When I first started trading, I copied someone else’s setup down to the letter. Same indicators, same entry triggers, same everything. The results were nothing like theirs. Looking back, the reason is obvious — it was their setup, not mine.

There’s an old saying: “Know yourself and know your enemy, and you will never be defeated.” Trading works the same way. Before you analyze the market, you have to analyze yourself. That said, even with perfect self-knowledge, nothing in trading is ever 100%. But there’s a world of difference between trading without a defined identity and trading with a clear, personal framework. Over time, that difference shows up in your P&L.

There’s no shortage of things people say matter in trading. Technical analysis, risk management, macro conditions, economic data — they’re all valid. But there’s something that needs to come before all of that: defining what kind of trader you actually are.

Here are the 3 things I defined over 2.5 years — and what they look like in practice.

Reading Charts in My Own Language — Timeframes and Indicator Settings

I work with exactly two timeframes: the 1-hour chart and the 6-minute chart.
I read trend direction on the 1-hour, and time my entries on the 6-minute. Most of my exits happen on the 6-minute as well.

I do check the daily chart every day — but I don’t use it for technical analysis. Taking a position based on the daily means committing to a swing trade, which brings overnight swap costs into the equation and forces you to sit through three full session shifts: Asia, Europe, and the U.S. Surviving all of that requires institutional-level capital and risk tolerance. For retail traders, wrapping up positions within the same day is simply more realistic.

So why the 1-hour and 6-minute specifically?

It comes down to how Bollinger Bands are set by default. Bollinger Bands — developed by John Bollinger — plot two standard deviations above and below a 20-period moving average, giving you a probabilistic range for where price is likely to move. What matters to me is what the 20, 120, and 240-period moving averages actually represent across different timeframes.

MA Period	6-Minute Chart	1-Hour Chart
20 periods	~2 hours	~1 day (20 hours)
120 periods	~half a day (12 hours)	~1 week
240 periods	~1 full day (24 hours)	~2 weeks

Looked at this way, these two timeframes let you track different time horizons simultaneously. The 6-minute gives you short-term momentum, while the 1-hour tells you whether that momentum aligns with the broader weekly trend.

For a sub-indicator, I use one thing only: Stochastics.

My settings are %K length 20 / %K smoothing 5 / %D smoothing 3. The smoothing values came from trial and error — these are simply the numbers that let me read the oscillator at a glance without second-guessing. I set horizontal lines at 80, 60, 50, 40, and 20. I treat 80 as overbought, 20 as oversold, and 50 as the midpoint. The 60 level signals either a pullback entry for shorts or a take-profit zone for longs. The 40 level does the opposite — pullback entry for longs or take-profit for shorts.

The 80, 50, and 20 lines come standard. You’ll need to manually add the 60 and 40. Once you do and pull up a chart, it’ll be immediately clear why those two levels matter.

Risk Isn’t a Probability — Decide What You’re Willing to Lose First

Most people think of risk as the probability of losing money. In trading, that framing will get you in trouble. Risk isn’t a probability — it’s the exact dollar amount you stand to lose if your stop gets hit.

Calculating your risk means measuring the distance between your entry and your stop loss in dollar terms. Managing your risk means sizing your position so that loss never exceeds a set percentage of your account. Do that consistently, and no single stopped-out trade can blow up your account.

My take on risk-reward ratios is a little unconventional.

Most trading courses tell you to set a target price before you enter and make sure your reward is at least 2x or 3x your risk. I don’t buy it. Nobody knows how far price will travel on any given move. Pinning a fixed target to your trade is forcing the market to fit your expectations — and the market doesn’t care about your expectations.

Instead, I let my Stochastics tell me when to exit.

• On a long → take partial or full profit when Stochastics hit 60, or ride it to 80
• On a short → take partial or full profit when Stochastics hit 40, or ride it to 20

As your trade log grows, your average reward naturally emerges from the data. Risk-reward ratio isn’t an input you set before a trade — it’s an output you measure after enough trades. For what it’s worth, when I do the math on my own stats, it comes out close to 1:1.

The reason this works is straightforward: my win rate is high. My current setup produces a win rate above 80%. Even accounting for the trades that close in the red, the overall picture sits above 90%. When your win rate is that high, you don’t need a 1:3 risk-reward ratio to stay profitable — the math takes care of itself.

I Don’t Read the News — I Read the Candles

Here’s the honest truth: macro conditions and economic data are useful for one thing — identifying when a significant directional move might be triggered. That’s it.

Whether a data print comes in above or below expectations, whether the tone of financial media is bullish or bearish — none of that has a reliable, consistent relationship with which direction price actually moves. Prices rally on bad news. They sell off on good news. It happens all the time. What matters isn’t the number — it’s how market participants react to the event. That reaction is written directly into the candle.

After any major economic release, there’s only one thing I look at: Was that candle a bull candle, a bear candle, or a doji?

• Bull candle: Favor longs until the next major event
• Bear candle: Favor shorts until the next major event
• Doji (roughly equal upper and lower wicks): Expect consolidation — trade the range until the next catalyst

Spending energy trying to interpret headlines is a losing game. Watching how price actually responds to events is where the edge is.

A Setup Is Knowing Why You Were Wrong

I still have bad trading days. But now I know exactly why — I strayed from my setup.

Defining your setup isn’t a guarantee of profits. It’s about building a framework that explains your wins and your losses. Without that framework, a winning trade teaches you nothing and a losing trade is just pain. Lasting in this game without a framework isn’t discipline — it’s luck.

Under this approach, my MDD (Maximum Drawdown — peak-to-trough loss relative to account size) has stayed under 3%, and I’ve been consistently returning over 20% per month. The two years before this? Annual P&L was negative. Back then, my approach was a patchwork of other people’s methods and I was constantly second-guessing myself based on what other traders claimed to be making.

I won’t be posting specific financial figures regularly going forward. Partly because I don’t want anyone chasing results without understanding the process behind them. And partly because I know myself — if I start getting feedback on my numbers, I’ll let that noise affect my trading. This blog is about trading well, not just trading profitably.

Next up, I’ll walk through how this setup looks in action on a real chart.

If you have questions about the setup, or want more detail on the Bollinger Band or Stochastics configuration, drop a comment below. If there’s enough interest, I’ll put together a deeper breakdown in the next post.

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