The Avex Trading Plan Series — Part 4
Series Note:
This is Part 4 of the Avex Trading Plan Series. In Part 1, we discussed why every trader needs written rules. In Part 2, we explained why copying another trader’s strategy can be dangerous. In Part 3, we covered backtesting. Now we move to the next step: optimisation.
Optimising trading strategy is not about making your system more complicated.
This is one of the biggest mistakes traders make.
They backtest a strategy, find some losses, and immediately think:
“I need another filter.”
Then another one.
Then another one.
Soon the strategy becomes so complicated that the trader cannot execute it in live market conditions.
That is not optimisation.
That is confusion.
Real optimisation is different.
It means using your backtest results to make the strategy cleaner, more focused, and easier to execute.
The goal is not to create a perfect strategy.
The goal is to create a repeatable one.
What Does It Mean to Optimise a Trading Strategy?
Optimising Trading Strategy Starts With Removing Weak Setups
Optimising a trading strategy means improving the rules after reviewing real data.
You are not guessing.
You are not adding rules because you feel nervous.
You are not changing the system after one loss.
You are looking at your backtest and asking:
- Which setups worked best?
- Which setups failed most often?
- Which session gave cleaner results?
- Which market condition created the best trades?
- Which trades should be filtered out?
- Which targets made the most sense?
- Which rules are useful?
- Which rules only add confusion?
This is how a strategy becomes stronger.
Not by adding more noise.
By removing what does not belong.
Optimisation Starts After Backtesting
Optimising Trading Strategy Without Adding Too Many Rules
Many traders try to optimise too early.
They watch a few examples and immediately adjust the rules.
That is not enough.
Before you optimise, you need data.
This is why backtesting comes first.
You need to test the strategy across enough historical examples before making decisions.
If you change the rules after five trades, you are not optimising.
You are reacting emotionally.
A real optimisation process needs a sample size.
You need to see how the strategy behaves across:
- winning trades
- losing trades
- strong trend days
- trading range days
- choppy sessions
- news conditions
- different times of day
- different market cycles
Only then can you see what is actually helping and what is hurting.
Before improving any system, a trader should first understand why backtesting a trading strategy matters before going live.
Numbers Matter More Than Feelings
A trader may love a setup because it looks beautiful.
But beautiful setups are not always profitable.
Another setup may look simple or boring, but produce better results over time.
This is why numbers matter.
Your backtest should tell you:
- win rate
- average reward-to-risk
- total R result
- maximum losing streak
- average drawdown
- best session
- worst session
- best market condition
- worst market condition
These numbers help you make better decisions.
For example, you may discover that your strategy performs well during New York but badly during London.
That does not mean the strategy is useless.
It may mean the strategy should only be traded during New York.
Or you may discover that your strategy works well inside trading ranges but performs badly in strong spikes.
That does not mean you need to delete the strategy.
It means you need a market condition filter.
This is real optimisation.
Optimising trading strategy should always start with evidence from your own backtesting, not with emotion, frustration, or the desire to add more rules.
For traders who are still learning the basic idea of testing a system, Investopedia also explains backtesting as a way to evaluate how a trading strategy would have performed using historical data.
Remove Weak Setups First
Many traders think optimisation means adding.
But often, the best optimisation is removing.
Remove the setups that do not perform well.
Remove the session that creates poor results.
Remove the market condition that damages the strategy.
Remove the entry pattern that creates too much drawdown.
Remove the rule that looks smart but does not improve performance.
A clean strategy is usually built by subtraction.
This is important.
If you start with ten strategy ideas, you do not need to keep all ten.
You test them.
You compare them.
You remove the weak ones.
Over time, you may find that only one or two strategies are truly worth keeping.
That is not failure.
That is progress.
Do Not Add Filters Randomly
Filters can be useful.
But random filters can destroy a strategy.
A filter should exist only because the data proves it helps.
For example, a useful filter may be:
- only trade during New York session
- avoid high-impact news
- do not trade the middle of a range
- only take trades after a clear pullback
- only enter after price confirms rejection
- avoid trades when risk-to-reward is poor
- avoid weak signal candles
- avoid late entries after the move is extended
These filters can improve a strategy.
But only if the backtest supports them.
Do not add a filter because one trade lost.
Do not add a filter because you feel afraid.
Do not add a filter because someone online said it sounds professional.
Every filter must answer one question:
Does this improve the result or the execution?
If the answer is no, remove it.
Simple Is Not Weak
Many traders believe a professional strategy must be complicated.
That is not true.
A simple strategy can be powerful if it is clear, tested, and repeatable.
For example:
“I only trade XAUUSD during New York. I wait for price to reach the edge of a trading range. I enter only after rejection. I place the stop beyond the range edge. I target the middle or opposite side of the range. I stop after two losses.”
This is simple.
But it is also structured.
The trader knows:
- instrument
- session
- market condition
- entry location
- confirmation
- stop loss
- target
- daily limit
That is much better than a complicated strategy with ten indicators and no clear decision rule.
Simple does not mean easy.
Simple means executable.
Optimise One Variable at a Time
Another mistake is changing everything at once.
A trader changes the session, target, stop loss, entry confirmation, timeframe, and filter all together.
Then the trader does not know what improved the result.
Was it the session?
Was it the stop?
Was it the target?
Was it the market condition filter?
You cannot know.
That is why optimisation should be done step by step.
Change one variable.
Test again.
Review the result.
Then decide.
