⚠️ Personal research and trading journal — not investment advice. The author does not provide licensed advisory services.
Every retail investor has a version of the same story. Mine started the way most do: reading about the method, believing in the method, then trading the method — and losing money in the way most people lose money. Not dramatically. Just slowly, through a hundred small optimistic decisions that felt right at the time.
The thing about conviction-based trading is that it feels like analysis. You read the book, you understand the logic, you look at the chart and the story holds together. What you don't do — what nobody teaches you to do — is check whether any of it is actually true.
The question that changed everything
Three years into this, I asked myself a question I'd been avoiding: does this setup actually have an edge, or does it just look like it should?
The test was simple. Take the setup I trusted most. Run it across twenty years of data. Compare the outcome to a random baseline of qualifying stocks on the same dates. Ask: does this beat the alternative, or does it just move with the tide?
The answer was uncomfortable. The setup I'd been using had edge — but it was smaller than I thought, narrower than I thought, and almost entirely dependent on market conditions I hadn't been tracking. In a confirmed uptrend: real edge. In everything else: nearly zero.
That single test changed how I thought about everything. Not "is this method good or bad" — but "how do I know what I claim to know?"
The list of things that failed
Once I started testing properly, I built a list.
The shakeout-and-rally pattern — canonical Minervini, the one everyone cites. Tested against a date-matched baseline. Failed. The "too extended" warning signal. Looked like it had edge. Bootstrap CI spanned zero. The IBD buy-zone language. Strong initial read. Turned out to be late-stage narrative — by the time analysts said "still in the buy zone," the move was already priced in. Volume dry-up during base construction. Intuitive, visually convincing. Failed consistency check year by year.
The list is now past ten items. I publish every one.
Not because I enjoy being wrong. Because the map of what doesn't work is as useful as the map of what does — maybe more useful, because it stops you wasting years on things that feel true but aren't.
What survived
Not much. One setup. Two systems running in parallel on separate capital pools. A handful of filters that survived bootstrap CI and out-of-sample walk-forward across two markets. An edge that is real but modest — roughly +0.35R per trade net of costs in the Thai market, weaker in the US — with most years losing and a handful of big years driving the whole result.
That's it. After all the testing, the answer wasn't a sophisticated system. It was a simple one, honestly measured.
Why publish it
There are thousands of people in Thai retail trading who are exactly where I was three years ago. Reading the methods, believing the methods, not measuring the methods. The industry has no incentive to tell them that most of what they're reading has never survived a proper baseline test.
I can't fix that. But I can publish the test methodology. Show what failed and why. Show what passed and how confident the pass actually is. Let the evidence be the argument.
The brand is called MOEasymmetry — asymmetric risk. The name applies to the trading method: risk a little, aim for a lot. It also applies to what I'm trying to do here: one honest researcher publishing failures, against an industry of confident claims with no receipts.
The asymmetry is the whole point.
Track. Study. Wait. Strike.
Personal research and trading journal — not investment advice. The author does not provide licensed advisory services. — MOEasymmetry