Math & Markets: Building & Scaling Algorithmic Trading Strategies

Experiments in building and scaling quantitative & algorithmic trading strategies across a variety of asset classes

Math & Markets is a build-in-public journal — one where I build, test, and scale various quantitative and algorithmic trading strategies.

The ToC below captures my posts, for easy access and readability.

SaaSocalypse Series:

• Part 4: Structuring the SaaS Trading Strategy

• Part 3: Three Value Hypothesis for SaaS

• Part 2: A Quant Framework for SaaS

• Part 1: Anatomy of a Sector Re-Rating

Venezuela Oil Crisis Trading Strategy series:

• Part 4: Decision Framework, OPEC+ Scenarios, and the Operational Playbook

• Part 3: Implementation — Option Structures, Position Sizing, Risk Management

• Part 2: Sector Mapping and the “Chess” Trade Logic

• Part 1: The Event, The Scenarios, and Why This Isn’t About “Oil Up”

Positioning for the AI End-Game:

• Positioning for the AI Endgame (Part 2 - The Strategies)

• Positioning for the AI Endgame (Part 1 - The Setup)

• The Convergence — When AI Meets Blockchain in Financial Markets

The Mathematics of Position Sizing (Kelly Criterion series):

• Part 3: Practical Kelly

• Part 2: When Kelly Goes Wrong

• Part 1: The Kelly Criterion from First Principles

The Volatility Series:

• Part 7: Practical Vol Trading

• Part 6: Building a Volatility Surface

• Part 5: Can Second-Order Greeks Save Your Short Vol Strategy?

• Part 4: The Greeks Deep Dive

• Part 3: Is VIX Term Structure Arbitrage Actually Profitable?

• Part 2: Trading Strategies

• Part 1: Understanding the Fear Gauge

0DTE Strategy Series:

• V3 of the Two-Engine 0DTE Strategy: Monte Carlo Reveals the Edge

• V2 of the Two-Engine 0DTE Strategy: Stress Test Results & Upgrades

• Two-Engine 0DTE Strategy: A Mathematical Risk Model for High-Frequency SPX Premium Selling

Gold & Silver:

• The Sicilian Defense: Silver and the Gold-Silver Ratio

• The Knight’s Outpost: Strategic Gold Allocation

Hidden Markov Models:

• HMM Series, Part 3: Ensemble Regime Detection

• HMM Series, Part 2: Why Backtests Lie About Regime Detection

• HMM Series, Part 1: First-Principles Guide to HMMs

Correlation Series:

• The Correlation Problem, Part 3 — Building Correlation-Aware Hedging

• The Correlation Problem, Part 2 — Detection Lag Problem

• The Correlation Problem, Part 1 — The -0.35 Illusion

Decay Series:

• The Decay Problem, Part 3 — The Math of Adaptation vs. Overfitting

• The Decay Problem, Part 2 — CUSUM, Bayes, and Knowing When to Quit

• The Decay Problem, Part 1 — Half-Lives of Alpha: Why Every Strategy Eventually Dies

Microstructure Edge Series:

• Microstructure Edge, Part 4 — Building the Microstructure Signal Layer: From Theory to 50 Lines of Python

• Microstructure Edge, Part 3 — The Options Tail Wagging the Stock Market Dog: How Dealer Gamma Exposure Moves Prices

• Microstructure Edge, Part 2 — The Open Is a Liar, the Close Is a Stampede: Auction Mechanics Most Traders Ignore

• Microstructure Edge, Part 1 — The Plumbing Beneath the Price: Order Flow, Toxicity, and the Signals Most Traders Ignore

Carry Trade Series:

• Carry Trade, Part 1 — Carry Trade: The Oldest Edge in Finance

• Carry Trade, Part 2 — When the Escalator Becomes an Elevator: Timing Carry Crashes

• Carry Trade, Part 3 — Building a Carry Portfolio That Survives: Diversification, Momentum Hedging, and the V6 Carry Upgrade

Synthetic Replication Series:

• Part 4: Is the Complexity Worth the Sharpe?

