Originally published in French on objectifeco.com, April 10, 2013. The site was purged in 2016; this text survives only in the Internet Archive (Snapshot). Translated, not rewritten: what follows is the original argument as it was made, including what time has since proven wrong. Where that happens, you'll find a note from the desk, dated 2026.
I'd like to use the news as a hook to talk about a notion that gets far too little consideration in trading.
Context.
It comes down to an obvious point whose effects we never quite measure properly:
Good news in a positive, euphoric market won't have the same consequences as the exact same news in a negative market, or one in crisis.
Conversely, good news in a rotten market won't carry the same potential as it would in an optimistic one.
Put like that, it sounds obvious, doesn't it?
So why do people, every single day, do exactly the opposite in their trading?
First, a demonstration by example.
Take the single most iconic number published on financial markets: I'm talking about NFP, Non-Farm Payrolls. It's the US unemployment figure. It comes out on the first Friday of every month, at 2.30 p.m. French time.
Desk note, 2026: strictly, non-farm payrolls is the number of jobs added outside farming; the unemployment rate is a separate figure published in the same monthly report. The release usually falls on the first Friday of the month, at 8.30 a.m. New York time.
It's rare for this number not to move the market. But watch closely and you'll see its impact can swing anywhere from mild to a full nightmare.
Obviously, when you want to analyse the impact of a number on the markets, it's never the number itself that matters; it's the gap between that number, on the day it's published, and what analysts were expecting.
That's when we talk about a good number, a bad number, or a statistic with nothing much to say.
Another trap: a good number for the economy isn't necessarily a good number for the market. Once again, it all depends on expectations.
Which is exactly why the market's reaction can be hard to make sense of at times.
Let me give you a few examples.
In 1999, the economy was running flat out. What we called the dot-com boom. The economy was creating hundreds of thousands of jobs, and the unemployment figures reflected that golden run. And yet, whenever the unemployment number came in really too good, the market fell, sometimes quite violently.
In a virtuous economic cycle, too much positive pressure on the jobs market risks pushing wages up. That rise then feeds through into prices, what we call inflation, one of the market's sworn enemies. The market hates that, and falls hard. What it actually wants is an economy that grows, but at a measured pace.
Conversely, after two and a half years of a bear market reflecting the economic contraction triggered by 11 September 2001, it's obviously every bad statistic that gives the market a cold.
Desk note, 2026: the bear market he describes began in March 2000, when the dot-com bubble burst, and the US recession began in March 2001. The attacks of 11 September 2001 deepened a decline that was already under way.
By contrast, last Friday, a distinctly average number, dropped into a market that had been euphoric for weeks, had only a modest effect. Barely a full percentage point of decline, for a few hours, before it was wiped out entirely over the following two days.
The rule is this: the market's general context, at the moment a statistic or an announcement is published, matters at least as much as the announcement itself (or, to be precise, as much as the gap between the announcement and what the market was expecting).
The two biggest effects will always come from:
- bad news landing in a pessimistic market;
- good news landing in an optimistic one.
The reverse pairings carry little weight.
Very often, traders have their nose down over the handlebars. They forget the context.
Among the hundreds of traders I've been watching for years, I've picked out two traits that, in my view, explain part of why they don't succeed:
Traders aren't flexible enough in how they trade. Even the best of them, with a seasoned technique, don't adapt to context nearly enough. The most basic adaptation would simply be to only work the upside when the market's euphoric, or only the downside when it's in crisis. Over the years, almost none of my clients have shown that ability.
Traders don't factor the general context into their trading nearly enough. What I call the general context often boils down to what you might call the underlying trend and the volatility. But it's a bit more subtle than that. The fear or euphoria you feel coming off the market itself is hard to put a number on. And yet, stepping back just a little from the market, traders know perfectly well what context they're in.
So what are the best ways to adapt to the market's context?
The first thing is to use filters.
Every style of trading needs its own filters. A counter-trend specialist, for instance, really doesn't want to find himself in a strongly trending market. That particular filter can be hard to build or find, but others, much more basic, have the potential to improve your trading enormously.
Do you adjust your trading based on volatility, for instance? If not, get moving and study the impact volatility has had on your past results. I can assure you, you'll learn a great deal, and improve enormously, once you've applied a few simple recipes.
Are you capable of taking more risk in the direction of the market, of its underlying trend, than against it?
Do you pay enough attention to what I'd call the "mood"? That is: the political backdrop, the data calendar, a certain emotional state running through the market.
I'm sure you're starting to see what I mean. And this list is far from exhaustive.
In automated trading too, you can add this kind of filter to make your trading more effective.
But there's a danger lurking here. Overfitting, obviously.
To caricature it a little: you can easily land on a system with dozens of parameters, each one helping to narrow down and optimise the exact context in which the system performs. But who's to say the future will look like the past? Nobody. If anything, it's more likely the opposite: the future will always throw market conditions across our path that we've never once seen before.
For a good filter to actually work, it has to be simple. And the test period has to be long enough for us to be confident of its effectiveness, statistically at least.
Which is exactly why I've always preferred holding several simple systems in my portfolio, rather than one very complicated one. My overfitting risk goes down, and the diversification lets me smooth out my performance.
After all these years, I'm still surprised by how little perspective, how little altitude, retail traders have on their own trading. I wonder how many of them have the curiosity to actually analyse their results, question their own method, and test it properly.
And what I understand even less is that the only ones who succeed are the ones who've been through exactly that. THERE IS NO OTHER WAY TO SUCCEED. Learn. Correct. Improve.
Part of a series. This article belongs to Market Regime: Every Strategy Is Built for One Kind of Weather. Related: How to Give Yourself a Better Chance of Success When Opening a Position and The Value Added by a "Filtered" Strategy. Background: volatility in the Ouinex glossary.
About the author. Samuel Rondot has traded since 1995, self-taught. Between 2009 and 2017 he published around 300 articles on objectifeco.com, abcbourse.com and his own blog, many of them drawn from what he saw in hundreds of client accounts. Objectifeco wiped its archive in 2016; the Internet Archive kept a copy, and every article republished here links to its original. He now runs the Strategy at Ouinex.
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