the raw logs and full portfolio simulation code: GitHub Page
If you have any suggestions or advice, my Gmail is: [email protected]