|
Rosario, Santa Fe, Argentina
Posts: 2 since Jun 2026
Thanks Given: 1
Thanks Received: 3
|
What Oxford Actually Taught Me About Building Systems That Survive
This entry documents the Oxford Algorithmic Trading Programme — not the credential, but what transferred into live practice.
The framework: Prof. Vulkan's four-principle model for building and evaluating algorithmic strategies. The differentiator from purely technical programmes is emphasis on when to reject a model — a skill most quants undervalue until a drawdown teaches it for them.
What I use daily, mapped to real problems:
Behavioural Finance — Momentum anomalies, anchoring, disposition effect. Most systematic shops ignore behavioural alpha because it's harder to formalize. That's precisely why edge still lives there.
System Architecture — Rule-based logic with explicit entry/exit conditions, position sizing, and regime filters. Auditable. Non-discretionary. Every parameter justified before it ships.
Model Evaluation — Sharpe decomposition, drawdown profiling, capacity constraints, survivorship bias detection. The question isn't "does this backtest look good" — it's "does this deserve capital."
Live Translation — Slippage modeling, execution latency impact, parameter decay. The gap between backtest and live is where most systems die. Closing that gap is the actual job.
ML Placement — Where machine learning adds signal versus where it manufactures overfit. LLM-assisted signal generation with proper validation gates, not prompts dressed as research.
How I can help you specifically:
Struggling to trust your backtest? I'll audit it — bias detection, regime breakdown, realistic cost modeling — and give you a written verdict with documented criteria, not an opinion.
Have an idea that won't fully formalize? I'll help convert intuition into testable structure: explicit logic, economic rationale for every variable, walk-forward validation before any capital touches it.
Want ML in your system but unsure where? I'll map where it genuinely adds signal in your specific setup — and where it would silently overfit.
Need better tooling? Balance curve dashboards, drawdown analytics, performance attribution — built for your workflow, not generic templates.
I'm here to connect with serious traders, exchange ideas, and take on a small number of collaborations where I can add genuine depth.
Good to meet you all.
|