There's a war in trading that nobody talks about openly.
On one side: discretionary traders who pride themselves on reading charts, sensing market mood, and making judgment calls in real-time. They view systematic traders as rigid robots missing obvious context.
On the other side: systematic traders who build rule-based systems and execute without emotion. They view discretionary traders as undisciplined gamblers dressing up gut feelings as "analysis."
Both sides are partly right. Both sides are partly wrong.
The truth is that discretionary and systematic trading are tools, not religions. Understanding both approaches-and potentially combining them-is essential for any serious crypto trader.
This guide breaks down both approaches, their genuine advantages and disadvantages, and helps you determine which fits your personality, schedule, and goals.
Before we compare, let's define clearly.
Discretionary trading involves making trading decisions based on judgment, experience, and real-time analysis. The trader interprets market conditions and decides what to do in the moment.
Characteristics:
- Entries based on pattern recognition and market feel
- Flexible rules that adapt to context
- Human judgment drives all decisions
- Can incorporate qualitative information
- Every trade is somewhat unique
Example discretionary process:
- Look at BTC chart, see it's approaching resistance
- Notice RSI is overbought and volume is declining
- Observe that altcoins are showing relative weakness
- Read news about upcoming regulatory concerns
- Decide: "This looks like a good short setup, I'll enter here with a stop above the resistance"
The trader synthesized multiple inputs and made a judgment call. Another trader looking at the same information might reach a different conclusion.
Systematic trading involves making trading decisions based on predefined rules that can be coded and backtested. The trader's job is to follow the system, not to interpret it.
Characteristics:
- Entries based on specific, unambiguous criteria
- Rules are fixed and don't change trade-to-trade
- Human judgment is minimized or eliminated
- Only quantitative information is used
- Every trade of the same type is identical
Example systematic process:
- System rule: Short when
10-day MA crosses below 20-day MA AND RSI(14) > 70 AND price is below 50-day MA
- Check current conditions: 10 MA just crossed below 20 MA, RSI is 73, price is below 50 MA
- All conditions met. Enter short with stop at 2× ATR above entry, target at next support level
- No judgment involved. The system dictates the trade
Every time these conditions appear, the same trade is taken. The trader's feelings about the market are irrelevant.
Discretionary trading has genuine advantages that systematic approaches can't replicate.
Markets change. Conditions that worked yesterday may not work tomorrow. A discretionary trader can recognize this shift in real-time and adapt.
Example: A support level that has held 5 times might fail on the 6th test because of a news event. A systematic trader following "buy at support" rules would buy again. A discretionary trader might recognize the changed context and skip the trade.
Crypto markets are particularly prone to sudden regime changes. A discretionary trader can say "this doesn't feel right" and stand aside when systems are about to get chopped up.
Not everything that matters can be quantified.
Qualitative factors a discretionary trader might use:
- Quality of a project's team
- Narrative shifts in the market
- Sentiment from social media not captured in simple metrics
- Unusual activity that suggests insider knowledge
- Regulatory mood shifts
A systematic trader can only use data that can be coded. A discretionary trader can use anything they observe.
Discretionary traders can create unique trade ideas that a system would never generate.
Example: "BTC is consolidating, ETH looks strong relative to BTC, and there's a major Ethereum upgrade next week. I'll go long ETH against BTC to express this view while hedging overall crypto exposure."
This kind of nuanced trade requires human creativity and contextual understanding.
Sometimes markets do things that no historical data prepared you for.
- Example: March 2020 COVID crash. Markets moved in ways that broke most systematic approaches. Discretionary traders who recognized the extremity could either step aside or take contrarian positions at historic levels. Systematic traders often got stopped out repeatedly.
In true black swan events, human judgment-while imperfect-can be better than rigid rules.
Systematic trading has advantages that discretionary traders struggle to match.
The biggest killer of trading accounts is emotion. Systematic trading removes it entirely from trade decisions.
When you're following a system:
- You don't panic sell at bottoms
- You don't FOMO buy at tops
- You don't revenge trade after losses
- You don't size up after wins
- You don't skip trades because you're "not feeling it"
Every trade is the same. The system decides, you execute. Your feelings are irrelevant.
For most traders, this alone makes systematic trading superior. The average discretionary trader underperforms their own strategies because of psychological errors.
Systematic rules can be backtested against historical data. You can know before risking real money:
- What the win rate is
- What the maximum drawdown was
- How the system performed in different market conditions
- What the expectancy is per trade
Discretionary trading can't be backtested because every trade involves judgment that you can't replicate historically. You only find out if your discretion works after years of live trading.
A systematic approach produces consistent results. Trade 100 times, and every trade was executed identically. This creates clean data for analysis and improvement.
It also scales. A systematic trader can:
- Trade multiple systems simultaneously
- Trade multiple assets without quality degradation
- Automate execution entirely
- Step away from screens without missing opportunities
Discretionary trading requires your attention for every trade. There's no scaling without proportional time investment.
Discretionary traders make worse decisions when they're:
- Tired
- Stressed
- Distracted
- On a losing streak
- On a winning streak (overconfidence)
Systematic traders execute the same whether it's their first trade or their hundredth. The system doesn't have bad days.
