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When I was younger I used to think the more complicated the analysis, the better it must be.
I'd pile on every indicator I could find. Bollinger Bands, RSI, MACD, stochastic, Fibonacci retracements, and whatever else was flavour of the month.
My charts looked like a Christmas tree. Lights everywhere. Lines crossing lines crossing lines.
And it felt good. It felt like I was doing proper analysis. Like the complexity itself was proof that I was serious about this.
Most of it was noise.
I'd sit there staring at six different signals and three of them would say buy, two would say sell, and one would say nothing at all. So I'd freeze. Or I'd override the whole thing and go with my gut anyway, which defeated the entire purpose of having the indicators in the first place.
Over time I realised that a huge amount of what actually works in markets eventually comes back to one very simple idea.
The moving average.
Look at the orange line here.
That’s the 200 daily moving average on the SPX.
Can you visually see how the 200 daily moving average can show you the right direction?
At its core, a moving average is just a way of filtering out noise so you can see the underlying direction. That's it. And once you start looking for that concept, it shows up everywhere.
In nature, a river doesn't carve a canyon in a day. It's the average flow over thousands of years that does the real work. Temperature trends that actually matter for crops or ecosystems are never about today's weather, but the smoothed average over weeks and months. Even animal migration patterns follow gradual shifts in conditions rather than reacting to every single day's temperature.
Markets work the same way.
Most quantitative modelling, when you strip away the fancy language and the PhD-level maths, is often just trying to do a more sophisticated version of this exact thing. Trend-following systems, momentum models, volatility filters, even some machine learning approaches in finance... a lot of them are ultimately trying to identify whether price is above or below some kind of smoothed average, or how far it's deviated from it.
The 200 day moving average is probably the most famous example. Institutions still watch it. Trend-following funds have made billions using variations of it. And the reason it keeps working isn't because it's magical.
It's because it forces you to respect the dominant direction instead of getting chopped up by every bit of short-term noise.
Now here's where this gets relevant to you.
Because this isn't just a charting problem. The exact same mistake shows up on the fundamental side, and it might actually be worse there because it disguises itself as being thorough.
I see it constantly. Someone's got a portfolio of 25-30 positions and for each one they're cross-referencing P/E ratios, forward earnings estimates, free cash flow yield, debt-to-equity, revenue growth rates, insider buying patterns, analyst revisions, and short interest.
That's eight variables per position. Across 30 holdings, that's 240 individual data points they're trying to hold in their head simultaneously.
Nobody can do that. Not you. Not me. Not the analyst at Goldman who gets paid seven figures to try.
But it gets worse, because these variables constantly contradict each other. The P/E says cheap, but the free cash flow yield is deteriorating. Revenue growth is accelerating, but insiders are selling.
The analyst consensus just upgraded, but short interest is climbing, which could mean a squeeze is coming but could also mean the smart money sees something the analysts don't.
So now you're not just processing 240 data points. You're trying to weigh them against each other, in real time, with your own money on the line, while your brokerage app is flashing red and green at you every three seconds.
The output of all that research is paralysis.
You don't buy because three of the eight metrics aren't quite where you'd like them to be. You don't sell because two of them still look strong. You hold and do nothing, which feels like discipline but is actually just indecision with a nicer name.
And the cruellest part is that you spent four hours on a Tuesday night getting to that non-decision. You read the 10-Q and you pulled up the institutional ownership changes. You compared the company to three peers in the same sector. You did the work.
The work just didn't produce an action. Because it was never going to. The more inputs you add, the more likely they are to conflict, and the more likely you are to freeze at the exact moment that matters.
Sound familiar?
The problem with most complex analytical frameworks, whether technical or fundamental, isn't that they're wrong. It's that they overfit.
They work beautifully on historical data, they look rigorous in a backtest, and then they fall apart the moment the regime shifts because the model was tuned to noise, not signal.
A simple moving average approach tends to survive longer precisely because it's humble. It doesn't pretend to predict the future.
It just tells you what the current directional bias is. And that single piece of information, applied consistently, is worth more than 240 conflicting data points applied sporadically.
This is something I had to learn the hard way over years of overcomplicating my own process. And it completely changed how I think about markets.
The best practitioners I know, and I mean the ones running real capital, not the ones posting 47-slide threads on X... they all converge on the same conclusion eventually.
Fewer variables. Clearer rules. Faster execution.
This is one of the core principles we hammer on inside the Academy. We don't build ever more complicated systems.
We build clear, simple, mechanical frameworks that survive regime changes because they're rooted in how capital actually flows, not in how many variables you can cram into a spreadsheet.
And listen, if this resonates and you're sitting there right now knowing that your process has too many inputs and not enough clarity on what actually drives your decisions...
I'd genuinely like to help you untangle it.
I'm opening up some 30-minute calls where we can go over whatever's on your mind. Your portfolio. Your process. Your market questions. Whatever you're stuck on.
Every week you spend refining a system with too many inputs is a week where those inputs are cancelling each other out and leaving you with nothing but a spreadsheet and a stomach ache.
You can book a slot here: Book your 30-minute call
P.S. Genuine question for you, and I'd love to hear your answer. Hit reply and tell me...
How many variables do you actually look at before making a decision on a position? And more importantly, when those variables contradict each other (and they will), what's your dealbreaker? If you don't have one, that's the whole problem in one sentence.
I read every reply.
David Fink Money