For example:
First, test the strategy with a 1:1 reward-to-risk.
Then test it with 1:2.
Then test it with 1:3.
Compare the results.
After that, test session performance.
Then test whether avoiding news improves the outcome.
This keeps the process clean.
A trader should not optimise like someone guessing.
A trader should optimise like someone investigating.
The real goal of optimising trading strategy is to make your decision-making cleaner, faster, and easier to repeat.
Risk-Free and Break-Even Rules Must Be Tested
Many traders move stop loss to break-even because it feels safe.
But break-even is not always automatically good.
Sometimes it protects the account.
Sometimes it removes you from trades too early before the real move happens.
That is why risk-free rules must be tested.
For example, you may compare:
- no break-even rule
- move to break-even after 1R
- move to break-even after price passes first target
- move to break-even only if market structure changes
- partial close plus break-even
- fixed stop until target or invalidation
The best answer depends on the strategy.
Do not assume.
Test it.
A rule is useful only if it improves the strategy or improves your ability to execute the strategy calmly.
News Filters Must Also Be Tested
Some traders avoid all news.
Some traders trade around news.
Some strategies work better during volatility.
Some strategies get destroyed by spread, slippage, and fast movement.
This is why news filters must be tested.
If your strategy performs badly around high-impact news, then avoiding news becomes part of your plan.
If your strategy only works after news volatility settles, then timing becomes important.
If your broker spread becomes too wide during news, your backtest must consider that.
Again, optimisation is not about opinion.
It is about evidence.
The question is not:
“Do I like trading news?”
The question is:
“Does my strategy perform better or worse around news?”
Optimisation Should Make Live Trading Easier
A good optimisation process should make your live trading easier.
It should reduce confusion.
It should reduce hesitation.
It should reduce emotional decisions.
It should make the trading plan more specific.
If optimisation makes the system harder to follow, something is wrong.
For example, a good optimisation result may be:
“I will only trade this setup during New York, only after price reaches a range edge, only if the rejection candle closes strongly, and only if the reward-to-risk is at least 1:1.5.”
That is clearer.
But a bad optimisation result may be:
“I need RSI, MACD, two moving averages, Fibonacci, liquidity sweep, order block, fair value gap, trendline break, volume confirmation, and news alignment before I enter.”
That may sound professional.
But if the trader cannot execute it in real time, it is not useful.
A trading strategy must survive the live market.
It must be clear enough to follow under pressure.
Avoid Curve Fitting
Curve fitting happens when a trader adjusts the strategy too much to fit the past perfectly.
The backtest looks amazing.
But the strategy fails in live market.
Why?
Because it was over-optimised.
The trader built rules that worked only for old data, not for real future conditions.
This is dangerous.
If every rule is too specific, the strategy becomes fragile.
For example:
“I only trade on Tuesday, after three bearish candles, when RSI is exactly below 43, after price taps a level twice but not three times, with a 1.7R target.”
This may fit one backtest.
But it may not be practical or repeatable.
Good optimisation improves clarity.
Bad optimisation creates a perfect-looking past and a weak future.
The goal is not a perfect backtest.
The goal is a strategy that makes sense and can be forward tested.
The Best Strategy Is Usually the Cleanest Strategy
After enough testing, the trader usually learns something important:
The best strategy is rarely the most complicated one.
It is the one with:
- clear rules
- clear invalidation
- controlled risk
- simple execution
- tested performance
- emotional compatibility
- repeatable conditions
A clean strategy tells you what to do.
It also tells you what not to do.
That second part is very important.
If your strategy does not tell you when to stay out, you will still overtrade.
A good strategy protects you from the market.
A great strategy protects you from yourself.
This is also why building a personal trading strategy is more useful than copying another trader’s rules.
Simple Strategy Optimisation Checklist
Before finalising a strategy, ask:
- Did I test enough examples?
- Did I compare sessions?
- Did I compare market conditions?
- Did I test different risk-to-reward options?
- Did I check normal losing streaks?
- Did I remove weak setups?
- Did I avoid adding unnecessary filters?
- Did I test break-even rules?
- Did I test news conditions?
- Can I execute this strategy live without confusion?
If the answer is no, the strategy needs more work.
But more work does not mean more complexity.
It means cleaner decision-making.
When done correctly, optimising trading strategy helps you remove unnecessary noise and focus only on the setups that match your tested edge.
Coming Next
In Part 5 of the Avex Trading Plan Series, we will discuss how to write a trading plan.
A strategy tells you how to trade.
A trading plan tells you how to behave before, during, and after the trade.
That is where discipline becomes written.
Next article: How to Write a Trading Plan That Protects You From Emotional Decisions
Series Navigation
Previous: Backtesting a Trading Strategy: Why Traders Must Test Before Going Live
Next: How to Write a Trading Plan That Protects You From Emotional Decisions
Final Thought
Optimisation is not about making your strategy look smarter.
It is about making your strategy cleaner.
A trader should not add rules just to feel safer.
A trader should use backtest results to remove weakness, improve clarity, and protect execution.
The goal is not to trade more.
The goal is not to create a complicated system.
The goal is to build a strategy that is clear enough to repeat and strong enough to test in live conditions.
Trade cleaner.
Not more complicated.
Avex Traders
A good strategy does not need to impress people.
It needs to protect your process.
Risk Disclosure: Trading forex, gold, and other leveraged products involves significant risk and may not be suitable for every trader. This article is for educational purposes only and does not constitute financial advice.