LIVE — AUTOMATED TESTING PHASE

Discretionary trading
doesn't work.

Most retail traders fail not because of psychology — but because they are trading unvalidated models and calling the losses a mindset problem. The correct approach is systematic: build a hypothesis, validate it through data, automate it entirely.

This site documents that process in full — including a live automated forex model built from scratch.

model_status.py
# Model 01
status = "live_testing"
instruments = ["EURUSD", "GBPUSD", "AUDUSD",
              "USDCAD", "USDCHF", "NZDUSD"]
win_rate = "27–35%"
expectancy = "+0.25R to +0.37R"
avg_rr = "3.0–4.5R"
validation = "15/15 profitable years"
sample_size = 26000 # trades
Core Belief

Why discretionary trading fails

01

The model is untested

Most retail strategies have never been validated against real data. Without a defined hypothesis and a rigorous testing process, there is no way to separate edge from luck.

02

Psychology is a scapegoat

When a losing streak hits, the retail narrative blames discipline and mindset. In reality, trading an unvalidated model makes it impossible to separate losses caused by poor process from losses that are simply part of a valid strategy's distribution.

03

The correct process exists

Build a hypothesis. Validate it manually with a small sample. Confirm it through automated backtesting across years of data. Then automate execution entirely.

Who
Zach Simpson
2.5 years in markets

2.5 years in markets. Started the same way most retail traders do — discretionary price action, pattern recognition, and the belief that psychology was the variable standing between losses and consistency.

It wasn't. The model was unprofitable. Psychology was covering that up.

Since then: a complete transition to systematic, data-driven strategy development. One validated automated forex model currently in live testing. A YouTube series documenting the full process. And this site — built to share the work publicly.

Community

Join the Discord

Free to join. Built for traders who take research and validation seriously — daily market briefs, episode discussion, and a community working through the same process.

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