• Part 3: The Volatility Surface

• Part 2: Replicating Hedge Fund Strategies

• Part 1: LEGO Bricks of Options: Put-Call Parity

Complete Trading Strategies series:

• Part 94: Synthetic Replication, Part 4: Is the Complexity Worth the Sharpe?

• Part 93: Synthetic Replication, Part 3: The Volatility Surface

• Part 92: Synthetic Replication, Part 2: Replicating Hedge Fund Strategies

• Part 91: Synthetic Replication, Part 1: LEGO Bricks of Options: Put-Call Parity

• Part 90: Carry Trade, Part 3 — Building a Carry Portfolio

• Part 89: Carry Trade, Part 2 — Timing Carry Crashes

• Part 88: Carry Trade, Part 1 — Carry Trade: The Oldest Edge in Finance

• Part 87: Synthetic Markets: Practical Guide to Stochastic Data Generation

• Part 86: Microstructure Edge, Part 4 — Building the Microstructure Signal Layer

• Part 85: Microstructure Edge Series, Part 3 — How Dealer GEX Moves Prices

• Part 84: Microstructure Edge Series, Part 2: Auction Mechanics

• Part 83: Microstructure Edge Series, Part 1: Plumbing Beneath the Price

• Part 82: Decay Series, Part 3 — The Math of Adaptation vs. Overfitting

• Part 81: Decay Series, Part 2 — CUSUM, Bayes, and Knowing When to Quit

• Part 80: Decay Series, Part 1: Half-Lives of Alpha: Why Every Strategy Dies

• Part 79: Dual Allocator V6.3 and V6.4: Recent Experiment Results

• Part 78: SaaS Series, Part 4: Structuring a SaaS Trading Strategy

• Part 77: SaaS Series, Part 3: Three Hypotheses for SaaS Value

• Part 76: SaaS Series, Part 2: A Quant Framework for SaaS

• Part 75: SaaS Series, Part 1: Anatomy of a Sector Re-Rating

• Part 74: The Sicilian Defense: Silver and the Gold-Silver Ratio

• Part 73: The Knight’s Outpost: Strategic Gold Allocation

• Part 72: HMM Series, Part 3: Ensemble Regime Detection

• Part 71: HMM Series, Part 2: Why Backtests Lie About Regime Detection

• Part 70: HMM Series, Part 1: First-Principles Guide to HMMs

• Part 69: The Correlation Problem, Part 3 — Building Correlation-Aware Hedging

• Part 68: The Correlation Problem, Part 2 — Detection Lag Problem

• Part 67: The Correlation Problem, Part 1 — The -0.35 Illusion

• Part 66: Vol Series, Part 7: Practical Vol Trading

• Part 65: Vol Series, Part 6: Building a Volatility Surface

• Part 64: Vol Series, Part 5: Second-Order Greeks & Short Vol Strategy

• Part 63: Vol Series, Part 4: Greeks Deep Dive

• Part 62: Vol Series, Part 3: Is VIX Term Structure Arbitrage Profitable?

• Part 61: Vol Series, Part 2: Trading Strategies

• Part 60: Vol Series, Part 1: Understanding the Fear Gauge

• Part 59: V6.1: Refining the Dual Allocator with Better Data and a TLT Guardrail

• Part 58: V3 of the Two-Engine 0DTE Strategy: Monte Carlo Reveals the Edge

• Part 57: V2 of the Two-Engine 0DTE Strategy: Stress Test Results & Upgrades

• Part 56: Evaluating 10 Tactical Options Strategies vs. My Asymmetric Framework

• Part 55: Deconstructing Buffett: The Trading Mechanics of Berkshire Hathaway

• Part 54: Building a Market Regime Analyzer

• Part 53: Stress-Testing V6 with Synthetic Markets (Part 2: Results & Failures)

• Part 52: Stress Testing V6 with Synthetic Markets (Part 1: Stochastic Model)

• Part 51: Documenting 7 Asymmetric Return Strategies

• Part 50: Building a Smarter Hedge: Why Delta Alone Isn’t Enough

• Part 49: Does Lower Delta Mean Lower EV? Retail’s Effect on Options Pricing

• Part 48: Optimizing V6: Trust the Backtest, Verify the Validation

• Part 47: Can FRED Data Predict Markets? Testing 11 Equity & Bond Strategies

• Part 46: The Mathematics of Position Sizing 3/3 (Practical Kelly Criterion)

