CodeMarketLabs
After eight years in market finance at Lyxor, HSBC and Société Générale, here are the 12 trading lessons that separate gamblers from real investors: market efficiency, the true learning curve (8 to 10% a year within six months, 20% for the best hedge funds), edge decay, process versus result, beta versus alpha, sizing, multi-strategy, backtesting and automation. Plus a complete free training plan and book library.
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How to borrow cash on the financial markets without touching your portfolio, using a four-leg options structure called the box trade. Covers strike selection, execution on Interactive Broker, how to calculate your real implied borrowing rate with a free Excel calculator, and the concrete situations where this Lombard-loan alternative actually makes sense.
A full walkthrough of the framework I use to analyze any company before investing: the 3 tools you need, how to read the business and its moat, the 4 charts that show profitability and growth, balance sheet and management quality checks, and a full peer valuation. Applied live to Amazon, PE 20.7x, EV to EBITDA 13x versus a 30x historical average, ROE between 13 and 20 percent, plus the one chart, EPS versus price, that changed how I invest.
The complete framework institutions use instead of fixed dollar amounts and naive stop losses: volatility based position sizing, correlation adjusted notional, VaR and Conditional VaR limits, and a written trading mandate. Includes real numbers: a portfolio going from 9443 dollars of naive notional to 13400 dollars once correlation is accounted for, and a 20 percent target return with 10 percent volatility mandate for a Sharpe ratio of 2.
A former markets desk trader (Societe Generale, HSBC, Lyxor) breaks down why the standard retail risk management playbook, the 2 percent per trade rule, the fixed R sizing, the stop loss as a safety net, is built on a Bernoulli model that never holds on real markets. Covers why win rate is not stationary, why sizing without volatility is meaningless, why a stop loss is not an execution guarantee, why leverage should never be a function of stop distance, and how institutional desks actually separate the trader role from the risk manager role.
How prop firms actually work behind the scenes, the two business lines, the B-book and A-book, and how I built Polyquid, a platform letting traders use one account across Hyperliquid perpetuals and Polymarket, solo in 33 days on Python, Django, FastAPI and Next.js, with latency under 100 microseconds.
A former trader and portfolio manager at Société Générale's private bank breaks down the exact process used in institutions to build an investment portfolio: passive vs active management, top-down vs bottom-up approaches, a full asset class overview, how to set your risk level using the efficient frontier, and how to actually pick your holdings. Everything you need to go from zero to a coherent, diversified allocation, without needing to be a finance genius.
8 years of systematic trading, and these 5 mistakes I made all of them. From biased backtests and survivorship bias to ghost orders, infrastructure failures, and crash recovery — a complete breakdown of what goes wrong and exactly how to fix it.
A complete breakdown of the Python backtesting framework I built with Claude Code — and how you can backtest any strategy from a single prompt. Covers the cash-flow engine architecture, the CLAUDE.md context file, overfitting prevention, and a live demo: MA Crossing 20/50 on SPY (2000–2026), +17.0% total return, Sharpe -0.08, 138 trades — including the full AI audit of why the result is bad and what to fix.
A complete breakdown of long/short equity strategies as used in institutional trading: mean reversion, relative value, divergence, beta hedging, and two Python backtests — JPMorgan vs Goldman Sachs and SPY vs FEZ. Includes IBKR execution and an honest assessment of the risks nobody talks about.