Archive - Math & Markets

How to Use the ML for Trading Tools: A Labs Walkthrough

How-to article on the Feature Engineering Explorer, SHAP Explorer, and Tree Builder

7 hrs ago • K. Iyer

XGBoost Identified SHAP Values, Non-Linear Regimes, and VIX Reversal (2.2 Sharpe In-Sample; 0.15 Out-of-Sample)

Machine Learning Series Part 2: Why trees beat neural nets for trading

20 hrs ago • K. Iyer

From If-Else to XGBoost: Why the Hard Part Isn't the Model

Machine Learning Series Part 1: We Tested 20 ML Features. Only 7 Beat the Noise Floor.

May 12 • K. Iyer

The V6 Options Overlay: Is the Complexity Worth the Sharpe?

Part 93 — A three-leg put spread collar, conditional engagement rules, and the honest answer to whether V6 needs options at all

May 11 • K. Iyer

The Volatility Surface: Where Every Option Is a Different Bet on a Different Fear

Part 92 — The smile, the smirk, the term structure, and the four dimensions of vol surface trading

May 6 • K. Iyer

April 2026

Replicating Hedge Fund Strategies with Four Options Trades

Part 92 — Risk reversals as momentum, covered calls as vol selling, collars as tail hedging, and why convexity is the only free lunch left

Apr 11 • K. Iyer

The LEGO Bricks of Options: Put-Call Parity and the Art of Building Any Payoff You Want

Part 91 — Understanding synthetic positions changes how you think about risk

Apr 10 • K. Iyer

Building a Carry Portfolio That Survives: Diversification, Momentum Hedging, and the V6 Carry Upgrade

Part 90 — Multi-asset carry, the diversification illusion, the carry-momentum hedge, and what V6 should actually implement

Apr 3 • K. Iyer

When the Escalator Becomes an Elevator: Timing Carry Crashes

Part 88 — Three modes of carry failure, early warning signals, and the regime framework for knowing when to step back

Apr 1 • K. Iyer

March 2026

Carry Trade: The Oldest Edge in Finance

Part 88 — FX carry, bond roll-down, the volatility risk premium, and why every asset class pays you to hold risk overnight

Mar 28 • K. Iyer

Synthetic Markets from Scratch: A Practical Guide to Stochastic Data Generation

Part 87 — How to build, calibrate, validate, and stress-test with market data that never existed

Mar 27 • K. Iyer

Building the Microstructure Signal Layer: From Theory to 50 Lines of Python

Part 86 — Composite scoring, position scaling, walkforward results, and the concrete implementation plan for V6

Mar 26 • K. Iyer

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