The "right" approach depends heavily on who you are. Be honest with yourself.
You're highly intuitive. You naturally pick up patterns and "feel" when something is off. You've been right about things before you could explain why.
You enjoy the analysis process. Looking at charts, reading news, synthesizing information-this is engaging, not draining. You'd do it even if you weren't trading.
You're emotionally stable under pressure. You don't panic in drawdowns or get euphoric in winning streaks. You can make clear decisions when money is on the line.
You have significant screen time available. Discretionary trading requires attention. If you have hours daily to dedicate, it's viable. If you're trading between meetings, it's not.
You've already proven success with discretion. If you have a track record showing your judgment adds value, trust it. If you don't, you're hoping, not trading.
You're analytically minded. You think in rules, conditions, and probabilities. You prefer "if X then Y" over "it depends."
You struggle with emotional control. Be honest. If you've revenge traded, FOMO'd in, or panic sold, a system protects you from yourself.
You want passive or semi-passive income. Systematic trading can be automated. Discretionary trading cannot.
You have limited time. A system can be developed during off-hours and executed with minimal time during market hours.
You value process over outcome. You'd rather follow a losing system correctly than win by breaking rules. You understand that long-term success comes from consistency.
Discretionary trader who should be systematic:
- Constantly second-guessing decisions
- Performance varies wildly with emotional state
- Can't explain why recent trades were taken
- Losing trades consistently bigger than planned
Systematic trader who should be discretionary:
- Constantly overriding system signals
- Missing obvious context that affects trades
- Frustrated by "stupid" entries the system takes
- Better paper-trading results than live results (override behavior)
Academic research on discretionary vs. systematic trading shows some consistent patterns.
Among professional fund managers:
- Systematic funds show lower volatility and more consistent returns
- Discretionary funds show higher highs and lower lows
- Risk-adjusted returns (Sharpe ratio) tend to favor systematic approaches
- In trending markets, both perform similarly
- In choppy markets, systematic approaches often outperform
For retail traders, the data is clearer:
- The vast majority of retail discretionary traders lose money
- Systematic traders who actually follow their systems have better outcomes
- The main advantage of systems for retail is emotional discipline
- Few retail traders successfully transition from losing discretionary to winning systematic without extensive work
The famous discretionary traders you hear about represent survivorship bias. For every legendary discretionary trader, thousands of discretionary traders blew up accounts. You don't hear about them.
Systematic trading has similar survivorship bias-most systems don't work-but the failure is usually slower and more measurable, giving traders time to adapt.
Many successful traders don't choose between discretionary and systematic. They combine elements of both.
Framework:
- System generates trade signals
- Discretion decides which signals to take
Example:
- System: Long when price closes above 20-day high with volume > 150% average
- Discretionary filter: Only take signal if macro environment is favorable and no major news event is pending
This approach captures systematic consistency while allowing human judgment to filter out obviously bad signals.
Framework:
- Human generates trade ideas
- System determines position sizing, stop placement, and exit rules
Example:
- Discretionary analysis identifies ETH as attractive long based on chart pattern and narrative
- System dictates: Entry at $3,200, stop at $3,050 (2× ATR), position size at 1% account risk, take 50% profit at 2:1, trail remainder
This approach allows creativity in idea generation while eliminating emotional mismanagement of good ideas.
Framework:
- Systematic rules identify market regime
- Different strategies apply based on regime
Example:
- Regime detection: If ADX > 25, market is trending; use trend-following system
- Regime detection: If ADX < 20, market is ranging; use mean-reversion system
- Discretion: If regime is unclear, reduce size or sit out
This allows adaptation to changing conditions while keeping execution systematic.
If you choose discretionary trading, you still need structure. Pure improvisation is gambling.
- Analysis Process
Define how you analyze markets:
- What timeframes do you look at, in what order?
- What indicators do you check?
- What data outside the chart do you incorporate?
- How do you identify key levels?
Consistency in analysis process creates consistency in decision quality.
- Setup Definitions
Define what setups you trade:
- What patterns do you look for?
- What constitutes a valid version of each pattern?
- What are the minimum requirements for a trade?
You don't need rigid rules, but you need a vocabulary for describing what you're doing.
- Risk Rules
These should be systematic even if your entries are discretionary:
- Maximum risk per trade
- Maximum total portfolio risk
- Stop loss requirements (every trade must have one)
- Position sizing formula
Non-negotiable. Your discretion shouldn't extend to how much you can lose.
- Trade Review Process
Document every trade:
- What was the thesis?
- What did you see in the chart?
- How did you feel before/during/after?
- What worked? What didn't?
This creates a feedback loop. Without documentation, discretionary trading is just a series of unexamined decisions.
Systematic trading requires rigorous development before live trading.
- Hypothesis Formation
Start with an idea about market behavior:
- "Crypto trends tend to persist"
- "Extreme RSI readings tend to reverse"
- "Breakouts from consolidation often continue"
This hypothesis becomes the basis for your system.
- Rule Definition
Convert the hypothesis into specific rules:
- Entry: When exactly do you enter?
- Exit: When exactly do you exit (profit, loss, time)?
