FDA catalysts are asymmetric bets. I use Monte Carlo simulations, Kelly sizing, and historical approval data to find the ones worth taking—then publish every position, win or lose.
Get the next trade before I post it publicly. No spam, ever.
Continuous monitoring of FDA calendar, clinical trial databases, and regulatory filings. Market cap filters ($400M-$5B), optimal timing windows (45-120 days), and priced-in risk detection.
Monte Carlo simulations modeling stock moves, IV crush, and time decay. Historical FDA approval rates by phase, indication, and designation. Management track record analysis.
Real-time Open Interest tracking with accumulation alerts. Put/call skew analysis, notional significance scoring, and institutional positioning detection.
Constantly Monitoring
The biotech options space is filled with hype, FOMO, and traders who treat FDA catalysts like lottery tickets.
Trading based on "feeling good" about a stock instead of calculated probabilities and expected returns.
All-in bets on one PDUFA date with no consideration of multiple catalysts or time diversification.
Position sizes based on "conviction" rather than mathematical frameworks like Kelly Criterion.
Influencers who only show winners. No accountability, no learning, no real track record.
Sound familiar? There's a better way.
A systematic, quantitative methodology built by an engineer who believes in math over hype. If the math doesn't work, I don't trade.
10,000 Monte Carlo simulations per strike. ENR threshold of 140%+ for new entries. IV crush modeling, time decay curves, and percentile analysis (5th-95th).
Mathematical position sizing: (Win% x Payout - Loss%) / Payout. Half-Kelly for volatility dampening. Tiered sizing: Heavy (>15%), Standard (8-15%), Light (3-8%).
Single binary events for high-conviction PDUFA plays. Multi-catalyst LEAPs for free-rolling when the math aligns. 2-9 month horizons.
54 trades. 29 companies. Every position timestamped and published.
Because hiding losses isn't a strategy—it's a scam.
| Ticker | Position | Entry | Exit | Return | Catalyst |
|---|---|---|---|---|---|
| INSM | Jan $60C | $4.20 | $10.15 | +141% | PDUFA Approval |
| CRNX | Dec $15C | $2.85 | $6.10 | +114% | Phase 2 Data |
| IMVT | Nov $35C | $3.40 | $0.85 | -75% | Phase 3 Miss |
| VKTX | Jan $70C | $5.50 | $9.25 | +68% | Obesity Data |
| VRNA | Dec $10C | $1.20 | $2.75 | +129% | RSV Results |
* All trades timestamped on entry. P&L calculated from actual fills. Losses shown prominently—because that's how you learn and build trust.
This isn't about hitting home runs on every trade. It's about math, diversification, and accepting that losses are part of the game.
When a catalyst misses or the FDA rejects, these options often go to zero. We try to exit for partial recovery when possible, but total loss is a normal outcome. This is expected, not a failure of the system.
The strategy requires diversification across multiple catalysts. No single trade should risk your portfolio. With 10-20 positions, the winners cover the losers and generate net positive returns over time.
A 60% win rate with +150% average winners and -80% average losers still generates strong returns. That's why position sizing and ENR calculations matter more than any single trade.
Options trading requires understanding leverage and position sizing. Our systematic approach aims to put the odds in your favor through disciplined analysis and risk management. As with any investment, only use capital you've allocated for trading.
Here's what I'm holding right now. Real positions, real money, entered January 21, 2026.
This is what members see before I post publicly.
Data refreshes every 30 minutes during market hours
This is the level of detail you get with every trade alert.
Entry price, break even, buy zones, ENR scores, thesis reasoning, risk factors, and CONT scores—all updated in real-time.
Continuation Score—predicting post-catalyst price action
Ever watched a biotech get FDA approval only to see the stock dump 20%? That's "sell the news" in action—and it kills traders who hold through catalysts blindly.
CONT Score predicts whether a stock will continue running after a positive catalyst or get dumped immediately. It factors in what the market has already priced in.
"The approval was priced in" is how traders lose money on winning bets.
Get full access FREE for 6 months while we build our public track record. Lock in lifetime discounts before paid tiers launch.
Then 50% off forever ($39/mo) when paid launches
No credit card required. No spam. Cancel anytime.
What you'll get when paid tiers launch (Founding Members keep full access at 50% off)
Always free on Twitter & Reddit
$79/mo (or $39 for Founders)
I'm an engineer who got tired of watching biotech "gurus" post wins and bury losses. So I built a system that forces accountability—starting with my own.
My background is in systematic thinking: breaking complex problems into quantifiable components, building models, and making decisions based on expected value rather than emotion.
The result: A methodology that calculates expected returns, sizes positions mathematically, and compounds edge over time. Every trade public. Every loss analyzed.
"Most traders treat biotech like a casino. I treat it like an engineering problem. The math doesn't lie, and neither does my track record."
Access 690+ biotech catalysts via REST API. PDUFA dates, Phase 2/3 readouts, FDA designations, and our proprietary CONT scores. Perfect for quant traders, fintech apps, and research platforms.
Starting at $49/month