Options Income Research

Systematic Premium Selling — Active Research

Exploring AI-driven options strategies to harvest the volatility risk premium — the structural tendency for implied volatility to exceed realized volatility. All strategies use defined-risk structures with predetermined max loss.

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Important Disclaimer

This website is for educational and informational purposes only. Nothing on this site constitutes investment advice, a recommendation, or a solicitation to buy or sell any security. The author is not a registered investment advisor, broker-dealer, or financial planner. All trading involves risk of loss. Past performance does not guarantee future results. Options involve risk and are not suitable for all investors. Please read Characteristics and Risks of Standardized Options before investing. The author may hold positions in securities discussed on this site. Full Risk Disclosure | Terms of Service

Premium Selling on Broad Indices

Defined-risk structures on liquid index options. Strategies adapt to market regime.

AI-Assisted Trade Timing

Claude reasoning models assess market context, risk exposure, and opportunity quality before entry.

Flow and Disclosure Analysis

Congressional filings and institutional flow provide educational context for market environment.

Asymmetric Opportunity Scanning

Unusual options activity surfaces asymmetric risk/reward setups worth researching.

The macro signal layer that informs strategy timing is live, auditable, and statistically validated. Full methodology — including deflated Sharpe, CSCV overfit testing, and per-signal calibration — is published at /methodology.

90d Win Rate

73.2%

216 scored signals · walk-forward validated

Holdout Win Rate

70.2%

Blind out-of-sample · 2021–2025

Permutation p-value

0.002

Highly significant vs random (p<0.01)

Sharpe Ratio

0.30

Return per unit of risk · 30d window

Triple Signal Decision Tree

Earnings growth, credit spreads, and valuation dispersion feed a deterministic decision tree. Walk-forward validated across 23 years of data with no lookahead bias. Outputs BULLISH / CONTRARIAN_BUY / CAUTION with dynamic confidence calibrated from live backtest accuracy.

VIX Regime Classifier

Four volatility regimes drive strategy weighting. Premium income structurally increases during elevated-VIX environments — a pattern visible in the CBOE BuyWrite Index (BXM) going back to 1986.

Flow and Disclosure Layer

Unusual options activity, congressional STOCK Act filings, and institutional positioning provide macro context. Informational only — never signal-overriding.

AI Reasoning Layer

Claude reasoning models synthesize signal outputs, risk exposure, and market context before trade entry. LLM-assisted pre-market assessment and opportunity ranking.

Historical context: The CBOE BuyWrite Index (BXM) tracks a mechanical covered call strategy on the S&P 500 going back to 1986. The pattern across four decades is consistent — outperformance in flat or down markets, underperformance in strong bull runs. This is the expected structure of covered calls: capped upside in exchange for predictable premium income. The research here explores more adaptive variants.

Volatility Risk Premium

The structural gap between implied and realized volatility, and how to systematically harvest it.

Congressional Disclosures

STOCK Act filings analyzed as educational context, not as trading signals.

Insider Activity Patterns

Form 4 filings and 10b5-1 plan analysis for research purposes.

Implied Volatility Rank Rotation

How IV rank shifts across sectors and tickers over time.

AI Pre-Market Assessment

LLM-driven synthesis of overnight news, futures, and market structure.

Execution

Tastytrade

AI

Claude (reasoning and analysis)

Market Data

Unusual Whales

Automation

Python

Alerts

Telegram

Storage

Supabase

Site

Next.js + Vercel

First live trade executed April 10, 2026.

System in active development — building toward full automation. Research continues on strategy selection, risk assessment, and AI-assisted decision making.

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