Superior Risk Management for Trading Returns

Everyone focuses on entries. Where to get in, what pattern to trade, which indicator to use. Laurent Bernut thinks this is why most traders fail. The entry is largely irrelevant to your long-term outcome. What matters is how much you bet, how you manage drawdowns when they come, and whether your strategy can survive long enough to compound.

Laurent is a short-selling specialist with a background at Fidelity and multiple hedge funds. He later founded Alpha Secura Capital and TraderLogix. He’s a repeat BST guest — one of the more colorful ones, with a direct style and a habit of making complex ideas land with memorable analogies. In this episode, recorded while he was based in Tokyo, he walked through his framework for what “superior” risk management actually means and demonstrated it with a simulation of dynamic position sizing.

The core argument: superior returns come not from better entries, but from surviving drawdowns that ordinary traders can’t weather.

Watch the full episode below, then read on for the complete breakdown.

Table of Contents

What “superior” risk management actually means

Laurent defined superior risk management in terms of investor behavior rather than returns. Investors — whether external capital or your own psychology — react to drawdowns in three ways, all predictable:

Magnitude — A drawdown that’s too large causes panic, regardless of how the strategy recovers afterward
Frequency — Frequent smaller drawdowns erode confidence and patience even when magnitude is contained
Duration — A drawdown that lasts too long tests patience in a way that neither magnitude nor frequency alone does

The goal of superior risk management isn’t to maximize returns in a good year. It’s to build something that doesn’t fail due to any of those three pressure points. His analogy: you don’t build a boat for fair weather. If you’re planning to sail seriously, you build a boat that will survive the storm, even if it’s not the fastest boat on calm water.

Translated to trading: the optimal strategy isn’t the one with the highest average return. It’s the one with the best risk-adjusted return that also keeps investors (including yourself) from pulling capital at the worst time.

The real driver of returns: position sizing, not signals

The trading edge is a mathematical formula. It’s called gain expectancy: average win multiplied by win rate, minus average loss multiplied by loss rate. That formula is what it is. You can’t control it directly. What you can control is how much you bet.

Laurent referenced the trend followers of the 1980s — traders like Richard Dennis, who by his own account had a long-term win rate of around 35%. They expected every trade to be a loser. They walked into trades thinking this one probably won’t work. When it did work, they let it run. What made them extraordinary wasn’t their signal; it was their ability to bet the right amount and manage position size through losing streaks without blowing up.

Position sizing is where the real leverage lives. A strategy with a 50% win rate and a 2:1 payoff ratio will compound wealth if sized correctly and destroy capital if sized incorrectly. The signal is relatively unimportant compared to this.

The tolerance for drawdown framework

Laurent runs his strategies with an explicit drawdown tolerance built in. In his simulation (run in Python on a Nikkei equity curve), he showed three lines:

The equity curve itself (black line)
The watermark — the peak equity curve at any given point (green line)
The tolerance threshold — a defined percentage below the watermark where risk gets reduced (red dotted line)

The rule is simple: when the equity curve falls from the watermark to the tolerance threshold, reduce risk. When the strategy recovers and starts working again, increase risk back to full exposure. This is the anti-Martingale approach. You don’t double down when losing. You pull back. You load up when winning.

He referenced Millennium Partners as a real-world example: at a 5% drawdown from peak, they withdraw 50% of assets under management from a manager. That’s a hard threshold. Your tolerance for drawdown determines how much runway you have before capital leaves.

Why Martingale destroys accounts

Martingale — doubling your position size after each loss — has a statistical property Laurent called “certainty of ruin.” The math is straightforward: to guarantee you eventually win, you need infinite capital. Nobody has infinite capital. Every outcome leading up to your final winning trade means you’ve gone broke. The hedge funds that shorted GameStop in 2021 learned this in real time — they were certain they were right about the fundamental value, but the market stayed irrational long enough to eliminate their capacity to hold.

The correct response to losing is to reduce risk, not increase it. The strategy’s drawdown tells you something about the current market environment for that approach. Reducing exposure is information-responsive behavior. Doubling down is emotional.

The floor and ceiling approach to market direction

Beyond position sizing, Laurent described a framework he developed for reading market direction called “floor and ceiling.” The concept: when a market makes a peak and then makes subsequent swing highs that are materially lower, cumulative probability tells you the market is likely to go sideways or down. When a market prints a bottom and then makes higher swing lows that are materially higher, probability favors upward continuation.

He applies this in relative and absolute terms — looking at both the absolute price level and how a stock or market performs relative to its peers or index. This is how he identifies short-selling candidates: names that have shown the floor-and-ceiling pattern of lower highs relative to the broader market, even during periods when the index is rising.

Long-short: same edge, different sides

Laurent’s view on long versus short is deliberately symmetrical. He does long-short, trades Forex pairs, and consults for shops managing Japanese equities shorts. His framing: long and short “taste like chicken.” The mechanics are the same — you’re looking for an edge, sizing correctly, and managing risk. The direction of the trade is almost incidental.

That said, he acknowledged that short positions carry unique risks, particularly overnight. Short squeezes, gap-up openings, and thin borrow availability can all cause losses that exceed any stop level. For that reason, he prefers to express bearish views through put options or put spreads on multi-day timeframes rather than carrying naked short equity positions overnight. The defined loss on an options position gives him more control over the risk.

The transgenerational test

Laurent’s ultimate criterion for a trading system isn’t its Sharpe ratio or its annual return. It’s whether the system would still be functioning if he weren’t around to manage it. He called this the “transgenerational” standard. If the system’s survival depends on the operator making active discretionary decisions during every crisis, it’s not robust. If it can weather a drawdown, reduce risk automatically, recover, and compound over time with minimal intervention — that’s what he’s building toward.

For most retail systematic traders, the practical version of this is simpler: can you follow the rules of your system through a 20% drawdown without intervening? If not, you haven’t managed your risk correctly. You’ve built something too aggressive for your actual psychology.

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