- Position size: How much do you trade?
Rules must be unambiguous. If two reasonable people could interpret a rule differently, it's not specific enough.
- Backtesting
Test rules against historical data:
- Minimum 100 trades, preferably 200+
- Test across different time periods
- Test across different market conditions
- Account for realistic costs (fees, slippage)
Results should show positive expectancy with acceptable drawdown.
- Out-of-Sample Testing
Test on data the system wasn't developed on:
- Reserve 20-30% of data for out-of-sample testing
- Or use walk-forward analysis
- Performance should be similar to in-sample (if much worse, you've overfit)
- Paper Trading
Trade the system without real money:
- Execute every signal
- Track as if it were real
- Verify that live execution matches backtest assumptions
- Live Trading with Small Size
Start with 25-50% of intended position sizes:
- Run for minimum 20-30 trades
- Compare performance to expectations
- Scale up only if results match
- Calling gambling "discretion"
Discretion means judgment informed by expertise. If you can't explain your decision-making process, you're not being discretionary-you're guessing.
- Nodocumentation
Without recording your decisions and rationale, you can't learn. You'll repeat the same mistakes indefinitely.
- Risk rules treated as guidelines
"I'll just risk a little more on this one" is how accounts blow up. Risk rules must be systematic even for discretionary traders.
- Overconfidence after wins
Discretionary traders often attribute wins to skill and losses to bad luck. This creates dangerous overconfidence. Your judgment isn't as good as you think after a winning streak.
- Analysis paralysis
More information doesn't always mean better decisions. At some point, you need to act. Discretionary traders can fall into endless analysis that prevents any trading.
- Overfitting
Adding parameters until the backtest looks perfect creates a system that only works on historical data. Simplicity usually outperforms complexity.
- Overriding signals
If you're going to override your system, why have one? Every override is a discretionary trade that destroys your statistical edge.
- Abandoning during drawdown
All systems experience drawdowns. Abandoning a system during drawdown-often right before it recovers-is the most common systematic trading mistake.
- Testing without costs
Ignoring fees, slippage, and funding rates makes backtests look better than reality. Always include realistic costs.
- Assuming markets don'tchange
A system that worked from 2019-2024 might not work from 2025 onward. Markets evolve. Periodic review and adaptation is necessary.
Step 1: Document your current discretionary process
What do you actually look at? What triggers your entries? Start writing down rules you already implicitly follow.
Step 2: Identify the systematic components
Some of your process is probably already rules-based. Isolate these.
Step 3: Test the systematic components
Backtest the rules you've identified. See which hold up.
Step 4: Gradually reduce discretion
Start following the tested rules strictly for some trades while remaining discretionary for others. Compare results.
Step 5: Commit to systematic execution
Once you've proven the systematic approach works, commit fully. Remove yourself from decision-making.
Step 1: Understand why your system makes money
If you don't understand the edge, you can't apply discretion appropriately.
Step 2: Identify where discretion might add value
Are there obvious situations where your system takes bad trades? Can you filter these?
Step 3: Test discretionary filters
Take your system signals but apply discretionary filters. Track results separately.
Step 4: Gradually add judgment
Incorporate more discretion in defined areas while keeping core execution systematic.
Step 5: Maintain systematic risk rules
No matter how discretionary you become, position sizing and risk management should stay systematic.
Yes. Profitable traders exist using pure discretion, pure systematic, and everything in between. The key is matching your approach to your psychology, executing consistently, and having positive expectancy.
Systematic is easier to start. You follow rules, and the feedback is clear. Discretionary requires developing intuition that takes years. However, systematic development (building good systems) is technically complex.
I recommend starting with a simple systematic approach. This builds discipline, teaches you about expectancy and drawdowns, and creates objective feedback. Add discretion later once you have experience.
Track it. Take all system signals but flag which ones you would have skipped with discretion. Compare results of "would have skipped" trades to "would have taken" trades. After 100+ data points, you'll know.
Automated execution is by definition systematic. However, you can build systems that incorporate factors that feel discretionary (sentiment analysis, news keywords, etc.) even if the execution is automated. The line between "complex systematic" and "discretionary" can blur.
The discretionary vs. systematic debate has no universal answer. Both approaches can work. Both approaches can fail.
What matters is:
- Understanding both approaches deeply
- Choosing based on honest self-assessment, not ego
- Executing your chosen approach with discipline
- Continuously measuring and improving
Most traders will do best with a hybrid: systematic risk management and trade execution, with some discretionary input on idea generation or signal filtering.
Find your balance. Test it. Refine it.
Whether you trade discretionary, systematic, or hybrid, Thrive provides the tools to measure and improve your performance:
- Trade tagging - Categorize trades by approach, setup type, and discretionary overrides
- Performance comparison - See which approach actually performs better for you
- System signal tracking - Log system signals even when you override them
- Discretionary documentation - Capture your thesis and reasoning for every discretionary decision
- AI pattern recognition - Discover whether your discretion adds or subtracts value
You can't improve what you don't measure. Thrive makes measurement effortless.
Stop guessing which approach works. Start knowing.
→ Find Your Trading Edge with Thrive
