用逻辑去分析

Why I started to intentionally reduce trading at 'mid-price levels'

Reviewing the past 100 orders, I specifically counted:

When opening positions near support/resistance levels, the risk-reward ratio is generally still visible;

When opening positions randomly in the middle of the price range, it has almost been 'random fluctuations → transaction fee players' in the long term.

The numbers are quite honest:
Trades at mid-price levels accounted for 60% of my entry frequency but contributed to less than 20% of my profits, while consuming a lot of time and energy.

So for the next month, the experiment I set for myself is:
Only allow trades at the 'edges' — close to key support/resistance/breakout points,
While treating the middle positions as just watching the show.

I want to see if, when I cut off the 'ineffective areas',
Will the account curve start to look cleaner.
#用逻辑去分析

How I design a "1 trade"

A single transaction for me is not "just call a direction + casually open a position," but a small model:

Input:

Entry price = Breakthrough / Pullback / Key interval edge

Stop loss price = The position where the structure is broken

Process:

Risk = Distance between entry price and stop loss price × Position size

Target = 2 to 3 times the risk (2R to 3R)

Output:

This trade is +2R / +3R / −1R

As long as I maintain:
Average profit R value > Average loss R value,
Even if the win rate is only 40% to 50%,
This system is statistically profitable.

I no longer ask "Can this trade double my account in one go,"
I only ask "Is this trade reasonable in my system."
#用逻辑去分析

Use the "Four Quadrants" to label your trades

Many people review their trades, only looking at profits and losses, without considering "what type of trade this is".
I created a simple four quadrants for myself:

Direction correct + Execution correct

Direction correct + Execution wrong (early take profit, holding the position, not following the plan)

Direction wrong + Execution correct (stop loss when needed)

Direction wrong + Execution wrong

After a month, I found that:
👉 The real hindrance comes from the quadrant of "Direction wrong + Execution wrong", which accounts for less than 20% but contributes to more than 70% of the losses.

The logic is straightforward:
All future improvements will focus on this quadrant first—
it's not just about increasing the win rate, but finding ways to minimize the occurrences of "Direction wrong + Execution wrong".
#用逻辑去分析

I determine whether "today is a good day to trade" in three steps

Most people just want to know whether to go long or short today,
but I first ask myself a more fundamental question every day: Is today suitable for taking action?

My process is very simple, three steps:
1️⃣ Look at the volatility range:

If the expected volatility for the day is less than half of yesterday's, I directly reduce the frequency or even don’t trade at all.
2️⃣ Look at the structure:

If the highs and lows are messy and the moving averages are tangled, treat it as a consolidation day and only consider light positions at extreme levels.
3️⃣ Look at my own state:

Lack of sleep, two consecutive losses, unstable emotions → This day is automatically downgraded to an "observation day".

If any of these three criteria are not met, I would rather accept "missing out" than "acting recklessly".
True logical trading starts not with finding opportunities, but with filtering out the days when one should not take action.
#用逻辑去分析