Risk Management: Designing Your Trading to Protect the Account First

From here, we move into the risk management section.

In orientation, strategy, and patterns we talked about:

which strategies to use,
which patterns to look at,
and how to think about trend vs mean reversion environments.

Now we focus on something that sits above all of that:

the rules that keep your account alive.

Many traders spend most of their time asking:

“Which strategy makes the most money?”

In real markets, the order is usually closer to:

1️⃣ How much can I afford to lose?
2️⃣ Within that, which strategies do I want to run?

This article is the orientation for everything under
risk-management.

1. Why risk management comes before strategy

Risk management is not just about “feeling safer”.
It’s a requirement if you treat trading as a probability game.

In trading:

even with a high win rate,
losing streaks will come sooner or later,
when market conditions change,
your strategy’s edge can weaken,
with leverage, even small mistakes
can become account-level damage.

That’s why professional traders think less about

“How much can this strategy make?”

and more about

“When this strategy is wrong,
can my account survive?”

Risk management assumes:

every strategy can and will go through bad periods,
your rules must let you stay in the game
long enough for your edge to matter.

2. The seven pillars we’ll cover in this series

Under risk-management,
we split risk management into seven parts.

Risk-reward & R-multiples
→ risk-reward
- for each trade:
  - how much you risk (R),
  - and how much you aim to make (reward),
- measuring performance in R-multiples.
Stops, exits, and take-profit rules
→ stop-loss
- where to place your stop,
- how and when to take partial / full profits,
- deciding “when to get out” in advance.
Position sizing
→ position-sizing
- how much of your account
  you risk on one trade,
- turning that into actual size
  (contracts, coin amount).
ATR-based sizing
→ atr-sizing
- using atr
  to account for different volatility levels,
- adjusting your size to fit each market’s “breathing room”.
Max loss rules (1–2% type rules)
→ max-loss
- “At what daily/weekly/monthly loss
  do I stop trading and step back?”
- adapting the common 1–2% rules
  to your own account.
Drawdown & recovery math
→ drawdown
- what drawdown is,
- how much return you need to climb back to breakeven.
Loss psychology & mental risk management
→ loss-psychology
- common patterns during losing streaks,
- revenge trades, over-leveraging,
  and other psychological traps.

Together, these seven pillars form
a “survival-first trading blueprint” for your account.

3. Questions to ask yourself when designing risk rules

Before going deeper into the sub-articles,
it helps to ask yourself:

“What % of my account
am I truly comfortable risking on one trade?”
“How much can I lose in a day/week/month
before I force myself to stop trading and reassess?”
“Is my current leverage level realistic
for my account size and experience?”
“If I lose five, seven, ten trades in a row,
can my account survive that?”
“Do I distinguish between
losses that follow my rules
and losses caused by breaking them?”

The articles under risk-management
will gradually turn your answers
into concrete numbers and rules.

4. A very simple example: thinking in terms of 1R

One of the most useful ideas in risk management is “1R”
(covered in detail in risk-reward).

For example:

your account is 10,000 USD,
you decide to risk 1% per trade,
so 100 USD is your max loss for one position.

Here, 1R = 100 USD.

If:

the distance between your entry and your stop
is 50 USD per coin,

you size your trade so that
if the stop is hit,
you lose exactly 100 USD (−1R).

Then:

if you make 200 USD → +2R,
if you make 300 USD → +3R, and so on.

This lets you evaluate strategies in R-multiples:

Strategy A: average +0.5R per trade
Strategy B: average +1.2R per trade

No matter how your account size changes,
you can compare the quality of systems in a common unit.

5. Common mistakes in risk management

5-1. Focusing only on win rate, ignoring R/R

It’s easy to get attracted to things like:

“This system has an 80% win rate.”

But if one loss wipes out
four or five winners,
the account is still in danger.

Risk management is about:

win rate,
and risk-reward,
and position size,
and max loss rules

all combined, not isolated metrics.

5-2. Increasing leverage and bet size

too aggressively when things go well

When results are good,
it’s natural to think:

“This is my chance. I should press harder.”

That’s exactly when it becomes easy
to break your own rules from:

and take risks you didn’t plan for.

The core purpose of risk management is closer to:

“Not maximizing this single hot period,
but building a structure that can withstand
both good and bad periods.”

5-3. Changing your rules after a few losses

widening stops after two or three losses,
suddenly increasing size to “make it back in one trade”,

is essentially like resetting
your whole risk plan on tilt.

As much as possible:

design your rules when you’re calm,
and adjust them slowly over time
based on proper review, not emotion.

6. How to read this series

Risk management is not something
you “memorize once and complete”.

It’s something you’ll revisit
over and over as you gain experience.

A suggested order:

Start with risk-reward
→ understand R and risk-reward structure.
Then stop-loss
and position-sizing
→ design each individual trade.
Then atr-sizing
→ learn to account for volatility differences
between markets.
Then max-loss
and drawdown
→ set limits at the account level
for max loss and drawdown.
Finally, loss-psychology
→ build a mental framework
for staying disciplined during losing periods.

In short, risk management is:

not about “How fast can I get rich?”
but “How long can I stay in the game?”

If you combine:

the strategy work in strategy
with
the account-level rules in risk-management,

your system becomes less about
finding “perfect entries”
and more about building a structure that can survive
both rallies and drawdowns.

That shift alone
moves you much closer
to thinking like a professional trader.