• Part 45: The Mathematics of Position Sizing 2/3 (When Kelly Criterion Fails)

• Part 44: The Mathematics of Position Sizing 1/3 (Intro to Kelly Criterion)

• Part 43: The Recession Anxiety Index, Extended

• Part 42: Satellite Port Monitoring: 48 Global Ports & Time Series Data

• Part 41: Satellite Data for Port Monitoring: 32 Global Ports

• Part 40: When Millions of People Google “File Unemployment”

• Part 39: Adding Options to V6 to Help Push Dual Allocator Sharpe > 1.0

• Part 38: Building a Put Credit Scanner

• Part 37: Why Buy-and-Hold Outperformed Every Options Strategy (2020–2025)

• Part 36: Two-Engine 0DTE Strategy: High-Frequency SPX Premium Selling

• Part 35: Testing a Macro Sleeve Strategy: Take Two

• Part 34: Preparing for COVID-esque Volatility Regime Changes

• Part 33: My First Crypto Trading Strategy: A Study in Overfitting

• Part 32: Dual Allocator V6: Rebuilding After the Lookahead Bias Massacre

• Part 31: Lookahead Bias: From 3 Strategies Down to 1

• Part 30: Machine Learning to Improve Two-Factor Dual Allocator

• Part 29: Testing End-of-Day Execution Filtering

• Part 28: Adding a Volatility Gate to My New Dual Allocator Strategy

• Part 27: Revisiting the Dual Allocator Strategy with Claude

• Part 26: Why Market Making Beat Momentum Trading (H/MFT Strategy)

• Part 25: Testing the Forecast-to-Fill Model on Gold Futures (arXiv 2511.08571)

• Part 24: Should I Add an Options Hedge? (Short Answer: Not Yet)

• Part 23: End In Sight: Separating Signal from Noise

• Part 22: Using SHAP to Improve the Dual Allocator and Volatility Sleeve

• Part 21: A New SPY/VIX Long-or-Cash Model (w/ Synthetic Regimes)

• Part 20: Testing the Hybrid Ensemble as an Overlay

• Part 19: Retraining the Hybrid Ensemble on Synthetic Regimes

• Part 18: Building Synthetic SPY: Fake Data to Test Real Strategies

• Part 17: Testing a Hybrid ML Ensemble (arXiv 2510.22348)

• Part 16: Five Strategies, Five Lessons: A Look Back

• Part 15: A Cross-Asset Defensive Overlay (plus Overfitting)

• Part 14: Trying to Trade the Chop: ETF Mean-Reversion Experiment

• Part 13: Kicking the Tires on a Currency Sleeve

• Part 12: Building a Bayesian Blender and Early Findings

• Part 11: The First Cross-Asset Indicators I’m Prototyping

• Part 10: Making the Allocator Multi-Dimensional

• Part 9: Detecting Volatility Regimes

• Part 8: A Framework for Classifying Future Strategies

• Part 7: Hedge Sizing vs. Alpha Sizing for the Volatility Sleeve

• Part 6: Equity Curve Results: Allocator vs. Volatility Strategy

• Part 5: Going Live: Daily Ops, Execution, and Risk Controls

• Part 4: Backtesting, Allocators, and Findings

• Part 3: Environment, Modules, and Data Flow

• Part 2: Measuring Momentum

• Part 1: Building a Systematic Long/Short Strategy

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Remember: Alpha is never guaranteed. And the backtest is a liar until proven otherwise.

These posts are about methodology, not recommendations. Some of the approaches discussed here involve complex instruments (e.g., options and derivatives) and high-risk (e.g., short vol strategies) and not suitable for all investors. Many of my analyses probably contain errors — if you find them, please let me know.

While I may hold positions in some of the underlying assets discussed here, my posts are not an endorsement or a recommendation of those underlying assets.

The material presented in Math & Markets is for informational purposes only. It does not constitute investment or financial advice.

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